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Vol. 1 2021

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Copyright © African Scientific Research and Innovation Council, 2021 Published by: African Scientific Research and Innovation Council Plot 114 Yakubu Gowon Crescent Asokoro Abuja, Nigeria

ISSN 2795-3580 (online) 2795-3637 (print)

The views expressed in the ASRIC Scientific Journals are those of the authors and not necessarily those of the African Scientific Research and Innovation Council; the African Union Scientific, Technical and Research Commission; or the organisations that they belong to.

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Editor in Chief:

Prof. Driss Ouazar, Vice Chair, Communication, ASRIC; Hassan II Academy of Science and Technology; Professor

Editorial Advisory Board:

Prof. Ratemo Michieka, Chair, ASRIC; Professor of the University of Nairobi Honorary Secretary, Kenya National Academy of Sciences

Mr James Phir, Vice Chair, Scientific and Innovation, ASRIC; Executive Director of the Zambia Academy of Sciences; Researcher at the University of Zambia

Prof. Mosto Onuoha, Vice Chair, Scientific and Innovation, ASRIC; President of the Nigerian Academy of Science; Professor Emeritus

Prof. Beban Sammy Chumbow, Vice Chair, Resource Mobilization, ASRIC; President ACALAN; Pro Chancellor; Professor Emeritus

Dr. Eng. Ahmed Hamdy, Executive Director, ASRIC; Executive Director, AU-STRC

The editorial correspondence should be sent to: Editor-in-Chief, ASRIC Scientific Journals, African Scientific Research and Innovation Council, Plot 114 Yakubu Gowon Crescent Asokoro Abuja, Nigeria

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Table of contents

Vitamin D and Covid-19 State of Evidence: Literature Review ...... 1 Mandatory Institutional Quarantine in the Response to COVID-19 in Uganda: Field Notes from Frontline Health Workers ...... 7 Artificial intelligence CNN-WCA model and Weiner filtered FRFCM image segmentation technique for extraction and classification COVID-19 Virus ...... 18 The Role of Smart Technology in managing Infectious Diseases in the Developing World. The Case of Covid-19 Pandemic in Kigali City - Rwanda ...... 33 Lipophilic Efficiency as an Important Metric in the Design of SARS coronavirus 3C-like proteinase (3CL-pro) Inhibitors: Guidepost towards Lead Selection and Optimization in the Treatment of COVID-19 ...... 45 Frugal Chemoprophylaxis against COVID-19: Possible preventive benefits for the populace ...... 63 The initial 100-day COVID-19 landscape in Kenya: trends, mitigations and impacts ...... 83

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Available online at www.asric.org

ASRIC Journal on Health Sciences 1 (2021) 1-6

a Université Mohamed V de Rabat b Université Ibn Tofail c CNRST

Received 17 August 2020; revised 23 January 2021; accepted 30 July 2021

Abstract

Following the occurrence of the global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), some studies highlighted the possible importance of vitamin D against the disease. Several studies have supported the role of vitamin D in the regulation of the immune system. Vitamin D can suppress cytokine production simultaneously by stimulating the innate immune system, thus reducing viral load, and by decreasing the overactivation of the adaptive immune system to respond immediately to viral load. Vitamin D activity is mediated by its receptor (VDR), which acts as a transcription factor modulating the expression of genes triggering the response against viruses. Observational studies report an independent association between low serum concentrations of 25-hydroxyvitamin D and susceptibility of the respiratory tract to acute infections. Calcitriol (1,25-dihydroxyvitamin D3) is acting on the ACE-2/Ang (1-7)/ MasR axis leading to improved expression of the angiotensin converting enzyme (ACE-2). ACE-2 is a receptor used by SARS- CoV-2 to infect host cells. Previous studies identified an association between high levels of ACE2 and improvement in the general health status of covid-19 cases. In additional, ACE-2 has been shown to protect against acute respiratory lesions. We conducted a review of the literature to clarify the protective role of vitamin D against SARS-CoV-2 infection through a review of the recently published studies.

Keywords: COVID-19; Vitamin D, Immune system; Respiratory system

1. Introduction

The novel Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who was first reported in Wuhan, China, in December 2019, is defined by the World Health Organization as a global pandemic. This global health concern leading to a substantial need for patient hospitalization, treatment at intensive care units (ICUs), and invasive ventilation [1,2]. Immune systems, play a major role in the susceptibility and pathogenesis of viral diseases. The importance of vitamin D in the modulation of both innate and adaptive immune systems has been since many years. Moreover, several studies have previously found that there is evidence that vitamin D may help to prevent viral infections, such as SARS-CoV-19, through its role in immunity [3,4,5]. Vitamin D or 1,25-dihydroxyvitamin D or calcitriol is a fat-soluble vitamin that has long been known for its role in protecting bone tissue. It is also known to have significant effects on overall health [6,7], hence studies on vitamin D have increased exponentially in recent years. In our country, although sunlight is important, hypovitaminosis D is estimated at 90% in women and 85% in men. For this reason, in order to reach an optimal concentration, which must be higher than 30ng/Ml, it is necessary to systematically supplement at risk individuals [8,9,10,11].

