Prevalence and risk factors for epilepsy in Cameroon
Thesis submitted for the Degree of Doctor of Philosophy by:
Dr Samuel A. Angwafor Department of Clinical and Experimental Epilepsy Institute of Neurology University College London
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Declaration I, Samuel Anye Angwafor, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis.
Samuel A. Angwafor
2
Acknowledgements I would like to thank my supervisors, Prof. Ley Sander, Dr. Gail Bell and Prof. Alfred K.
Njamnshi for their guidance and support from the conception of this project to its completion and for all the learning opportunities they provided me. I am particularly indebted to Dr. Gail
Bell for her patience and for her insightful input to this project and all the manuscripts that I have produced related to this work.
Special appreciation goes to the District Medical Officer of the Batibo, Dr Ajabmoh Henry and the Chief of Bureau for Health for Batibo, Flora Avera Fonyuy for their collaboration in recruitment and training of field workers. I would like to acknowledge all the chiefs of health areas and the community volunteers for sacrificing their time to participate in this project. I would like to thank Mr Atanjang Godlove for helping with translation of the questionnaires and for initiating contact of the research team with some traditional rulers.
I wish to express special gratitude to the population of the Batibo Health District who generously welcomed the research team to their homes, especially the people with epilepsy and the controls who sacrificed their time to be present at the health centres and to respond to our questions. I sincerely hope that this research is the beginning of a journey together, to improve the quality of life of people with epilepsy in this community.
I would like to thank Dr Kilton Nforchu, Dr Ngarka Leonard, Dr. Nfor Leonard for assisting with the clinical examination during the pilot of this research. I am thankful to Mr Theophilus
Njamnshi and Miss Choh Soh-Bang for their assistance during the fieldwork and assisting with the data entry.
Special gratitude to Dr Wim Otte for sacrificing time from his busy schedule to assist with data processing and analysis.
I would like to thank Jane de Tisi and Juliette Solomon for their guidance and assistance in various administrative aspects with UCL throughout my project
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I would like to thank all my colleagues and friends at the Epilepsy Department at Queen
Square with whom I have had a truly memorable time.
I greatly appreciate the support I received from the Epilepsy Society in the realisation of this project, especially at times when the challenges seemed insurmountable.
Most importantly, I wish to express special gratitude to my family, especially my lovely wife,
Awah, and my two baby girls, Neh and Nanga, for graciously accepting to endure 4 years of my absence. I hope I have made you proud.
Finally, I am grateful for the assistance I have received as a Commonwealth Scholar, funded by the UK government.
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Abstract
This project was designed to ascertain the prevalence and risk factors for epilepsy in a rural health district in the North-West Region of Cameroon. A community-based epilepsy screening targeted all inhabitants, six years and older, in all 16 health areas in the Batibo Health District.
During door-to-door visits, fieldworkers used a validated questionnaire to interview consenting heads of households about the possibility of epilepsy in eligible residents of the house. All people with suspected epilepsy were subsequently assessed by a physician who confirmed or refuted the epilepsy diagnosis after clinical assessment. People with epilepsy and randomly selected healthy subjects were interviewed by a nurse who obtained relevant demographic details and information on exposure to risk factors for epilepsy. Out of 39,527 permanent residents screened, 546 had active epilepsy. The age-standardised prevalence of active epilepsy was 3.5% (95% CI: 3.2-3.9). The prevalence of active epilepsy varied widely between health areas, ranging between 1.2% and 7.7%. The peak age-specific prevalence was in the
20-29 age group. Epilepsy was focal in 59% of people, and the median age at first seizure was 11 years (Interquartile range: 8-15). The 1-year incidence of epilepsy was estimated to be 171/100,000 (95%CI: 114.0-254.6). About 81% of people with epilepsy were either untreated or receiving inappropriate treatment. Family history of epilepsy was the main factor associated with epilepsy after multivariate analysis (OR: 6.8; 95% CI: 3.2-14.1). The characteristics of active epilepsy in this Cameroonian population, mainly the geographical heterogeneity and the pattern of the age-specific prevalence suggest that cysticercosis and/or onchocerciasis may be involved. These and other risk factors for epilepsy need to be further investigated through robust case-control and prospective studies in this population. We briefly discuss public health strategies that may useful in redressing the burden of epilepsy in
Cameroon.
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Impact Statement
We have demonstrated the feasibility of large scale screening for epilepsy in Cameroon, using trained community volunteers and local health workers. This method can be scaled up to other regions in Cameroon to provide a clearer picture of the nationwide burden of epilepsy in
Cameroon. To our knowledge, this is the largest epidemiological study of epilepsy in
Cameroon using a standardised methodology and we expect that evidence generated by this this study will be a useful resource for local health authorities in the North-West Region, the
Ministry of Health and local and international organisations, in planning to reduce the burden of epilepsy in Cameroon. In this project, we established a register of 546 people with epilepsy, which has been shared with the local health authorities (who have committed to respect the confidentiality of the individuals) and it is hoped that this will facilitate the planning for epilepsy care and the allocation of resources to improve on access to treatment for people with epilepsy in this region. This study has shown that epilepsy is a major public health problem in the North-
West Region and raises hypotheses about potential causes, especially neurocysticercosis and onchocerciasis. The database of almost 40, 000 people that we have created, including 546 people with epilepsy, is an invaluable cohort and sampling pool for future epidemiological studies to investigate the risk factors for epilepsy, its outcome, and other co-morbidities associated with the condition in Cameroon. In this study, we present important medical and social consequences of the wide epilepsy treatment gap in Cameroon. We trained selected health workers in all the health areas in the study site, on the diagnosis and management of epilepsy. To redress the epilepsy burden in this region, we propose a community-centred, nurse-led model for the management of epilepsy. We recommend that non-governmental organisations, in partnership with local health authorities, community leaders and the Ministry of Public Health use this as a resource to improve on the access to care and quality of life of people with epilepsy in Cameroon. This can potentially empower the affected people to participate actively in social and economic activities, leading to huge socio-economic gain for their families and the community.
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Table of Contents
Declaration ...... 2
Acknowledgements ...... 3
Abstract ...... 5
Impact Statement ...... 6
List of Tables ...... 11
List of Figures ...... 12
List of Abbreviations...... 13
1 Introduction and objectives ...... 15
1.1 Introduction ...... 15
1.2 Aim ...... 16
1.3 Objectives ...... 16
2 Literature review ...... 17
2.1 Prevalence and incidence of epilepsy ...... 17
2.2 Risk factors for epilepsy in sub-Saharan Africa: a systematic review ...... 18
2.2.1 Introduction ...... 18
2.2.2 Methods ...... 19
2.2.3 Results ...... 21
2.2.4 Discussion ...... 25
2.2.5 Conclusion ...... 29
2.3 Parasites and epilepsy ...... 29
2.3.1 Summary ...... 29
2.3.2 Introduction ...... 30
2.3.3 Malaria and epilepsy ...... 33
2.3.4 Cysticercosis and Epilepsy ...... 38
2.3.5 Onchocerciasis, epilepsy and nodding syndrome ...... 42
2.3.6 Toxocariasis and epilepsy ...... 49
7
2.3.7 Toxoplasmosis and epilepsy ...... 50
2.3.8 Schistosomiasis and epilepsy ...... 51
2.3.9 Paragonimiasis and epilepsy ...... 52
2.3.10 Sparganosis and epilepsy ...... 53
2.3.11 Human African Trypanosomiasis and epilepsy ...... 54
2.3.12 Conclusion ...... 56
2.4 Comorbidities of epilepsy ...... 56
2.5 Premature mortality in epilepsy ...... 56
2.6 Redressing the burden of epilepsy in SSA: the way ahead ...... 57
2.6.1 Clarifying the relationship between epilepsy and a variety of factors ...... 57
2.6.2 Preventing epilepsy by targeting parasites in endemic areas ...... 58
2.6.3 Improving access to care for people with epilepsy ...... 59
3 Study setting ...... 61
3.1 Cameroon ...... 61
3.2 Batibo Health District ...... 63
3.3 Ndu Health District ...... 65
4 Pilot of fieldwork ...... 67
4.1 Procedure ...... 67
4.2 Results ...... 69
4.3 Discussion ...... 73
5 Methods: fieldwork ...... 75
5.1 Definition of terms ...... 75
5.2 Planning, recruitment and training of personnel ...... 76
5.3 Census of households and persons ...... 76
5.4 Epilepsy screening and cross-sectional study of people with epilepsy...... 77
5.5 Selection of participants for the case-control study ...... 79
5.6 Ethical considerations ...... 79
5.7 Statistical analysis ...... 80
8
6 Cross-sectional epilepsy survey: findings and significance ...... 82
6.1 Results ...... 82
6.1.1 Household and population census ...... 82
6.1.2 Epilepsy Screening ...... 83
6.1.3 Prevalence of epilepsy ...... 87
6.1.4 Incidence of epilepsy ...... 92
6.1.5 Clinical characteristics of epilepsy ...... 92
6.1.6 Treatment and associated factors ...... 95
6.1.7 Perceptions of epilepsy ...... 97
6.1.8 Medical and social consequences of epilepsy ...... 97
6.2 Discussion ...... 98
6.2.1 Census of study population and epilepsy screening ...... 98
6.2.2 Life-time prevalence of epilepsy ...... 99
6.2.3 Prevalence of active epilepsy ...... 99
6.2.4 Incidence of epilepsy ...... 107
6.2.5 Clinical characteristics of seizures and epilepsy ...... 110
6.2.6 Putative causes of high prevalence of epilepsy in the Batibo Health District . 112
6.2.7 Epilepsy-related injuries ...... 118
6.2.8 Epilepsy treatment and associated factors...... 123
7 Case control study: findings and significance ...... 125
7.1 Results ...... 125
7.1.1 Factors associated with epilepsy in children ...... 125
7.1.2 Factors associated with epilepsy in adults ...... 129
7.2 Discussion ...... 132
7.2.1 Genetic Factors ...... 132
7.2.2 Adverse perinatal and childhood events ...... 133
7.2.3 Head Injury ...... 134
7.2.4 Nutrition-related factors ...... 134
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7.2.5 Having animals in household ...... 135
7.2.6 Hygiene and sanitation ...... 136
7.2.7 Ivermectin coverage ...... 136
7.2.8 Alcohol, smoking and recreational drug use ...... 136
7.2.9 Education ...... 136
8 Limitations, conclusion and future directions ...... 138
8.1 Limitations ...... 138
8.2 Conclusion ...... 140
8.3 Future Directions ...... 141
8.3.1 Improving access to treatment through a community-centred initiative ...... 141
8.3.2 Multi-centre epidemiological study of epilepsy in Cameroon ...... 143
8.3.3 Further studies of risk factors for epilepsy in the Batibo Health District ...... 143
8.3.4 Monitoring the impact of onchocerciasis control on the incidence of epilepsy144
8.3.5 Summary of proposal for a pilot trial of Taenia solium elimination to reduce the burden of epilepsy in Cameroon ...... 144
References ...... 148
Appendix ...... 169
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List of Tables
Table 1. Case-control studies: infection-related risk factors for epilepsy in SSA ...... 21
Table 2. Case-control studies: non-infection related risk factors· for epilepsy in SSA ...... 22
Table 3. Prospective and retrospective cohort studies of risk factors of epilepsy in SSA ...... 24
Table 4. Parasites commonly associated with epilepsy ...... 32
Table 5. Causes of early reactive and late seizures in parasitic infestation ...... 55
Table 6. Epilepsy screening in the pilot sites ...... 71
Table 7. Seizure semiology and epilepsy types in pilot sites ...... 72
Table 8. Census Results ...... 83
Table 9. Epilepsy Screening ...... 86
Table 10. Prevalence of active epilepsy by health area ...... 88
Table 11. Prevalence of active epilepsy by age and gender ...... 90
Table 12. Seizure and epilepsy characteristics ...... 94
Table 13. Treatment of epilepsy and related factors ...... 96
Table 14. Prevalence of active epilepsy from recent community-based studies in SSA ...... 101
Table 15. Prevalence of epilepsy in various communities in Cameroon ...... 104
Table 16. Incidence of active epilepsy from community-based studies in SSA ...... 110
Table 17. Factors associated with epilepsy in children (≤16 years): raw data ...... 127
Table 18. Factors associated with epilepsy in children (≤16 years): after imputation* ...... 128
Table 19. Factors associated with epilepsy in adults (>16 years): raw data ...... 130
Table 20. Factors associated with epilepsy in adults (>16 years): after imputation* ...... 131
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List of Figures
Figure 1. PRISMA flow diagram of search of studies of risk factors for epilepsy in SSA ...... 20
Figure 2. Life Cycle of Plasmodium falciparum (CDC, 2016a) ...... 33
Figure 3. Possible epileptogenic substrates of malaria ...... 37
Figure 4. Life Cycle of Taenia solium adapted from Nash and Garcia, 2011 ...... 38
Figure 5. Possible epileptogenic substrates in neurocysticercosis ...... 42
Figure 6. Life Cycle of Onchocerca volvulus (CDC, 2016b) ...... 43
Figure 7. Possible epileptogenic pathways of onchocerciasis ...... 48
Figure 8. Map of Cameroon with Basic Health information (Maps, 2012) ...... 62
Figure 9. Map of Batibo Health District ...... 65
Figure 10. Flow chart of study design and recruitment of participants ...... 85
Figure 11. Map of Batibo Health District showing of prevalence of epilepsy with respect to
Momo River ...... 89
Figure 12. Gender specific prevalence of active epilepsy by age category ...... 91
Figure 13. Age-specific prevalence of active epilepsy ...... 91
Figure 14 (A-I). Sample of people with sequelae of burns resulting from seizures ...... 122
Figure 15. Community-centred initiative of epilepsy care in the Batibo Health District ...... 142
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List of Abbreviations
AED Anti-epileptic Drug
BBB Blood Brain Barrier
CI Confidence Interval
CNS Central Nervous System
CSF Cerebrospinal Fluid
DMO District Medical Officer
DALYs Disability-adjusted Life Years
EEG Electroencephalogram
EITB Enzyme-linked immunoelectrotransfer blot
ELISA Enzyme-Linked Immunosorbent Assay
HAT Human African Trypanosomiasis
HIC High-income country
HIV Human Immunodeficiency Virus
ILAE International League Against Epilepsy
IQR Interquartile range
LMIC Low- middle-income country
MMP-9 Matrix-metalloproteinase-9
MRI Magnetic Resonance Imaging
NS Nodding Syndrome
OR Odds Ratio
PfEMP-1 Plasmodium falciparum Erythrocyte Membrane Protein-1
RBC Red blood Cell
SSA Sub-Saharan Africa
SUDEP Sudden Unexpected Death in Epilepsy
TLR4 Toll-like receptor 4
Th T-helper
13
WHO World Health Organization
YLD Years lived with disability
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Chapter 1: Introduction and objectives
1 Introduction and objectives
1.1 Introduction
Epilepsy is one of the commonest neurological conditions and a major cause of disease burden worldwide, especially in sub-Saharan Africa (SSA), where it is among the top five contributors to disability-adjusted life years (DALYs) due to neurological diseases (Feigin et al., 2017). In Cameroon, as in many countries in SSA, epilepsy constitutes a major public health challenge because of the huge treatment gap and the high disability and mortality that is associated with it (Kamgno et al., 2003). Studies in some communities in Cameroon have led to suggestions that Cameroon may be one of the countries most affected by epilepsy
(Njamnshi et al., 2005, Prischich et al., 2008). Some of the values reported in these studies may not accurately reflect the prevalence of epilepsy in Cameroon, especially small studies such as the one in which 181 people were screened for epilepsy and a prevalence of
135/1,000 was reported (Prischich et al., 2008). In many parts of Cameroon, the prevalence of epilepsy remains unknown despite anecdotal reports from the local health authorities and community leaders, of clustering of cases within families and communities. These claims are, however, not supported by hospital statistics and this is not surprising given that popular myths about epilepsy may have a negative effect on health-seeking behaviour (Njamnshi et al., 2009,
Njamnshi et al., 2010).
Neurocysticercosis and onchocerciasis are two human parasitic diseases cited as common risk factors for epilepsy in SSA and both are endemic in many parts of Cameroon. In the
Western regions of this country (North-West, South-West and West) there are an estimated
50,000 cases of cysticercosis (Praet et al., 2009). Cameroon has many endemic foci for onchocerciasis, most of which are found around fast-flowing rivers which provide suitable habitats for the simulium fly, the vector responsible for onchocerciasis (Tekle et al., 2016).
Understanding the prevalence and incidence of active epilepsy in the areas where these risk factors are also endemic and the factors responsible for probable clustering of cases is,
15
Chapter 1: Introduction and objectives
therefore, a necessary step in tackling epilepsy in these parts of Cameroon. The present study was designed to investigate the prevalence, incidence and risk factors for epilepsy in the
Batibo Health District, a rural health district in the North-West Region of Cameroon which is endemic for onchocerciasis and where conditions are suitable for high level of transmission of
Taenia solium. Evidence from this research is expected to provide the basis for further research on the burden of epilepsy in Cameroon and inform national policy on prevention and management of epilepsy in Cameroon.
1.2 Aim
The aim of this project was to generate evidence to contribute towards policy to redress the burden of epilepsy in Cameroon by ascertaining the prevalence, incidence and risk factors for epilepsy in the North-West Region, where environmental factors predisposing to epilepsy abound.
1.3 Objectives
• To estimate the prevalence of active epilepsy in the North-West Region of Cameroon,
using the Batibo Health District as a case-study
• To estimate the incidence of epilepsy in the study population
• To identify potential risk factors for epilepsy in the study population
• To describe clinical features of active epilepsy in Cameroon and how they relate to
possible aetiologies
• To ascertain the treatment gap of epilepsy, its determinant factors, and consequences
in the study population
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Chapter 2: Literature review
2 Literature review
2.1 Prevalence and incidence of epilepsy
Epilepsy is a major cause of disease burden worldwide and in a recent systematic review it was reported that between 1990 and 2016, epilepsy was persistently among the top 30 causes of Years Lived with Disability (YLDs) (Vos et al., 2017). Epilepsy is characterised by the occurrence of seizures which are signs and/or symptoms of brief abnormal excessive or synchronous activity in the neurons of the brain. The lifetime prevalence of epilepsy is the proportion of people who will have at least one unprovoked seizure in their lifetime and this is estimated to be about 5% of the world population (Leonardi and Ustun, 2002). The concept of active epilepsy is important because it describes the segment of people with seizures for whom health resources need to be prioritised. The International League Against Epilepsy
(ILAE) recommends that for epidemiological studies, active epilepsy should be defined as the occurrence of two or more unprovoked seizures in an individual, at least one of which occurred in the previous 2-5 years, but also includes people on anti-epileptic treatment (Thurman et al.,
2011). There is currently no consensus on the worldwide prevalence and incidence of active epilepsy. A recent systematic review of international studies estimated the prevalence of active epilepsy to be 6.4/1,000 (95% CI: 5.6–7.3) and the cumulative incidence of epilepsy to be
67.8/100,000 persons (95% CI: 56.7–81.0) (Fiest et al., 2017). These pooled estimates are controversial and misleading given the substantial heterogeneity of the designs of the component studies.
The incidence and prevalence of epilepsy are generally quoted as being two to three times higher in low and middle-income countries (LMIC) than in high-income countries (HIC) (Ngugi et al., 2010). Poorly developed health systems and the high incidence of infections can satisfactorily explain the higher incidence of epilepsy in LMICs compared with HICs (Ba-Diop et al., 2014). On the other hand, the difference in prevalence of epilepsy between LMICs and
HICs is debatable because of the significant differences in study methods between LMICs and
17
Chapter 2: Literature review
HICs and these include differences in selection criteria of study populations and in methods of case ascertainment (Bell et al., 2014). Whereas most studies in HICs rely on hospital records to estimate the prevalence of epilepsy, studies in LMICs mostly use a door-to-door strategy to screen for epilepsy. In addition, the target population is usually selected based on prevailing of risk factors for epilepsy. Consequently, studies in LMICs are more likely to identify people with epilepsy and hence to report a higher prevalence of epilepsy than studies in HICs.
Recently in SSA, many studies, covering large populations and using validated community- based methods to identify people with epilepsy have provided reliable estimates of the prevalence of epilepsy in many countries (see Table 14 Chapter 6). The prevalence of epilepsy in these studies varies between 4.3/1,000 (95% CI: 2.7-5.9) in Nigeria (Nwani et al., 2015) and
40/1,000 in Burkina-Faso (Millogo et al., 2012). Previously, data on the incidence of epilepsy was scarce but there have recently been some studies reporting on incidence of epilepsy in
SSA. These show that the incidence of epilepsy is in the range 64 to 350/100,000 person- years (Table 16, chapter 6). The variation in incidence and prevalence of active epilepsy within and between countries is probably due to differences in the prevalence of risk factors for epilepsy, although the effect of differences in study design is not negligible and must be considered.
2.2 Risk factors for epilepsy in sub-Saharan Africa: a systematic
review
2.2.1 Introduction
It is estimated that at least 60% of epilepsy in SSA is symptomatic (Kariuki et al., 2014) and this proportion could be higher if more neurophysiological and imaging examinations were used to confirm the diagnosis of epilepsy in SSA. Many cases of symptomatic epilepsy in SSA are probably secondary to acquired conditions, most of which could be preventable. In this review, evidence associating a wide variety of factors with epilepsy in SSA is presented and areas where important knowledge gaps remain are highlighted.
18
Chapter 2: Literature review
2.2.2 Methods
Literature Search
An extensive literature search, with neither date nor language restrictions, was performed for articles in the following databases: Pubmed, Scopus, Web of Science and African Index
Medicus. For all the databases, the search strategy included the following three steps; list of
54 countries in SSA AND list of all known causes and risk factors of epilepsy AND “epilepsy
OR epilep* OR seizures OR seizure OR convulsion OR convuls*”. The details of search strategy are found in the appendix and the PRISMA Flow diagram is presented below (Figure
1).
Inclusion Criteria:
• Observational case-control or cohort studies of risk factors for epilepsy involving only
people with active epilepsy
• Diagnosis of epilepsy confirmed by a clinician
• Compared the rate of exposure to the risk factor between cases and controls, providing
a risk estimate (OR or RR)
Exclusion Criteria
• Case-control studies that were entirely hospital-based
• Studies with no clear definition of active epilepsy
19
Chapter 2: Literature review
Pubmed: Web of Science: Scopus: Africa Index Medicus:
1247 citations 831 citations 900 citations 47 citations
Non-duplicate citations screened: 1467
Excluded after abstract and title screen: 1302
Articles retrieved: 165
Excluded after application of inclusion/exclusion criteria: 142
Articles included: 23
Figure 1. PRISMA flow diagram of search of studies of risk factors for epilepsy in SSA
Data Extraction and Analysis
Data extraction was conducted using a Microsoft Excel spreadsheet designed to capture important details about the study methods. Meta-analysis was not done because of the heterogeneity of the studies and because the risk factors were too diverse for any pooled odds ratio (OR) to yield meaningful interpretation.
20
Chapter 2: Literature review
2.2.3 Results
Of the 23 articles studied, 17 were case-control studies which recruited people with epilepsy after a population screening for epilepsy and randomly selected controls from the same population. The results of the case-control studies are presented on Tables 1 and 2. The remaining six studies were either prospective or retrospective cohort studies (Table 3). Except for a study on traumatic brain injury in Nigeria, all the cohort studies were on neurological infections and involved only children.
21
Chapter 2: Literature review
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81 Controls 392 374 72 38 1 996 191 814 648 72 262
93 with epilepsy 381 187 72 38 986 880 191 39 324 72 245 People
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Table Table Valuesare odds ratios with confidence 95% interval in bracketsValues in bold indicatestat 22
Chapter 2: Literature review
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Controls 392 636 362 174 816 996 648 36 262
infection related risk factors risk related infection
-
People with epilepsy 381 445 131 174 816 880 324 18 245
Tanzania, Tanzania, Country Ghana Kenya Benin Tanzania Kenya Ghana, Kenya, Uganda, South Africa Burundi Cameroon South Africa
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Table Table Valuesare odds ratios with confidence 95% interval in bracketsValues in bold indicatestatistical significance.
23
Chapter 2: Literature review
Table 3. Prospective and retrospective cohort studies of risk factors of epilepsy in SSA
Study Country Risk Study Design Exposed Non- Percentage RR/ 95% CI Factor Expos of epilepsy Studied ed in exposed
Adeloye Nigeria Head Injury Prospective study 165 NA 33.3% NA and with Missile in people with Odeku, missile head injury 1971
Birbeck Malawi Cerebral Prospective study 132 264 37.5% Undefined: et al., Malaria of Children with no cases of 2010 Retinopathy- epilepsy in positive Cerebral non- Malaria exposed
Kenya Cerebral Retrospective 152 179 7% 4.4 (1.4- Malaria Cohort of children 13.7)
between 6 months Carter et and 9 years al., 2004 Kenya Malaria with Retrospective 156 179 6.4% 6.1 (2.0- Complicate Cohort of children 18.3) d seizures between 6 months and 9 years
Edmond Senegal Bacterial Prospective study 66 66 21.2% NA et al., Meningitis of Children with 2010 Bacterial meningitis
Idro et Uganda Cerebral Prospective study 23 NA 52.2% NA al., 2010 Malaria of children between 12-79 months
Ngoung Mali Cerebral Prospective cohort 101 222 17/1,000 14.3 (1.6- ou et al., Malaria study of children person- years 132.0) 2006a with cerebral malaria and with non-cerebral malaria
NA: Data not available
24
Chapter 2: Literature review
2.2.4 Discussion
Non-Infection related risk factors
Family history
Most of the studies show that people with epilepsy are two to seven times more likely to have a first-degree relative with epilepsy than are controls (Ngugi et al., 2013a, Ae-Ngibise et al.,
2015, Edwards et al., 2008, Wagner et al., 2014, Matuja et al., 2001, Nsengiyumva et al.,
2003, Mung'ala-Odera et al., 2008). In Tanzania for example, 46% of people with epilepsy had a family history of epilepsy, three quarters of whom had at least two first degree relatives with epilepsy (Matuja et al., 2001). While it is possible that this strong association is due to hereditary factors, it could also result from shared exposure to environmental factors among family members, and from recall bias that is inherent in these studies. Consanguineous marriages could be partly responsible for the clustering of cases of epilepsy in some communities, as seen in the Tanzanian study where 32% of 60 people with epilepsy with at least two first-degree relatives with epilepsy came from consanguineous marriages (Matuja et al., 2001). In many African countries, marriage within the same tribe or ethnic group is highly encouraged, and this may facilitate inheritance of genetic traits that predispose to epilepsy.
Head injury
Head injury is an important risk factor of epilepsy and the risk increases with the severity and the degree of penetration (Thapa et al., 2010). In Africa, most cases of head injury result from road traffic accidents, which are often severe because of poor road infrastructure and insufficient use of road safety measures such as seat belts and helmets. Among five case- control studies, two found a significant association between epilepsy and a history of head injury, both reporting head injury in 8% of people with epilepsy (Edwards et al., 2008, Ngugi et al., 2013a). The epilepsy risk may have been overestimated in these studies because of recall bias. It is not clear why the three other studies found no such association (Wagner et al., 2014, Nsengiyumva et al., 2003, Ae-Ngibise et al., 2015). Some of the studies did not
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distinguish between head injuries occurring before and after the onset of seizures and so did not account for reverse causality. The lone prospective study in this review found that about one third of people with missile injury in Nigeria developed epilepsy over three to five years of follow-up (Adeloye and Odeku, 1971).
Adverse perinatal events
In SSA, due to geographical distance to health facilities, traditional beliefs and economic challenges, home deliveries are common, resulting in a high neonatal mortality rate: 35 per
1,000 (WHO, 2010). Those who survive perinatal complications often incur brain damage and neurological sequelae such as epilepsy. Adverse perinatal events have been strongly associated with epilepsy in case-control studies, most of which show that people with epilepsy have up to seven times higher odds of having had perinatal complications than healthy controls (Ae-Ngibise et al., 2015, Edwards et al., 2008, Matuja et al., 2001, Ngugi et al., 2013a,
Wagner et al., 2014). The risk may, however, have been overestimated because parents of people with epilepsy may be more likely than those of controls to recall a perinatal complication.
Stroke
There is limited data on post-stroke epilepsy in SSA. It is particularly challenging to assess the risk of epilepsy associated with stroke in case-control studies because of limited diagnostic tools and poor medical record systems. Only one study looked at the risk of epilepsy associated with stroke and found that 2% of people with epilepsy and 0.5% of controls had a history of stroke with no significant difference found (Ngugi et al., 2013a). Post–stroke epilepsy is, however, unlikely to explain the clustering of people with epilepsy in communities in SSA.
Use of recreational drugs
In most cases of recreational drug use, seizures are rare and are often acute symptomatic seizures, frequently aggravated by use of crack cocaine and concurrent alcohol abuse
(Pascual-Leone et al., 1990) . Little is known, however, about the risk of epilepsy associated
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with prolonged substance abuse, especially in Africa. Two case-control studies in this review found no significant association between substance abuse and epilepsy (Ngugi et al., 2013a,
Ae-Ngibise et al., 2015). One major challenge of investigating the use of recreational drugs as a risk factor of epilepsy using interviews is that people are likely to give socially acceptable responses. Substance abuse may not be directly associated with unprovoked seizures but may predispose to other risk factors such as head injury.
Malnutrition
The relationship between epilepsy and malnutrition is complex and causality can be bidirectional. Malnutrition in any given individual could either be one among many factors predisposing them to epilepsy or could aggravate an already existent seizure disorder (Crepin et al., 2009). Meanwhile, people with epilepsy in SSA are frequently subjected to numerous food taboos and restrictions based on false beliefs about epilepsy, which can lead to malnutrition. Two large case–control studies using anthropometric measurements and nutritional assessment found no significant relationship between epilepsy and malnutrition
(Ae-Ngibise et al., 2015, Ngugi et al., 2013a). Meanwhile, another study in Benin reported that the prevalence of malnutrition was less common among controls (9%) than cases (22%) with a prevalence odds ratio of 0.7 (95% CI: 0.6-0.9) (Crepin et al., 2007).
Febrile seizures
A history of febrile seizures was found to be significantly associated with epilepsy in two of three case-control studies with ORs of 2 and 4 (Mung'ala-Odera et al., 2008, Matuja et al.,
2001). In many African countries, it is difficult to differentiate between febrile seizures and acute symptomatic seizures due to infections. This situation notwithstanding, in communities where acute febrile illnesses are common, a high occurrence of febrile seizures, especially complex febrile seizures, may lead to brain injury and epilepsy later in life. A family history of febrile convulsions also seems to be strongly associated with epilepsy and one study found an OR of 14.6 (95% CI: 6.3-34.1) (Edwards et al., 2008). This positive family history of febrile seizures among people with epilepsy may reflect susceptibilities to any of the inherited
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epilepsy syndromes that begin with febrile seizures. Alternatively, it may also indicate an epileptogenic role for the febrile seizures, especially if they are repetitive or prolonged.
Infection-Related Risk factors
Meningitis
Only one study looked at the risk of epilepsy after meningitis. This study was carried out in
Senegal and followed 66 children with bacterial meningitis and an equal number of healthy controls for 7 months, looking for the development of neurological sequelae. About 21% of children with meningitis developed epilepsy and the risk of major neurological sequelae was three times higher than for controls (Edmond et al., 2010). In many countries in SSA, inadequate health infrastructure and economic hardship contribute to inadequate treatment of meningitis which often results in high fatality and neurological sequelae, including epilepsy.
HIV Infection
New-onset seizures are common in HIV infection and a majority of these are provoked by CNS opportunistic infections related to the advanced disease (Modi et al., 2009, Siddiqi et al.,
2015). In one German study, it was found that 6.1% of HIV-infected people had new-onset seizures (Kellinghaus et al., 2008). The risk of seizures associated with HIV-infection in SSA is probably significantly higher given the higher prevalence of opportunistic infections. In
Zambia, almost all new-onset seizures in HIV-infected cohort were provoked, and attributable to a variety of CNS opportunistic infections, mainly toxoplasmosis, cryptococcosis and viral encephalitis. Over half of these seizures episodes were multiple and prolonged seizures
(66%); status epilepticus occurred in 15% (Siddiqi et al., 2017, Potchen et al., 2014).
The risk and determinants of long-term epilepsy in HIV infected individuals in SSA are unknown. In this review, none of the case control studies found a significant association between a positive HIV serology and epilepsy. This is surprising given the high prevalence of
HIV and opportunistic infections in SSA and their strong association with new onset seizures and a high rate of seizure recurrence (Siddiqi et al., 2017, Potchen et al., 2014). In one
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Zambian study of 81 people with HIV and new-onset seizures followed for a median of 306 days, 25% developed epilepsy. The risk of epilepsy in this cohort has probably been significantly underestimated because of the relatively short follow-up period and the high case fatality reported (37%) (Siddiqi et al., 2017). The case fatality of people with HIV and new- onset seizures could also be an important source of bias in the case control studies, resulting in a failure to detect a true association. Prospective studies among newly diagnosed HIV positive cohorts should provide a better estimate of the risk of epilepsy associated with HIV infection in SSA. In conclusion, the risk of epilepsy associated with HIV infection in Africa is unknown but seems to be strongly related to the prevalence of advanced HIV disease and opportunistic CNS infections. Early and adequate anti-retroviral treatment may therefore be key in preventing epilepsy in HIV infected people in SSA.
Parasites: See Section 2.3 below.
2.2.5 Conclusion
Most studies of risk factors for epilepsy in SSA have been case-control studies, most of which show an association between epilepsy and a variety of non-infectious factors, especially a family history of epilepsy, perinatal complications predisposing to brain injury and febrile seizures. Infections such as meningitis and parasitic infestations (discussed in detail below) are also strongly linked with epilepsy in most case control studies. There is a need for more prospective cohort studies in SSA to better ascertain the magnitude of certain risk factors associated with epilepsy in SSA.
2.3 Parasites and epilepsy
2.3.1 Summary
Parasitic diseases and epilepsy are common and are both major causes of mortality and disease burden in LMICs. The main objective of this review was to present the epidemiological evidence associating parasites with epilepsy and to discuss potentially important substrates for epileptogenesis. Epilepsy is strongly associated with malaria and neurocysticercosis in
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endemic areas and there is growing evidence that onchocerciasis could also be a major risk factor for epilepsy. For most other parasitic infestations, the risk seems to be limited to specific geographical areas. The risk of epilepsy after parasitic infestations seems to be determined mainly by the degree of cortical involvement and evolution of the primary cortical lesion to gliosis or to a calcified granuloma. Favourable host genetic factors and parasite-specific characteristics could also be involved. In situations where cortical involvement by the parasite is either absent or minimal, parasite-induced epileptogenesis through an autoimmune process seems plausible, based on preliminary evidence. Further research to identify important markers of epileptogenesis in parasitic infestations will have huge implications for the development of trials to halt or delay onset of epilepsy in endemic communities.
2.3.2 Introduction
The higher burden of epilepsy in LMICs than in HICs could, in part, be attributed to the high incidence of brain infections in LMICs (Ba-Diop et al., 2014). There is compelling evidence to support an association between many brain infectious disorders (e.g., bacterial meningitis and viral encephalitis) and epilepsy, but similar evidence for other infectious disorders, including parasitic infestations, has only recently been proposed. The main parasitic infestations frequently associated with epilepsy include cysticercosis, malaria, onchocerciasis, toxoplasmosis, toxocariasis, schistosomiasis, paragonimiasis, trypanosomiasis, and sparganosis (Table 4). Most of these parasites have complex life cycles involving multiple hosts, including humans. The life cycles (reviewed briefly below) are perpetuated in LMICs because of environmental (e.g., poor sanitation), host (e.g., poor hygiene) and agent (e.g., climactic factors favouring vector proliferation) factors (Table 4).
Seizures occurring during the active phase of a parasitic infestation of the brain are usually a result of the inflammatory response in the cerebral cortex directed against the parasite. Very often the seizures cease when the inflammation subsides. Conversely, seizures occurring after recovery from the active infestation are probably the result of long-term structural and physiological effects including hyper-excitation and synchronisation of neurons. The latter, fits
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with the conceptual definition of epilepsy, requiring an enduring predisposition of the brain to develop unprovoked epileptic seizures (Fisher et al., 2005). Understanding the mechanisms that underpin the epileptogenic process in parasitic infestations may be critical in developing targeted interventions for primary and secondary prevention of epilepsy associated with parasites.
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Table 4. Parasites commonly associated with epilepsy
Parasite Type of parasite Brain Disease: Factors favouring Regions most affected mechanism transmission
Plasmodium Protozoa Cerebral Malaria: Good breeding 212 million new cases in 2016 falciparum sequestration, environment for (microparasite) rosetting, impairment vector (Anopheles 90% of cases and 92% of of BBB. mosquitoes) deaths occur in sub-Saharan Africa (WHO, 2015) Taenia solium Trematode Neurocysticercosis: Poor sanitation Endemic in parts of Asia, Latin inflammation causing faecal oral America and sub-Saharan (helminth) provoked by contamination, free- Africa (Ganaba et al., 2011) degenerating brain range pig farming cyst and consumption of infected pork Onchocerca Nematode Nodding Syndrome: Living in proximity to 21 million people worldwide volvulus mechanism not river where the (helminth) known vector (black fly) Over 1 million cases of breeds blindness (99% in sub-Saharan Africa) (Coffeng et al., 2014)
Toxoplasma spp Protozoa Cerebral Contact with cats, Sero-prevalence high Toxoplasmosis: poor food hygiene worldwide because of (microparasite) multiple focal widespread contact with cats parenchymatous (Lafferty, 2006) lesions
Toxocara spp Nematode Cerebral Poor food hygiene, Latent infection common Toxocariasis: contact with dogs worldwide because of (helminth) granulomatous and cats ubiquitous contact with dogs reaction to death of (Lynch et al., 1988) juvenile larva
Schistosoma Trematode Cerebral Human contact with Affects about 200 million people spp Schistosomiasis: fresh water in Latin America, sub-Saharan (helminth) peri-ovular containing larvae Africa and Asia (Ross et al., inflammation and 2002) granulomas 85% occur in Africa (Carod- Artal, 2010) Spirometra Cestode Cerebral Poor food and water Occurs mainly in China, Korea mansoni Sparganosis: hygiene and Japan (Kim et al., 1996) (helminth) intracerebral haematoma, inflammatory tunnels Paragonimus Trematode Cerebral Feeding or cultural Main countries affected are spp Paragonimiasis: habits that promote Cameroon, Nigeria, Liberia, (helminth) peri-ovular consumption of Peru, China, Ecuador, inflammation poorly cooked Philippines and the Republic of crustaceans Korea (Keiser and Utzinger, 2005; Chai, 2013)
Trypanosoma Protozoa Human African Good breeding Occurs in 36 sub-Saharan brucei Trypanosomiasis: environment for the African countries: gambiense (microparasite) neuronal loss vector (tsetse fly) 70% cases occur in the Democratic Republic of Congo (DRC); 2804 reported cases in 2015 (WHO, 2017)
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2.3.3 Malaria and epilepsy
Background
Over 3 billion people world-wide, mainly in Africa and parts of Latin America and Asia, are exposed to malaria. The infective agent is Plasmodium, of which three species (P. ovale, P. malariae, and P. vivax) do not usually produce cerebral involvement, while the other (P. falciparum) frequently implicates the brain, producing severe complications such as cerebral malaria and death, especially in children below 5 years (WHO, 2015). P. falciparum is transmitted by the female anopheles mosquito which injects sporozoites into the blood stream during a human bite. The parasites migrate to the liver of the human where they mature into merozoites and are released to infect red blood cells (RBCs). Within the RBC, merozoites evolve through several stages into schizonts that are eventually released to infect new RBCs
(Figure 2).
Figure 2. Life Cycle of Plasmodium falciparum (CDC, 2016a)
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Cerebral malaria is the most serious and most often fatal complication of falciparum malaria
(Oluwayemi et al., 2013). Criteria to diagnose cerebral malaria in clinical and field practice are well-validated and include profound loss of consciousness lasting >1 hour; asexual parasitaemia on blood films; and exclusion of alternative causes of encephalopathy (Newton et al., 1990). The pathophysiology of cerebral manifestations in malaria has now begun to be understood. Typically, the plasma membranes of parasitised RBCs form knobs containing protein which facilitate adhesion to the endothelial surface of cerebral vasculature
(MacPherson et al., 1985, Turner et al., 1994). Through this process, parasitised RBCs progressively become sequestered within the cerebral micro-circulation and form rosettes with uninfected less deformable RBCs, thereby compromising cerebral blood flow (Doumbo et al.,
2009). Sequestration, rosetting, and the release of several pro-inflammatory substances lead to breakdown of the blood brain barrier (BBB), cerebral ischaemia and, eventually, coma
(Tripathi et al., 2009, Gwer et al., 2012).
Association with seizures and epilepsy
Acute malarial infection is frequently associated with seizures. In children under 5 years old, it is important to distinguish between malaria-associated seizures and febrile seizures; as malaria is responsible for up to 45% of seizures with fever in children in SSA (Familusi and
Sinnette, 1971). Childhood febrile seizures are mostly isolated, generalised and brief. Malaria- associated seizures, however, are often focal (47%), repeated, prolonged (70%) and in cerebral malaria, about half of such seizures are status epilepticus (Waruiru et al., 1996,
Kariuki et al., 2013, Crawley et al., 1996). Unlike febrile seizures which, by definition, occur in a setting of elevated temperature, over half of seizures in children with uncomplicated malaria occur at a time when the rectal temperature is less than 38°C (Waruiru et al., 1996). There is a positive correlation between the level of parasitaemia and the frequency of convulsions
(Hendrickse et al., 1971); this suggests that malaria-associated seizures may be a direct consequence of the effect of parasitised RBCs on the brain micro-vasculature and the BBB
(Newton et al., 1996, Enwonwu et al., 2000). It is clear from these observations that malaria-
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associated seizures have a complex phenotype and that they are a common feature of malaria regardless of its severity. These seizures are, however, pathophysiologically and phenotypically distinct from febrile seizures as well as from unprovoked seizures that occur long after recovery.
Cerebral malaria is strongly associated with an increased risk of subsequent epilepsy
(Brewster et al., 1990, Idro et al., 2010). In Gabon, the odds of prior cerebral malaria episodes were four times higher among people with epilepsy than in people without epilepsy [95% CI:
1.7-8.9] (Ngoungou et al., 2006b). A recent meta-analysis of eight studies reported that cerebral malaria was associated with an increased risk of a wide spectrum of long term neurological sequelae, including epilepsy (OR 4.7; 95% CI: 2.5-8.7) (Christensen and Eslick,
2015). Interestingly, the finding of malaria-specific retinopathy, which has been noted to correlate well with cerebral parasitaemia, has been observed to be predictive of the occurrence of unprovoked seizures or epilepsy (Taylor and Molyneux, 2015). In a prospective study in Malawi, 12 of 132 children with retinopathy-positive cerebral malaria developed epilepsy compared with none of their age-matched 264 non-comatose controls (with non- cerebral malaria) (Birbeck et al., 2010). For yet unknown reasons, there is a distinct group of subjects with clinical cerebral malaria who lack the malaria-specific retinopathy (retinopathy- negative), indirect evidence of a lack of central parasitaemia. While the risk of epilepsy in the retinopathy-negative group is higher than that of non-cerebral malaria subjects, there is apparently no difference in risk of epilepsy between retinopathy-negative and retinopathy- positive survivors of cerebral malaria (Postels et al., 2012). It has been suggested by some that central parasitaemia may not be the only critical factor for the development of cerebral malaria and that retinopathy-positive and retinopathy-negative forms of cerebral malaria may be pathophysiologically distinct but have identical outcomes (Bearden, 2012). Very little is known about the risk of epilepsy associated with uncomplicated malaria. Three case-control studies found no significant association (Ngugi et al., 2013a, Wagner et al., 2014, Kamuyu et al., 2014) (Table 1).
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Epileptogenic Mechanisms
Epileptogenesis in cerebral malaria is not fully understood but may involve several factors
(Figure 3): epileptogenic structural and physiological changes in the brain due to the cerebrovascular effects of CNS parasitaemia (Kampondeni et al., 2013); kindling effects of febrile and/or malaria-associated seizures (Idro et al., 2006, Birbeck et al., 2010); hippocampal sclerosis due to the damaging effects of cerebral malaria on the hippocampus (Kihara et al.,
2009); and an autoimmune process involving the production of IgM against Plasmodium falciparum and specific IgG against a rosetting plasmodium falciparum erythrocyte membrane protein 1 (PfEMP-1) domain (Rovira-Vallbona et al., 2012). Genetic factors could also play a crucial role in epileptogenesis in the aftermath of malaria; it has been shown that a family history of epilepsy is significantly associated with an increased risk of epilepsy and adverse neurological outcome after cerebral malaria (Ngoungou et al., 2006a, Postels et al., 2012). In a genetic study among Gambian children, it was concluded that polymorphisms for certain cytokine genes like homozygotes of the (tumour necrosis factor 2) (TNF2) allele, implicated in the pathogenesis of cerebral malaria, may be associated with a seven-fold increase in the risk of death and neurological sequelae after cerebral malaria (McGuire et al., 1994).
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Immunological Factors Effects of Central Parasitaemia on the Brian
• Coma • Lack of premunity to cerebral malaria
• Vasculopathy leading to granuloma formation • Antibodies to the voltage-gated calcium
• Inflammation and gliosis channels
• Hippocampal sclerosis • Low levels of IgG and IgM to certain Plasmodium falciparum antigens especially • Demyelination PfEMP • Focal cortical defects
• Generation of excitotoxic amino acids Genetic Factors • Increased mRNA expression of pro- inflammatory cytokines • Inherited or acquired genetic predisposition to epilepsy
• Polymorphisms to certain Effects of malaria- cytokine genes predisposing to associated seizures and cerebral malaria febrile seizures • Genetic predisposition to febrile seizures or early reactive • Kindling effect of malaria seizures associated seizures and febrile seizure
• Brain injury from status epilepticus
Tendency for recurrent unprovoked seizures
Figure 3. Possible epileptogenic substrates of malaria
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2.3.4 Cysticercosis and Epilepsy
Background
Taeniasis/cysticercosis complex is a neglected tropical disease of humans and pigs, occurring predominantly in pig-rearing communities in LMICs (Ganaba et al., 2011). The adult tapeworm, Taenia solium, (a cestode) inhabits the human intestines and there, releases thousands of eggs. The eggs contaminate the environment during defaecation in open areas because of the lack of sanitary methods of faecal disposal. Free-ranging pigs then ingest eggs, which develop into larvae which, in turn, penetrate the intestines and migrate to various organs, forming cysts. When humans consume cysts contained in under-cooked pork from infested pigs, these cysts liberate larvae which evolve to the adult worm in their intestines, causing Taeniasis. Neurocysticercosis, however, occurs when humans become aberrant intermediate hosts and ingest the eggs which develop into onchospheres and penetrate the intestinal wall to migrate to the brain, where they form cysticerci. This represents the most serious consequence of Taenia solium infestation in humans (Figure 4 and Table 5).
Figure 4. Life Cycle of Taenia solium adapted from Nash and Garcia, 2011
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Parasites that lodge in the brain parenchyma evolve through four main stages: vesicular, colloidal, granulo-nodular and granulomatous/calcified stages. The vesicular stage is asymptomatic and comprises a live, viable cyst, containing the invaginated scolex of the parasite and cyst fluid, surrounded by an unenhanced cyst wall. The parasite evades destruction through a complex process of immune tolerance and the ability of the cyst wall to suppress the release of pro-inflammatory cytokines (Verma et al., 2011, Amit et al., 2011).
The colloidal cyst, which is often symptomatic, represents the early degenerative (active) stage of the cyst and is characterised by destruction of the parasite, releasing antigens which trigger an intense inflammatory response leading to a disruption of the BBB (Verma et al.,
2011, Amit et al., 2011). In the granular-nodular stage, progressive degeneration of the cyst transforms it into a small nodular lesion with small ring enhancement on imaging. From this stage the parasite either involutes or evolves to a granulomatous calcified lesion (Lerner et al., 2012).
Association with seizures and epilepsy
Seizures can occur at any stage of neurocysticercosis, although the provoking factors vary depending on the stage. There is a theoretical distinction between acute symptomatic seizures provoked by degeneration of the parasite, as evidenced by at least one degenerative parasite on neuroimaging, and remote symptomatic seizures, occurring beyond the degenerative stage, a reflection of differences in the mechanisms involved (Beghi et al., 2010). The inflammatory cascade described earlier and the resulting angiogenesis and impairment of the
BBB are important triggers of seizures in the degenerative or active stage (Gupta et al., 2013) and this is confirmed by neurophysiological and imaging studies showing that focal EEG abnormalities correlate with cyst location and “activity” (Chayasirisobhon et al., 1999). The exact mechanism of remote symptomatic seizures is not yet fully understood; a few hypotheses are briefly discussed below. From a practical perspective, the distinction between acute and remote symptomatic needs to be interpreted with caution because there might be a combination of calcific and active neurocysticercosis lesions in the same individual at a given
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time, hence it is difficult to ascertain which lesion is provoking the seizures. Extreme variability of the duration of the various stages of the cyst also makes it challenging to determine a time period within which to differentiate between acute and remote symptomatic seizures (Carpio and Romo, 2014), especially in LMICs where neuroimaging facilities are not widely available.
An estimated 30% to 40% of adult-onset epilepsy in Africa and Latin America has been attributed to neurocysticercosis (Arruda, 1991, Nicoletti et al., 2005, Millogo et al., 2012). A recent systematic review of studies evaluating the risk of epilepsy associated with neurocysticercosis or cysticercosis reported an OR of 2.7 (95% CI: 2.1-3.6) (Debacq et al.,
2017). Some determinants of long-term epilepsy include the presence of a calcified lesion, co- existence of multiple cysts and recurrent acute seizures at presentation (Del Brutto, 1994). A few studies in communities where pig rearing is common have failed to show any association between neurocysticercosis and epilepsy (Secka et al., 2010, Elliott et al., 2013). While differences in methods could explain these discrepancies, there could be differences between communities in susceptibility to neurocysticercosis and its complications because of genetic variation of Taenia solium species or acquired immunity to the parasite (Vega et al., 2003,
Campbell et al., 2006, Jayaraman et al., 2011). It should, however, be noted that in areas where neurocysticercosis and epilepsy are endemic, the two conditions could coexist independently due to shared environmental or socio-economic factors.
Epileptogenic mechanisms (Figure 5)
The main epileptogenic substrate in neurocysticercosis is the formation of the calcified cysticercus granuloma with its accompanying perilesional oedema (Rajshekhar and
Jeyaseelan, 2004, Sharma et al., 2011, Rathore et al., 2013). Perilesional oedema is thought to be the result of an inflammatory response to the intermittent release of antigenic remnants of the parasite in the calcified lesion (Gupta et al., 2002, Fujita et al., 2013). The calcified granuloma could also predispose to long-term seizures by facilitating gliosis in cortical tissue; perilesional gliosis has been shown to correlate with epileptic events (Pradhan et al., 2003).
Another important plausible mechanism for epileptogenesis in neurocysticercosis is
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hippocampal sclerosis either due to the kindling effect of the acute symptomatic seizures or the damaging effect of the parasite itself on the hippocampus. This is supported by evidence showing an association between neurocysticercosis and temporal lobe epilepsy and a frequent correlation between the side of the calcified lesion and that of the hippocampal sclerosis (Bianchin et al., 2013, Rathore et al., 2013, Bianchin et al., 2014).
Certain genetic factors of the host are important in determining the severity of the inflammatory response to neurocysticercosis. There is evidence that Toll-like receptor 4 (TLR4) genetic polymorphism is a risk factor for the development of epilepsy in people with neurocysticercosis by contributing to alteration of the Th1/Th2 axis, favouring inflammation (Verma et al., 2010).
In one study, significantly higher matrix metalloproteinase 9 (MMP-9) gene polymorphism with differential upregulation of MMP-9 was observed in people with symptomatic neurocysticercosis compared with those with no symptoms (Gupta et al., 2012). Studies that looked at family history of epilepsy as a risk factor for epilepsy after neurocysticercosis have so far reported inconsistent results (Kelvin et al., 2009, Blocher et al., 2011, Sharma et al.,
2011).
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Calcified lesion Gliosis
• Perilesional oedema around • Irritation of the cortex calcified granuloma • Initial precipitating injury on • Neo-angiogenesis hippocampus • Toxicity of calcium on
surrounding cortex • Initial precipitating injury on hippocampus
Hippocampal sclerosis Host and/or parasite factors
• Initial precipitating injury • Preferential neural caused by calcified lesion tropism of certain or gliosis parasite species • Kindling effect of reactive • Host Toll-like receptor-4 seizures and status genetic polymorphism epilepticus favouring inflammation • Pre-existing hippocampal • MMP-9 gene malformation polymorphism • Effects of MMP-9 on the Tendency for unprovoked seizures • Pre-existing sub-clinical synaptic physiology epileptogenic lesion
Figure 5. Possible epileptogenic substrates in neurocysticercosis
2.3.5 Onchocerciasis, epilepsy and nodding syndrome
Onchocerciasis (river blindness) is an infestation by microfilariae and the adult worm of
Onchocerca volvulus, which affects over 21 million people, mostly in SSA. Isolated foci also exist in Yemen and Latin America (Coffeng et al., 2014). Humans are the only definitive host
(Figure 6). The larvae of the Onchocerca volvulus are introduced into humans by the simulium
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fly during a blood meal. The larva develops into an adult worm and the female permanently incarcerates itself in a subcutaneous fibrous capsule and releases 1300–1900 microfilariae per day which predominantly migrate to the skin and eye (Burnham, 1998). When microfilariae reach the eye, they provoke neutrophil and eosinophil infiltration and the release of cytokines into the corneal stroma (Gillette-Ferguson et al., 2007, Pearlman and Gillette-Ferguson,
2007). Wolbachia are rickettsiae transmitted together with Onchocerca volvulus by the simulium fly and, by promoting larval development and adult worm fertility, are important in the pathogenesis of onchocerciasis (Hise et al., 2003). In chronic infestation, repeated microfilaria invasion of the cornea and the release of Wolbachia from worm degeneration sustains inflammation, resulting in corneal opacification, loss of vision and blindness
(Pearlman and Gillette-Ferguson, 2007).
Figure 6. Life Cycle of Onchocerca volvulus (CDC, 2016b)
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Evidence of association with epilepsy
The clinical manifestations of onchocerciasis have been traditionally confined to involvement of the eye and skin. The ocular manifestations comprise corneal scaring and blindness, while the cutaneous involvement takes the form of papular lesions and nodular scarring (Pearlman and Gillette-Ferguson, 2007). In addition, an association of onchocerciasis with seizures and epilepsy has been proposed based on accruing evidence from population-based observational studies. For example, in Cameroon and the Democratic Republic of Congo, the prevalence of epilepsy has been shown to increase with proximity to rivers, which are good breeding grounds for the simulium fly (Boussinesq et al., 2002, Colebunders et al., 2016b). In parts of West,
East and Central Africa, there exists a positive correlation between hyperendemicity of onchocerciasis and a high prevalence of epilepsy in many communities (Ovuga et al., 1992,
Kaiser et al., 1996b, Kaiser et al., 1998, Newell et al., 1997, Boussinesq et al., 2002). Several case-control studies, using varied methods, have shown significantly higher prevalence of onchocerciasis in people with epilepsy compared with controls (Ovuga et al., 1992, Kaiser et al., 1996b, Newell et al., 1997, Boussinesq et al., 2002, Kaiser et al., 2011). Others, however, have failed to demonstrate any association between the two conditions (Kabore et al., 1996,
Druet-Cabanac et al., 1999, Farnarier et al., 2000, Konig et al., 2010, Prischich et al., 2008).
The results of a recent meta-analysis were inconclusive, although it was observed that the strength of the association increased with precision of onchocerciasis diagnosis (Kaiser et al.,
2013). While the demonstration of an association between onchocerciasis and epilepsy in observational studies could be co-incidental due to shared environmental risk factors, accumulating evidence from clinical and experimental studies suggests a causal relationship and implicates onchocerciasis in the development of a severe epileptic encephalopathy in childhood, known as Nodding Syndrome (see below).
Evidence of association with Nodding Syndrome
Nodding syndrome (NS) is a unique epileptic encephalopathy occurring in epidemics within specific communities in South Sudan, Tanzania, and Uganda and typically starting in children
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between the ages of 5 and 15 years (Foltz et al., 2013). It is characterised by head nodding in a previously healthy child who then experiences progressive physical and mental growth retardation, psychiatric problems and increasing frequency and severity of the nodding episodes (Lacey, 2003, Idro et al., 2013a, Sejvar et al., 2013). The head nodding episodes have a striking resemblance to reflex epilepsies, given their systematic association with several triggers such as exposure to heat or cold, the sight of food, eating, and sensory stimuli
(Winkler et al., 2008, Spencer et al., 2013). Seizure types observed in children with NS include absences, myoclonic seizures and generalised tonic-clonic seizures; these typically start within 1-3 years of the onset of head nodding (Idro et al., 2013b, Sejvar et al., 2013, Winkler et al., 2014).
The aetiology of NS remains a mystery despite its unique epidemiological profile. Of all the studies investigating a wide variety of possible aetiologies, onchocerciasis has been most consistently associated with NS (Lacey, 2003, Foltz et al., 2013). Imaging studies show positive correlations between onchocerciasis and a variety of Magnetic Resonance Imaging
(MRI) changes associated with NS. In a prospective clinical and imaging study of NS involving
62 individuals in Tanzania, MRI abnormalities correlated with a positive skin polymerase chain reaction (PCR) to Onchocerca volvulus, although cerebro-spinal fluid (CSF) analysis was negative for the parasite (Winkler et al., 2014). Findings of cortical, sub-cortical, and cerebellar atrophy among people with NS could reflect sequelae of an inflammatory reaction, suggesting present or past brain invasion by the parasite (Idro et al., 2013b, Sejvar et al., 2013, Winkler et al., 2013). In Tanzania, MRI in 32 people with epilepsy, of whom 12 had NS, showed a tendency for correlation between intra-parenchymal cerebral pathologies and infection with
Onchocerca volvulus; this was most pronounced in children and adolescents with NS compared with those with other types of epilepsy (Winkler et al., 2013). It has also been shown that a dysfunction in the growth hormone and gonadal axis is the main culprit for growth failure observed in adolescents with NS (Piloya-Were et al., 2014). This dysfunction raises the possibility of direct infiltration of the pituitary gland by microfilariae provoking inflammation. It
45
Chapter 2: Literature review
could also be a secondary manifestation of a severe malnutrition related to onchocerciasis known as the Nakalanga Syndrome; this syndrome affects children who, after normal infant and early childhood development before the age of 8 years, experience physical and mental retardation, skeletal abnormalities and failure to develop secondary sexual characteristics
(Kipp et al., 1996). In a study in Burundi, all nine people with epilepsy and growth retardation had some manifestation of the Nakalanga Syndrome and all tested positive for onchocerciasis
(by skin snip or ELISA) (Newell et al., 1997). In conclusion, whereas there is strong evidence from clinical and imaging studies linking Onchocerciasis with epilepsy, the lack of evidence so far supporting the presence of Onchocerca volvulus in the brain of people with NS is a mystery and needs to be clarified.