1 Corresponding author. Email addresses: (Bakrat, A.) 1

Vitamin D deficiency is caused by a range of risk factors, including age, aging skin, limited sun exposure and increased body mass index (BMI) [12,13]. The aim of this study is to clarify the protective role of vitamin D against SARS-CoV-2 infection through a review of the recently published studies.

2. Methods

We narratively reviewed the published literature. PubMed search was performed with the keywords: COVID-19 and Vitamin D. The selected language was English. Among the 437 publications identified, 8 were retained. The first selection was based on the article type and the second was based on title and abstracts (Figure 1).

Figure 1: Flow chart showing article selected

3. Results

The results of the different studies were homogeneous concerning the protective role of vitamin D against COVID-19 infection. Castillo et all stated that calcifediol can significantly reduce the admission of covid-19 patients to intensive care units. The calcifediol appears to have the potential to reduce the severity of COVID-19 by improving clinical outcomes in hospitalized patients. According to Tan et al, a supplementation combining vitamin D / magnesium / vitamin B12 in COVID-19 positive cases was significantly associated with a reduction in clinical deterioration requiring oxygen therapy during hospitalization (17.6% vs 61.5%, p = 0.006). In the same sense Vassiliou demonstrated that COVID-19 non-survivor’s cases had lower ICU admission 25(OH)D levels compared to survivors. The study protocol for a randomized controlled trial conducted by Annweiler et al aimed to compare the effect of a single oral dose of cholecalciferol versus a single oral standard dose in COVID-19 older adults. They initiated this study based on the hypothesis that vitamin D supplementation will improve the prognosis of COVID-19. In order to analyze the vitamin D level in COVID-19 patients and its impact on the disease severity Jain et al have measured the vitamin d status in two groups infected with SARS-CoV-2; the first group was symptomatic and the second group was severely ill. The prevalence of hypovitaminosis D was higher in group B and the mean level of vitamin D was highly significant between both groups. These results are similar to those obtained in india by Padhi et al. which revealed a significant association of lower 25(OH)D with SARS-CoV-2 related deaths and susceptibility to infection. In additionally,

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Karahan et Katkat, they found that mean serum 25(OH) vitamin D level was significantly lower in patients with severe-critical COVID-19 compared with moderate COVID-19 (10.1 ± 6.2 vs. 26.3 ± 8.4 ng/mL, respectively, p<0.001). While according to Ling et al the high-dose cholecalciferol booster therapy, regardless of baseline serum 25(OH)D levels, appears to be associated with a reduced risk of mortality in acute in-patients admitted with COVID-19. Also, they report that the serum 25(OH)D levels were not associated with COVID-19 mortality.

Table 1: Studies including the role of vitamin D against COVID-19. Author, Design of study Population Methods and/or Aims Results reference Castillo et Parallel pilot 76 COVID-19 50 patients was Only one cases in the group who al. 2020 randomized patients were treated with treated with calcifediol required [14] open label, enrolled calcifediol and 26 admission to the Intensive Care double-masked patients did not Unit, while in the untreated group clinical trial, treated with 13 patients required admission in Spain calcifediol the Intensive Care Unit (2% vs 50%; p< 0.001) Of the patients treated with calcifediol, none died, and all were Discharged. Of the patients untreated two cases died. Vassiliou Prospective 30 COVID-19 25(OH)D was COVID-19 patients who died in the et al. 2020 observational patients were measured in serum of ICU within 28 days appeared to [15] study, Greece enrolled COVID-19 critically have lower ICU admission ill patients on ICU 25(OH)D levels compared to admission survivors Tan et al. Cohort 43 COVID-19 17 patients were Fewer treated patients than controls 2020 [16] observational patients aged received vitamin D, required initiation of oxygen study, Singapore ≥50 years old magnesium, and therapy during hospitalization were enrolled vitamin B12 and 26 (17.6 % vs 61.5%, P = 0.006) were a control group Annweiler Open-label, 260 COVID- Compare the effect of Study protocol et al. 2020 multicenter, 19 patients a single oral high [17] randomized aged ≥65 years dose of controlled old were cholecalciferol (Two superiority trial, enrolled 200000IU drinking France vials at once on the day of inclusion )versus a single oral standard dose of cholecalciferol (One 50000IU drinking vials at once on the day of inclusion ) Jain et al. Prospective 154 COVID- Current Study The mean level of vitamin D was 2020 [18] observational 19 patients included 91 highly significant between both study, India aged between asymptomatic groups studied (27.89 ± 6.21 30 and 60 COVID-19 patients in Group A and 14.35 ± 5.79 in years old (Group A) and 63 Group B ; p<0.001) were enrolled severely ill patients requiring Intensive Care Unit admission (Group B). Serum 25 (OH)D estimation was performed to compare both groups

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Ling et al. Retrospective 986 COVID- Determine whether Regardless of the serum level of 2020 [19] cross-Sectional 19 patients COVID-19 mortality 25(OH)D at baseline, treatment with multi-centre were enrolled was affected by cholecalciferol appears to protect observational serum 25- against mortality study, Britain hydroxyvitamin D (25(OH)D) levels, or cholecalciferol therapy, and to elucidate any other predictors of COVID-19 mortality. Padhi et al. Observational Indian Determined the Inverse correlation was observed 2020 [20] study, India population correlation between between the mean level of 25(OH)D vitamin D and and SARS-CoV-2 infection rate COVID-19 disease in (r = −0.43, p = 0.02) and mortality the Indian population rate (r = −0.42, p = 0.02). Karahan et retrospective 149 COVID- Investigate the role of Mean serum 25(OH) vitamin D Katkat, observational 19 patients serum 25(OH) level was significantly lower 2021 [21] study, Turkey were enrolled vitamin D level on in patients with severe-critical COVID severity and COVID-19 compared to that of related mortality patients with moderate COVID-19 (10.1 ± 6.2 vs. 26.3 ± 8.4 ng/mL, respectively, p<0.001) Serum 25(OH) vitamin D was independently associated with mortality in COVID-19 patients.

4. Discussion

The recent global outbreak of COVID-19 has imposed devastating impacts worldwide, especially among at-risk individuals [22]. Studies have supported the importance of vitamin D in the regulation of the immune system. [5]. Vitamin D can suppress cytokine production by simultaneously stimulating the innate immune system and decreasing the overactivation of the adaptive immune system to respond immediately to viral load [23]. Vitamin D activity is mediated by its receptor (VDR), which acts as a transcription factor modulating the expression of genes that trigger the response against viruses. Previous observational studies show independent associations between low serum 25-hydroxyvitamin D levels and susceptibility of the respiratory tract to acute infections [24]. Calcitriol (1,25-dihydroxyvitamin D3) is acting on the ACE-2/Ang (1-7)/ MasR axis leading to improved expression of the angiotensin converting enzyme (ACE-2). ACE-2 is a receptor used by SARS-CoV-2 to infect host cells. Previous studies identified an association between high levels of ACE2 and improvement in the general health status of covid-19 cases. In additional, ACE-2 has been shown to protect against acute respiratory lesions [25,26]. Mounting evidence indicates that vitamin D is strongly linked to pathogen elimination through increased expression of cathelicidin [27]. In additional, vitamin D can increase the production of regulatory T-lymphocytes through the adaptive immune response. Randomized controlled trials among healthy adults have consistently shown that a significant reduction in respiratory tract infections has been confirmed in people taking daily vitamin D supplementation, compared to controls [28]. A meta-analysis report of nine studies conducted by Laplana et al. confirmed that vitamin D can inhibit enveloped viruses [29]. British researchers have shown that the highest rates of infection and mortality have been found in populations with low vitamin D levels [30]. In some countries such as Spain and Italy where vitamin D deficiency, although, its receives adequate sunlight throughout the year, COVID-19 infections and deaths associated with the disease was very prevalent. While, in Norway and Sweden, where vitamin D supplementation and vitamin D- fortified foods are more current, mortality and infection rates were lower. The low population

4 mortality due to COVID-19 in southern countries (35° north latitude) supports the hypothesis that vitamin D is a significant determinant of disease severity [31].

5. Conclusion

As stated by the international literature data, it is necessary to prescribe vitamin D supplementation systematically for people at risk of hypovitaminosis (such as children, adolescents, women of childbearing age, pregnant women, the elderly, etc…). Thus, it is essential to support the immune system of people at risk of contracting respiratory viral infections by prescribing vitamin D supplementation.