Possible epileptogenic mechanisms
Several plausible hypothetical mechanisms have been advanced to justify a causal relationship between onchocerciasis, epilepsy and NS (Figure 7). The possibility of cerebral lesions occurring as a result of direct infestation of the brain by microfilariae released in large numbers by the adult worms is interesting given that microfilarial load seems to correlate with the epilepsy risk. Access of microfilariae to the brain could occur naturally due to high microfilarial load or following anti-parasitic treatment. It has been suggested that anti-filarial treatment (Ivermectin) could facilitate access of microfilariae into the blood and CNS through inflammation and breakdown of the BBB, provoked by the release of parasite antigens
(Edwards, 2003). This is supported by correlation between microfilarial load and the risk of epilepsy and evidence of the appearance of microfilariae in the blood, urine or CSF following anti-filarial treatment (Fuglsang and Anderson, 1973) (Duke et al., 1976). The lack of inflammatory markers in the CSF does not support this theory (Konig et al., 2010) and CSF contamination by microfilariae from blood or the skin remains a possibility.
Onchocerciasis could also cause epilepsy through an autoimmune process. Similarities have been shown between E1 antigens of Onchocerca volvulus and several ankyrin-related neuronal proteins (Erttmann et al., 1996). This raises the possibility of an autoimmune
46
Chapter 2: Literature review
phenomenon (similar to that which occurs in the skin manifestation of the disease) as a cause of epilepsy in onchocerciasis. More recently, some evidence shows that antibodies to leiomodin-1, a protein that is cross-reactive with Onchocerca volvulus antigens, are more common in the sera and the CSF of people with NS compared with healthy controls and, in mice, leimodin-1 is preferentially expressed in parts of the mouse brain affected in people with
NS (Johnson and Tyagi, 2017).
Finally, it is possible that onchocerciasis causes epilepsy or NS through its endosymbiotic relationship with Wolbachia or another unknown pathogen with which it is transmitted. Chronic filariasis has a modulatory effect on the immune system and thus suppresses inflammation
(Gondorf et al., 2015). Death of microfilariae, could release Wolbachia antigens, triggering an inflammatory response that results in breakdown of the BBB, enabling access of either microfilaria or Wolbachia, or both, into the brain. Epileptic seizures could then result from a sustained inflammatory response leading to neuronal loss and gliosis as a result of repeated exposure to Wolbachia. If this were the case, one would expect Wolbachia or inflammatory markers in the CSF to reflect the ongoing inflammatory process. These have not been shown so far (Konig et al., 2010).
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Chapter 2: Literature review
Autoimmune phenomena Similarities between antigens of O. volvulus and ankyrin-related proteins in parts of the neuronal cell Host predisposition Antibodies to leiomodin-1, a protein cross- Chronic ill-health due to reacting with O. volvulus and expressed in onchocerciasis human neurons Severe malnutrition
Nakalanga syndrome Invasion of brain by microfilariae and/or wolbachia Findings of microfilariae in blood urine and cerebrospinal fluid; microfilariae load correlates positively with risk of epilepsy; Wolbachia burden associated with disease severity.
?
Nodding Syndrome Recurrent unprovoked seizures
? ?
Other possible causes of Nodding syndrome • Unknown neurotropic virus • Toxins • Micronutrient deficiency • Another unknown pathogen
Figure 7. Possible epileptogenic pathways of onchocerciasis
48
Chapter 2: Literature review
2.3.6 Toxocariasis and epilepsy
Toxocariasis is a common zoonotic infestation by larvae of Toxocara spp, a nematode which inhabits the gut of dogs (Toxocara canis) and cats (Toxocara catis) (Glickman and Schantz,
1981). In humans, ingested embryonated eggs persist in the juvenile larval stages, penetrate through the gut wall and migrate to several body organs including the brain (Despommier,
2003). As exposure to dogs is ubiquitous, infestation is common worldwide, both in HICs and
LMICs (Stensvold et al., 2009). Toxocariasis may present with a wide variety of acute neurological syndromes, including seizures, meningo-encephalitis, behavioural disorders, cerebral vasculitis, space occupying lesions and encephalomyelitis (Despommier, 2003,
Helsen et al., 2011, Marx et al., 2007, Vidal et al., 2003). Chronic infestation is much more common and thought to be associated with epilepsy in some LMICs and possibly HICs.
Several case–control studies report significant associations between exposure to Toxocara spp (using serology) and epilepsy in diverse populations in Europe (Arpino et al., 1990,
Nicoletti et al., 2008), South America (Nicoletti et al., 2002), Asia (Zibaei et al., 2013) and
Africa (Nicoletti et al., 2007, Kamuyu et al., 2014). A systematic review of seven studies estimated the pooled odds of exposure to Toxocara spp of 1.9 [CI: 1.5-2.4] implying an association between exposure and epilepsy (Quattrocchi et al., 2012); this association is not necessarily causal. An alternative explanation is that people with epilepsy are likely to be exposed to Toxocara eggs, which abound in the soil, while falling to the ground during seizures. Shared risk factors such as poor socio-economic status could also explain the co- existence of toxocariasis and epilepsy in some people.
Epileptogenesis in toxocariasis may be determined by the degree of parasitic invasion of the brain. Several animal experiments suggest that chronic infestation is crucial in determining the degree of CNS involvement in Toxocariasis; larvae become progressively more neurotrophic as the infestation progresses (Holland and Hamilton, 2013, Eid et al., 2015, Othman et al.,
2010). These experiments also show that chronic infestation results in astrogliosis, increased expression of pro-inflammatory cytokines and significant disturbances in neurotransmitter
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Chapter 2: Literature review
profile favouring excitation (Liao et al., 2008, Eid et al., 2015, Othman et al., 2010). The same mechanism could be responsible for epileptogenesis in humans.
2.3.7 Toxoplasmosis and epilepsy
Toxoplasmosis is a zoonotic infestation of humans and cats caused by Toxoplasma gondii, a ubiquitous obligate intracellular protozoan. The sero-prevalence of toxoplasmosis varies between 15% and 85% depending on population factors such as feeding and cultural habits, the level of food and water hygiene, and contact with cats (Lafferty, 2006). Domestic cats and their relatives are the only known definitive hosts and they shed large quantities of un- sporulated oocysts of the parasite in their faeces. Humans are intermediates hosts and after cysts are ingested from various food sources, the parasite traverses the intestinal lumen and migrates to the brain with the help of macrophages. Parasites in the neurons undergo proliferation, while those in microglial cells and other cells of the immune system upregulate genes encoding pro-inflammatory and anti-inflammatory cytokines (Suzuki, 2002b, Suzuki,
2002a). The resulting delicate balance between pro-inflammatory and anti-inflammatory factors, which ensures control of the infection in the host by effectively halting the replication of the parasite, is lost in immunocompromised people causing multiple focal parenchymatous lesions and encephalopathy (Weisberg et al., 1988). Chronic toxoplasmosis is traditionally considered to be asymptomatic in immunocompetent people, although it is increasingly linked with epilepsy and other neuropsychiatric conditions such as depression, schizophrenia and memory impairment (Alvarado-Esquivel et al., 2011, Gajewski et al., 2014). Two large community-based studies in several African countries both reported slightly increased odds of exposure to Toxoplasma gondii among people with epilepsy compared with healthy controls
(Ngugi et al., 2013a, Kamuyu et al., 2014). A recent systematic review revealed an OR of 2.3
(95% CI: 1.3-3.9) (Ngoungou et al., 2015a).
The possible mechanisms of epileptogenesis in toxoplasmosis are mostly hypothetical.
Studies show that toxoplasmosis can lead to modification of behaviour and reduced psychomotor performance through its effect on dopamine and testosterone (Flegr, 2007), and
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Chapter 2: Literature review
that people with chronic toxoplasmosis are at increased risk of road traffic accidents (Flegr et al., 2002, Yereli et al., 2006, Kocazeybek et al., 2009) which could in turn increase the risk of post-traumatic epilepsy. Human behavioural modification by toxoplasma could also predispose to epilepsy by promoting exposure to other parasites which cause epilepsy. People with toxoplasmosis have two times higher odds of being co-infected with Toxocara spp, another risk factor for epilepsy (Jones et al., 2008).
2.3.8 Schistosomiasis and epilepsy
Schistosomiasis is a parasitic disease of humans caused by various species of the trematode,
Schistosoma spp, which affects over 200 million people, mostly in Africa (Ross et al., 2002).
In developed countries, schistosomiasis is often encountered in people who travel to endemic areas and complications sometimes occur several years after the initial exposure (Rose et al.,
2014). Three mains species of Schistosoma are frequently encountered in human disease: S. mansoni, haematobium and japonicum. Humans are infested through contact with fresh water that contains free-swimming larvae called cercariae, which penetrate the skin, enter the venous circulation and migrate through the lungs to the portal circulation where they form pairs and move to the mesenteric veins or the vesical plexus and produce eggs (Ross et al., 2002).
The eggs pass into the lumen of the intestines (S. japonicum and S. mansoni) and the bladder
(S. haematobium) and are shed in faeces or urine (Ross et al., 2002). In endemic areas, cerebral invasion by the eggs of Schistosoma spp is common and can affect over one quarter of the population, although most of these individuals are asymptomatic (Scrimgeour and
Gajdusek, 1985). The inflammatory reaction to the parasite ranges from mild inflammation around scattered ova to severe peri-ovular inflammation, forming giant granulomas (Carod-
Artal, 2010, Ross et al., 2002). Cerebral schistosomiasis can present acutely as a diffuse encephalopathy, especially in immunocompromised people. Sub-acute and chronic manifestations are, however, more common and present as focal neurological deficits, seizures and headache (Ferrari and Moreira, 2011). Acute seizures in cerebral schistosomiasis result mainly from the granulomatous reaction to the presence of the eggs of
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Chapter 2: Literature review
the parasite in the brain (Betting et al., 2005). To date, no epidemiological studies have assessed the risk of epilepsy associated with exposure to schistosomiasis. Meanwhile, there are case reports of seizures occurring several years after exposure to Schistosoma spp (Rose et al., 2014) including in people in whom ova deposition was initially asymptomatic (Hayashi,
1979).
2.3.9 Paragonimiasis and epilepsy
Paragonimiasis is a food-borne zoonotic infestation caused by a trematode of the genus
Paragonimus; it is endemic in many countries in Asia, Africa and South America and the risk of infestation is highest in villages near freshwater bodies where the intermediate hosts live
(Keiser and Utzinger, 2005). Paragonimus westermani is the main species responsible for human paragonimiasis worldwide. Humans are the definitive host and become infested after consumption of the larvae from raw or poorly cooked crustaceans. The adults live in pairs in the lungs and form cysts which rupture into airways, releasing eggs which are either expelled in sputum or swallowed and passed in faeces (Procop, 2009). Cerebral paragonimiasis is the most common form of extra-pulmonary paragonimiasis and accounts for over 50% of such cases (Kusner and King, 1993). Inflammation in the brain ultimately results in the formation of granulomas which may become calcified and appear as multiple cystic calcifications with a soap bubble appearance on plain skull X-Rays (Oh, 1967, Procop, 2009) or conglomerate calcifications on CT (Kusner and King, 1993). Cerebral paragonimiasis is often symptomatic, although the symptoms may set in insidiously, taking months to years to develop. It is a great mimic of other CNS conditions such as cerebral tuberculoma or cerebrovascular disorders
(Chen et al., 2008, Singh et al., 2011, Wu et al., 2013). Consequently, in endemic LMICs it may only be diagnosed after severe complications such as epilepsy, headache, visual disturbance, and motor and sensory disturbances have been established (Chai, 2013).
Epileptic seizures (acute symptomatic seizures, new onset seizures, recurrent unprovoked seizures and status epilepticus) are the most common presentation of paragonimiasis (Chai,
2013). Acute seizures are likely to be caused by the inflammation, arteritis, haemorrhage and
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Chapter 2: Literature review
mass effect while late seizures may result from the calcified lesions and gliosis. To date, there have been no case-control studies to investigate an association between paragonimiasis and epilepsy at the population level.
2.3.10 Sparganosis and epilepsy
Sparganosis is a rare human parasitic disease caused by sparganum which is the plerocercoid larva of the cestode, Spirometra mansoni. This parasite is mostly limited to China, Japan,
Korea and Taiwan. Cats and dogs are the definitive host and harbour the adult worms which shed eggs that are passed out in faeces. Once in water, the eggs hatch and release larvae that evolve through several stages in the first intermediate host, copepods, which are fresh water crustaceans and in second intermediate hosts which include snakes, frogs and chickens. Humans become infested either from accidentally drinking water contaminated with copepods or from eating poorly cooked intermediate hosts which contain sparganum which migrates and lodges mostly in muscles or subcutaneous tissue. Cerebral sparganosis is rare and usually presents chronically as recurrent headaches or epileptic seizures, sometimes mimicking a brain tumour (Lo Presti et al., 2015). Surgical specimens from people with cerebral sparganosis reveal many inflammatory tunnels which are either eosinophilic or contain live or degenerate larvae which correlate with the tunnel-like and ring-like enhancements on MRI (Hong et al., 2013), representing tracks of the migration of the parasite within the brain (Shirakawa et al., 2010). Cerebral migration of the parasite and the accompanying granulomatous reaction is probably responsible for the focal neurological deficits observed in cerebral sparganosis, including epileptic seizures (Kim et al., 1997). It is difficult to estimate how much sparganosis contributes to the burden of epilepsy. The only epidemiological study was carried out in Korea and compared serology to anti-sparganum antibodies between 2,667 randomly selected people with epilepsy and 858 healthy controls.
The seropositive rate was higher among the people with epilepsy (2.5%) than in healthy controls (1.9%) with an odds ratio of 1.32 (Kong et al., 1994).
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Chapter 2: Literature review
2.3.11 Human African Trypanosomiasis and epilepsy
Human African Trypanosomiasis (HAT), also known as sleeping sickness, is a disease that is limited to rural communities in about 36 SSA countries where its vector (tsetse fly) is found
(WHO, 2017b). It is caused by protozoa of the genus Trypanosoma, and Trypanosoma brucei gambiense is responsible for 98% of cases. The parasite is transmitted to humans by bites from infected tsetse flies which acquire the infection by biting infected humans or animals. In the acute phase, parasites multiply in lymph nodes and the blood, sometimes causing non- specific symptoms such as fever, headache, stiffness and pains in the joints. In the chronic stage, parasites cross the blood brain barrier to the CNS where they cause a wide range of neurological symptoms including seizures, psychiatric disorders, movement disorders, coma and death. Sustained control efforts by the WHO have led to a steady drop in the burden of the disease; the number of reported cases dropped from 17,616 in 2004, through 9878 in
2009, to 2804 cases in 2015 (WHO, 2017b). There are currently no population studies of the risk of epilepsy associated with trypanosomiasis.
54
Chapter 2: Literature review
n
lesional
-
level
-
Wolbachia
acquired risk factors of epilepsy such as epilepsy acquiredrisk of factors
inflammatory cytokines inflammatory
-
status and seizures,seizures febrile associated -
malaria
to calcified granuloma with accompanying peri accompanying granuloma calcified with to
Probable facilitators of lateseizures Probablerecurrent of facilitators
tation caused by blood products from cerebral haemorrhage cerebral from blood products by caused tation
immune phenomena immune -
epilepticus damage irri Cortical Parenchymal brain damage due to effects of coma and central central and of to coma due damage brain Parenchymal effects parasitaemia effectKindling of Demyelination,granuloma and gliosis cystEvolutionof oedema gliosisHippocampal to due sclerosis low chronic and seizures symptomatic acute effectKindling of granuloma calcified inflammationthe in Auto or Brainmicrofilariae by invasion of risk brai and ofneurotropismparasite the Chronic increases infestation Astrogliosis Increasedpro of expression favouring excitation profile, Disturbancesinneurotransmitter parasite Neuronalthe by damage species oxygen substances reactive and Productionof excitotoxic psychomotor behaviourreduced manipulationand of Gene upregulation, other exposingperformance,to headinjury ova oracuteasymptomatic from infection the granulomaGliosisin from deposition Calcifiedgliosis lesion and Gliosis Neuronalloss
: multiple
: little or no or little :
vasculature; vasculature;
-
infestation
halopathy
angiogenesis
-
ute neurologicalfeatures ute
compromised hosts compromised
-
ischaemic effects of parasitised ischaemicof effects
parasitic
-
Seizures Causes of Acute
in
ovular inflammation and formation formation andinflammation ovular
-
hypoglycaemia rare seizures phase so RBCs on cerebral microcerebralRBCson disturbance; fever; anaemia; electrolyte of Larvalcauseantigens release of breakdown inflammatorycytokines, theneo BBB and No ac known acutelittle the in Very inflammation Immuno inflammatory focalparenchymatous lesionsencep and Immunocompetent hosts inflammation Peri haemorrhage cerebral of granuloma, haemorrhageInflammation, arteritis, massandeffect Granulomatousreaction
Hypoxic
seizures
late
and
Disease
reactive
Malaria Neurocysticercosis Onchocerciasis Toxocariasis Toxoplasmosis Schistosomiasis Paragonimiasis Sparganosis Human African Trypanosomiasis
early
of
termani
s
rucei
b
we
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.
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5
Plasmodium Taenia Onchocerca Toxocara Toxoplasma Schistosoma Paragonimus Spirometra Trypan gambiense
Table 55
Chapter 2: Literature review
2.3.12 Conclusion
Epilepsy is strongly associated with malaria and neurocysticercosis in endemic areas and there is growing evidence that onchocerciasis could also be a major risk factor for epilepsy.
For most other parasitic infestations, the risk seems to be limited to specific geographical areas. The risk of epilepsy after parasitic infestation seems mainly determined by the degree of cortical involvement and the evolution of the primary lesion to gliosis or to a calcified granuloma. Favourable host genetic factors and parasite-specific characteristics are also likely to be involved. In situations where direct cortical involvement by the parasite is either absent or minimal, parasite-induced epileptogenesis through an autoimmune process seems plausible, based on preliminary evidence. Further research to identify important markers of epileptogenesis in parasitic infestations is necessary for the development of trials to halt or delay onset of epilepsy in endemic areas.
2.4 Comorbidities of epilepsy
People with epilepsy are at greater risk of psychiatric, neurodegenerative and medical conditions than the general population, (Gaitatzis et al., 2004). The exact extent and nature of this association is unclear and these conditions could co-exist with epilepsy in an individual as a dual pathology due to a shared aetiology or because of a causal relationship. These comorbidities often have a negative impact on the quality of life of people with epilepsy, sometimes more than the seizures themselves (Linehan et al., 2011). In SSA, there is a huge stigma associated with epilepsy which often results in social exclusion of people with epilepsy with devastating consequences on the quality of life of people affected and their families
(Baskind and Birbeck, 2005).
2.5 Premature mortality in epilepsy
People with epilepsy generally have an increased risk of premature death which could be related to epilepsy, its underlying aetiology or to other causes unrelated to epilepsy.
Premature mortality is high in LMICs as well as HICs, although there is an excess mortality in
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Chapter 2: Literature review
LMICs which is largely due to higher rates of status epilepticus, injury and drowning because of limited access to treatment (Levira et al., 2017). Meanwhile in HICs, premature mortality is especially high in people with other comorbidities, when seizures are secondary to metabolic conditions and when the seizures are convulsive (Thurman et al., 2017, Keezer et al., 2016).
Important seizure-related causes of premature mortality in both HICs and LMICs include status epilepticus, sudden unexpected death in epilepsy (SUDEP), and unintentional injuries
(Thurman et al., 2017). Most risk factors for premature mortality are preventable and it is important that this is addressed by health professionals taking care of people with epilepsy and policy makers.
2.6 Redressing the burden of epilepsy in SSA: the way ahead
2.6.1 Clarifying the relationship between epilepsy and a variety of factors
Previously, most studies investigating risk factors of epilepsy in SSA have been case-control studies and, although many have shown an association with epilepsy, the relationship remains equivocal in most cases. Even for factors which have been consistently associated with epilepsy, this does not necessarily prove causation. One essential prerequisite for causality is to demonstrate that exposure to the risk factor preceded the onset of seizures. Once association has been established in cross-sectional and case-control studies, it is important that robust prospective longitudinal studies as well as experimental studies are carried out to ascertain any causal relationship with epilepsy. Longitudinal cohort studies are well suited for the investigation of many risk factors for epilepsy and present several other advantages: they will clarify the temporal relationship between the risk factor and epilepsy; they can more accurately estimate the incidence and burden of epilepsy than cross-sectional studies; and they can be instrumental in the evaluation of the effectiveness of interventions to prevent epilepsy or to improve access to care. Increasing the use of contemporary neurophysiological and neuroimaging tools, where available, in epilepsy studies will greatly improve the
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understanding of the epileptogenic substrates involved. Epilepsy studies in Africa that have used (Electroencephalogram) EEG and MRI technology have greatly improved our understanding of epilepsy related to neurocysticercosis, in the aftermath of cerebral malaria and in nodding syndrome. From a public health perspective, a logical final step once a risk factor has been unequivocally associated with epilepsy is to determine the population attributable fraction of epilepsy, which reflects the proportion that can be prevented by elimination of the risk factor. Such estimates will be important in advocating policies that aim to prevent epilepsy by targeting specific risk factors in some communities
2.6.2 Preventing epilepsy by targeting parasites in endemic areas
As discussed earlier, there is strong evidence to suggest that parasites, especially Taenia solium, Plasmodium falciparum and possibly Onchocerca volvulus, are mainly responsible for the high incidence and prevalence of epilepsy in LMICs. Targeting these parasites could therefore be an effective strategy to rapidly reduce the incidence of epilepsy in these regions.
Previously, the focus has been on improving access to diagnosis and treatment of parasitic infestation. Prompt diagnosis and treatment of cerebral malaria with anti-malarial medication will probably reduce the morbidity and mortality of cerebral malaria although its impact on epilepsy prevention may be difficult to ascertain because of the increased likelihood of new cases of epilepsy associated with improved survival. For neurocysticercosis, anti-parasitic treatment is controversial. Trials have shown that, although treatment with albendazole in people with neurocysticercosis can lead to a modest reduction in the risk of recurrent seizures in the short-term, its effect on the long-term risk of epilepsy is unknown and probably negligible
(Abba et al., 2010). In addition, it targets mainly people with symptomatic neurocysticercosis, hence only a small proportion of people with taeniasis or cysticercosis who are at risk of epilepsy.
Parasite elimination may be an effective strategy, therefore, to prevent epilepsy in endemic countries. In Honduras, parasite control measures that included improved sanitation, education and sensitisation, and yearly deworming of students over an 8-year period led to a
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decrease in the incidence of epilepsy and a three-fold drop in neurocysticercosis-associated epilepsy (Medina et al., 2011). An even bigger impact could be achieved with elimination of the parasite and recent evidence suggests that Taenia solium elimination is feasible. In Peru, a trial of repeated mass chemotherapy of humans and pigs combined with vaccination of pigs, was effective in considerably reducing porcine and human cysticercosis in an endemic population (Garcia et al., 2016). Replication of such interventions in other cysticercosis endemic areas in parallel with longitudinal epilepsy studies could hopefully yield more evidence on its feasibility, sustainability, and effectiveness in preventing epilepsy. There is also some evidence that good therapeutic coverage with ivermectin (to eliminate Onchocerca volvulus) in some communities correlates with a drop in the incidence and prevalence of epilepsy in Cameroon (Boulle et al, 2017) and in reduction in nodding syndrome epidemics in
Tanzania (Colebunders et al., 2015).
2.6.3 Improving access to care for people with epilepsy
The epilepsy treatment gap measures the level of access to care for people with epilepsy and can be useful in planning and allocation of resources for epilepsy programmes. It is defined as “the difference between the number of people with active epilepsy and the number whose seizures are appropriately treated in a given population at a given point in time expressed as a percentage” (ILAE, 1997). There are disparities, between and within countries, in the treatment gap of epilepsy depending on the location and level of socio-economic development.
Whereas the treatment gap is usually 10% or less in HICs, it can be as high as 95% in some
LMICs. Within LMICs, the treatment gap is twice as high in rural areas as in urban areas and even in HICs, treatment gaps of up to 50% have been reported in selected populations (Meyer et al., 2010). In LMICs, there is a wide range of causes of the epilepsy treatment gap, the most important being: high level of stigma with its negative effect on health-seeking behaviour; inadequate skilled manpower; unaffordable cost of treatment; and unavailability of AEDs
(Mbuba et al., 2008, Meyer et al., 2012). This is not surprising given the paucity of neurological resources in many LMICs; in 2004, the WHO estimated that in SSA, there was an average of
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one neurologist per 3.3 million people and almost no neurology specialist nurses. It also estimated that in SSA, over 80% of financing for neurological care is through out-of-pocket payments (WHO, 2004). While the situation may have improved since then, any gains are most likely to be concentrated in hospitals in the big cities. Considering that people in rural areas bear the biggest burden of epilepsy in LMICs, any programme which aims to reduce significantly the epilepsy treatment gap in Africa must prioritise rural communities. Across
SSA, there have been several initiatives by local organisations or health workers, often in partnership with international donor bodies, to improve access to care for people with epilepsy in some communities. A majority of these interventions have been successful because they engaged the community and maximised the limited resources within the local health system through the following methods; targeting the most affected people (living in rural areas); encouraging participation of community volunteers; led by trained non-physician health workers; supervised by physicians in local or referral hospitals; and prioritised the use of phenobarbital which is the most available and affordable AED in LMICs (Watila et al., 2017)
(Njamnshi, 2009). Despite their relative success in improving access to treatment for people with epilepsy, the sustainability of these programmes once the funding from the donor organisation expires is debatable. For the gains from these programmes to be sustained, there must be engagement and commitment from African governments to treat epilepsy as a priority and to continue financing those programmes that are successful and effectively integrated within the health system country concerned, once the funding from the donor organisation has ended.
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Chapter 3: Study setting
3 Study setting
3.1 Cameroon
This study was carried out in Cameroon, a country in Central Africa with a population of about
22 million people, covering 475,442 square kilometres and divided into ten administrative regions, each of which is further divided into smaller administrative units called sub-divisions
(Figure 8). Two of the regions are majority anglophone (South-West and North-West) based on their British colonial history while people in the other eight regions are majority francophone
(being part of a former French colony). English and French are the official languages but most people speak at least one of the local languages or dialects of their ethnic group. Cameroon exhibits most of the major climates and vegetation of Africa: mountains, desert, rain forest, savanna grassland, and ocean coastland. This geographical diversity, combined with the presence of over 250 ethnic groups, each speaking at least 3 languages, has earned it the reputation of “Africa in miniature”.
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Chapter 3: Study setting
CAMEROON
Surface area: 475,650 Km²
Population: 22.2 million
Number of regions: 10
Life expectancy (M/F): 56/58 years
Official languages: English and French
Ethnic groups: over 250
Expenditure on health as percentage of GDP: 5.8%
Neonatal mortality rate: 25/1,000
Doctor/patient ratio: 19/100,000
Number of neurologists: 22
Figure 8. Map of Cameroon with Basic Health information (Maps, 2012)
The health system of Cameroon is made up of three levels:
• The Central level: The Ministry of Public Health is responsible for development of
health policy
• The Intermediate level: The Regional Delegation of Public Health in each of the ten
administrative regions coordinates and supervises health activities in each region.
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Chapter 3: Study setting
Each region is headed by a Regional Delegate for Health and has at least one regional
referral hospital.
• The peripheral level: The basic operational unit is the health district which is headed
by a District Medical Officer (DMO). At this level, national health policy is implemented.
Each health district is divided into health areas, each with at least one health centre,
which is the primary point of contact for health. All health districts have a referral district
hospital. Volunteers from the community, also known as community relay agents, often
participate in health activities that require engagement and participation of the
community.
The main referral hospitals in Cameroon are found in the major cities of Yaoundé and Douala where all the 22 neurologists and neuroimaging and neurophysiology resources are found.
Consequently, there is a mismatch between the availability of neurological resources and the need of the population for neurological care; most people with severe and disabling neurological conditions such as epilepsy are found in the rural areas and the regional towns.
Two health districts in the North-West Region were selected for this project: Batibo and Ndu.
3.2 Batibo Health District
The Batibo Health District is found in the North-West Region (one of the two anglophone regions) of Cameroon; about 400 Km from the capital city, Yaoundé and 45km from the regional capital city, Bamenda (Figure 9). It spans two administrative sub-divisions (Batibo and Widikum) with a total surface area of about 58 Km2 covered by grasslands and a dense forest. It is divided into 16 health areas and has an estimated population of about 82,000 inhabitants, most of whom practise subsistence agriculture. As well as its high production of crops such as maize, yams, colocasia and beans, Batibo is also known for high production of palm oil which is sold in the entire region and beyond. Most of the inhabitants speak either
Pidgin-English (lingua franca) or the Batibo language and its dialects. Traditional health practice is common and many people consult traditional healers for epilepsy because it is widely believed to be caused by witchcraft (Njamnshi et al., 2009). The Batibo Health District
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is one many health districts in the North-West Region that are most affected by HIV infection:
The HIV prevalence here is approximately 6.5% which is about 70% higher than the national prevalence (Personal communication, DMO). The Batibo Health District was chosen as the main site for this study for the following reasons;
1. Epilepsy is regarded as a serious problem and in some communities, there are reports
of clustering of cases and families with all siblings affected which suggests that strong
environmental and genetic factors may be involved.
2. Pig-breeding is widely practised and pork consumption is popular in this area, hence
exposing the population to taeniasis and cysticercosis, which can contribute to
increasing the risk of epilepsy in this community. Pig-farming is a major source of
income for farmers and it is driven by a high demand for pork, which is a constant
feature in most traditional ceremonies such as weddings and funerals; the quantity of
pork served during these and other social events usually reflects the wealth and social
standing of the host in the community. Most pig-farmers sell their pigs in the Batibo
and Widikum council markets which are among the biggest rural markets in the North-
West Region.