References

1. Wu, F., Zhao, S., Yu, B., Chen, Y. M., Wang, W., Song, Z. G., ... & Zhang, Y. Z. A new coronavirus associated with human respiratory disease in China. Nature 2020; 579(7798), 265-269. 2. Liu J, Liu S. The management of coronavirus disease 2019 (COVID-19). J Med Virol. 2020 3. Bikle, D.D. Vitamin D and immune function: Understanding common pathways. Curr. Osteoporos. Rep. 2009, 7, 58–63. 4. Grant,W.B.; Lahore, H.; McDonnell, S.L.; Baggerly, C.A.; French, C.B.; Aliano, J.L.; Bhattoa, H.P. Evidence that Vitamin D Supplementation Could Reduce Risk of Influenza and COVID-19 Infections and Deaths. Nutrients 2020, 12, 988. 5. Aranow C, Vitamin D and the immune system, J. Invest. Med. 59 (6) (2011) 881–886. 6. Adams JS, Hewison M. Update in vitamin D. J Clin EndocrinolMetab 2010;95:471-8. 7. Amstutz, V., Cornuz, J., Krieg, M.-A., and Favrat, B. (2011). [Vitamin D: update and recommendations]. Rev Med Suisse 7, 2332, 2334–2337. 8. Handor N, Elalami S, Bouabdellah M, et al. Dosage de la 25 OH vitamine D: expérience du laboratoire central de biochimie clinique du Centre Hospitalier Ibn Sina. Pan Afr Med J 2014;17:152. 9. Abourazzak FZ, Khazzani H, Mansouri S, Ali ou Alla S, Allali F, El Maghraoui A, et al. 2016.- Recommandations de la Société Marocaine de Rhumatologie sur la VTD chez l’Adulte. Revue Marocaine de Rhumatologie.3‑15. 10. El Maataoui A, Biaz A, El Machtani S, Bouhsain S, Dami A, El Maghraoui A, et al. 2016.-Vitamin D status in healthy Moroccan men and women aged 50 years and older: a cross-sectional study. Arch Osteoporos.11(1):24. 11. Chakhtoura M, Rahme M, Chamoun N, El-Hajj Fuleihan G. VitaminD in the Middle East and North Africa. Bone Rep 2018;8:135–46. 12. Holick, M. F. (2007). Vitamin D deficiency. New England Journal of Medicine, 357(3), 266-281. 13. Morris HA. Vitamin D: a hormone for all seasons--how much is enough?. Clin Biochem Rev. 2005;26(1):21- 32. 14. Castillo, M. E., Costa, L. M. E., Barrios, J. M. V., Díaz, J. F. A., Miranda, J. L., Bouillon, R., & Gomez, J. M. Q. (2020). Effect of calcifediol treatment and best available therapy versus best available therapy on intensive care unit admission and mortality among patients hospitalized for COVID-19: A pilot randomized clinical study. The Journal of steroid biochemistry and molecular biology, 105751. 15. Vassiliou AG, Jahaj E, Pratikaki M, Orfanos SE, Dimopoulou I, Kotanidou A. Low 25-Hydroxyvitamin D Levels on Admission to the Intensive Care Unit May Predispose COVID-19 Pneumonia Patients to a Higher 28-Day Mortality Risk: A Pilot Study on a Greek ICU Cohort. Nutrients. 2020 Dec 9;12(12):3773. 16.Tan CW, Ho LP, Kalimuddin S, et al. Cohort study to evaluate the effect of vitamin D, magnesium, and vitamin B12 in combination on progression to severe outcomes in older patients with coronavirus (COVID-19). Nutrition. 2020;79-80:111017. 17. Annweiler C, Beaudenon M, Gautier J, Simon R, Dubée V, Gonsard J, Parot-Schinkel E; COVIT-TRIAL study group. COvid-19 and high-dose VITamin D supplementation TRIAL in high-risk older patients (COVIT-TRIAL): study protocol for a randomized controlled trial. Trials. 2020 Dec 28;21(1):1031. 18. Jain A, Chaurasia R, Sengar NS, Singh M, Mahor S, Narain S. Analysis of vitamin D level among asymptomatic and critically ill COVID-19 patients and its correlation with inflammatory markers. Sci Rep. 2020 Nov 19;10(1):20191. 19. Ling SF, Broad E, Murphy R, Pappachan JM, Pardesi-Newton S, Kong MF, Jude EB. High-Dose Cholecalciferol Booster Therapy is Associated with a Reduced Risk of Mortality in Patients with COVID-19: A Cross-Sectional Multi-Centre Observational Study. Nutrients. 2020 Dec 11;12(12):3799.

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20.Padhi S, Suvankar S, Panda VK, Pati A, Panda AK. Lower levels of vitamin D are associated with SARS- CoV-2 infection and mortality in the Indian population: An observational study. Int Immunopharmacol. 2020. 21. Karahan S, Katkat F. Impact of Serum 25(OH) Vitamin D Level on Mortality in Patients with COVID-19 in Turkey. J Nutr Health Aging. 2021;25(2):189-196. 22. Daneshkhah, A., Agrawal, V., Eshein, A., Subramanian, H., Roy, H. K., & Backman, V. (2020). The possible role of vitamin D in suppressing cytokine storm and associated mortality in COVID-19 patients. MedRxiv.

23. Goncalves-Mendes N, Talvas J, Dualé C, et al. Impact of Vitamin D Supplementation on Influenza Vaccine Response and Immune Functions in Deficient Elderly Persons: A Randomized Placebo-Controlled Trial. Front Immunol 2019;10. 24. Cannell JJ, Vieth R, Umhau JC et al (2006) Epidemic influenza and vitamin D. Epidemiol Infect 356:1129– 1140. 25. Cui C, Xu P, Li G et al (2019) Vitamin D receptor activation regulates microglia polarization and oxidative stress in spontaneously Cui C, Xu P, Li G et al (2019) Vitamin D receptor activation regulate microglia polarization and oxidative stress in spontaneously hypertensive rats and angiotensin II-exposed microglial cells: role of renin-angiotensin system. Redox Biol 26:101295. 26. Kuka K, Imai Y, Penninger JM (2006) Angiotensin-converting enzyme 2 in lung diseases. Curr Opin Pharmacol 6:271–276. 27. Hewison M. Vitamin D and the immune system: new perspectives on an old theme. Endocrinol Metab Clin North Am. 2010;39(2):365–79. 28. Bergman P, Lindh AU, Björkhem-Bergman L, Lindh JD. Vitamin D and Respiratory Tract Infections: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. PLoS One. 2013;8(6):e65835. 29. Laplana M, Royo JL, Fibla J, Vitamin D. Vitamin D Receptor polymorphisms and risk of enveloped virus infection: A meta-analysis. Gene. 2018; 678:384–94. 30. Ilie, P.C., Stefanescu, S. & Smith, L. The role of vitamin D in the prevention of coronavirus disease 2019 infection and mortality. Aging Clin Exp Res (2020). 31. Rhodes JM, Subramanian S, Laird E, Kenny RA. Editorial: low population mortality from COVID-19 in countries south of latitude 35 degrees North supports vitamin D as a factor determining severity. Aliment Pharmacol Ther. 2020 Apr 20.

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Available online at www.asric.org

ASRIC Journal on Health Sciences 1 (2021) 7-17

a Department of Health Policy Planning and Management, School of Public Health, College of Health Sciences, Makerere University b Department of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University. c Department of Infant and Reproductive Health, Ministry of Health

Received 21 October 2020; revised 13 July 2021; accepted 30 March 2021

Abstract

Introduction/Background: On 21st March 2020, the Ministry of Health of Uganda confirmed the first case of COVID-19 and established measures like institutional quarantine for high-risk travelers to interrupt transmission. Methods: From 21st March to 30th September 2020, alumni of Makerere University School of Public Health including Clinicians, Infection Prevention and Control Specialists, Epidemiologists and Psychosocial Experts supporting Ministry of Health conducted a prospective follow up of travelers under quarantine at 13 hotels and two Government Learning Institutions. Their roles; daily observation of the travelers, coordination to other response arms like laboratory, case management. We analysed demographics of the travelers, documented best practices and challenges experienced during implementation. Results: We followed up 1882 travelers, and 1225/1882 (65.1%) were female, 62 (3.3%) children below 12 years, 96 (5.1%) tested positive for COVID-19 of whom 73 (76%) were male. Of the 96 cases, 29 (30.2%) showed COVID-19 related symptoms. No death was registered amongst the 96 high-risk travelers that tested positive during institutional quarantine. Best practices: Monitoring travelers for onset of symptoms, timely onsite sample collection and writing reports. Challenges: Logistical impediments. Conclusion: The Ministry of Health should use experiences to revise guidelines with special focus on challenges that impeded effective implementation of institutional quarantine.

Keywords: Institutional quarantine; Frontline Health Workers; COVID-19; Travelers; Uganda

1. Introduction

Globally, COVID-19 has continued to affect many countries and communities in different ways impacting health, education, economies, travel among other sectors (Alkhamees, Alrashed et al. 2020). A total of 86,931,368 cases with 1,878,281 deaths were reported worldwide as of January 6th 2021 at 12:19 pm EAT (Worldometer 2021). In bid to control the spread of COVID-19, many countries adopted efforts including institutional quarantine as guided by the world health organisation (Jamil, Mark et al. 2020). Institutional quarantine (I.Q) is the process when a country or individual decides to have its population or section of them kept in a predefined place for a particular time frame (Tison, Avram et

1Corresponding author. Email addresses: [email protected], Tel: +256782505983 (Brenda Nakazibwe)