3. The Batibo Health District is among the endemic foci for onchocerciasis in the North-
West region. It contains a fast-flowing river (River Momo) which may favour the
breeding of the simulium fly, the vector of Onchocerca volvulus. Considering consistent
reports associating onchocerciasis with epilepsy, we sought to obtain evidence of any
such association between them in this community
4. The Batibo Health District has a reputation of strong community participation in health
and community relay agents have vast experience of volunteering in disease
surveillance and health sensitisation activities requiring engagement with the
community. These community relay agents constituted a readily available pool of
volunteers for recruitment to carry out census and epilepsy screening.
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5. I have previously worked as a medical officer in this health district for about 5 years
during which time I set up an epilepsy clinic within the district hospital to improve
access to care for people with epilepsy. During this period, I established important
liaisons with the community and the health authorities of the health district which were
essential for the realisation of this project.
Figure 9. Map of Batibo Health District (kindly provided by the DMO for Batibo): the red line shows the boundary between Batibo and Widikum sub-Divisions
3.3 Ndu Health District
The Ndu Health District is found in the North–West Region of Cameroon and some 160 km from the regional capital city, Bamenda. It is a rural health district found in the Ndu Sub-
Division which has nine health areas, 17 health centres and one district hospital. It has a population of about 87,000 inhabitants. The main source of income is subsistence farming and there is a big tea plantation which employs many inhabitants. Livestock rearing is widely
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practised and most households keep goats, sheep and chickens for subsistence. Pig-breeding and pork consumption are less common than in Batibo which is partly because Ndu has a substantial Muslim population. Pidgin-English and the local language, Limbum, are spoken by most inhabitants. Traditional medicine is also popular in the Ndu Health District. From the health district statistics and informal interviews with people in the community and the DMO, epilepsy was not identified as a common problem here. The Ndu Health District was chosen as a suitable comparison with the Batibo Health District on the following grounds: it has a similar demographic composition to the Batibo Health District; epilepsy is not perceived to be common in this health district; the ecological factors in Batibo that predispose to epilepsy are not common in Ndu.
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Chapter 4: Pilot study
4 Pilot of fieldwork
4.1 Procedure
The aim of the pilot study was to assess the feasibility of carrying out this population-based epilepsy screening for epilepsy in the study sites within the available period (6-7 months). The pilot study took place between July and September 2016 in one health area in each health district. Volunteers for the community screening for epilepsy were selected from the pool of community relay agents and nurses within each health area and invited to the district hospital where they received training. During the training in each study site, an interpreter with good knowledge of English, Pidgin-English and the local language translated the questionnaire to ensure that the same terms were used by field workers. At the end of the training, teams of two (a community relay agent and a nurse) were formed and assigned to specific quarters/villages for the community screening.
The screening procedure was adapted from the three-stage methodology that has been previously validated for the community screening of epilepsy in similar communities in SSA
(Ngugi et al., 2012). The screening questions concerned only people 6 years and older, to avoid including children with febrile seizures.
Stage 1: Heads of households or the most senior occupant were approached by the screening team to inquire whether any member of the household, 6 years or older, has epilepsy using the following 3 questions:
1. Do you/any member of the household have fits or has someone ever told you that
you/any member of the household have fits?
2. Do you/any member of the household experience episodes in which your/their legs or
arms have jerking movements or you/they fall to the ground and lose consciousness?
3. Have you/any member of the household experienced an unexplained change in
your/their mental state or level of awareness; or an episode of “spacing out” that
you/they could not control?
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Questions 1 and 2 are identical to the ones used in previous studies in Africa (Kariuki et al.,
2014, Ngugi et al., 2013a). Question 3 was added to increase the chances of identifying non- convulsive seizures and was adapted from one of the symptoms-based questions from a recent validation study in Canada (Keezer et al., 2014). A “yes” or “probable” response to any of the questions was considered as a positive screen and led to further interview in stage 2.
Stage 2: People in the household who screened positive in stage 1 were further interviewed by the nurse in the team using a symptom-specific 10-item questionnaire to identify convulsive and non-convulsive seizures. This was done during the same stage 1 visit if the concerned individual was present or in a subsequent visit to the household if the individual was not present. The following questions were included:
1. Did anyone ever tell you that you/this member of the household had a seizure or
convulsion caused by a high fever when you were a child?
2. Have you/this member of the household ever been told by a doctor that you have
epilepsy or epileptic fits?
3. Have you/this member of the household ever been told by someone else that you
have epilepsy or epileptic fits?
4. Have you/this member of the household ever fallen to the ground without a reason
and experienced twitching?
5. Have you/this member of the household ever fallen to the ground without a reason
and wet yourself?
6. Have you/this member of the household ever fallen to the ground without a reason
and bitten your tongue?
7. Did anyone ever tell you/this member of the household that when you/they were a
small child, you/they would daydream or stare into space more than other children?
8. Have you/this member of the household ever noticed any unusual body movements
or feelings when exposed to strobe lights, flickering lights, or sun glare?
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9. Shortly after waking up, either in the morning or after a nap, have you/this member of
the household ever noticed uncontrollable jerking or clumsiness, such as dropping
things or things suddenly “flying” from your hands?
10. Have you/this member of the household ever had any other type of repeated unusual
spells?
Questions 2 to 6 are identical to those used in other validated African studies (Kariuki et al.,
2014, Ngugi et al., 2013a). Questions 1 & 7-10 were adapted from the symptoms-based questions in the Canadian validation study and were added to identify people with non- convulsive seizures (Keezer et al., 2014). A “yes” or “possible” response to any of the questions was considered as a positive screen (except when the yes response was to
Question 1 alone).
Stage 3: Those who screened positive after stage 2 were invited to the health centre or hospital where they were further interviewed and examined by a physician (all senior trainee neurologists from the University of Yaoundé 1) who made the final decision on the epilepsy diagnosis.
Data was analysed in STATA 14. Crude prevalence of active epilepsy was estimated by dividing the number of people with active epilepsy by the total number of people screened in stage 1. The prevalence estimate was further divided by the participation rate between stage
1 and stage 3 to correct bias due to attrition. Age-standardisation could not be done because there was no suitable database of census of the study populations.
4.2 Results
The results of the epilepsy screening are summarised in Table 6. During a period of about six weeks, 1,628 households were visited in both health districts during which 8,224 people, 6 years or older, were screened for epilepsy. A total of 92 people had active epilepsy: 79 in
Batibo Health District and 13 in the Ndu Health District. The crude prevalence of active epilepsy, adjusting for attrition was 35.1/1,000 (95% CI: 27.9-43.6) in Batibo and 7.3/1,000
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Chapter 4: Pilot study
(95% CI: 4.4-12.8) in Ndu. The mean age of people with epilepsy in Batibo was 26.0 years
(SD:11.3) while that of people with epilepsy in Ndu was 23.0 years (SD:7.8). In the Ndu Health
District there was low participation rate in stage 3 of the screening (34.4%) compared with the
Batibo Health District (72.3%). This was probably due to more effective community mobilisation and sensitisation about the project and the longer study duration in Batibo with respect to Ndu. About 23% of people screened in stage 3 were not included in the enumeration of people with active epilepsy for a variety of reasons: events were non-epileptic; seizures were provoked; participant was younger than 6 years; epilepsy was non-active (no seizures in the preceding 12 months). The characteristics of the people with active epilepsy in both health districts are presented in Table 7.
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Table 6. Epilepsy screening in the pilot sites
Batibo Ndu Overall
Number of 696 932 1,628 households visited
Population 3,114 5,110 8,224 screened
People screened 139 (4.5%) 68 (1.3%) 207 (2.5%) positive in stage 1 of interview (%)
People screened 137 (98.6%) 61 (89.7%) 198 (95.7%) positive in stage 2 of interview (%)
People screened in 99 (72.3%) 21 (34.4%) 120 (60.6%) stage 3 (%)
People with active 79 (79.8%) 13 (61.9%) 92 (77.5%) epilepsy (%)
Crude prevalence 25.4 (20.4-31.5) 2.5 (1.5-4.4) 11.2 (9.1-13.7) of active epilepsy per 1,000 (95% CI)
Prevalence of 35.1 (27.9-43.6) 7.3 (4.4-12.8) 18.6 (15.2-22.8) active epilepsy adjusting for attrition/ 1,000*
Mean age of 26.0 (±11.3) 23 (±7.8) 25.6 (± 10.9) people with epilepsy (years)**
Percentages are a proportion of the preceding value within the column
* To correct for attrition between stages, the crude prevalence for Batibo was divided by 0.72 and that of Ndu by 0.34 which are the percentages of people who screened positive in the community who turned up for clinical assessment in stage 3.
** The data include only those aged 6 years or older
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Table 7. Seizure semiology and epilepsy types in pilot sites Batibo (N=79) Ndu (N=13) Overall (N=92) Age at seizure onset n = 73 n = 12 n=85 0-5 7 (9.6%) 0 7 (8.2%) 6-10 25 (35.2%) 1(8.3%) 26 (30.6%) 11-15 28 (38.4%) 5 (41.7%) 33 (38.8%) 16-20 6 (8.2%) 2 (16.7%) 8 (9.4%) >20 7 (9.6%) 4 (33.3%) 11 (12.9%)
Seizure types* n = 79 n = 13 n = 92 Generalised convulsive 41 (51.9%) 7 (53.9%) 48 (52.2%) Generalised other motor 12 (15.2%) 2 (15.4%) 14 (15.2%) Generalised absence 8 (10.1%) 1 (7.7%) 9 (9.8%) Focal onset with secondary 28 (35.4%) 3 (23.1%) 31 (33.7%) generalization Focal motor 4 (5.1%) 0 4 (4.4%) Focal non-motor 6 (7.6%) 0 8 (8.7%) Focal dyscognitive 8 (10.1%) 2 (15.4%) 10 (10.9%)
Seizures in preceding month n = 75 n = 12 n = 87 0 29 (38.7%) 5 (41.7%) 34 (39%) 1-5 38 (50.7%) 6 (50%) 44 (50.6%) >5 8 (10.7%) 1 (8.3%) 9 (10.4%)
Timing of seizures n = 78 n = 13 n = 81 Night mainly 29 (37.2%) 1 (7.7%) 30 (37%) Daytime mainly 8 (10.3%) 1 (7.7%) 9 (11%) Anytime 40 (51.3%) 10 (76.9%) 50 (61.7%) On waking up 1 (1.3%) 1 (7.7%) 2 (2.4%)
Self-report of status epilepticus 12/62 (19.4%) 1/10 (10%) 13/72 (18.1%)
Epilepsy Type n = 77 n = 13 n = 90 Focal 35 (45.5%) 6 (46.2%) 41 (45.5%) Generalised 31 (40.3%) 5 (38.5%) 36 (40%) Undetermined 11 (14.3%) 2 (15.4%) 13 (14.6%)
Skin injury from seizures 31/75 (41.3%) 6/13 (46.2%) 37/88 (42%) *People could have more than one seizure type
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4.3 Discussion
The results of the pilot confirmed our hypothesis that the prevalence of epilepsy is high in the
Batibo Health District. Given that the same method was used in the Batibo and Ndu Health
Districts, the large difference in the crude prevalence of active epilepsy between them is probably related to differences in the prevalence of factors predisposing to epilepsy. A detailed discussion of these results and their implications is presented in chapter 6. After reviewing the conduct of the pilot and considering limitations, the following adjustments were made for the fieldwork:
The Ndu Health District was dropped: The study was initially planned to be carried out in the
Batibo and Ndu Health Districts over a period of 7-9 months. After the pilot, however, we realised that this would not be feasible because of logistic difficulties, limited resources and time constraints. Consequently, Ndu Health District was dropped and we concentrated resources on the Batibo Health District for this project. We plan to include Ndu Health District as a control site in future projects investigating the risk factors for epilepsy in Cameroon, when more resources become available.
Baseline census population included: There was no readily available and reliable database of the study population to enable standardisation of our prevalence estimates and computation of age-specific prevalence values. To address this limitation, we included a census of households and people in the survey.
Changes to sampling strategy for the case-control study: Attempts to recruit controls during the pilot were unsuccessful because almost all invited healthy subjects did not come to the hospital for assessment. For the fieldwork it was decided that controls would be randomly selected from the database of people without epilepsy after the census and would be visited and interviewed at home by nurses.
Modification of screening method: The fieldworkers complained that there were too many screening questions and they were time consuming to administer. We also realised that too
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many questions made it more likely for errors to be made during the interviews especially since they had to be translated to be administered to other languages. Consequently, the screening process was modified to include fewer questions and only two stages (described below).
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Chapter 5: Methods
5 Methods: fieldwork
5.1 Definition of terms
To ensure that the findings of this research are comparable with results of other studies, the terminology and the classifications used in this study are mostly based on recommendations by the ILAE for epidemiological studies (Thurman et al., 2011): Below are a few definitions of important terms frequently used in the study:
Active epilepsy: Two or more unprovoked seizures, at least one of which must have occurred within 1 year preceding the study, irrespective of AED treatment
Focal epilepsy: Focal (or focal-onset) seizures and/or presence of a focal neurological deficit that occurred before onset of seizures
Generalised epilepsy: Generalised seizures and no focal seizures nor focal neurological deficits
Indeterminate epilepsy: indeterminate seizures and/or insufficient information to determine type of epilepsy
Febrile seizures: Seizures in the setting of raised body temperature when the individual was less than five years old. This information was obtained from parents or guardian and restricted to children (less than 16 years old) to limit recall bias
Status epilepticus: seizures lasting more than 30 minutes or repetitive seizures with no recovery of consciousness between seizures. When patients or caregivers were unable to time the duration of seizures, the duration was estimated by relating them to the duration of normal daily activities in their environment such as trekking time to market, health centre, schools etc.
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Inadequate epilepsy treatment: Someone with active epilepsy who has missed AED treatment for more than a total of 7 days in the month preceding the study or who is taking AED not prescribed by health worker; or inappropriate AED dosage.
New case of epilepsy: Person with epilepsy whose first seizure occurred within the 12 months preceding the study
Permanent residents: Living within the health district for at least the preceding 3 months
5.2 Planning, recruitment and training of personnel
The DMO authorised the study and sent out official notices to churches, traditional authorities and quarter heads to inform them about the study and request their consent and co-operation.
All research personnel received training on the study during which the tools were presented and roles and responsibilities clearly outlined (appendix). For each health area, selected community relay agents and nurses were convened for a training session, usually 3-7 days before the scheduled commencement of the screening in the health area (appendix). An interpreter with good knowledge of English, Pidgin-English and the local language assisted in the interpretation of the questionnaire to ensure that its administration was as accurate and as uniform as possible.
5.3 Census of households and persons
All the households and the permanent residents of the Batibo Health District were targeted by the census within which the epilepsy screening process was embedded. With the help of the
DMO and chiefs of health areas, each health area was conveniently divided into zones and census and screening teams were formed and allocated to each zone. Each team consisted of a community relay agent and a nurse, both of whom had to be resident within the health area and be familiar with the zone. Preference was given to people who had previously volunteered in activities with extensive outreach, especially those involved in the programme of community distribution of ivermectin for the onchocerciasis control programme. Using the
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census form (appendix), each team enumerated all the houses within their zone and obtained demographic information on the occupants from the head or the most senior occupant of the household. Unoccupied houses were revisited once, where possible.
5.4 Epilepsy screening and cross-sectional study of people with
epilepsy
The population was screened for convulsive and non-convulsive epilepsy in a 2-stage process described below. The screening concerned only permanent residents who were 6 years or older, to avoid the risk of misclassification as epilepsy of febrile seizures and other provoked seizures common before this age.
Stage 1
Immediately after obtaining census information, heads of household (acting as proxies for the rest of the family) were interviewed by the field workers to identify permanent residents of the house with suspected epilepsy. The questionnaire included 5 questions, which were adapted from those used during the pilot (above). The following questions were included:
Q1) Do you/this member of the household have fits or has someone ever told you that you/they have fits?
Q2) Do you/this member of the household experience episodes in which you/they fall to the ground and lose consciousness or wet yourself or bite your tongue?
Q3) Have you/this member of the household ever fallen to the ground without a reason and experienced jerking movements of the legs/arms?
Q4) Have you/this member of the household experienced an unexplained change in your mental state, behaviour, or level of awareness that you/they could not control?
Q5) Did anyone ever tell you/this member of the household that when you/they were a small child, you/they would daydream or stare into space more than other children?
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Questions 1 and 2 are general screening questions, Question 3 targeted convulsive seizures while question 4 and 5 were included to identify non-convulsive seizures. A “yes” response to any of the five questions was recorded as a positive screen for epilepsy and the person concerned was invited to the nearest health centre on a specific date for further assessment by a physician. The person with suspected epilepsy was encouraged to come along with a member of the same household who had witnessed the event(s). The house-to-house screening was supervised by the chief of the health area who randomly visited 10-15 households each and compared their findings with those of the screening teams. A few irregularities were observed whereby some of the field workers did not conduct the interviews as stipulated during the training. This, however, concerned only two teams and the relevant individuals were replaced by other trained volunteers no later than the second day of screening. The screening lasted 5-7 days depending on the population of the zone.
Stage 2
People with suspected epilepsy from stage 1 were assessed at the health centre by a physician within 2-5 days of the end of stage 1 screening in their community. The physician established the final epilepsy diagnosis after a detailed event and medical history using a semi-structured questionnaire (appendix). To limit the travel distance for participants and encourage participation, we carried out the clinical assessment in at least one health centre in each health area. The dates for clinical assessment were carefully chosen to avoid clashes with major events in the village calendar.
For people with epilepsy who were already on AEDs, treatment was reviewed and, where indicated and feasible, adjustments were made to improve seizure control. Those who were not already on treatment and for whom treatment was indicated were placed on either phenobarbital or carbamazepine which are the drugs that are most available and affordable in the health district. All people with epilepsy were offered 2 to 3 months’ worth of medication
(phenobarbital or carbamazepine) free of charge. Group education sessions were organised in each site during which the importance of treatment adherence was emphasised.
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5.5 Selection of participants for the case-control study
Of 546 people identified with active epilepsy, 395 were available for recruitment in the case- control study and complete data was obtained from 380 people. Four hundred and twenty
(420) healthy subjects were randomly selected as controls from the database of people who screened negative during stage 1 using the “RAND ()” command on Microsoft Excel; data could be obtained from 278 of them yielding a response rate of 66.4%. People with epilepsy were interviewed by a nurse immediately after clinical assessment by the physician, using a structured questionnaire designed to identify exposure to known historical risk factors of epilepsy. Control subjects were interviewed during a visit to their home by the screening teams. Information from participants who are cognitively impaired was gathered with the help of a caregiver. The questionnaire for participants aged 16 years and below was slightly different from that of people above 16 years old (appendix).
5.6 Ethical considerations
Ethical clearance was obtained from the National Ethics Committee of Cameroon National and administrative authorisation for the research was granted by the DMO (appendix).
Furthermore, community consent was obtained from local community leaders where necessary. During the household survey, verbal consent was obtained from the head of the household before proceeding with the interview. An information sheet was presented to all adult participants (> 21years) and written informed consent obtained. Where the participant did not understand English or Pidgin-English, an interpreter was called upon to assist. For minors according to Cameroon law (≤21 years), assent was obtained from them as well as the signed consent of their parents when they were available. To protect the confidentiality of participants, data was anonymised before analysis. All people with epilepsy identified during the study were included in an epilepsy register that was created to be used for future epilepsy- related research. This register was also shared with the DMO, who is also bound by a duty to respect the confidentiality of the participants. The importance of sharing such a database with
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the local health authorities cannot be overemphasised as this enables an objective appreciation of the magnitude of epilepsy in this district and facilitates follow-up of cases and local planning to address the problem. People with epilepsy for whom treatment was indicated and who consented were provided with 2-4 months’ worth of AEDs (phenobarbital or carbamazepine) free of charge. At the end of the study, a two-day epilepsy training was provided for all the doctors and at least two nurses per health area. Chiefs of health centres were encouraged to start running special monthly epilepsy clinics to improve follow-up of people with epilepsy in their health area. We engaged with staff of the epilepsy clinic which was previously running in the district hospital and proposed strategies to improve both attendance by people with epilepsy and the quality of care provided.
5.7 Statistical analysis
Data was entered in Excel and statistical analysis was conducted using R statistical software
(version 3.2). The crude prevalence of active epilepsy was estimated by dividing the total number of people with active epilepsy by the population screened in stage 1. The 1-year incidence of epilepsy was calculated by dividing new cases by the total population screened negative for epilepsy in stage 1. Age-standardised prevalence and incidence was calculated with the epitools package, based on the Cameroon’s national demographic distribution across age bins for 2013 (Portal, 2014). The standardisation and exact confidence intervals were determined with the direct method. The prevalence values were corrected for attrition by dividing the age-standardised prevalence values by 0.47, the proportion of people screened positive in stage 1 who participated in the clinical assessment in stage 2. Prevalence values were reported by age categories, gender and health area. Prevalence ratios with their confidence intervals were computed for health areas, using Ashong as reference and for age categories, using the 6-9 age bin as reference.
Analysis of the case-controls study was performed separately for children (≤16 years) and adults (>16 years). Initially, the raw data were analysed without taking into account the missing
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fields as well as the non-response among controls (66 children and 76 adults). For each group
(children and adults) the odds ratios, confidence intervals and P-values were generated from univariate analysis and multivariate analysis of the variables. Only factors which were statistically significant in the univariate analysis were included in the logistic regression model.
Secondarily, bias due to non-response among controls was adjusted by imputation using the
Multiple Imputation by Chained Equation (MICE) package in the R statistical software (version
3.2). Pooling was done with the Rubin’s Rule as implemented in the MICE package in the R statistical software. This means that based on the dataset, 25 new datasets are generated where the missing data are filled with data computed on the existing numbers in the dataset.
The odds ratios, 95% confidence intervals and P values are determined by pooled results of
25 logistic regression models fitted on 25 imputed datasets. Again, only statistically significant factors in the univariate analysis were included in the logistic regression model.
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Chapter 6: Cross-sectional epilepsy survey
6 Cross-sectional epilepsy survey: findings and
significance
6.1 Results
6.1.1 Household and population census
In this study, 8,398 homes were visited by trained community enumerators during which basic demographic information concerning 39,527 permanent residents, aged 6 years and above was collected from the most senior household member. The mean age of the sample population was 27.7 years (SD: 18.4) and 53.4% were female. Batibo and Widikum health areas, which include the administrative headquarters of the Batibo and Widikum Sub-Divisions respectively, were the most populated health areas. Information on pig-keeping was available for 12 out of 16 health areas; pig-keeping was practised in about one-third of households. The proportion of households keeping pigs varied between health areas, ranging from 2.4% in
Bifang to 69% in Ashong (Table 8).
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Chapter 6: Cross-sectional epilepsy survey
Table 8. Census Results
Health area Number of Number of Gender Households keeping households people (female) pigs visited enumerated
Anjake 206 702 50.4% NA
Ashong 704 3,414 55.8% 486/704 (69%)
Batibo 1,177 6,199 56% 451/1,177 (38.3%)
Bessi 484 2,017 54.4% 244/484 (50.4%)
Bifang 375 1,831 48.3% 8/374(2.4%)
Eka 404 2,479 50% NA
Ewai 824 3,017 54.6% 251/824 (30.5%)
Ewoh 358 1,642 52.6% 89/358 (24.9%)
Guzang 575 2,632 55.6% 241/575 (41.9%)
Gwofon 541 2,023 53.8% 173/541 (32%)
Kugwe 540 3,001 54.6% 118/540 (21.9%)
Kulabei 626 2,677 55.6% 137/622 (22%)
Larinji 331 1,683 47.2% NA
Olorunti 255 1,290 49.7% NA
Tiben 396 1,674 53.8% 56/389 (14.4%)
Widikum 602 3,246 50.3% 86/602 (14.3%)
Overall 8,398 39,527 53.4% 2,340/7,190 (32.6%)
NA: Data not collected by the enumerators
6.1.2 Epilepsy Screening
All 39,527 residents aged 6 years and above enumerated during the census were screened for epilepsy. About 12% of households had a suspected case of epilepsy and 2% had more than one person with suspected epilepsy. A breakdown of the outcome of the screening per health area is presented in Table 9 and Figure 10. Of 1,396 residents with suspected epilepsy in stage 1, 47.1% effectively visited health centres for assessment by the clinician in stage 2.
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Chapter 6: Cross-sectional epilepsy survey
In addition, 21 people who had been screened negative in stage 1 also attended the health centre for clinical assessment. The participation rate between stage 1 and stage 2 varied between 32% in Kulabei and 66.6% in Anjake. Out of 679 people assessed by the clinician,
639 (94.1%) people had confirmed epileptic events in the past and 546 (80.5%) people were diagnosed with active epilepsy. All the 21 people who had screened negative in stage 1 but decided to attend stage 2 were found to have a history of epileptic events and active epilepsy was confirmed in 13 of them (61.9%).
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Chapter 6: Cross-sectional epilepsy survey
Estimated population of the Batibo Health District eligible for epilepsy screening (≥6 years); N=65,878
Migrated/ absent/temporary residents; N= 26,351
Stage 1: Population census and door-to- Eligible population enumerated and screened; N= 39,527 (60%) door epilepsy screening
No epilepsy (Sampling
Screened positive; frame for controls); N= 38,110 N=1,396 (5.6%)
Stage 2: Screened negative Participated; N= Assessment by stage 1, self-referred; 658 (47.1%) physician N= 21
Randomly selected healthy subjects (controls); N=420
Confirmed active epilepsy; N= 546
Missing or incomplete data; N= 142
Cases interviewed Controls interviewed during Case-control study by nurse; N= 380 home visits; N= 278
Figure 10. Flow chart of study design and recruitment of participants
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Chapter 6: Cross-sectional epilepsy survey
Table 9. Epilepsy Screening
Health People Suspected Suspected Total Confirmed Confirmed area screened epilepsy epilepsy screened epileptic active in Stage 1 seen in in stage 2 * event (s) epilepsy Stage 2
Anjake 702 18 (2.6%) 12 (66.6%) 12 12 (100%) 11 (91.67%)
Ashong 3,414 85 (2.5%) 44 (51.8%) 44 40 (90.9%) 31 (77.5%)
Batibo 6,199 184 (3%) 86 (47.6%) 88 84 (95.5%) 67 (79.7%)
Bessi 2,017 58 (2.9%) 21 (36.2%) 22 15 (68.2%) 11 (73.3%)
Bifang 1,831 120 (6.6%) 50 (41.7%) 55 44 (80%) 39 (88.6%)
Eka 2,479 61 (2.5%) 39 (63.9%) 39 38 (97.4%) 33 (86.8%)
Ewai 3,017 110 (3.7%) 49 (44.6%) 49 43 (87.7%) 34 (79.1%)
Ewoh 1,642 100 (6.1%) 50 (50%) 51 50 (98.4%) 43 (86%)
Guzang 2,632 46 (1.8%) 25 (54.4%) 26 26 (100%) 20 (76.9%)
Gwofon 2,023 70 (3.5%) 38 (54.3%) 38 37 (97.4%) 34 (91.9%)
Kugwe 3,001 71 (2.4%) 42 (59.2%) 44 41 (93.2%) 36 (87.8%)
Kulabei 2,677 128 (4.8%) 41 (32%) 46 46 (100%) 41 (81.1%)
Larinji 1,683 21 (1.3) 11 (52.4%) 11 11 (100%) 11 (100%)
Olorunti 1,290 53 (4.1%) 31 (58.5%) 31 31 (100%) 25 (80.7%)
Tiben 1,674 106 (6.3%) 60 (56.6%) 61 60 (98.4%) 52 (86.7%)
Widikum 3,246 165 (5.1%) 59 (35.8%) 62 61 (98.4%) 58 (95.1%)
Overall 39,527 1,396 658 (47.1%) 679 639 (94.1%) 546 (85.5%)
(5.6%)
Data in bracket are percentages of the number in the preceding column *Including 21 people who were negative in stage 1 but who turned up for stage 2 screening
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6.1.3 Prevalence of epilepsy
Lifetime prevalence of epilepsy
The lifetime prevalence of epilepsy was obtained by dividing the number of people with a history of unprovoked epileptic seizures (639) by the total population screened in stage 1. We estimated the crude lifetime prevalence of epilepsy to be 1.7%. After age-standardisation and adjusting for attrition (non-participation between stage 1 and 2) the lifetime prevalence of epilepsy was estimated at 4.1% (95% CI: 3.7-4.4%).
Prevalence of active epilepsy
The number of people with active epilepsy (546) was divided by the population screened to obtain the crude prevalence of active epilepsy which was estimated at 14.4/1,000 (95% CI:
13.3-15.5). After age-standardisation and correction for attrition, the prevalence of active epilepsy was found to be 34.7/1,000 (95% CI: 31.8-37.8).
Prevalence of active epilepsy by health area
There was significant variation in the prevalence of active epilepsy between health areas.
Whereas the prevalence of active epilepsy was 2 to 4 times higher in Tiben, Ewoh, Bifang and
Widikum relative to Ashong, the prevalence in Bessi was about half of that in Ashong; Ashong was the reference health area for computing the prevalence ratios (Table 10). It was observed that, except for Kugwe, the health areas with the highest prevalence (Tiben, Bifang, Widikum,
Gwofon, Ewoh and Olorunti) were also the closest to the river with respect to the other health areas. In addition, within health areas, communities with crude prevalence of at least 2% were mostly clustered around the Momo river (Figure 11). A further breakdown of the prevalence of epilepsy by community is found in the appendix.
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Table 10. Prevalence of active epilepsy by health area
Health Population Crude Age- Age- Prevalence area screened prevalence/1,000 standardised* standardised ratio prevalence/1,000 prevalence adjusted for attrition**/1,000
Anjake 702 15.8 (8.3-28.9) 17.1 (8.5-30.9) 37.5 (20.4-65.8) 1.6 (0.8-2.9)
Ashong 3,414 9.8 (6.8-14.0) 11.6 (7.7-16.9) 24.6 (16.3-28.4) 1
Batibo 6,199 11.7 (9.7-14.1) 12.7 (9.8-16.2) 27.0 (20.8-34.5) 1.2 (0.9-1.5)
Bessi 2,017 5.1 (2.6-9.8) 5.8 (2.7-11.2) 12.2 (5.7-23.8) 0.5 (0.2-1.0)
Bifang 1,831 22.2 (15.9-30.7) 23.8 (16.7-33.2) 50.5 (35.4-70.1) 2.3 (1.6-3.1)
Eka 2,479 14.8 (10.4-20.9) 16.4 (11.2-23.4) 34.9 (24.0-49.7) 1.5 (1.1-2.1)
Ewai 3,017 11.2 (7.8-15.9) 12.8 (8.7-18.2) 27.3 (18.6-38.8) 1.1 (0.8-1.6)
Ewoh 1,642 24.4 (17.0-34.7) 27.7 (18.9-39.4) 58.8 (40.1-83.7) 2.5 (1.7-3.5)
Guzang 2,632 7.8 (4.9-12.3) 10.2 (6.1-16.1) 21.8 (13.1-34.3) 0.8 (0.5-1.3)
Gwofon 2,023 16.7 (11.7-23.7) 21.4 (14.7-30.2) 45.5 (31.3-64.5) 1.7 (1.2-2.4)
Kugwe 3,001 16.1 (11.4-22.6) 19.7 (13.5-28.0) 41.9 (28.7-59.6) 1.7 (1.2-2.3)
Kulabei 2,677 16.0 (11.6-21.8) 18.3 (13.1-25.2) 39.1 (27.9-53.5) 1.6 (1.2-2.2)
Larinji 1,683 7.0 (3.7-12.9) 8.3 (4.0-15.5) 17.4 (8.6-32.9) 0.7 (0.4-1.3)
Olorunti 1,290 19.0 (12.5-28.7) 19.5 (12.5-30.6) 41.5 (26.6-65.0) 1.9 (1.3-2.9)
Tiben 1,674 33.4 (25.0-44.2) 36.0 (26.4-48.2) 76.5 (56.2- 3.4 (2.6-4.5)
102.2)
Widikum 3,246 18.7 (14.3-24.4) 18.9 (14.3-24.7) 40.3 (30.4-52.4) 1.9 (1.5-2.5)
Overall 39,527 14.4 (13.3-15.7) 16.3 (14.9-17.8) 34.7 (31.8-37.8) -
Values in parenthesis represent the 95% confidence interval *Age standardisation used the Cameroon census population of 2003 ** 47% of people screened positive in stage 1 were assessed in stage 2. To adjust for this, the age- adjusted prevalence was divided by 0.47.
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Figure 11. Map of Batibo Health District showing of prevalence of epilepsy with respect to Momo River
Prevalence of active epilepsy by age and gender
Table 11 and Figures 12 and 13 show the gender- and age-specific and prevalence of active epilepsy. The peak prevalence of active epilepsy was in the 20-29 age category followed by people in the 30-39 and 10-19 age groups. Overall, there was no difference in the prevalence of epilepsy between genders except between the ages of 35 and 45 where the prevalence seemed to be slightly higher in males than in females (Figure 12).
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Table 11. Prevalence of active epilepsy by age and gender
Total Number of people Age-standardised Prevalence Screened with active prevalence adjusted Ratio (95% CI) epilepsy for attrition (95% CI)
Sex
Female 19,322 275 30.2 (26.8-34.0) 1
Male 16,935 249 31.2 (27.6-34.5) 1.03
Age
6-9 5,374 20 7.9 (4.9-12.4) 1
10-14 6,198 37 12.6 (9.0-17.7) 1.6 (1.2-2.2)
15-19 4,917 100 43.3 (35.4-52.7) 5.5 (4.5-6.7)
20-24 3,265 104 67.7 (55.7-82.2) 8.6 (7.0-10.4
25-29 2,761 112 86.2 (71.6-103.7) 10.9 (9.0-13.1)
30-34 2,236 85 80.8 (65.1-99.9) 10.3 (8.2-12.6)
35-39 2,181 30 29.1 (20.2-42.1) 3.7 (2.5-5.3)
40-44 1,946 9 9.78 (4.7-19.4) 1.2 (0.6-2.4)
45-49 1,704 1 1.2 (0.1-8.0) 0.2 (0.01-1.0)
50-54 1,509 8 11.2 (5.2-23.1) 1.4 (0.7-2.9)
55-59 937 5 12.1 (4.2-27.9) 1.4 (0.5-3.5)
60-64 1,086 4 7.8 (2.5-21.4) 1.0 (0.3-2.7
65-100 2,168 9 8.8 (0.5-17.5) 1.1(0.5-2.2)
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Age-specific prevalence of active epilepsy by gender
10 9 8 7 6 5 4 3 2 1 Percentage Percentage with epilepsy 0
Age category
Male Female
Figure 12. Gender specific prevalence of active epilepsy by age category
PREVALENCE OF EPILEPSY BY AGE CATGEORY
8.6 8.1 6.8
4.3 2.9
PERCENTAGE WITH EPILEPSYWITHPERCENTAGE 0.8 1.3 0.9 1.1 1.2 0.8 0.9 0.1
AGE CATEGORY
Figure 13. Age-specific prevalence of active epilepsy
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6.1.4 Incidence of epilepsy
We estimated the crude 1-year incidence of epilepsy to be 66.7 (95%CI: 44.5-99.2). After age- standardisation, the 1-year incidence of epilepsy was determined to be 171.1 (95%CI: 114-
254.60). There was parity in gender representation among the incident cases. The median age of the incident cases was 13.5 years (IQR: 7-18).
6.1.5 Clinical characteristics of epilepsy
The median age of people with active epilepsy was 25 years (IQR: 18-30). The mean age was
25.2 years (SD: 11.1). The mean age at first seizure was 12.5 years (SD: 8.2). The median age at first seizure was 11 years (IQR: 8-15) and there was little variation between health areas (10-13), except in the Larinji health area where the median age at first seizure was 7 years (IQR: 6-10). Seizures started before the age of 10 years in 46.2 % of people. About
7.4% of people had had their first seizure after the age of 20 years and there was no significant difference in the adult-onset epilepsy between health areas (P=0.690).
Results of seizure and epilepsy characteristics are summarised in Table 12. Generalised convulsive seizures were the most common types of seizure; about 60% of people had experienced primarily generalised seizures while almost 20% had focal-onset secondarily generalised seizures. Focal seizures were also common, especially focal dyscognitive seizures which were reported by 14% of people with epilepsy. About 20% had seizures which could not be classified because of insufficient details due to lack of a reliable eyewitness.
Seizures occurred only at night-time during sleep in 22.6% of participants.
Seizures occurred at least monthly in about 60% of people; 4.1% had daily seizures, 7.7% had them weekly and 48.8% had them monthly. About 25% of participants had experienced at least one episode of status epilepticus. Daily seizures occurred more frequently in children
(10.5%) relative to adults (2.7%)(P=0.007). There was no difference in seizure frequency between males and females.
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Based on the seizure characteristics, medical history and physical examination, the physician determined that 58.9% of people had focal epilepsy while 26.5% had generalised epilepsy.
Focal epilepsy was slightly more frequent in children (63.7%) than adults (58.1%), although the difference was not statistically significant (P=0.70). Focal epilepsy did not vary between health areas (P=0.594). There was no difference in focal epilepsy between old cases (60%) and new cases (73.1%) (P=0.418). In 14.6% of cases, the type of epilepsy could not be determined because of incomplete information.
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Table 12. Seizure and epilepsy characteristics
Number Percentage Age at seizure-onset Total = 435 0-5 41 9.4% 6-10 160 36.8% 11-15 138 31.7% 16-20 64 14.7% >20 32 7.4%
Seizure type* N = 545 Primarily generalised seizures 329 60.4% Generalised other motor 41 7.5% Generalised absence 41 7.5% Focal-onset secondarily generalised 95 17.4% Focal motor 17 3.1% Focal non-motor 32 5.9% Focal dyscognitive 80 14.7% Undetermined 106 19.4%
Self-reported status epilepticus 86/338 25.4%
Seizure frequency N = 506 Daily 21 4.2% Weekly 39 7.7% Monthly 244 48.2% Skips some months 202 39.9%
Seizure timing N = 526 Daytime mainly 24 4.6% Night mainly 119 22.6% Anytime 378 71.9% On awakening 5 1%
Type of epilepsy N=543 Focal 320 58.9% Generalised 144 26.5% Undetermined 79 14.6% *People could have more than one seizure type
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6.1.6 Treatment and associated factors
Approximately 85% of people with active epilepsy were on anti-epileptic treatment, mainly phenobarbital (58.6%) and carbamazepine (26.5%). For those who were not on treatment, the main reasons advanced were ineffectiveness of AEDs (30.4%) and unavailability of AEDs
(15.1%). About 65% of people with epilepsy on AED treatment had interrupted treatment for a continuous period of at least 7 days in the past month and the main reason given for this was unavailability of AEDs (58%). Response to treatment was generally good; 77.7% of people on AED treatment reported improvement in seizure frequency since starting current
AED treatment. Meanwhile, 20.5% did not find the AEDs helpful in controlling their seizures
(seizures remained the same or got worse). Anti-epileptic treatment was deemed, by the physician, to be inadequate (treatment gap) in 80.6% of people. The clinician considered the following factors in deciding whether treatment was adequate: adherence to treatment regime, the appropriateness of choice and dosage of AED, the source and the prescriber of the AED.
The epilepsy treatment gap was wider (88.4%) for people living further than 30-minutes’ walking distance from the nearest health centre compared with those who lived closer to the health centre (77.4%)(P=0.002). There was no variation in treatment gap with age and gender.
Most people had tried some alternative treatment for epilepsy: 54% had taken traditional medicine while 62.2% had consulted a priest or pastor for prayers to cure epilepsy (Table 13).
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Table 13. Treatment of epilepsy and related factors
AED Treatment
Currently on AED 459/543 84.5% treatment
Phenobarbital 318/543 58.6%
Carbamazepine 144/543 26.5%
Valproate 1/542 0.2%
Phenytoin 10/543 1.8%
AED prescriber
Doctor/nurse 323/442 73.1%
Pharmacy attendant 46/442 10.4%
Relative/self-prescribed 73/442 16.5%
Effect of AED on seizures
Seizures stopped 8/434 1.8%
Seizures reduced 337/434 77.6%
No effect 81/434 18.7%
Seizures got worse 8/434 1.8%
Adequate Treatment 84/430 19.5%
Alternative treatments
Use of traditional 289/535 54.0% medicine
Prayers by priest/pastor 331/532 62.2%
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6.1.7 Perceptions of epilepsy
About 23% of participants thought that epilepsy was caused by witchcraft or some supernatural factors and 4.6% thought it was natural. Most people could not tell the cause of epilepsy. About 48% believed that epilepsy can be cured; 34% believed that the best cure was
AEDs, 15.2% believed in prayers as the best cure while 2.4% felt the same about traditional medicine. Neither the belief in a cure for epilepsy nor in witchcraft as a cause of epilepsy was significantly associated with being on AED treatment (P> 0.5 in each case).
6.1.8 Medical and social consequences of epilepsy
About 29% of participants had an epilepsy or seizure-related injury: 18% had burns and 16.3% had wounds or bruises resulting from an epileptic seizure. Burns were more common in people with generalised epilepsy (29.6%) than focal epilepsy (14.7%) (p<0.001). Burns were also significantly more common in people who had previously experienced status epilepticus
(24.7%) than in those with no history of status (13.6%) (P=0.02). Interestingly, more people who were currently on AED treatment had burns compared with people who were not on
AEDs; 20.2% vs 3.9% (P<0. 0001). There was no significant difference in the prevalence of burns between males and females or between children and adults.
About 45% of participants had at least one physical sign of moderate to severe malnutrition
(tooth decay, glossitis, brittle hair, pale conjunctivae, emaciated appearance). About 47% people with epilepsy had food taboos and the main food types they avoided were okra soup
(63%), chicken (29%) and pork (33.9%). Epilepsy was associated with poor school attendance; about 40% of children were not attending school and, for 74% of them, epilepsy was the reason why they dropped out of school.
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6.2 Discussion
6.2.1 Census of study population and epilepsy screening
The main purpose of the census was to obtain a denominator to enable a reliable estimation of the burden of epilepsy in our study population. The coverage of the eligible study population
(60%) was satisfactory given the relatively short period for the census and the fact that it was carried out in parallel with epilepsy screening. Temporary migration out of the health district may have significantly contributed to non-participation in the enumeration and this may have been facilitated by two important factors. First, the study period (March-June 2017) corresponded with a period of peak migration by farmers and their families to their farm houses in the neighbouring South-West Region, where the land is more fertile. Secondly, the study also corresponded with a protracted period of political unrest in the North-West and South-
West Regions during which there were mass protests and arrests causing limited economic activity and shutdown of schools. Since the completion of the project, the situation has deteriorated significantly and recently, after 2 local government officials were allegedly kidnapped in Batibo by an organisation advocating for independence of the two anglophone regions, more people have fled Batibo anticipating a further escalation in violence. It is difficult to ascertain to what extent these migratory factors may have affected our sample population given the lack of up-to date census data of our study population. Any resulting selection bias is, however, probably minimal given the large sample size. In addition, some demographic characteristics of our study population are compatible with data obtained during a recent ivermectin distribution campaign. For example, 53.7% of our sample was female which is almost identical with that of the population enumerated during the ivermectin distribution
(53.2%) (personal communication, DMO).
This study was set up to estimate the prevalence of epilepsy and associated risk factors in a rural health district in the North-West Region of Cameroon. To our knowledge, these are the largest cross-sectional and case control studies of epilepsy in Cameroon, using ILAE guidelines for epidemiological study of epilepsy (Thurman et al., 2011). The non-participation
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in stage 2 of people screened positive in stage 1 (53%) may be due to the lack of road infrastructure in many parts of the health district, limiting accessibility to the centres by people from remotely located communities. Non-participation could also result from fear, by people with epilepsy, of disclosing their epilepsy status to other members of the community. In Batibo, as in many communities in SSA, there is a high level of stigma and discrimination towards people with epilepsy which can lead to concealment of the condition by the people affected and their families (Njamnshi et al., 2009). Concealment may also explain why 21 people who screened negative in stage 1 opted to be assessed by the clinician in stage 2 since it was observed that all of them had a history of epileptic events and 13 had active epilepsy.
Variations in participation in stage 2 between health areas may be related to the differences in levels of community engagement and mobilisation for health activities between health areas.
6.2.2 Life-time prevalence of epilepsy
The age-standardised life-time prevalence of epilepsy in the present study (4.1% [95% CI:
3.7-4.4%]) is significantly higher than the median life-time prevalence of epilepsy for developed countries (0.6%) (Ngugi et al., 2010). It is similar to the value reported in a previous study of a rural population in the Centre Region of Cameroon (4.9% [95% CI; 3.9-6.0])
(Njamnshi et al., 2007); both Cameroonian estimates are close to or above the 95th percentile of values of the lifetime prevalence of epilepsy in rural communities in LMICs (median: 1.5%
[5th–95th percentile range: 0.5–4.9]) (Ngugi et al., 2010). While the Cameroonian estimates do not necessarily represent the prevalence of lifetime epilepsy in the country, given that communities studied were selected based on speculation that epilepsy is common in them, they nonetheless show that certain communities in Cameroon may be among the most affected by epilepsy in SSA.
6.2.3 Prevalence of active epilepsy
We focused specifically on people with active epilepsy because, from a public health perspective, they are the category of people with epilepsy who need to be prioritised in the
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allocation of resources to alleviate the burden of epilepsy in this community. The prevalence of active epilepsy in our study population is high but may have been underestimated since our estimate did not correct for sensitivity of the 2-stage screening method, which is estimated to be 76.7% in countries in SSA (Ngugi et al., 2012). Assuming this sensitivity in our study population, the prevalence of active epilepsy in Batibo could be as high as 45.2/1,000.
Comparing with other studies in SSA
The prevalence of active epilepsy in this rural Cameroonian health district (34.7/ 1,000 [95%
CI: 31.8-37.8]) is above the 75th percentile of estimates from studies in SSA (median 14.2:
IQR= 8.0-33.2) (Ba-Diop et al., 2014). It is challenging to compare estimates of the prevalence of active epilepsy between individual studies in SSA because of several differences in study methods including: type of study population (rural vs urban); screening methods (door-to-door vs cross-sectional); definition of active epilepsy; methods of case ascertainment; and the size of study population studied.
To ensure an objective assessment of how the prevalence of active epilepsy in this study relates with values from other studies in SSA, comparison was limited to population-based studies of active epilepsy of at least 1,000 people carried out within the past 25 years in SSA
(Table 14). The prevalence of active epilepsy in this study is significantly higher than estimates from most countries. In one study which was carried out across five countries in SSA from which the present study was adapted, the highest prevalence was reported in Ifakara,
Tanzania 14.8/1,000 (13.8-15.4) (Ngugi et al., 2013a) which is less than half the estimate in this study. Whereas our study included people with non-convulsive seizures, the multi-centre
African study was restricted to people with convulsive epilepsy, which may partially explain the difference. The difference in case definition notwithstanding, this study confirms the observation of regional variations in the prevalence of epilepsy in Africa in a recent systematic review; the prevalence was highest in the Central African region (all the studies were from
Cameroon) and lowest in East Africa (Ba-Diop et al., 2014).
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Table 14. Prevalence of active epilepsy from recent community-based studies in SSA
Location/Country Study Identification of people Active epilepsy Prevalence / Study period Population with epilepsy definition /1,000 (95% Study CI) Present study Batibo Health 39,525 2-stage screening: Two or more 34.7 (31.8- District, Cameroon House-to-house unprovoked 37.8) 2017 screening with a follow- seizures with at up assessment of people least one in the with suspected epilepsy preceding 12 by physicians with months epilepsy training Pilot of present Ndu Health 5, 110 3-stage screening: 2 Two or more 7.3 (4.4- study District, Cameroon stages of House-to- unprovoked 12.8) 2016 house screening with a seizures with at follow-up assessment of least one in the people with suspected preceding 12 epilepsy by physicians months with epilepsy training
Ae-Ngibise et Kitampo, Ghana, 113,796 House to house survey in Two or more 10.1 (9.5- al., 2015 2010/2011 two stages. First stage seizures, at least 10.7) with broad questions one in past 12 followed-up with more months detailed symptom-based question
Almu et al., Zay Society, 1,154 Door-to door screening Two or more 29.5 2006 Ethiopia, 2005 with questionnaire by seizures and at trained community least one in past 5 volunteers years; use of AED
Birbeck and Chikankata, 55,000 Door-to-door survey by Two or more 12.5 Kalichi, 2004 Zambia, 2001 trained community seizures, at least volunteers one in past 12 months epilepsy; AED treatment in past 12months
Colebunders et Oriental Province 2,906 Household screening by Seizures within past 23 al., 2016b DRC, 2014 team comprising 6 years physician, nurse and community distributor of Ivermectin (every third household)
Debrock et al., Zinvie, Benin, 3,134 Three methods: door to 21.1 2000 1997 door screening, key community informants, medical records
Dent et al., South Tanzania, 4,905 Door to door screening seizures in previous 7.7 (3.4- 2005 1999 by a team made of 5 years 12.1) medical student, nurse and community worker
Edwards et al., Rural Kenya, 2003 151,408 Door to door screening Two or more 4.5 (4.1-4.9) 2008 by census team followed seizures, one in past 12 months
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by detailed interview by health worker
Houinato et al., Rural Benin 2006- 11, 668 Three methods: Two more 12.7 (10.7- 2013 2007 household screening by unprovoked 14.9) community investigators; seizures with no use of key informants; immediate cause medical records
Kaiser et al., West Uganda 4,743 Questionnaire during Two or more 13 1996b 1994 Population census seizures in previous 2 years
Levick et al., Democratic 12,408 House to house Two or more 33 2017 Republic of Congo screening by team unprovoked 2014-2016 including a clinician seizures without fever
Kilifi Kenya 2007- 233 881 7.8 (7.5-8.2) 2008 3-stage screening: 1st Agincourt South 83, 121 stage: house to house 7.0 (6.2-7.4) Two or more Africa 2008- 2009 screening by community convulsive seizures volunteers. Iganga-Mayuge, 69, 186 24 hours apart, the 10.3 (9.5- Uganda 2009 2nd stage: in-depth last in the past 12 11.1) interview by health months
Ifakara, Tanzania 104, 889 workers 14.8 (13.8- 2009 15.4) Ngugi et al., 3rd stage: confirmation by 2013a Kintampo, Ghana 129, 812 physician 10.1 (9.5- 2010-2011 10.7)
Nwani et al., South-East 6,800 House to house to survey 4.3 (2.7-5.9) 2015 Nigeria, 2015 by community volunteers
Rwiza et al., Tanzania, 1991 18,183 House to house survey Two seizures, at 10.2 1992 by 4th year medical least one in past 24 students and Nurses months
Winkler et al., Tanzania 2003- 7,399 House to house survey Seizure in past 5 8.7 (6.7–11) 2009b 2004 by community workers years; or taking AED
Comparing with other studies in Cameroon (Table 15)
The prevalence of active epilepsy was about 5 times higher in Batibo than in Ndu Health
District, the other site in the North-West Region where the pilot survey was carried out. Given that identical methods and questionnaires were used in both study sites, this difference confirms our hypothesis that epilepsy is more common in Batibo than in Ndu and this probably reflects a disproportionate exposure to predisposing factors to epilepsy in health districts
(discussed below).
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The prevalence of active epilepsy in the Batibo Health District corroborates with previous reports of high prevalence of epilepsy elsewhere in the Centre Region (49.4/1,000) (Njamnshi et al., 2005, Njamnshi et al., 2007) and the Littoral Region (135/1,000) (Prischich et al., 2008).
It is difficult to ascertain the magnitude and the significance of the differences between these studies given that they used different methods. For example, in the study in the Centre Region, the population screened for epilepsy (1,898 people) was over 20 times smaller than ours and unlike in the present study, the definition of epilepsy was not limited to people with active epilepsy (Njamnshi et al., 2005). The prevalence of 135/1,000 reported in a village in the
Littoral Region may not be applicable to the larger community because of the very small study population of 181 people (Prischich et al., 2008); during a recently completed follow-up survey to review the high prevalence of epilepsy in this population, epilepsy was confirmed in 16 out of all 207 inhabitants of the village, yielding a crude prevalence of 77/1,000 which was not significantly different from the crude prevalence reported in the previous study (105/1,000)
(Personal communication, Njamnshi).
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Table 15. Prevalence of epilepsy in various communities in Cameroon
Location/Cou Study Identification of Definition of Prevalence ntry/ Study Population people with epilepsy active /1,000 Study period epilepsy (95% CI) Present study* Batibo, North- 39,525 2-stage screening: Two or more 34.7 (31.8- West Region, House-to-house unprovoked 37.8) 2017 screening with a seizures with follow-up assessment at least one in of people with the preceding suspected epilepsy by 12 months physicians with epilepsy training Present study, Ndu Health 5, 110 3-stage screening: 7.3 (4.4- Pilot* District, House-to-house 12.8) ** Cameroon, screening with a 2016 follow-up assessment of people with suspected epilepsy by physicians with epilepsy training Njamnshi et al., Billomo, 1, 898 House-to-house: NA 49·0 (39·6– 2007 Centre confirmation of cases 60·0) ** Region, 2007 by physician Njamnshi et al., Bilomo, Centre 1,900 House-to-house: NA 58·4 (48·1– 2005 Region ,2000 confirmation of cases 70·4) ** by physician Prischich et al., Kelleng, 181 Cross-sectional: 2- Two or more 134·5 2008* Littoral stage house to house seizures, with (90.0– Region, 2008 screening in stage 1 at-least one in 178.0) followed by the past 12 confirmation of cases months by a physician at health centre *Studies limited to active epilepsy **values not age-standardised NA: Not available
Variation in the prevalence of epilepsy between health areas in the Batibo Health District
The prevalence of active epilepsy in this study varied significantly between health areas and, even within health areas, there was clustering of cases of epilepsy in some communities
(Supplementary Table 1, appendix). Clustering of epilepsy in this study is further supported by the fact that about 2% of households had more than one person with epilepsy; by comparison, in a recent study in the Democratic Republic of Congo where strong evidence of
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clustering of cases of epilepsy was demonstrated using geo-localisation methods, a similar proportion of households (1.5%) had more than one case of suspected epilepsy (Levick et al.,
2017). Reasons for variations in the prevalence of epilepsy between communities and the clustering of cases are diverse and could include the following: disproportionate access to basic health infrastructure and services; differences in exposure to social and environmental factors that increase the risk of epilepsy; and variations in genetic susceptibility to epilepsy.
The possible roles of genetic and environmental factors are discussed later.
Access to health facilities is unlikely to be an important factor associated with epilepsy in this study since all health areas have at least one health facility and the fact that there was no apparent difference in the prevalence of epilepsy between the most remotely located health areas (Anjake, Bifang, Eka, Kugwe, Larinji, and Olorunti) and those located closer to the district hospital (Ashong, Batibo, Bessi, Ewai, Ewoh, Guzang, Gwofon, Kulabei, Tiben and
Widikum) (Table 10). On the other hand, it is possible that practice of traditional medicine in this community and people’s attitudes towards it could contribute to differences in the prevalence of epilepsy between communities; temporary or permanent migration of people with epilepsy and relatives to be close to a traditional healer or witch doctors with a strong reputation of treating epilepsy and other neuro-psychiatric ailments is a common practice in the Batibo Health District (Personal communication, DMO). It is possible that such a practice, over a long time, could contribute to clustering of cases in communities with the highest concentration of traditional healers. This is, however, unproven and is unlikely to be the sole factor responsible for the differences in prevalence across the entire health district.
Gender-specific differences in prevalence of epilepsy
In HICs, the prevalence of epilepsy is generally higher in males than females, probably because of general increased risk-taking behaviour in males, predisposing to brain injury.
Overall, there was no significant gender-specific difference in the prevalence of epilepsy in our study population. A few large-scale studies in Uganda, South Africa and Tanzania
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corroborate our findings (Colebunders et al., 2016b, Ngugi et al., 2013a). Most studies in
SSA, however, have either reported a higher prevalence of epilepsy in males (Ngugi et al.,
2013a, Ae-Ngibise et al., 2015, Birbeck and Kalichi, 2004, Dent et al., 2005, Nwani et al.,
2015, Osuntokun et al., 1987) or females (Winkler et al., 2009b, Rwiza et al., 1992). These discrepancies in the relationship between gender and epilepsy across SSA may reflect the involvement of gender-dependent factors that could vary between communities or countries.
These factors may include; gender-dependent differences in exposure to common risk factors for epilepsy; differences between genders in premature mortality due to epilepsy; and differences between genders in awareness, stigma, and health seeking behaviour with respect to epilepsy.
Age-specific differences in the prevalence of epilepsy
In this study the peak prevalence of epilepsy was in the 3rd and 4th decades of life. People in this age group are also likely to be the most depended-upon by their families and the community and, consequently, epilepsy may constitute a huge social and economic burden for the families and the community. Our findings contrast with those from most studies in Africa which show a peak prevalence before the age of 20 (Birbeck and Kalichi, 2004, Colebunders et al., 2016b, Dent et al., 2005, Kaiser et al., 1996b); in a multi-centre African study the peak prevalence occurred before 18 years in four sites (Ghana, Kenya, Tanzania, Uganda) and was similar to ours in only one site (South Africa) (Ngugi et al., 2013a). A few studies in SSA reported similar patterns in age distribution of the prevalence of epilepsy to the present study
(Houinato et al., 2013, Rwiza et al., 1992, Winkler et al., 2009b) and there is some evidence suggesting that this pattern of age distribution of the prevalence of epilepsy is consistent with onchocerciasis or neurocysticercosis as aetiologies (discussed below). Differences in incidence, seizure remission rates and premature mortality due to epilepsy between countries could also be responsible for discrepancies in the pattern of age-specific prevalence of epilepsy in SSA.
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6.2.4 Incidence of epilepsy
Among people with active epilepsy during the cross-sectional survey, those whose first seizure occurred in the 12 months preceding the study were recorded as incident cases. The 1-year incidence of epilepsy in the Batibo Health District of 171.1/100,000 persons [95% CI: 114-
254.60]) has probably been underestimated because of the cross-sectional design of this study (discussed in detail below). Stigma towards people with epilepsy is common in this health district (Njamnshi et al., 2009), and could also have contributed to the underreporting of new-onset seizures because these people and their families may be more hesitant than those with established epilepsy, to disclose their condition. When the present study was designed, there was no information on the incidence of epilepsy in Cameroon. Data from a prospective cohort study in the Mbam Valley in the Centre Region has since become available and reveals an incidence of 350/100,000 person-years which is about twice the value in this study (Chesnais et al., 2017). The difference between this incidence rate and that of our study can be related to the fact that in using the cross-sectional design, our study may have grossly underestimated the incidence of epilepsy.