7 al. 2020). In some countries, institutional quarantine took a period of fourteen days from the time a person tests positive for COVID-19 (Tison, Avram et al. 2020). Such institutional quarantine would go on until the second or subsequent test(s) were done and one turned negative for COVID-19. For many countries in Sub Saharan Africa history of travel abroad (especially from countries categorized as high risk) was part of the case definition for COVID -19 screening hence the need for efforts to restrict interactions among travelers and home community members (Organization 2020) (Moloney and Moloney 2020). These were proactive measures that enabled early detection through epidemiological analyses of places/origin of COVID-19 which would enable interrupted transmission (Lumu 2020)(Weinberger-Litman, Litman et al. 2020). On 21st March 2020, the Ministry of Health of Uganda confirmed the first case of COVID-19 and this person was a high risk traveller (Olum and Bongomin 2020). Following guidance from WHO, Uganda had already established places like hotels, hospitals, public schools and others to serve as institutional quarantine sites (I.Qs) (Olum and Bongomin 2020). As a management strategy, various stakeholders like the Ministries of Health, hotel owners, institution heads, hospital management, immigration, airlines, security organs, hygiene service establishments, service providers (mobile catering groups) were involved in providing services (Sarki, Ezeh et al. 2020). Most of the high-risk travelers voyaged by air and entered through Entebbe International Airport, Wakiso district (Tumwesigye, Biribawa et al. 2020), there were both nationals and non-nationals who had travelled overseas for various reasons like work, studies, seeking treatment (Kitara and Ikoona 2020). Furthermore, ground crossings like Mutukula, Busia, Malaba border points were the other points of entry that were used by the travelers. The country had two categories of I.Qs; Public I.Qs which were government education training centres and these were absolutely free, where the travelers did not have to pay for any services ranging from food and accommodation and Private I.Qs which were either hotels and or apartments where all services were at a cost and these constituted the highest number of the I.Q establishments that were in place (Sarki, Ezeh et al. 2020). Most f of the I.Q centers were located in Wakiso district (where the airport is located) and Kampala (the capital city of Uganda). The returnees were both males and females, though more males showed signs and symptoms for COVID-19 (Migisha, Kwesiga et al. 2020). At each of the I. Qs , the MoH deployed frontline health workers of various cadres who included a Clinician, Epidemiologist, Infection Prevention and Control Expert and a Psychosocial Expert) (Migisha, Kwesiga et al. 2020). These health workers offered the necessary support like monitoring temperature, reporting signs and symptoms developed by persons in I.Q, coordinating with the laboratory team to take off samples, identifying underlying conditions like diabetes, hypertension, coordinating charter ambulances and offering psychosocial support given the fact many people/returnees had anxiety about the disease (Lumu 2020)(Ainamani, Gumisiriza et al. 2020). All the high risk travelers were mandated to have two COVID-19 tests with first sample at 0 days (first day at I.Q) and the 2nd at 14 days of admission in quarantine as was the practice in many countries and all the tests were polymerase chain reactions (PCR) tests (Ndejjo, Naggayi et al. 2020). Uganda had deliberate efforts aimed at “Flattening the Curve” literally meaning ,keeping the COVID-19 cases as minimal as possible (Sarki, Ezeh et al. 2020). This was through early detection of cases, timely management of COVID-19 cases at Mulago National Referral Hospital, Naguru Hospital or Entebbe Grade B Hospital, all public health facilities (Migisha, Kwesiga et al. 2020). Each traveller would receive a ‘Certificate of Discharge from Quarantine’ from the I.Q Team after completion of the mandatory 14-daty I.Q following a negative PCR test. Their room and property would then be disinfected by the MoH Disinfection Team and they would then be ready to return home. This paper therefore, focusses on institutional quarantine for returnees in Uganda specifically to; (1) assess demographic characteristics of the travelers who were in institutional quarantine; (2) document best practices in the management of Institutional Quarantine; and (3) describe challenges during the implementation of Institutional Quarantine. It is hoped that the lessons learnt will inform improvements in the management of institutional quarantine for COVID-19 and any other infectious diseases in the future.

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2. Methods, Techniques, Studied Material and Area Descriptions

Design and population This was a prospective follow-up of COVID-19 high risk travelers under mandatory quarantine at fifteen Institutional Quarantine Centers (IQCs) in Kampala and Wakiso Districts. Setting This was a follow-up of high-risk travelers (returnees) under institutional quarantine from 21st March to 30th September. When Uganda confirmed her index COVID-19 case, the Government through the Ministry of Health instituted a number of public health measures to combat the spread of COVID-19 and mitigate its effects. Among the measures employed was Institutional Quarantine (I.Q) which was directly supervised by the Ministry of Health (MoH). The MoH appointed an I.Q Secretariat that was in charge of deploying teams to do the daily I.Q follow up at 60 National and centralized institutional quarantine sites (I.Qs). Teams were set up and established in Kampala and Wakiso Districts. The teams were recruited through a rigorous formal application process and were trained on how to run I.Q sites and provided with online and hardcopies of I.Q guidelines to support their operations. Each appointed team constituted four (4) technical staff who included a Clinician, Epidemiologist, Infection Prevention Specialist (IPC) and a Psychosocial Specialist. At each I.Q site was appointed a “team” and the team was also supported by a driver, the laboratory team, security personnel, hotel/Government facility staff and hospital focal points. The teams were mandated to do daily observations of the travelers, monitor their temperature (thermo-flashes were provided),report signs and symptoms, coordinate laboratory teams to take off samples in the event a traveller developed signs and symptoms or was starting or completing quarantine. The teams also reported any travelers with underlying health conditions. Additionally, the I.Q teams coordinate government ambulatory services for returnees to receive medical attention whenever there was need. The I.Q team was also responsible for organizing transport from the MoH for returnees upon completing their 14-day quarantine period owing it to the fact that in the first months after institution of mandatory quarantine for every returnee, (March to June), the country was under total lockdown and people were neither able to use their private cars nor public transport. The teams were also responsible for filling in a daily I.Q monitoring tool/checklist from the MoH for each person in quarantine, write daily reports and send them to the I.Q Secretariat. These were vital for capturing updates for each person in quarantine ranging from number of new entrants, those that developed signs and symptoms, those hospitalized either for COVID or any other disease and new positive COVID-19 cases. Additionally, monthly activity reports were also written and still submitted to the I.Q Secretariat for monitoring. Approval to publish the field experiences was sought and obtained from the Ministry of Health, Uganda and Makerere University School of Public Health.