The incidence of epilepsy in this Cameroonian population is higher than the median incidence for LMICS (81.7 /100,000 [IQR: 28.0-239.5]) (Ngugi et al., 2011). Our results are similar to those of two African studies; one in Kenya (156/100,000) (Mung'ala-Odera et al., 2008) and the other in Uganda 187/100,000 (95% CI: 133-256) (Kaiser et al., 1998). Comparison between studies reporting the incidence of epilepsy in Africa must, however, be done with caution because of several methodological differences between studies; methods of case ascertainment and case definition; study design (retrospective vs prospective); follow-up or observation period; and type of epilepsy (life-time epilepsy vs active epilepsy) (Table 16). For example, studies that do not include people with non-convulsive seizures are likely to significantly underestimate the incidence of epilepsy (Ngugi et al., 2013a). Retrospective cohort and cross-sectional studies such as the present study may underestimate the incidence of epilepsy because reliance on recall can lead to inaccurate seizure reporting, especially
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when the recall period is long; in a Ugandan study where both retrospective and prospective methods were used to estimate the incidence of epilepsy, significantly more new cases were identified during the prospective phase than in the retrospective phase (Kaiser et al., 1998).
Finally, studies that include children below 5 years are prone to bias because of the risk of misclassification of febrile seizures or malaria-associated seizures, resulting in overestimation of incidence.
At a glance, the incidence of epilepsy in this study seems to be consistent with the high prevalence reported in the same community, yet when our results are compared with those of the recent Cameroonian study presented above (Chesnais et al., 2017) and another study in
Kenya (Ngugi et al., 2013b), there is an apparent mismatch between the incidence and the prevalence of epilepsy in our population. In the Kenyan study where incidence and prevalence where determined during two cross-sectional studies 5 years apart, the authors estimated that the incidence of all epilepsies (convulsive and non-convulsive) could range between 154 and
231/100, 000, which includes the value reported in our study. Meanwhile, the prevalence of epilepsy in the same population was 4.5/1,000 (95%CI: 4.1-4.9) which, allowing for non- convulsive epilepsy seizures which were not included, is significantly lower than the prevalence reported in our study (34.7/1,000). In the recently completed Cameroonian study, the incidence of 350/100,000 person-years was reported in the same community where the lifetime prevalence of epilepsy was found to be 4.9%, which is similar to that in this study
(4.1%). Extrapolating from the above studies therefore, one would have expected a higher incidence of epilepsy in our study, to correspond with the prevalence observed in the same population. This mismatch may partly be explained by the likelihood that the incidence of epilepsy has been underestimated as discussed above: correcting for attrition between the screening stages in the present study (dividing the incidence by 0.47), we estimate that that real incidence of epilepsy in this community could be about 361/100,000 persons-years. In addition, the mismatch between prevalence and incidence of epilepsy in this study relative to the other African studies could also be related to differences in aetiological factors, seizure
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remission rates and in premature mortality associated with epilepsy between the study populations.
Over three quarters of the incident cases were less than 20 years, with one-third of them less than 10 years and this would have been higher if people less than 6 years were included; the results are similar to findings in other studies in Africa where the proportion of incident cases aged less than 20 years ranged between 57.5% and 95%. Whereas the young age profile of incident cases in this study could suggest a strong role for genetic factors and could point towards inherited epileptic disorders such as juvenile myoclonic epilepsy and other inherited generalised epilepsies, the predominance of focal epilepsy among the incident cases (73%) favours secondary epileptogenic brain insults. Many studies in LMICs and a few in some
African countries report another peak in incidence in people above 50 years (Wagner et al.,
2015, Ngugi et al., 2013b), which was neither the case in our study nor most other studies in
Africa (Mung'ala-Odera et al., 2008, Houinato et al., 2013, Kaiser et al., 1998, Rwiza et al.,
1992, Tekle-Haimanot et al., 1997). This is not surprising given the low life expectancy in SSA and the high mortality that is associated with causes of epilepsy at this age, especially stroke
(Feigin et al., 2014).
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Table 16. Incidence of active epilepsy from community-based studies in SSA
Author year Location /Period Population Study design Follow- Incidence/100,0 up period 00 person- years
Present Batibo Health District, 39,525 Cross- 1 year 171.1 (114- study Cameroon, 2017 sectional study 254.60) Houinato et Rural Benin, 2006- 11,520 Longitudinal 18 69.4 (30-136.8) al., 2013 2007 cohort months Kaiser et al., West Uganda, 1991- 4,389 Prospective 4 years 156 1998 1995 and retrospective Mung'ala- Kenya, 2001-2004 8,326 Longitudinal 30 187 (133-256) Odera et al., cohort months 2008* Ngugi et al., Kenya, 2008-2012 151,408 Two cross- 5 years 77 (67.7-87.4) 2013b sectional studies 5 years apart Rwiza et al., Rural Tanzania, 1979- 16,635 Cross- 73 1992 1988 sectional study (historical data) Tekle- Central Ethiopia, 1997 61,686 2-4 years 64 Haimanot et al., 1997 Wagner et al., South Africa 2008- 276, 400 Two cross- 17.4 (13.1 (23) 2015 2012 person- sectional years surveys 4 years apart Winkler et al., Northern Tanzania, Cross- 81 (65 -101) 2009b 2003-2004 sectional study historical data * Only children between 6 and 12 years were included
6.2.5 Clinical characteristics of seizures and epilepsy
Age at seizure onset
The median age of seizure onset in this study population (11 years [IQR: 8-15]) is higher than
that reported in most studies in SSA, which is mostly less than 9 years (Kariuki et al., 2014,
Levick et al., 2017, Ae-Ngibise et al., 2015). Compared with a multi-centre study involving five
countries in SSA, the median age at onset of unprovoked seizures in this study is lower than
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found in Agincourt, South Africa (12.7: IQR: 3.4-27.0) but higher than that reported in the other sites: Ifakara, Tanzania (10.1; IQR: 2.4-17.4); Iganga, Uganda (2.0; IQR: 0.6-5.9); Kilifi, Kenya
(3: IQR:1.0-12.2); and Kitampo, Ghana (9.0; IQR: 3.0-15.0) (Kariuki et al., 2014). The moderately high age at seizure onset in this study, in the context of high malaria transmission and endemicity to onchocerciasis and cysticercosis raises the possibility that these parasitic diseases are involved. In a recent study in the Democratic Republic of Congo, the authors attributed a similarly high peak age of seizure onset (14-15) to onchocerciasis as a possible aetiology (Colebunders et al., 2016b).
Seizure frequency and status epilepticus and their implications
About 60% of people with epilepsy had frequent seizures (at least once a month), an indication that most of the people affected have uncontrolled seizures. The fact that daily seizures were more common in children (10.5%) than adults (2.7%) may be evidence of spontaneous remission of seizures with age or high mortality among those with severe epilepsy. The high rate of uncontrolled seizures in this study is consistent with the high treatment gap observed.
In about 22% of cases, seizures occurred only at night-time during sleep, when they were less likely to be observed and this contributed to the high proportion of unclassified seizures
(19.5%). About one quarter of people in this study had experienced status epilepticus which is within the range reported in African countries (4.7-40%) (Kariuki et al., 2014). Differences in the frequency of status epilepticus between countries in SSA probably reflects differences in access to treatment as well as the allocation of resources for epilepsy care. The frequency of status epilepticus could therefore be a reliable indicator of the quality of epilepsy treatment and adherence to treatment in African communities.
Seizure semiology and epilepsy classification
In this study seizures were classified according to the ILAE recommendations for epidemiological studies which was also used in a multi-centre study in five African countries
(Kariuki et al., 2014). The proportion of people in this study with focal seizures (41.1%) is similar to the average for the other African sites (45%), although it should be noted that there
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was variation between sites (31.3%-64.5%) (Kariuki et al., 2014). The type of epilepsy in this study was classified based on seizure semiology and findings on neurological examination; complementary examinations such as EEG and neuro-imaging were not available. Focal epilepsy was the most common epilepsy type (59%). It should be noted that most people with epilepsy in our study experienced more than one seizure type, which explains the predominance of focal epilepsy even though generalised seizures were the most reported seizure type. The proportion of focal epilepsy in this study is almost identical to findings in a multi-centre African study (60%) which used similar guidelines to define focal epilepsy, although EEG was also used to complement the diagnosis of focal epilepsy (Kariuki et al.,
2014). The preponderance of focal epilepsy in this study and many African studies is consistent with acquired structural brain abnormalities as the main causes of epilepsy in SSA.
6.2.6 Putative causes of high prevalence of epilepsy in the Batibo Health
District
Taenia solium cysticercosis
In the context of the high prevalence and incidence of active epilepsy in this pig-breeding rural
Cameroonian community, neurocysticercosis is an important aetiological factor to be considered. It is probably the commonest and most preventable cause of epilepsy in LMICs and, depending on the endemicity to cysticercosis in communities studied, it can be responsible for 18% to 57% of cases of active epilepsy (Rajshekhar et al., 2006, Raina et al.,
2012, Cruz et al., 1999, Mwape et al., 2015, Winkler et al., 2009a, Nsengiyumva et al., 2003).
Little is known about the risk of epilepsy associated with cysticercosis in the Batibo Health
District. In a study of 349 people with epilepsy in the Batibo Health District almost 16 years ago, 35% of them had positive antibody ELISA to Taenia solium (Zoli et al., 2003). This does not necessarily represent the risk of epilepsy given the absence of a control group and the poor sensitivity of serology relative to EITB in detecting people with calcific cerebral lesions
(Cruz et al., 1999); cerebral calcific cysts carry the highest risk of long-term recurrent seizures
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(Pradhan et al., 2003). The results, nonetheless, provide some indication of the level of exposure to Taenia solium and possible endemicity of the parasite in this health district.
Pig-breeding is widely practised in the Batibo Health District, driven by a high rate of pork consumption. The burden of human and porcine cysticercosis in the Batibo Health District is unknown but probably high based on several prevailing factors that favour the transmission of the parasite in humans and pigs. Firstly, traditional free-range pig-breeding is common in
Batibo and is generally associated with an increased risk of transmission of Taenia solium in pigs and humans (Ganaba et al., 2011). While almost all pig farmers reported that the animals were either penned or tethered, the chief veterinary technician for the district told us that most farmers also allow their animals to roam periodically to scavenge for food, to reduce the cost of feeding them. A similar practice was reported in some pig-breeding communities in Burkina-
Faso where pigs which were generally restrained for most of the year were often released to roam in the rainy season, resulting in an increased risk of porcine cysticercosis (Ganaba et al., 2011). Secondly, access to clean water is a major problem in the Batibo Health District and could further increase the risk of human cysticercosis. Most houses visited during the survey did not have access to clean pipe-borne water and relied on streams and other water sources of unreliable quality. Thirdly, lack of latrines and inappropriate usage increases the risk of human and porcine cysticercosis (Ganaba et al., 2011). In Batibo, whereas 91% of homes have a latrine, most are not constructed according to norms and less than 10% of latrine holes were routinely covered, which increases the risk of food contamination (Personal communication, Mayor of Batibo Council). Finally, the Batibo Health District has only two veterinary technicians and about 4 meat inspectors and given the high volume of livestock husbandry and pork consumption, it seems inevitable that most animals are slaughtered and consumed without proper inspection for cysticercosis and other zoonoses.
Conditions in the Batibo Health District, therefore, seem to be particularly suitable for the transmission of Taenia solium and, as a result, neurocysticercosis is probably endemic in this area and could be responsible for the high prevalence and incidence of epilepsy we have
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reported. This is supported by findings in the current study showing that the prevalence of epilepsy was over five times higher in the Batibo Health District than in a community in the
Ndu Health District with a larger Muslim population and where pig-breeding and pork consumption are less common. This corroborates with other studies in LMICs showing a correlation between the level of pig-husbandry and the prevalence of epilepsy in a community
(Singh et al., 2012, Prasad et al., 2007). It is not clear whether cysticercosis plays a role in the differences in the prevalence of epilepsy between health areas and in the clustering of cases in some communities and what ecological factors may be involved. Studies in some communities reveal that there can be clustering of carriers of Taenia solium in households
(Diaz Camacho et al., 1991), which may in turn predispose to clustering of cases of cysticercosis and epilepsy. There seemed to be no correlation between the level of pig keeping and the prevalence of epilepsy between health areas. This is not surprising given that the risk of cysticercosis depends more on contact with a human carrier of Taenia solium, than on contact with infected animals (Lescano et al., 2009). In addition, most pig-farmers sell their animals in the two major markets in the health district (Batibo and Widikum council markets), hence people from health areas where pig breeding is not common but who purchase pork from these markets are at risk of taeniasis. In a study in a Bolivian community endemic for cysticercosis, it was reported that the proportion of households with human disease was similar for households which owned pigs and those which did not; this was attributed to the fact that in communities where there is a high rate of pig infection there is ample opportunity for people to become infected, regardless of pig ownership (Carrique-Mas et al., 2001).
The characteristics of people with epilepsy further support the possibility of neurocysticercosis as a main aetiology. About 59% of the epilepsies were focal which may suggest cerebral insult as the cause of epilepsy and, while this may not be specific to neurocysticercosis, neurocysticercosis should be considered in this context. About 15% of people with epilepsy in this study had focal dyscognitive seizures, which is one of the characteristic features of temporal lobe epilepsy. Some authors have argued that neurocysticercosis is an important
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cause of temporal lobe epilepsy in endemic areas, although this remains subject of intense debate (Bianchin et al., 2012). Another important factor worth considering is the age pattern of the people with epilepsy in this study which is compatible with those of people with epilepsy in communities where neurocysticercosis has been identified as the main cause of epilepsy.
In the Batibo Health District, the peak prevalence of epilepsy was in the third and fourth decades of life and the mean age of people with epilepsy was 25.2 years (SD: 11.1). The median age of incident cases 13.5 years (IQR: 7-18). In one study in Burundi where the population attributable fraction of epilepsy due to neurocysticercosis was estimated to be 50%, the mean age of people with epilepsy was 26.8 years (SD:14.9) (Nsengiyumva et al., 2003) which is similar to the mean age of people with active epilepsy in this study. In Burkina-Faso, the prevalence of neurocysticercosis among people with epilepsy was highest in people over
40 years; people with epilepsy and neurocysticercosis were also more likely to have their first seizure above 12 years (Millogo et al., 2012), which corroborates with mean age of seizure onset in our study (12.4 years). In a series of studies in communities in Asia and Latin America where epilepsy was strongly linked with neurocysticercosis, the prevalence of epilepsy consistently peaked after 30 years and the mean age at seizure onset ranged between 15 and
21 years. (Raina et al., 2012, Rajshekhar et al., 2006, Singh et al., 2006, Villaran et al., 2009).
From this series of studies of epilepsy associated with neurocysticercosis, it seems that in communities where cysticercosis is endemic, seizures typically start around the mid-teens and the prevalence peaks in the 20-40 age group. The reasons for this relationship between neurocysticercosis-associated epilepsy and age are not clear but may be reflect age- dependent differences transmission dynamics of Taenia solium and vulnerability to symptomatic neurocysticercosis in the community.
To conclude, in the context of widespread pig-breeding and pork consumption and general poor hygiene and sanitation in our study population, several characteristics of the cohort of people with epilepsy are compatible with those of people with epilepsy attributed to neurocysticercosis. These findings, however, must be interpreted with caution given the
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likelihood of an alternative aetiology such as onchocerciasis (discussed below) and the possible confounding effects of other socio-economic factors related to poverty that could justify an independent coexistence of both conditions in our study population.
Onchocerciasis
Some findings in this study add to growing evidence linking onchocerciasis with epilepsy in
Africa (Kaiser et al., 2013). The Batibo Health District is one of many health districts in
Cameroon that are hyperendemic for onchocerciasis and it has been involved in sustained community treatment with ivermectin, known to be effective against the microfilariae.
Hyperendemicity to onchocerciasis in this health district is probably sustained by the fact that a river (River Momo) flows through most of the health district and could provide a suitable breeding ground for the simulium fly, the vector of Onchocerca volvulus; this is however yet to be proven since no entomological studies have been carried out around this river.
The high prevalence of active epilepsy observed in this hyperendemic focus corroborates with findings in other communities reporting a co-existence of a high prevalence of epilepsy and hyperendemicity to onchocerciasis in communities in Africa (Ovuga et al., 1992, Kaiser et al.,
1996b, Newell et al., 1997, Boussinesq et al., 2002, Kaiser et al., 2011, Dozie et al., 2006), including in the Mbam Valley in the Centre Region of Cameroon (Boussinesq et al., 2002,
Chesnais et al., 2017). The Mbam Valley is a major hyperendemic focus for onchocerciasis and contains the Sanaga River and its tributaries, known to be a suitable breeding environment for the simulium fly: in this area the prevalence of epilepsy was found to be 4.9% which is the highest reported in Cameroon (Njamnshi et al., 2007). It is possible that differential exposure to the Onchocerca volvulus and its vector is responsible for the differences in the prevalence of epilepsy between health areas and the clustering of cases of epilepsy in some communities in Batibo; the prevalence of epilepsy was generally higher in health areas and communities close to the Momo river compared with those located further from the river
(Figure 11). Similar observations of an inverse relationship between the prevalence of epilepsy and the geographical distance of the home from a fast-flowing river have been made in the
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Centre Region of Cameroon (Boussinesq et al., 2002) and, more recently, in the Democratic
Republic of Congo (Colebunders et al., 2016b). In the Democratic Republic of Congo, it was also shown that bathing daily in such rivers could be associated with an increased risk of epilepsy (OR: 16.33 [95% CI: 1.99–134.2]) (Colebunders et al., 2016a). Some authors have coined the term “river epilepsy” to refer to probable onchocerciasis-associated epilepsy in communities living close to rivers that favour the breeding of the simulium fly (Colebunders et al., 2016b). While an epileptogenic mechanism of onchocerciasis is yet to be established, this study and the recently completed cohort study in the Mbam Valley add to the growing evidence of a causal relationship between onchocerciasis and epilepsy.
It is possible that the high age of peak prevalence of epilepsy in the Batibo Health District is related to onchocerciasis as an aetiological factor. Many studies in onchocerciasis endemic areas have reported peak prevalence in the 10-19 age group followed by the 20-29 and 30-
39 age groups (Colebunders et al., 2016b, Kaiser et al., 1996a, Kaiser et al., 1998). The reasons for this age distribution are not known but some have suggested that a higher age of peak prevalence may reflect effectiveness of mass treatment with ivermectin in reducing the incidence of epilepsy in these communities. This is supported by recent evidence of a shift in the peak prevalence of epilepsy towards the older age groups in cohorts of people with epilepsy in hyperendemic communities with good ivermectin coverage in Cameroon and the
Democratic Republic of Congo (Boulle et al., 2017, Colebunders et al., 2016b). The Batibo
Health District has been involved in sustained community treatment with ivermectin for almost
10 years and, according to the statistics from the district health service, the therapeutic coverage has been good (>85%) with little variation between health areas (personal communication, DMO). It would be interesting, in future cohort studies, to investigate whether with time, any similar shifts in the age-specific prevalence of epilepsy occur in the Batibo.
Taken together, the ecological features of our study population, the clustering pattern of people with epilepsy and their age profile raise the possibility that onchocerciasis is a major cause of epilepsy in the Batibo Health District.
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HIV Infection
In this study, data was not gathered on the HIV status of the population because of logistic constraints and the challenges of dealing with ethical requirements for follow-up and treatment of those with a positive HIV diagnosis. Consequently, we cannot estimate the risk of epilepsy associated with HIV infection in the Batibo Health District. It is possible that the high prevalence of HIV in this health district significantly contributes to the high prevalence and incidence of epilepsy: the prevalence of HIV in Batibo (6.3%) is significantly higher than for the whole country (3.7%) (Personal communication, DMO). It is estimated that more than half of people affected either do not know their status or are not on treatment. Consequently, opportunistic infections such as, tuberculosis, meningitis, toxoplasmosis and encephalitis are the most common reasons for long-term hospital admission in the medical unit of the District
Hospital. In this context of high prevalence HIV and opportunistic infections, therefore, it is important that future epilepsy studies in this health district investigate to what extent these conditions contribute to the high incidence and prevalence of epilepsy and ascertain the impact of improved HIV prevention and treatment on the burden of epilepsy in this community.
6.2.7 Epilepsy-related injuries
The high proportion of people with sequelae of seizure-related injuries (29%), especially burns
(18%), is not surprising given the high frequency of uncontrolled seizures and status epilepticus. In HICs, where there is better access to treatment and awareness of the risks of seizures, seizure-related injuries are less common; for example, while burns due to seizures accounted for between 1.6% and 3.7% of burn unit admissions in HICs (Wirrell, 2006), they were responsible for 10.7% of admissions in a burn unit in Malawi (Boschini et al., 2014). The frequency of burns among people with epilepsy in Africa ranges varies between 7.5% and
20.4% and this could be due to factors such as access to treatment, frequency of convulsive seizures (which are more likely to predispose to injury) and awareness of the risks of seizures.
Epilepsy-related injuries, especially burns, further aggravate the burden of epilepsy among affected people and their families; seizure-related injuries are the main cause of premature
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mortality related to epilepsy (Thurman et al., 2017) and survivors of seizure-related burns are often left with severely disabling sequelae which can further aggravate stigma and compromise the quality of life of people affected. A selection of severe sequelae of burns caused by seizures among people with epilepsy in this study is shown in Figure 14. In rural communities in SSA such as Batibo, an individual’s standing in the village is mainly determined by their contribution to the welfare of their family and community, especially when roles are clearly defined. In Batibo and in most rural communities in Cameroon, cooking is carried out mainly by girls and women, usually on an open fire while older boys and men are expected to climb the palm tree to harvest palm nuts to make palm oil. Meanwhile children are responsible for fetching water from the stream and most laundry is done by women and children on the banks of the river or stream. These are just a few examples of chores that expose people with epilepsy to severe injury in Batibo and consequently, they often face an unfortunate dilemma: either they exempt themselves from such chores to avoid injuries, risking further stigmatisation, or they perform their roles and expose themselves to severe injuries or premature death.
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A. Two women with scars of burns due hot water during cooking
B. This 24-year-old lady has had two episodes of burns have left her with many scars and deformities. She cannot afford to keep away from the fireside because she must look after her 4 children, having recently been abandoned by her husband because of her epilepsy
C. These two adolescents are brother and sister with disbaling scars from burns. They also have younger sibling with epilepsy. Their mother is a widow with 6 children and cannot afford their AEDs so they mostly depend on donations
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D. The burns of this 14-year-old girl were so severe that her right forearm and left fingers had to be amputated. Thanks to a philanthropic organisation, she received plastic surgery on her left hand
E. This 19-year-old boy developed these deformities after having a seizure by the fireside and has since been unable to use his fingers and is totally dependent on relatives
F. The severe burns of this 25-year-old man left him blind in the right eye and with extensive scars on most of his face and upper torso.
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G. This 30-year-old woman has had seizures since she was 13 and she sustained these injuries after stopping her AEDs, after assurance from a traditional healer that he had cured her epilepsy
H. Finger deformities due to burns and fracture in a 17-year-old boy
I. Two women with severe deformities due to burns from seizures at the fireside
Figure 14 (A-I). Sample of people with sequelae of burns resulting from seizures
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6.2.8 Epilepsy treatment and associated factors
Most people with epilepsy in this study were on AEDs and phenobarbital was the most frequently used AED which is not surprising given its affordability: according to the Batibo
Health District drugs price list, a year’s treatment with phenobarbital costs less than £1 while carbamazepine and valproate are 5 to 10 times more expensive. This is consistent with recommendations that phenobarbital should be the first-line AED in rural communities in SSA
(WHO, 2017a). The epilepsy treatment gap in our study population is within the range of estimates for LMICs (Mbuba et al., 2008); most people on treatment were either non-adherent, had an inappropriate choice and dosage of AED, or purchased their drugs from an unreliable source (mobile drug hawkers, roadside drug stores and unlicensed pharmacies). Lack of
AEDs at the health centres was the main reason mentioned by people with epilepsy for poor adherence and this was corroborated by an inventory of the pharmacies during which it was observed that they were all regularly out of stock of phenobarbital and almost none had an alternative option such as valproate or carbamazepine. In some health areas, some people with epilepsy reported that pharmacy attendants occasionally inflated the prices of AEDs during shortages, obliging them to purchase from alternative sources. A similar observation was made in a previous study in the West Region of Cameroon where shortage of AED supplies was the main factor affecting adherence to epilepsy treatment (Preux et al., 2000). If this precarious situation of AED supplies in the Batibo Health District is not urgently addressed by the health authorities, optimism about the benefits of AED treatment will be lost (one third believed that their epilepsy is curable with AEDs) and more will be forced to purchase their
AEDs from unreliable sources or seek alternative treatments with unproven effectiveness.
Traditional medicine and spiritual healing by priests were popular alternative treatment choices by people with epilepsy in this study and this is consistent with the widely held belief in this community that epilepsy is caused by witchcraft (Njamnshi et al., 2009). Beliefs about the causes of disease can have a significant effect on health-seeking behaviour, in some cases leading people affected to seek alternative options such as traditional medicine,
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perceived to be more effective than hospital treatment. In this study, about 25% of people with epilepsy believed in witchcraft as the cause of their epilepsy and this belief did not seem to influence their being on AED treatment. This may suggest that the people with epilepsy in this community perceive the treatment options (hospital, traditional, spiritual) as complementary rather than competitive. A similar observation was made in the West Region where almost all people with epilepsy were taking both traditional medicine and AEDs (Preux et al., 2000). It was observed in a previous study in the Batibo Health District that traditional healers were willing to receive training on epilepsy and to cooperate with the district health authorities in seeking ways to improve care delivery to people with epilepsy (Njamnshi et al., 2010). In the long-term, however, inadequate management of people with epilepsy and poor seizure control
(fewer than 2% of people with epilepsy on treatment were seizure free) can reinforce the myth that AEDs are ineffective, predisposing people with epilepsy and their families to exploitation.
During this survey, the district health authorities revealed that some people from outside the health district with fraudulent claims of instant cure for epilepsy using African or Chinese traditional medicine periodically visit the most affected health areas and extort money from affected people and their families (Personal communication, DMO). These anecdotes underscore the complex social, cultural and economic factors underpinning the epilepsy treatment gap in the Batibo Health District and emphasise the need for an integrated approach, involving all the community stakeholders, to improve the quality of treatment for people with epilepsy.
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7 Case control study: findings and significance
Of the 546 people with active epilepsy, 380 were available to be interviewed for the case control study and complete data was obtained from them (312 adults and 68 children). Out of
420 randomly selected healthy subjects from the community (163 children and 257 adults), complete data could be collected from 278 people (181 adults and 97 children): data could not be obtained for 66 children (40.5%) and 76 adults (29.6%) and this non-response was adjusted for by multiple imputation as described in in the methods in section 5.
7.1 Results
7.1.1 Factors associated with epilepsy in children
The results of the analysis of factors associated with epilepsy are summarised in Tables 17 and 18: Table 17 shows the results of analysis of the raw data while Table 18 contains results of analysis after multiple imputation as described in chapter 5. While the results of the univariate analysis before and after imputation were generally similar for most variables, there were noticeable differences between the univariate analysis of the raw data and the imputed data for the following variables: abnormal pregnancy term, normal delivery, home delivery, febrile convulsion in a sibling and history of ivermectin treatment. These were the variables with the highest fraction of missing entries, given the challenges of obtaining information on childhood history in an environment where medical records are either non-existent or incomplete and considering that parents were not always available to provide the information.
The discrepancy in results for these variables probably resulted from the increased risk of error when imputing a large quantity of missing data. After multivariate analysis, however, the results before and after imputation were similar and the main factors associated with epilepsy were having dogs in the household and parents being related. The odds ratio for meningitis could not be computed because there was no case of meningitis among controls. Perinatal factors such as history of previous maternal still birth, abnormal pregnancy, complicated delivery, delivery at home and neonatal complications were more common in children with
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epilepsy than controls (based on analysis of the raw data), although the differences were not statistically significant after multivariate analysis of either the raw or imputed data. The vaccination status of children did not seem to differ between children and controls. More children with epilepsy (46%) than controls (10%) had a history of febrile seizures, although this was also not statistically significant after multivariate analysis. More children with epilepsy than controls lived in the same house as someone with epilepsy or had a family history of a first or second degree relative with epilepsy, but in each case the association was not significant on multivariate analysis. Ivermectin coverage for onchocerciasis control programme was less common in cases than controls but the difference was not statistically significant. Factors relating to hygiene and sanitation such as source of drinking water and toilet facilities were not significantly associated with epilepsy.
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Table 17. Factors associated with epilepsy in children (≤16 years): raw data
Risk Factor Children with Controls Univariate Analysis Multivariate Analysis active epilepsy OR (95% CI) P value OR (95% CI) P value Age 1.2 (1.1-1.3) 0.0004 1.2 (0.9-1.5) 0.247 Gender (male) 36/68 (52.9%) 77/163 (47.2%) 1.3 (0.7-2.3) 0.199 Orphan 4/51 (7.8%) 2/69 (2.9%) 2.9 (0.4-33.4) 0.706 History of maternal 12/49 (24.5%) 6/67 (8.9%) 3.5 (1.1-12.3) 0.0016 1.5 (0.1-16.9) 0.758 still birth Abnormal term 8/41 (19.5%) 2/61 (3.3%) 7.2 (1.3-71.6) 0.0069 NA pregnancy Normal delivery 44/48 (91.7%) 63/64 (98.4%) 0.2 (0.03-1.9) 0.086 Home delivery 15/52 (28.9%) 13/68 (19.1%) 1.7 (0.7-4.4) 0.212 Birth/neonatal 15/49 (30.6%) 11/68 (16.2%) 2.4 (0.9-6.5) 0.05 1.5 (0.2-9.3) 0.677 complication Completed vaccines 38/49 (77.6%) 49/68 (72.1%) 1.2 (0.5-3.3) 0.592 Febrile convulsion 23/50 (46%) 7/68 (10.3%) 7.8 (2.8-23.7) <0.001 4.1 (0.4-41.3) 0.231 Febrile convulsion in 8/51 (15.7%) 7/68 (10.3%) 1.7(0.5-5.9) 0.334 sibling Poor toilet facilities 58/68 (85.3%) 85/97 (87.6%) 0.8 (0.3-2.2) 0.664 Reliable water source 42/68 (61.8%) 63/97 (65%) 0.8(0.4-1.7) 0.676 Cats in household 16/51 (23.9%) 32/95 (33.7%) 0.6 (0.3-1.3) 0.178 Dogs in household 6/68 (8.8%) 25/97 (25.8%) 0.3 (0.08-0.7) 0.006 0.08 (0.07-1.1) 0.062 Pigs household 30/68 (44.1%) 50/97 (51.6%) 0.7 (0.4-1.4) 0.347 Person with epilepsy 20/68 (29.4%) 15/97 (15.5%) 2.3 (0.99-5.2) 0.03 2.4 (0.4-15.9) 0.370 in household 1st degree relative 14/68 (20.6%) 3/97 (3.1%) 8.1 (2.1-45.4) 0.0003 1.0 (0.04-23.3) 0.994 with epilepsy 2nd degree relative 26/67 (38.8%) 17/93 (19.3%) 2.78 (1.3-6.2) 0.004 2.4 (0.4-12.9) 0.311 with epilepsy Parents related 3/59 (5.1%) 12/72 (16.8%) 0.3 (0.05-1.07) 0.03 0.07(0.05-1.0) 0.05 History of meningitis 8/68 (16.8%) 0/93 NA Head injury 9/58 (15.5%) 2/76 (2.6%) 6.8 (1.3-66.3) 0.007 1.1 (0.02-54.4) 0.948 Received Ivermectin 57/86 (66.2%) 84/96 (87.5%) 0.7 (0.3-2.0) 0.504 Had same meal in 6/64 (9.4%) 7/90 (7.8%) 1.2 (0.3-4.5) 0.725 past 3 days Food taboos 35/68 (51.5%) 7/87 (8.1%) 12.1 (4.6-35.0) <0.001 2.9 (0.4-22.6) 0.226 Attends school 31/55 (56.4%) 57/72 (79.2%) 0.3 (0.1-0.8) 0.0058 0.3 (0.004-7.2) 0.356
Values in bold indicate statistical significance NA: Not available (could not be computed)
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Table 18. Factors associated with epilepsy in children (≤16 years): after imputation*
Risk Factor Univariate Analysis Multivariate Analysis
OR (95% CI) P value OR (95% CI) P value
Age 1.2 (1.1-1.3) 0.0004 1.2 (1.1-1.4) 0.0003
Gender (male) 1.2 (0.7-2.2) 0.479
Orphan 0.8 (0.2-3.4) 0.706
History of maternal still birth 1.0 (0.2-3.9) 0.91
Abnormal term pregnancy 0.6 (0.3-2.2) 0.547
Normal delivery 2.8 (1.1-7.4) 0.02 1.8 (0.5-6.5) 0.343
Home delivery 0.7 (0.3-1.4) 0.223
Birth/neonatal complication 1.0 (0.3-2.9) 0.914
Completed vaccines 2.0 (0.6-6.4) 0.241
Febrile convulsion 1.4 (0.4-6.4) 0.515
Febrile convulsion in sibling 0.7(0.2-2.6) 0.555
Poor toilet facilities 1.2 (0.3-5.3) 0.821
Reliable water source 1.4 (0.4-4.1) 0.726
Cats in household 0.5 (0.2-1.5) 0.245
Dogs in household 0.2 (0.05-0.7) 0.007 0.2 (0.05-0.6) 0.052
Pigs household 0.7 (0.3-1.7) 0.645
Person with epilepsy in 1.1 (0.4-3.4) 0.859 household
1st degree relative with epilepsy 1.7 (0.4-8.3) 0.481
2nd degree relative with epilepsy 1.7 (0.5-5.8) 0.391
Parents related 0.2 (0.03-0.7) 0.018 0.2 (0.03-0.8) 0.0237
History of meningitis ∞
Head injury 1.4 (0.2-11.8) 0.833
Received Ivermectin 2.2 (0.5-9.6) 0.301
Had same meal in past 3 days 0.8 (0.1-5.7) 0.823
Food taboos 3.9 (0.9-18.1) 0.08
Attends school 0.8 (0.2-2.5) 0.630
** Values computed after imputation using the MICE method to adjust for non-response from 66 controls and for missing entries: statistically significant values in bold
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7.1.2 Factors associated with epilepsy in adults
The results analysis for factors associated with epilepsy before and after imputation for missing data are presented on Tables 19 and 20 respectively. Overall, the results of the raw data and the imputed data were similar. After imputation and multivariate analysis, two factors were positively associated with epilepsy: family history of a first degree relative with epilepsy
(OR 7.4: 95%CI: 3.4-16.3) and having food taboos (OR 6.1: 95%CI: 2.9-12.6). The other factors which were significantly associated with epilepsy showed a negative association and these included: alcohol consumption (OR 0.4: 95%CI: 0.2-0.8), smoking (OR 0.1: 95%CI
:0.03-0.6), parents having a blood relationship (OR 0.05: 95%CI: 0.01-0.2), receiving ivermectin for onchocerciasis control (OR 0.2: 95%CI:0.1-0.5), and attaining post-secondary education (OR 0.1: 95%CI:0.01-0.4) and being married (0.4: 95%CI: 0.2-0.7). Having pigs, dogs or cats in the household were each less common among people with epilepsy than controls, although none of the difference were statistically significant. A history of conditions predisposing to brain injury (such as coma, stroke, meningitis and head injury) were more common among adults with epilepsy than in healthy subjects. These differences were however, non-significant after multivariate analysis.
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Table 19. Factors associated with epilepsy in adults (>16 years): raw data
Risk Factor People with Controls Univariate analysis** Multivariate analysis** active epilepsy
OR (95% CI) P value OR (95% CI) P value
Age 0.94 (0.93-0.96) <0.0001 0.96 (0.93-0.97) <0.0001
Gender (male) 145/312 (46.5%) 124/257 (48.2%) 0.9 (0.7-1.3) 0.673
Married 75/309 (24.3%) 104/171 (60.8%) 0.2 (0.1-0.3) <0.0001 0.5 (0.2-1.0) 0.06
Alcohol 130/310 (41.9%) 126/167 (75.5%) 0.2 (0.1-0.3) 0.007 0.4 (0.2-0.9) 0.02
Smoking 4/310 (1.3%) 15/167 (9.0%) 0.1 (0.03-0.4) <0.001 0.2 (0.03-1.9) 0.167
Recreational drugs 4/311 (1.3%) 6/167 (3.6%) 0.3 (0.07-1.5) 0.09
History of stroke 7/311 (2.3%) 1/168 (0.6%) 3.8 (0.5-174.0) 0.177
History of Coma 45/310 (14.5%) 11/166 (6.6%) 2.3 (1.2-5.3) 0.01 2.4 (0.7-8.7) 0.165
Poor toilet facilities 259/312 (83%) 155/181 (85.7%) 0.8 (0.5-1.4) 0.444
Reliable water source 174/312 (55.8%) 121/181 (66.9%) 0.6 (0.4-0.9) 0.015 0.6 (0.3-1.2) 0.124
Cats in household 86/311 (27.7%) 58/180 (32.2%) 0.8 (0.5-1.2) 0.284
Dogs in household 48/312 (15.4%) 43/179 (24%) 0.6 (0.4-0.9) 0.02 0.7 (0.3-1.8) 0.500
Pigs in household 102/312 (32.7%) 99/181 (54.7%) 0.4 (0.3-0.6) <0.0001 0.4 (0.2-0.8) 0.007
Person with epilepsy in 111/312 (35.6%) 35/181 (19.3%) 9.8 (5.2-20.1) <0.0001 0.4 (0.2-1.1) 0.100 household
1st degree relative with 128/312 (41%) 12/181 (6.6%) 4.1 (2.5-6.9) <0.0001 11.7 (3.7-36.9) <0.0001 epilepsy
2nd degree relative with 123/300 (41%) 25/174 (14.4%) 2.1 (0.8-5.1) 0.112 11.2 (3.9-32.4) <0.0001 epilepsy
Parents related 4/293 (1.4%) 23/123 (8.7%) 0.06(0.01-0.18) <0.0001 0.03 (0.07-0.1) <0.0001
History of meningitis 15/309 (4.9%) 2/169 (1.2%) 4.2 (0.9-37.8) 0. 383
History of head injury 40/308 (13%) 4/165 (2.4%) 6.0 (2.1-23.4) 0.0002 4.1 (0.9-17.9) 0.063
Received Ivermectin 190/311 (61.1%) 156/174 (89.7%) 0.2 (0.09-0.3) <0.0001 0.2 (0.1-0.7) 0.005
Same meal past 3 days 32/283 (11.3%) 11/172 (6.4%) 1.9 (0.9-4.2) 0.824
Food taboos 144/304 (37.4%) 21/171 (12.3%) 6.4 (3.8-11.2) <0.0001 4.8 (2.0-11.4) 0.005
Post-secondary 6/310 (1.9%) 11/171 (6.4%) 0.08 (0.02-0.9) <0.0001 0.3 (0.04-1.8) 0.175 education
Values in bold indicate statistical significance
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Table 20. Factors associated with epilepsy in adults (>16 years): after imputation*
Risk Factor Univariate analysis Multivariate analysis
OR (95% CI) P value OR (95% CI) P value
Age 0.94 (0.93-0.96) <0.0001 0.95 (0.93- <0.0001 0.97)
Gender (male) 0.9 (0.7-1.3) 0.673
Married 0.4 (0.3-0.6) <0.0001 0.4 (0.2-0.7) 0.006
Alcohol 0.3 (0.1-0.7) 0.007 0.4 (0.2-0.8) 0.01
Smoking 0.1 (0.02-0.4) 0.001 0.1 (0.03-0.6) 0.01
Recreational drugs 0.1 (0.03-0.7) 0.01 2.4 (0.2-26.4) 0.486
History of stroke 1.2 (0.04-41.4) 0.905
History of Coma 1.8 (0.8-4.2) 0.185
Poor toilet facilities 1.9 (0.9-3.9) 0.068
Reliable water source (tap water) 0.8 (0.4-1.7) 0.569
Cats in household 0.5 (0.3-0.8) 0.006 0.8 (0.4-1.5) 0.489
Dogs in household 0.7 (0.4-1.2) 0.171
Pigs in household 0.6 (0.3-1.0) 0.056
Person with epilepsy in household 1.7 (0.9-3.0) 0.073
1st degree relative with epilepsy 7.0 (2.8-17.8) <0.0001 7.4 (3.4-16.3) <0.0001
2nd degree relative with epilepsy 2.1 (0.8-5.1) 0.112
Parents related 0.05 (0.01-0.1) <0.0001 0.05 (0.01-0.2) <0.0001
History of meningitis 1.4 (0.1-17.2) 0.627
History of head injury 3.6 (0.8-16.5) 0.093
Received Ivermectin 0.2 (0.07-0.4) <0.0001 0.2 (0.1-0.5) <0.0001
Had same meal in past 3 days 1.6 (0.6-4.8) 0.349
Food taboos 5.4 (2.2-13.3) <0.0001 6.1 (2.9-12.6) <0.0001
Post-secondary education 0.1 (0.02-0.2) <0.0001 0.1 (0.01-0.4) 0.003
* Values computed after imputation using the MICE method to account for non-response from 76 controls and for missing entries: statistically significant values in bold
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7.2 Discussion
7.2.1 Genetic Factors
We have shown that family history is strongly associated with epilepsy in this Cameroonian population and this is similar to findings in other countries in SSA (Edwards et al., 2008)
(Matuja et al., 2001, Nsengiyumva et al., 2003, Wagner et al., 2014); In this study, having a first degree relative with epilepsy was strongly associated with epilepsy in adults but not children. This may imply the presence of inherited genetic factors predisposing to epilepsy which depend on some environmental triggers later in life such as infections (discussed above). The familial clustering of people with epilepsy in this study may be the result of differences in inherited genetic susceptibility to epilepsy between individuals exposed to the parasites discussed above and possibly other infections. A family history of epilepsy may also be due to the likelihood of exposure to the same environmental risk factors in people sharing the same household; this does not seem to apply in this study because living in the same house with someone with epilepsy was not significantly associated with epilepsy in either adults or children.
Consanguineous relationships could increase the risk of epilepsy because of the increased likelihood of offspring inheriting familial genes that predispose to epilepsy. In our study, being the offspring of related parents was associated with a reduced risk of epilepsy in children and adults and this contrasts with findings in a study in Tanzania where having consanguineous parents was significantly associated with epilepsy (Matuja et al., 2001). The reasons for the negative association are not clear but unknown social and cultural factors related to marriage and epilepsy in Batibo could be involved. Some of the differences could also result from misclassification due to interviewer bias; questions on consanguineous relationships can be complex in the African setting and are subject to diverse interpretations by both the interviewer and the respondent.
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7.2.2 Adverse perinatal and childhood events
Information on perinatal factors and childhood events that could predispose to epilepsy was collected for children (≤16years) only, since the recall of such events is less accurate in adults.
Epilepsy was strongly associated with meningitis in children and this is not surprising given that it is a known complication and was recently found to be strongly associated with epilepsy in a cohort study in Senegal (Edmond et al., 2010). None of the other perinatal and childhood factors investigated was associated with epilepsy and these include; history of previous maternal stillbirth, home delivery, complicated delivery, complication at birth or during the neonatal period, vaccination history, history of febrile seizures, and family history of febrile seizures.
The absence of a significant association between adverse perinatal events and epilepsy in this study contrast with most studies in SSA (Ae-Ngibise et al., 2015, Edwards et al., 2008,
Matuja et al., 2001, Ngugi et al., 2013a, Wagner et al., 2014) especially in the multicentre
African study where the odds of adverse perinatal events among people with epilepsy compared with controls was 6·4 (95% CI: 3·3–12·5) (Ngugi et al., 2013a). The lack of association between perinatal complications and epilepsy in Batibo is surprising given that in this health district, as in most rural health districts in Cameroon, basic obstetric and neonatal care remains inaccessible for most people (Personal communication, DMO). This finding may be related to high premature mortality in the children with perinatal complications, driven by other severe neurodevelopmental complications that may be involved.
While a history of febrile seizures was not significantly associated with epilepsy in multivariate analysis, it was nonetheless high among people with epilepsy in this study (46%) and similar to values reported in other studies in Africa that found a significant association (Matuja et al.,
2001, Mung'ala-Odera et al., 2008). It is worth noting that in general, an association between febrile seizures and epilepsy does not necessarily imply causation since febrile seizures could also be the first manifestation of some epilepsy disorders beginning in childhood.
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7.2.3 Head Injury
Head injury was not significantly associated with epilepsy in this study and this corroborates with most studies in SSA (Wagner et al., 2014, Nsengiyumva et al., 2003, Ae-Ngibise et al.,
2015). A few other studies in Africa found a significant association between head injury and epilepsy (Edwards et al., 2008, Ngugi et al., 2013a). Differences in the characteristics of the study sites could explain these inconsistencies. Batibo is largely rural with hardly any proper road infrastructure and most movement is either by foot or motor-bike through narrow bush roads. Compared to urban centres, therefore, people living here are less likely to suffer from head injuries due to road traffic accidents. Consequently, head injury is unlikely to be an important risk factor for epilepsy in this population. It should be noted that studies investigating head injury as a risk factor for epilepsy retrospectively may be biased because of confounding effects of falls during seizures.
7.2.4 Nutrition-related factors
Signs of malnutrition were common in this study population (45%) and this corroborates with findings in a previous study in Benin which reported higher odds of malnutrition among people with epilepsy with respect to controls (OR: 2.9: 95%CI: 1.6-7.1) (Crepin et al., 2007a). In SSA while malnutrition can be a predisposing factor to epilepsy in certain communities, it can also be a consequence of cultural beliefs about food and epilepsy. Food taboos have been shown to be strongly associated with epilepsy in Benin and this was confirmed in our study where we found a high proportion of people with epilepsy having food taboos (half of children and over one third of adults). In Batibo, foods most commonly avoided were okra soup, pork, and birds and the reasons for avoiding them reflect cultural beliefs about epilepsy which range from simple misconceptions to deeply rooted beliefs and customs. Pork is avoided because of knowledge that the pork tapeworm is associated with epilepsy, although in this case there is obviously a misconception that it is eating the pork after epilepsy is established that predisposes to seizures. Soup made with okra is, however, avoided because of the misconception that its slimy texture increases the risk of falls. Table birds are avoided because
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of a deeply rooted belief that epilepsy is due to bad spirits found in certain birds: in the Batibo language, one of the words used to refer to epilepsy is “awoshu”, which is a type of bird and many people associate generalized convulsions with the flapping of a bird’s wings.
Unfortunately, most of these foods are the most affordable in this community and of high caloric and protein value; avoiding them increases the risk of malnutrition which may further increase vulnerability to seizures, especially among people with epilepsy.
7.2.5 Having animals in household
Living in a house where pigs are kept was not significantly associated with an increased risk of epilepsy. A similar observation was made in another study in a community in Tanzania where neurocysticercosis was strongly linked with epilepsy (Hunter et al., 2015). This is not surprising given that, as discussed above, other more important factors such as proximity to a Taenia solium carrier and the level of personal hygiene are essential for the transmission of cysticercosis. Sustained contact with dogs and cats generally increases exposure to toxocariasis and toxoplasmosis, both of which are associated with an increased risk of epilepsy in LMIC as well as HICs (Ngoungou et al., 2015b, Quattrocchi et al., 2012). The lack of association between having these animals and epilepsy in this study does not necessarily imply that the zoonoses associated with them are not involved in epilepsy in this community.
In the multi-centre African study, whereas no significant association was found between having these animals and epilepsy, both toxocariasis and toxoplasmosis were significantly associated with epilepsy (Ngugi et al., 2013a). This is not surprising given that in LMICs, the risk of toxocariasis and toxoplasmosis may depend more on poor personal and food hygiene than on contact with these animals (cats and dogs) since they are usually not treated as pets and have relatively limited direct contact with humans who keep them, compared with HICs.
Both parasitic infestations need to be investigated in future studies of the risk factors for epilepsy in this population. They are, however, unlikely to explain the high prevalence of epilepsy reported in this population.
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7.2.6 Hygiene and sanitation
In this study, neither the lack of latrines nor the latrines holes not being covered was significantly associated with epilepsy. This was also the case for lack of a reliable water source. These basic factors of hygiene and sanitation are implicated in the transmission of certain food and waterborne parasitic infestations associated with epilepsy and, although they have not been associated with epilepsy in this study, they must be considered as part of any strategy to prevent epilepsy through parasite control.
7.2.7 Ivermectin coverage
Interestingly, in this study it was found that adults with epilepsy were less likely to have received ivermectin than controls, which corroborates with recent suggestions that ivermectin treatment could reduce the risk of epilepsy (by preventing onchocerciasis) (Colebunders et al., 2017): it is also believed to have anti-convulsant effects and could even be effective as an adjuvant in refractory seizures (Diazgranados-Sanchez et al., 2017). Alternatively, less therapeutic coverage with ivermectin among people with epilepsy could have resulted from the fact that some community distributors of ivermectin withheld the drug from people with epilepsy due to a misconception that epilepsy is one of the “severe” conditions for which ivermectin prophylaxis was contraindicated (Personal communication, DMO).
7.2.8 Alcohol, smoking and recreational drug use
People with epilepsy in this study were significantly less likely to be smokers or to take alcohol than controls. They were also less likely to have taken recreational drugs although the difference was not statistically significant in multivariate analysis. These results may suggest that people with epilepsy avoid alcohol and similar products for fear of triggering seizures.
7.2.9 Education
In this study, epilepsy seems to have a significant negative effect on education. Epilepsy was associated with poor school attendance; about 40% of children were not attending school and, for 74% of them, epilepsy was the reason why they dropped out of school. Significantly less
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people with epilepsy attained post-secondary education than controls. Reports from community leaders in Batibo suggest that some parents opt to withdraw their children from school to avoid the embarrassment the child may face when seizures occur at school. Some children are expelled from school by teachers with instructions that the child’s seizures should be well controlled before they are re-admitted. This is consistent with previous reports in this community showing a high level of stigma and discrimination towards people with epilepsy, especially children (Njamnshi et al., 2009). This unfortunate situation emphasises the importance of involving teachers in tackling epilepsy in Batibo and similar communities in
Cameroon.
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Chapter 8: Limitations, conclusions and future directions
8 Limitations, conclusion and future directions
8.1 Limitations
Some limitations need to be considered when interpreting the significance of the findings in this study. The study questionnaires were prepared in English but administered mainly in
Pidgin-English and various dialects of the Batibo language by field workers. There may have been variability, between field workers, in interpretation and the administration of the questionnaire. This was limited by involving interpreters with mastery of these languages to assist in the training of the field workers in each site although, ideally, the questionnaires should have been professionally translated, back translated to verify the accuracy of the translation, and validated. This was not possible because in this community most people can hardly read or write these languages and dialects.
During the epilepsy screening, in addition to questions designed to identify convulsive seizures which have been validated and used in many countries in SSA, supplementary questions in stage 1 (Question 3 for the pilot and main study) and stage 2 (questions 7-10 for the pilot and questions 4 and 5 for main study) were included to help identify non-convulsive seizures.
These questions are yet to be validated in the African setting. Given the complexity of the questions identifying non-convulsive seizures, it is very important that in the future, when more resources become available, the modified questionnaire used in this study is validated to ascertain its sensitivity in identifying people with all types of epilepsy, not only convulsive epilepsy.
The relatively short period of the survey may have affected the coverage because of less available time to revisit unoccupied houses especially in remotely located health areas.
Additionally, this may have contributed to attrition between the stages of the screening given that only 1-2 days were available for stage 2 screening in each health area. Attrition was limited by sending the survey timetable to all the health areas for public announcement about
2-4 weeks before the start of the survey in each site.
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The second stage of the epilepsy screening involved confirmation of diagnosis by me with the assistance of two senior trainee neurologists. Ideally, we should have conducted a reliability test and provided an interrater reliability score (Kappa statistic) to determine objectively the consistency between the physicians’ assessments in stage 2. We are however confident that any inconsistencies between the physician reports may be minimal because all the physician involved are experienced in epilepsy diagnosis and treatment, acquired through their long- term involvement in epilepsy clinics in tertiary hospitals in Yaoundé. Inconsistencies were further minimised by the workshop with the physicians at the beginning of the study during which the algorithm for diagnosis and epilepsy classification was adopted further (see appendix page 175).
During the interview of people with epilepsy in the hospital, we did not keep a record of people for whom eyewitness account was available nor did we indicate the relationship of the eyewitness to the person interviewed. This information would have enabled an objective verification of the reliability of the seizure history and epilepsy classification in this study.
Future studies should address this shortcoming.
In this study, correction for attrition between the stages of screening was done by dividing the estimate of the prevalence by the participation rate between stages (0.471). This assumed that the prevalence of epilepsy would be the same for those who were assessed in stage 2 and those who screened positive in stage 1 but were not assessed in stage 2. It can be argued that people who did not attend stage 2 were either less or more likely to have epilepsy and could be less likely to have frequent seizures (which may have contributed to their decision not to attend stage 2). The attrition correction, therefore, may have led to an over- or under- estimation of the burden of epilepsy. On the other hand, the prevalence estimates are conservative since they were not adjusted for the sensitivity of the screening method; the sensitivity of the 2-stage screening method in SSA is estimated to be 76.7% (Ngugi et al.,
2012).
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Given the relatively short recall period (one year), the incidence in this study may not reflect the long-term risk of epilepsy in this community. The values, however, provide a basis for estimating the risk of epilepsy in Cameroon.
The effect estimates for the case control studies should be interpreted with caution because one third of controls could not be interviewed and although adjustments were made by imputation during statistical analysis, this may nonetheless have affected the effect measures, especially for variables concerning pregnancy and childhood history where there is a tendency for non-response because of the lack of reliable medical records. This underscores the importance of using prospective studies in investigating risk factors of epilepsy in SSA, especially for events occurring in the perinatal and childhood period.
It is important to note that for certain factors such as family history, perinatal/childhood history, and head injury, the risk of epilepsy associated with them may be overestimated because of recall bias. On the other hand, the risk of epilepsy associated with factors such as alcohol consumption, smoking, recreational drug use may have been underestimated in this study and many studies in SSA because of the likelihood of participants providing socially acceptable responses or the fear of admitting what is a criminal offence in these countries. This emphasises the importance of prospective cohort studies to better estimate the relationship of these factors with epilepsy in SSA.
8.2 Conclusion
These cross-sectional and case-control studies have generated important new evidence on the epidemiology and clinical characteristics of epilepsy in Cameroon. There is a high prevalence and incidence of active epilepsy in Batibo, a rural health district in the North-West
Region, which is endemic for onchocerciasis and cysticercosis. It is possible that either or both parasitic infestations are implicated; clinical characteristics of people with epilepsy in our study population seem consistent with those of people with epilepsy attributed to these conditions in other LMICs. Significant differences in the prevalence of active epilepsy between health
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areas and the clustering of cases in some families and communities is probably the combined effect of differential exposure to these parasites and underlying inherited genetic factors predisposing to epilepsy. The high proportion of people with epilepsy who have disabling epilepsy-related injuries reflects the serious consequences of the wide epilepsy treatment gap in this population. There is an urgent need for studies to ascertain the major aetiologies of epilepsy and for strategies to be developed to prevent epilepsy and reduce the epilepsy treatment gap in Cameroon.
8.3 Future Directions
8.3.1 Improving access to treatment through a community-centred initiative
We have shown that the epilepsy treatment gap in Batibo is wide and this is probably mainly due to lack of health personnel with epilepsy training and limited access to good quality anti- epileptic medication. At the end of the study, epilepsy training was provided to all doctors and selected nurses from all health centres and hospitals within the health district. While this may have improved the quality of care received by people with epilepsy in the short-term, a sustained and coordinated effort is needed to improve access to treatment and the quality of life of people with epilepsy in Batibo Health District. We recommend strengthening the existing epilepsy clinic in the District hospital and setting up monthly epilepsy clinic days in all health centres in the Batibo Health District, led by nurses who would receive training/retraining on the diagnosis and management of epilepsy at least once a year. On clinic days dedicated trained personnel would exclusively attend to people with epilepsy, reviewing their seizure history and treatment and providing education and counselling. The nurse would ensure that there is always an adequate stock of AEDs in the pharmacy. They would be assisted by community volunteers with epilepsy training who would be responsible for outreach to people in geographically isolated communities or those unable to attend because of a disability. The community volunteers would be recruited from the pool of community relay agents and community distributors of ivermectin because of their knowledge of the community, and would be supervised by the epilepsy nurse at the health centre. The clinics would be supervised and
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coordinated by the district hospital epilepsy team, led by a physician with special training in epilepsy, who would also review difficult cases referred from the health centres. Subsidisation of AEDs would encourage participation and improve adherence to treatment. Potential sources of funding for this project could include a variety of local and international bodies: village development associations; Cameroon Ministry of Public Health; churches and faith- based organisations; non-for-profit organisations: grant bodies; and WHO. This programme would be sustainable because of the strong community involvement and integration within the existing health system within the Batibo health district (Figure 15).
Communnty health workers •Mobile clinics in hard-to-reach communities •Home visits for people with epilepsy unable to travel to health centre •Family visits to encourage adherence and trace cases lost to follow-up •Engagement with traditional and religious authorities and community organisations
Batibo District Health Service District hospital epilepsy team •Provide infrastructure Nurse-led health •Treatment of referred and personnel for the area epilepsy clinic: cases clinics diagnosis, •Counter-referral to •Ensure availaibility of treatment and health centre anti-epileptic drugs in counselling of all health centres people with •Coordination and supervision of health •subsidise anti-epileptic epilepsy area epilepsy teams drugs •Training of personnel
Potential partners and their roles •Ministry of Health: logistic support and funding •Batibo Council: funding, sensitisation •Village development organisations: sensitisation and funding •National and international not-for-profit organisations: funding •Grants bodies: funding •Churches and faithbased organisations: sensitisation and funding •Traditional rulers : sensitisation and community consent
Figure 15. Community-centred initiative of epilepsy care in the Batibo Health District
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8.3.2 Multi-centre epidemiological study of epilepsy in Cameroon
The choice of the Batibo Health District for this study was based on speculation that epilepsy and associated risk factors are common and on the prospects of using it as a pilot site for projects to reduce the burden of epilepsy in Cameroon. While the evidence from this study can assist the health authorities in planning strategies to tackle epilepsy in Batibo and other health districts with a similar profile, it may not be applicable for most health districts in
Cameroon. As a follow-up to this study, we propose a multi-centre epidemiological study of epilepsy in Cameroon to discern the ecological factors that may be responsible for the disparities in the prevalence of epilepsy between communities. In this study, the participating health districts would be chosen randomly so that the findings can be extrapolated to the rest of the country. If successfully completed, evidence from such a study could be used to advocate for a better and proportionate allocation of resources by health authorities to reduce the burden of epilepsy in Cameroon.
8.3.3 Further studies of risk factors for epilepsy in the Batibo Health District
Based on the preliminary findings from this study, we have hypothesised that neurocysticercosis and/or onchocerciasis could be responsible for the high prevalence of epilepsy we have reported in the Batibo Health District. A logical next step is to design robust observational studies to ascertain the magnitude of association between epilepsy and these parasitic infestations, as well as other risk factors. The database of almost 40.000 people, including 546 people with active epilepsy generated during the present study constitutes an important resource for recruitment of participants in such studies. We propose starting with a case-control study utilising diagnostic methods with good positive predictive value and incorporating complementary examinations such as skin microfilarial density measurements, cysticercosis assays, neuroimaging and EEG recording. A follow-up prospective cohort study focusing on important factors from the case control study would enable an accurate estimation of the risk, and computation of aetiological fractions and population attributable fractions for the most important epilepsy risk factors, which can be used for public health planning to
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prevent epilepsy in Cameroon. Prospective cohort studies could also provide new data on the incidence of epilepsy. Given the strong evidence of cases of NS on onchocerciasis-endemic areas, it is important that there is an active surveillance for cases of NS in such regions in
Cameroon.