3. Results

From Table 1, A total of 1882 high risk travelers in 15 approved sites were followed-up under mandatory institution quarantine between 21st march and September 30th of 2020. Of these travelers, 1225 (65.1%) were female and 62 (3.3%) were children below 12 years. During the follow-up period, a total of 96 (5.1%) tested positive for COVID-19 of whom 73 (76%) were male. 41 (42.7%) of the travelers who tested positive for COVID-19 did so on the 1st test, 50 (52.1%) tested positive on the second test and 5 (5.2%) on the 3rd test of the people that tested positive,29 (30.2%) showed COVID- 19 related symptoms, 21 (72.4%) of these were male (See Table 2). No death was registered amongst the 96 high-risk travellers that tested positive during institutional quarantine. A total of 66 /1882high- risk travellers reported having underlying conditions that included; pregnancy, diabetes, hypertension and asthma. In addition to analyzing the demographic and other related characteristics of the high-risk travelers, the I.Q teams documented best practices, facilitators for and challenges that impeded effective quarantine implementation as part of their field notes. These were developed into themes that are further presented in the following account;

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Table 1: Demographic characteristics of the travelers that were followed up in I.Q between 21march to 30th September 2020 Male Female Children (under Total 12 years ) Overall 657 1225 (65.1%) 62 (3.3%) 1882 Positives 73 (76%) 23 3 (3.13%) 96 (5.1%) Number of Persons positive 33 8 1 boy 41 (42.7%) on 1st test Number of Persons positive 35 15 2 girls 50 (52.1%) on 2nd test Number of Persons positive 5 0 0 5 (5.2%) on 3rd test Number that developed 21 (72.4%) 8 2 girls 29 (30.2%) Signs and symptoms Deaths 0 0 0 0 Number with Underlying 7 9 0 16 health conditions

Table 2: Other Traveller Parameters Analysed

Parameter Numbers (%) Reason for travel Work 1,7881 (94.7) Returning home from study 21 (1.1) Returning home from treatment 46 (2.4) Came for burial 34 (1.8) Point of Entry Used Entebbe International Airport 1834 (97.5) Ground borders 48 (2.5) Positive Cases by Institutional Quarantine Site Category Private 53(55.2%) Public 43(44.8%) Positive Cases Reporting signs and symptoms Males 21(1.1) Females 08 (0.04) Returnees category by site Public 937 (49.8) Private 945 (50.2) Total 1882 (100)

4. Best Practices

Health Service Delivery The quarantine team experts followed-up, monitored and screened the travelers on a daily basis. This was premised on the notion that in case a person in quarantine developed signs and symptoms for COVID-19 on any of the days during quarantine, the alert team would be reached, a sample taken off and detection done early. Temperature readings were also taken on a daily basis as part of the screening. In addition to our roles, we offered mental health and psychosocial support through counselling to the travelers as they had a wide range of concerns including but not limited to fear of testing positive for COVID-19, failed businesses, and marital issues. The service was also extended to their close family members as we had an uphill task of encouraging them that their loved ones would be okay. We also offered counselling particularly to travelers who tested positive in quarantine in preparation for evacuation and supported the ambulance team in picking them.

Capacity Building and Sensitisation Infection prevention and control (IPC) can be referred to as a ‘magic bullet’ for interrupting the transmission of COVID-19.This therefore being a disease with no known cure, the I.Q

10 teams deliberately trained and sensitized stakeholders they were working with like the hotel staff, drivers, the travelers ,security personnel in IPC .The stakeholders were taken through lessons on hand washing, proper and consistent wearing of the mask(covering nose and mouth),physical distancing (at least 2metres) and disinfection of surfaces. All these were measures employed to ensure there is limited transmission of the virus in and out of quarantine sites

Networking and Coordination In any public health emergency response, networking and good coordination among the different sub-pillars of the response is cardinal for efficacious service delivery. The same was the case with the COVID-19 response where pillars directly connected to the operations of I.Q on a daily basis had to build synergies to effectively complement each team’s roles. Notable among them was the laboratory teams that did a tremendous job in doing free timely sample collection to ensure that the discharge process of the travelers from quarantine does not get derailed. The other team that the I.Q teams worked closely with were the ambulance services (these were government ambulances that were at no cost) that were always on time to either evacuate confirmed COVID-19 positive cases to designated treatment centres upon receipt of results from the laboratory for case management or to transfer travelers in quarantine to hospital-for those who had underlying health conditions and needed medical attention .The hotel management and security (National Army and police) were also very helpful in ensuring that standard operating procedures for quarantine are adhered to since the I.Q team members were non-residents.