8.3.4 Monitoring the impact of onchocerciasis control on the incidence of
epilepsy
Once the population attributable fraction of epilepsy due to neurocysticercosis and onchocerciasis can be estimated from the above proposed observational studies, it would be important to conduct trials to determine the effectiveness of the elimination of these parasites on the reduction of the burden of epilepsy in Cameroon. There is preliminary evidence that sustained mass treatment with ivermectin to eradicate river blindness in hyperendemic foci in
Cameroon and the Democratic Republic of Congo may have led to a reduction in the incidence of epilepsy (Boulleet al., 2017, Colebunders et al., 2016b). Batibo is one of the hyperendemic onchocerciasis foci in Cameroon where there is ongoing mass yearly distribution of ivermectin.
It is important that, in parallel with ivermectin distribution to eliminate onchocerciasis, data is gathered on the incidence of onchocerciasis and matched with that of epilepsy to provide evidence of its effectiveness in reducing the burden of epilepsy.
8.3.5 Summary of proposal for a pilot trial of Taenia solium elimination to
reduce the burden of epilepsy in Cameroon
There have been several attempts to control the transmission of Taenia solium in endemic communities in LMICs using various combinations of the following measures: improved sanitation and access to clean water; public education on taeniasis and cysticercosis; training of pig farmers and veterinary workers; repeated mass chemoprohylaxis of humans (with albendazole, praziquantel, or niclosamide) and pigs (with oxfendazole); surveillance and treatment of humans for taeniasis; and pig vaccination against cysticercosis (Garcia et al.,
2016, Okello et al., 2016, Ash et al., 2017, Sarti et al., 2000, Diaz Camacho et al., 1991, O'Neal
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et al., 2014, Mwidunda et al., 2015). Most of these studies show that Taenia solium can be controlled or eradicated in the affected communities, although there is no consensus on which method is the most cost-effective and sustainable. In areas where epilepsy is also endemic and attributable to neurocysticercosis, including the incidence of epilepsy as an outcome measure to evaluate the effectiveness of these parasite control measures can be critical in advocating for their cost-effectiveness, given the economic advantage of epilepsy prevention in these communities. In Honduras, for example, parasite control measures (including mass deworming, surveillance and treatment for taeniasis, training of pig farmers and improved sewage disposal and access to clean water) over an 8-year period led to a three-fold reduction in neurocysticercosis-associated epilepsy (Medina et al., 2011). In Peru, after a single dose mass treatment with praziquantel 5mg/kg, there was a 56% reduction in the incidence of taenias 6 months post intervention (which persisted for up to 42 months) and a 70% reduction in the incidence of late-onset epilepsy (Sarti et al., 2000).
Taenia solium control or eradication projects have so far been limited to Asian and Latin
American LMICs and there is little evidence of how controlling or eradicating Taenia solium can affect the burden of epilepsy in SSA. We have shown that the high prevalence of epilepsy in the Batibo Health District in Cameroon could be related to neurocysticercosis. We propose a pilot prospective interventional cohort study, using the Batibo Health District as a case-study, to determine the feasibility and the cost-effectiveness of public health interventions in controlling Taenia solium transmission and reducing burden of epilepsy in endemic communities in Cameroon. Data from the study we have just completed could be used as a sampling frame for this project. A robust case-control study, using the standardised criteria for diagnosis of neurocysticercosis (Del Brutto et al., 2017), will ascertain the population attributable fraction of epilepsy due to neurocysticercosis in Batibo. A concurrent baseline cross-sectional study will determine the sero-prevalence of cysticercosis in a random selection of pigs and humans. All the 16 health areas will then be randomised to the control group or one of the two intervention groups as below:
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Control group:
➢ Public education about taeniasis and cysticercosis,
➢ Training of health workers in diagnosis and treatment of taeniasis:
➢ Training of veterinary technicians and meat inspectors in cysticercosis
Intervention 1: Surveillance and targeted chemoprophylaxis
➢ All the interventions in the control group
➢ Surveillance and treatment of taeniasis: people attending health centres and hospital
will be systematically screened for taeniasis by direct microscopic stool examination
and serology for coproantigens. People tested positive will be treated with single dose
albendazole. Single dose albendazole will also be offered to the other members of the
household and all regular contacts of the affected individuals
➢ Screening of all pigs for cysticercosis through tongue inspection and systematic
chemoprophylaxis for people (with niclosamide) and pigs (with oxfendazole) living
within a 2 to 5-household radius of any infected animal, depending on the clustering of
houses
Intervention 2: Mass chemoprophylaxis of pigs and humans and pig vaccination
➢ All the intervention in the control group
➢ Six-monthly mass treatment of animals and people with niclosamide and animals with
oxfendazole
➢ Pig vaccination
To measure the outcome of these interventions, six-monthly rounds of blood samples collected from randomly selected cohorts of people and pigs for 2 years, will be tested for cysticercosis using two serological diagnostic tests with high sensitivity and specificity (ELISA
& Enzyme-Linked Immunoelectroblot transfer for antibody detection). The seroprevalence and seroconversion rates of cysticercosis in these cohorts will be compared between intervention
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and control health areas. Concomitant data on the incidence of epilepsy, collected using a community-based screening exercise in the same cohort, will be linked with the prevalence/incidence values of cysticercosis allowing an estimation of the proportion of epilepsy that can be prevented by eradicating neurocysticercosis. This pilot project will last for two years and, depending on the results of this pilot phase and the availability of further funding, it will be extended to five years and involve other health districts. Results of this project could inform policy decisions by health authorities in Cameroon, to address these two related major causes of neuro-disability and economic burden.
147
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Appendix
Appendix A: Supplementary Results
Supplementary Table1. Relationship between the prevalence of epilepsy and age by health area
Health Area Prevalence of Median age Median age Proportion of active epilepsy* (IQR) of seizure adult-onset onset (IQR) epilepsy (>20 years)
Anjake 33.3 (16.1-58.4) 20 (17-23) 10 (9-11) 0/6 (
Ashong 21.8 (14.5-32.0) 20 (14-30) 8 (6-12) 1/25 (4%)
Batibo 24.0 (18.5-30.6) 25 (19-30) 12 (9-16) 7/56 (12.5%)
Bessi 10.8 (5.1-21.1) 21 (14-31) 13 (6-17) 1/9 (11.1%)
Bifang 44.8 (31.4-62.7) 27.5 (20-35) 10 (7-18) 4/31 (12.9%)
Eka 31.0 (21.3-44.1) 23 (19-28) 13 (10-15) 3/29 (10.3%)
Ewai 24.2 (16.5-34.4) 20 (17-29) 11 (9-15) 0/26 (0%)
Ewoh 52.2 (35.6-74.3) 25 (17.5-29) 10 (9-12) 1/34 (2.9%)
Guzang 19.3 (11.6-30.4) 22.5 (14.5- 11 (8-15.5) 0/20 (0%) 28)
Gwofon 40.4 (27.8-57.1) 22 (27-31) 11 (8-14) 1/29 (3.4%)
Kugwe 37.2 (25.5-52.9) 26 (18-30) 10.5 (7-13.5) 2/28 (7.1%)
Kulabei 34.7 (24.8-47.5) 22 (25-31) 10 (9-16 3/33 (9.1%)
Larinji 15.5 (7.6-29.2) 23 (18-25) 7 (6-13) 2/10(20%)
Olorunti 36.8 (23.6-57.7) 22 (18-27) 13 (9-16) 1/21 (4.8%)
Tiben 67.9 (49.9-90.7) 25 (18-30) 12 (9-13) 2/31 (6.5%)
Widikum 35.8 (27.0-46.5) 22 (18-28) 11 (9-15) 4/47 (8.5%)
Overall 25 (18-30) 11 (8-15) 32/435 (7.1.0%)
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Supplementary Table 2. Crude prevalence of epilepsy by zone (community)
Health Area Zone Crude prevalence of Level of active epilepsy Prevalence* Anjake 10/311 (3.2%) +++ Anjake Menda 1/391 (0.3%) +
Anoh 8/455 (1.8%) ++ Country 2/464 (0.4%) + Ngaku 3/439 (0.7%) ++ Ashong Njen 6/938 (0.6%) ++ Toofon 3/297 (1.0%) ++ Wumunganyi 8/820 (0.9%) ++
Atangha 4/304 (1.3%) ++ Bangie 1/821 (0.1%) + Bengang 4/240 (1.7%) ++ Bicho 0/102 (0%) + Egham 8/167 (4.2%) +++ Ewai I 8/406 (2.0%) +++ Ewai II 6/305 (2.0%) +++ Gowei 0/279 (0%) + Guka 0/100 (0%) + Kokum 1/219 (0.5%) + Batibo Kozoh 1/114 (0.9%) ++ Kuneck 3/141 (2.1%) +++ Mbengock 7/90 (7.8%) +++ Njifah 5/319 (1.6%) ++ Nyenjei 3/136 (2.2%) +++ Njimengie 1/131 (0.8%) ++ School yard 1/110 (0.9%) ++ Tad 2/231 (0.9%) ++ Kwojoh 2/568 (0.4%) + Mbunjei 2/249 (0.8%) ++ Njinyen 2/405 (0.5%) + Tichu 1/112 (0.9%) ++ Wumujong 1/77 (1.3%) ++
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Banjah 0/141 (0%) + Efah 0/363 (0%) + Goroko 0/115 (0%) + Bessi Gunda 1/177 (0.6%) ++ Kombeli 1/155 (0.7%) ++ Korogwam 0/119 (0%) + Kuronjei 2/130 (1.5%) ++ Njimeku 1/134 (0.8%) ++
Abeduh 3/112 (2.7%) +++ Borangu 5/138 (3.6%) +++ Bunti 7/303 (2.7%) +++ Bifang Ebendi 5/485 (1.0%) ++ Upper Bifang 15/501 (3.0%) +++
Ambombo 11/389 (2.8%) +++ Eka 13/1,107 (1.2%) ++ Eka Ngalla 3/423 (0.7%) ++ Nyen 6/560 (1.1%) ++
Bessom I 3/426 (0.7%) ++ Bessom II 6/296 (2.0%) +++ Enaah 6/447 (1.3%) ++ Ewai Enwen 5/551 (0.9%) ++ Enyoh 2/489 (0.4%) + Ewai 12/808 (1.5%) ++
Green Valley 9/221 (4.1%) +++ Korowan 4/230 (1.7%) ++ Ewoh Ngaku 4/169 (2.4%) +++ Nnen 7/333 (2.1%) +++ Numben 10/428 (2.3%) +++
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Akwah 0/154 (0%) + Awom 4/389 (1.0%) ++ Efit 2/135 (1.5%) ++ Guzang Kowom-Baracha 0/213 (0%) + New layout 0/228 (0%) + Njibat 0/109 (0%) +
Anong 6/703 (0.9%) ++ Gwofon 8/365 (2.2%) +++ Gwofon Ngyen-muwah 9/544 (1.7%) ++ Oshum 8/407 (2.0%) +++
Azei-Efah 1/259 (0.4%) + Kugwe I 13/873 (1.5%) ++ Kugwe II 16/861 (1.9%) ++ Kugwe Nufah Efah 3/120 (2.5%) +++ Sambesi-Efah 0/283 (0%) + Samiko-Efah 2/313 (0.6%) ++
Ambo 11/697 (1.6%) ++ Angie 3/350 (0.9%) ++ Elum 1/228 (0.4%) + Kulabei 15/503 (3.0%) +++ Kulabei Kuronyi 0/136 (0%) + Kurugon 1/147 (0.7%) ++ Kuruku 0/393 (0%) + Tekien 1/106 (1.9%) ++
Ishia 4/275 (1.5%) ++ Kanimbom 1/243 (0.4%) + Kwafong 2/182 (1.1%) ++ Larinji 1/134 (0.8%) ++ Larinji Lower achama 1/263 (0.4%) + Menka 0/250 (0%) + Upper anchama 1/363 (0.4%) +
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Barambichan 6/284 (2.1%) +++ Big Ambele 1/164 (0.6%) ++ Olorunti Egbe-Achuk 4/205 (2.0%) +++ Olorunti 14/637 (2.2%) +++
Keonom-ogwei 7/138 (5.1%) +++ Kurubei 14/251 (5.6%) +++ Ngaku 5/160 (3.1%) +++ Ofen 3/323 (0.6%) ++ Tiben Ofit-tingwei 6/140 (4.3%) +++ Ogeng 3/240 (1.3%) ++ Osei 5/175 (2.9%) +++ Terendem 4/150 (2.7%) +++
Abegun 2/331 (0.6%) ++ Angwi 1/226 (0.4%) + Bamben 6/192 (3.1%) +++ Boffe 5/244 (2.0%) +++ Widikum Bullam II 5/121 (4.1%) +++ Diche I 17/927 (1.8%) ++ Diche II 8/574 (1.4%) ++ Dinku 5/316 (1.6%) ++ Tikom 2/143 (1.4%) ++
*Crude prevalence active epilepsy: +: 0-5%: ++: 0.6-1.9%: +++: ≥ 2.0%
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Appendix B: Supplementary Information on study methods
B1. Search strategy for systematic review of observational studies of risk factors for epilepsy in SSA
Step 1: Country search sub-saharan africa OR africa south of the sahara OR angola OR benin OR botswana OR burkina-faso OR burundi OR cameroon OR cape verde OR central african republic OR Chad Tchad OR comoros OR congo OR congo brazzaville OR democratic republic of the congo OR cote d'ivoire OR ivory coast OR djibouti OR equatorial guinea OR eritrea OR ethiopia OR gabon OR gambia OR ghana OR guinea OR guinea-bissau OR kenya OR lesotho OR liberia OR madagascar OR malawi OR mali OR mauritania OR mauritius OR mozambique OR namibia OR niger OR nigeria OR réunion OR rwanda OR sao tome and principe OR senegal OR seychelles OR sierra leone OR somalia OR south africa OR sudan OR south sudan OR swaziland OR tanzania OR togo OR uganda OR zambia OR zimbabwe”
Step 2: Epilepsy search epilepsy OR epilep* OR seizures OR seizure OR convulsion OR convuls* OR nodding disease OR nodding syndrome
Step 3: Risk Factors risk factor OR risk factors OR parasite OR parasites OR nematode OR cestode OR trematode OR malaria OR plasmodium OR paragonimiasis OR paragonimus OR neurocysticercosis OR taenia solium OR cysticercosis OR onchocerciasis OR onchocerca volvulus OR onchocerc* OR schistosomiasis OR schistosoma OR toxoplasmosis OR toxoplasma OR toxocariasis OR toxocara OR sparganosis OR sparganum OR spirometra mansoni OR trypanosomiasis OR trypanosoma OR echinococcus OR hydatid* OR trichinella spiralis OR strongyloides stercoralis OR helminths OR protozoa OR meningitis OR encephalitis OR head injury OR brain injury OR perinatal injury OR genetic factors OR substance abuse OR drug abuse OR HIV
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B2. Study questionnaires
Pilot epilepsy screening questionnaire
Health District______Health Area: ______Quarter: ______
House Number: ______Number in household: ____
Stage 1 Questions (for household heads):
4. Do you/this member of the household have fits or has someone ever told you that
you/they have fits? Yes /_/ No/_/
5. Do you/this member of the household experience episodes in which your/their legs or
arms have jerking movements or fall to the ground and lose consciousness? Yes/_/
No/_/
6. Have you/this member of the household experienced an unexplained change in your
mental state or level of awareness; or an episode of “spacing out” that you/they could
not control?
Yes/_/ No/_/
A “yes” response to any of the questions will be considered as a positive screen
Number of people screened positive in the household______
Stage 2 Questions (Only concern those who have screened positive in Stage 1):
1. Did anyone ever tell you that you/this member of the household had a seizure or
convulsion caused by a high fever when you were a child?
2. Have you/this member of the household ever been told by a doctor that you have
epilepsy or epileptic fits? Yes /_/ No /_/
3. Have you/this member of the household ever been told by someone else that you have
epilepsy or epileptic fits? Yes /_/ No /_/
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4. Have you/this member of the household ever fallen to the ground without a reason and
experienced twitching? Yes /_/ No /_/
5. Have you/this member of the household ever fallen to the ground without a reason and
wet yourself? Yes /_/ No/_/
6. Have you/this member of the household ever fallen to the ground without a reason and
bitten your tongue? Yes/_/ No /_/
7. Did anyone ever tell you/this member of the household that when you/they were a
small child, you/they would daydream or stare into space more than other children?
Yes/_/ No /_/
8. Have you/this member of the household ever noticed any unusual body movements or
feelings when exposed to strobe lights, flickering lights, or sun glare? Yes /_/
No/_/
9. Shortly after waking up, either in the morning or after a nap, have you/this member of
the household ever noticed uncontrollable jerking or clumsiness, such as dropping
things or things suddenly “flying” from your hands? Yes/_/ No/_/
10. Have you/this member of the household ever had any other type of repeated unusual
spells? Yes /_/ No/_/
A “yes” response to any of the questions, except question 1 alone, is considered as a positive screen
Number of people in the household screened positive after stage 2______
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Household epilepsy screening record (Batibo Health District)
Health Area______Quarter______
House Number______Number in household______Pigs is Household? ___ Pigs roam______Name Code Age Sex Q1 Q2 Q3 Q4 Q5 Positive Screen
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Questionnaire for community screening for epilepsy (Batibo Health District)
Q1) Do you/this member of the household have fits or has someone ever told you that you/they have fits?
Q2) Do you/this member of the household experience episodes in which you/they fall to the ground and lose consciousness or wet yourself or bite your tongue?
Q3) Have you/this member of the household ever fallen to the ground without a reason and experienced jerking movements of the legs/arms,
Q4) Have you/this member of the household experienced an unexplained change in your mental state or level of awareness that you/they could not control?
Q5) Did anyone ever tell you/this member of the household that when you/they were a small child, you/they would daydream or stare into space more than other children?
If the response to any of the questions “Yes” then the person concerned should be invited to the hospital for assessment by the clinicians
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Interview Guide and Algorithm for Epilepsy Screening and Clinical Assessment of Participants by Clinician
Name of Clinician: ______Date______
Health District: ______Health Area______
I. Demographic Information of participant A1) Name of Participant______Code______
A2) Date of Birth______Age: ______
A3) Gender
Male Female A4) Tel Contact: ______
Epilepsy Screening questions (referring to the participant, or the child for whom the person is responding)
A5) Have you been told by doctor or nurse or relative that you have epilepsy?
Yes No Don’t know A6) Have you experienced involuntary jerks of parts of your body?
Yes No Don’t know A7) Have you ever fallen to the ground and lost consciousness or control of your bladder or had foam from your mouth or bitten your tongue?
Yes No Don’t know A8) Have you been told that you sometimes have brief lapses of consciousness or day dreaming or unusual spells?
Yes No Don’t know If the response to all of the above questions is “No”, then epilepsy can be ruled out.
A “Yes” or “don’t know” response to any of the above questions should be followed-up by more open questions to get a detailed description of the event (s) (preferably from one who has witnessed an event)
II. Seizure Semiology and History A9) Provide a brief and concise description of the event (s) (onset, evolution, duration, precipitating factors and the post-ictal state)
______
A10) Is (are) the event (s) an) epileptic? Yes (proceed to A12) No (answer A11 and stop interview) A11) What is the most probable alternative diagnosis? ______
A12) Have there been at least 2 unprovoked epileptic seizures, with at least one of them in the previous 12 months?
Yes (continue with Interview) No (stop Interview)
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A13) Date of first seizure______
A14) Seizure frequency
Daily ______ Monthly______ Weekly______ Other______A15) At what time of the day do seizures usually occur?
Anytime of the day Night time only On waking up from Daytime only (during sleep) sleep A16) Based on the seizure history, what type(s) of epileptic seizure(s) does the person have?
Generalised convulsive Focal motor Generalised other motor (myoclonus, Focal non motor: including sensory, eyelid myoclonus, epileptic spasms or autonomic and psychic generalised unspecified motor features) Focal dyscognitive Generalised absence Undetermined Focal onset with secondary generalisation A17) Has the person had a seizure that lasted more than 30 minutes or several seizures without recovery of consciousness between?
Yes No Don’t know III. Treatment History A18) Has the person been on treatment for at least the past 1 month?
Yes No (skip to A25) A19) What AED(s) is the person currently taking, and at what daily dose?
Phenobarbital______ Phenytoin______ Carbamazepine______ Other (specify)______ Sodium Valproate______A20) Who prescribed the AED the person is currently taking?
Doctor/Nurse Relative/friend Self-prescription Pharmacy attendant/drug store owner A21) What has been the effect of this medication on their seizures?
Seizures have stopped Seizures have got worse Seizures have reduced Don’t know No effect A22) Where does person get their AED?
Pharmacy Donation from family/well wishers Road side drug store/mobile drug vendor Other source (specify) A23) Number of days of missed treatment/doses in the past 1 month? ______
A24) What is the main reason for failing to take their medication? ______
A25) If the person is currently not on AED treatment, what is the reason?______
Not aware they have epilepsy AEDs are not available in pharmacy Don’t think AEDs are effective Fear of side-effects AEDs are too costly Other______A26) Has the person ever taken traditional medicine for epilepsy?
Yes No
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A27) Has the person consulted a priest/pastor/man of God for prayers or deliverance from their epilepsy?
Yes No A28) Overall, is management of their epilepsy adequate?
Yes No A29) What does the person consider to be the cause of their epilepsy? ______
A30) Does the person believe that they can be cured of their epilepsy? Yes Don’t Know No (skip to A40) A31) What, according to them, is the best option for them to be cured? ______
IV. Physical Examination A32) General appearance
Good health Ill-looking A33) Presence of dysmorphic features
Yes (specify)______ No A34) Skin Exam: Locate and describe abnormal findings (look for and count skin nodules)
Scars from burns ______ Nodules______ Scars from injury ______ Scarification______A35) Summary any abnormal findings on neurological exam
______
A36) Summarise any other abnormal finding in the other systems
______
A37) Based on the seizure types and neurological exam, what is the most probable epilepsy diagnosis? Focal epilepsy (Focal or focal onset seizures and/or Focal neurological deficits) Generalised Epilepsy (Generalised seizures) Undetermined (cannot be determined from seizure semiology)
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Risk Factors Questionnaire for Case-control study (Children: <16 years) Interviewer: ______Code: ______I. Household Information C1) Approximate trekking time to nearest Health Centre (mins)______C2) Transportation cost to nearest Health Centre (FCFA)______C3) Do the child have pit toilets/latrines near the house/ compound? Yes No C4) Is the latrine hole regularly covered? Yes No C5) What is the most regular source of drinking the child’s household/compound? Stream/ river/spring Tap Well Other______C6) Are there cats in the household? Yes No C7) Are there dogs in the household? Yes No C8) Are there pigs kept around the compound? Yes No II. Personal History C9) Religion of child Christian African traditional religion Muslim Other (specify)______C10) Relationship status of parents of child Not married Separated Married Orphan C11) Occupation of parents Student Trader/farmer Don’t know Salaried worker No occupation C12) Highest level of education attained by parents No school Secondary school and beyond Primary school Don’t know C13) School attendance Yes No C14) Has the person been forced to drop out of school because of epilepsy? Yes No III. Family History C15) How many people in the same compound/house as the child have epilepsy? _____ C16) Are there any of the following relatives with epilepsy?
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Brother/sister Uncle/aunt Other______ Parent Nephew/Niece None child Cousin C17) Is there is a blood relationship between the child’s parents? Yes No Don’t know
IV. Pregnancy/Childhood History C18) Has the mother in a previous or more recent pregnancy had a still born child or a death of the baby within 7 days of birth? Yes No Don’t Know C19) Maternal No problems HIV Threatened Hypertension Malaria abortion Diabetes Severe anaemia Others______ Seizures (transfusion) Don’t know C20) Time of birth of this child Premature Post-term Term Don’t know C21) Place of delivery Home Health Centre/Hospital C22) Method of delivery Normal vaginal delivery Complicated Delivery/C-Section C23) Did the child have difficulties crying, breathing or feeding after birth? Yes No Don’t Know C24) Was the child resuscitated immediately after birth? Yes No Don’t Know C25) Neonatal complications (first 1 month of life) None Neonatal seizures Other: ______ Neonatal infection Malformation_____ Don’t know Neonatal jaundice Neonatal tetanus C26) Did the child complete all vaccines according to the national immunisation calendar? Yes No Don’t Know C27) Did this child ever have convulsions during a fever when they were below 5 years? Yes No Don’t know C28) Do/Did any siblings have seizures during a fever as a child? Yes No Don’t know C29) Has the child ever been treated for meningitis? Yes No C30) Has the child ever been admitted for severe malaria or cerebral malaria? Yes No
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C31) Has the child even received blood transfusion for severe anaemia? Yes No 32) Were there any delays in attaining developmental milestones (crawling, walking, speech)? Yes No Don’t Know 33) Before the onset of epilepsy, has the child ever had a head injury after which he lost consciousness? Yes No Don’t know C34) Has the child received Mectizan during free distribution campaigns to eradicate river blindness? Yes No C35) Why has the child never received Mectizan? ______C36) Apart from AEDs what other medication does the child take regularly? ______V. Dietary History C37) What kind of meals did the child have in the past 3 days? Day before interview Main meal Day 1 Day 2 Day 3 C39) Are there any food types that the child avoids because of their epilepsy? Yes No (skip to C43) C40) Name any food types avoided ______VI. Nutritional assessment C41) Signs of Malnutrition Leg oedema Skin Gingival Glossitis depigmentation hypertrophy Brittle hair Bleeding gums Conjunctival palor Curved legs Tooth decay C42) Anthropometric Measurements: Weight (nearest 0.1Kg) ______Height (mm)______BMI:______Mid- arm circumference______C43) Overall Nutritional Status Malnourished Healthy
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Risk Factors Questionnaire for Case-control Study (Adults: >16 years) Interviewer: ______Code: ______I. Household Information B2) Approximate trekking time to nearest Health Centre (mins)______B3) Transportation cost to nearest Health Centre (FCFA)______B4 Is there a pit toilet/latrine near the house/ compound? Yes No B5) Is the latrine hole regularly covered? Yes No Don’t know B7) What is the most regular source of drinking the household/compound? Stream/ river Tap Well Other______B8) Are there cats in the household? Yes No B9) Are there dogs in the household? Yes No B10) Are there pigs kept around the compound? Yes No II. Personal History B12) Religion Christian Atheist Muslim African Traditional religion B13) Relationship status Never married Separated Married Widowed B14) Number of offspring: ______B15) Highest level of education attained No school Secondary Primary education Post-secondary B16) Occupation Student Farmer/ Trader Salaried Worker No occupation III. Family History B17) How many people in the same compound/house as the participant have epilepsy? ______
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B18) Are there any of the following relatives with epilepsy? Brother/sister Uncle/aunt Other______ Parent Nephew/Niece None child Cousin B19) Is there is a blood relationship between your parents? Yes No Don’t know B20) If you are married, is there blood relationship between you and your spouse? Yes No Don’t know IV. Social and Medical History B21) Do you take alcohol Yes No B22) Do you smoke? Yes No Prefer not to say B23) Have you ever taken recreational drugs? Yes No Prefer not to say B24) Indicate if you suffer from any chronic medical condition: ______-
B25) Have you ever suffered from a stroke?
Yes No Don’t know
B26) Have you ever been treated for meningitis?
Yes No Don’t know
B27) Have you ever been admitted in the hospital with prolonged loss of consciousness or coma?
Yes No Don’t know B28) Before the onset of epilepsy, have you ever sustained a head injury causing you to lose consciousness? Yes No Don’t know
B29) Have you received Mectizan during free distribution campaigns to eradicate River blindness?
Yes No
B30) Why have you never received Mectizan treatment? ______
B31) Apart from AEDs, are there any medications that you take regularly?______
V. Dietary History
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B32) What kind of meals have you had in the past 3 days?
Day before interview Main meal
Day 1
Day 2
Day 3
B33) Are there any food types that you deliberately avoid?
Yes No (skip to B35)
B34) What are some food types you avoid______VI. Nutritional Assessment B35) Signs of Malnutrition Leg oedema Skin Gingival Glossitis depigmentation hypertrophy Brittle hair Bleeding gums Conjunctival pallor Curved legs Tooth decay B36) Anthropometric Measurements Weight (nearest 0.1Kg): ______Height (nearest mm): ______BMI: ______Blood pressure: ______B37) Overall Nutritional status Malnourished (BMI< 18 / major signs of malnutrition) Healthy
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B3. Schedule for epilepsy screening Batibo health district
NB: As much as possible, each team should be made up of one health worker and one community mobiliser or volunteer.
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B4. Roles and Responsibilities of research personnel
Personnel Roles
Community - Household census and stage 1 interviews Relay Agents
Chiefs of - Supervision of household census and stage 1 screening health areas - Identification of volunteers for community screening - Obtained consent from community leaders - Coordination of sensitisation of the population on the project Interpreters - Assistance with interpretation of questionnaire into the local language during the training - Assistance with interpretation during the physician interview Nurses - Interview of people with epilepsy using a risk factor questionnaire - Interview of controls at home Physicians - Interview and clinical examination of participants in stage 2 - Prescription or modification of AED treatment when necessary Research - Daily data entry and cross-checking data entry forms for assistant consistency
Research - Preparation and validation of study protocol and tools Fellow - Application and follow-up for administrative and ethical clearance (Myself) - Recruitment and training of research personnel - Field coordination and supervision - Data entry and analysis
Statistician - Advanced statistical analysis
Supervisors - Provided overall scientific oversight - Reviewed and approved major adjustments to protocol
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B5. Ethical Clearance
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