Infection Prevention and Control To ensure that we minimize the transmission of the virus in the quarantine centers, we ensured that we (the I.Q team from MoH) adhered to strict standard operating procedures. We guided that hotel staff not to return home until the end of the 14-day quarantine period of a particular cohort of high-risk travelers. At the end of this period, we would also take off COVID-19 samples from them, the time we would be taking off the travelers’ day 14-day discharge sample to ascertain they are COVID- free .We also advised that hotel staff doing housekeeping minimally enter the guest rooms nor clean them but rather provide cleaning and washing materials for the guests to do their cleaning and laundry, we also ensured that only one staff was attached to a floor or section of the I.Q site for the whole time the travellers were in quarantine. Many times the travellers wanted to exercise and also bask under the sun to enjoy and gain Vitamin D, so we, together with security would ensure there was physical distancing of 4-6 meters so as to minimize contact.

Report Writing and Documentation There is a common adage that goes, “what is not written is not done” .In relation to the same, the I.Q teams complied daily and monthly reports to keep track of the updates in quarantine. Information on traveler demographics like sex, age, country of travel and date, underlying health conditions, outcome of COVID-19 PCR Test were captured in these reports. Additionally, the teams also developed and maintained a data base for all the people in quarantine in order to do systematic and strategic follow up of the travelers during and post quarantine.

5. Facilitators for Effective Quarantine Follow-Up

Good Leadership and Coordination The COVID-19 response was well coordinated by the Incident Management Team (IMT) being at the forefront. These were in charge of the overall synchronization of all the operations of the response to ensure that not only are cases reduced but also that service delivery is effective. They harmonized all the other sub-pillars that included surveillance, logistics, security, case management, laboratory services, quarantine among others to ensure that there is proper networking and that the teams were working towards a common goal of defeating the novel COVID-19 and mitigating its effect on the population.

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To further elucidate on the issue of good leadership, the I.Q teams were directly supervised by the I.Q Secretariat that was headed by the National Coordinator for Quarantine. They provided oversight direction and guidance, organized logistics and provided support supervision to the frontline teams as they executed their duties.

Generous Support of Partners In Uganda, there was support to the COVID-19 response that included but was not limited to finances, vehicles, fuel, airtime, food items, human resource, and quarantine space from development partners, civic societies, government, Non-Governmental Organisations and even individuals. All this support was cardinal for smooth running and coordination of the different interventions. For instance, the cars, fuel, airtime, human resource were some of those support points that reinforced the effective running of I.Q.

Availability of Well Documented Guidelines In the execution of our duties, the I.Q Secretariat availed soft and hard copies of properly documented guidelines for institutional quarantine. These offered specific guidance on areas like; persons to be quarantined, duration of admission in quarantine, requirements for an I.Q site, medical procedures, among others. The regulations in the I.Q guidelines made it easy to have uniformity and reference points for all our operations as frontline teams.

Dedicated Frontline Health Workers It cannot go without mentioning that the expertise of the carefully recruited technical frontline teams was cardinal in the effective implementation of I.Q objectives. Each team constituted a Clinician, Epidemiologist, IPC Specialist, Mental and Psychosocial Expert whose minimum qualification was a Masters Degree. These were teams of very dedicated individuals; we worked beyond the call of duty (including working over the weekends, public holidays and nights too), working overtime time, spending personal resources on airtime for the much needed coordination and communication, fuel and personal cars to travel to the quarantine centres for monitoring and internet data to download COVID -19 PCR results from the results dispatch system (RDS ) of the Ministry of Health and send them to the numerous travelers’ personal email accounts. We also were charged with issuing written discharge certificates (hardcopies) to all the people in quarantine upon completion of the quarantine admission period.

6. Challenges that Impeded Effective Quarantine Service Provision

Resources and Logistical Issues Despite the fact that for most of the part, the response went well, there were a few challenges we faced as frontline health workers in the execution of our duties. On most of the days from Mid-July to 30th September 2020, it became increasingly hard to get means of transport from MoH to travel to check on and monitor the travelers at the different quarantine sites so we had to use our private cars and some people public means to have the work done. There was no provision of airtime to the quarantine frontline team to coordinate quarantine activities yet all operations involved a lot of phone communication with the people in quarantine themselves, hotel management, laboratory teams, our supervisors, ambulance team, catering services. Additionally, there was a dire need for internet data to download COVID-19 results for all the people in quarantine, and then send to either their personal emails or WhatsApp pages. There was also inadequate provision of personal protective equipment (PPE) and even for the little we could get, there was no schedule or streamlined method of provision of PPE to quarantine, therefore sometimes, the teams totally lacked PPE and had to re-use masks, aprons, and lacked sanitizers or had to buy for themselves while on national duty. This lack of adequate PPE also trickled down to the hotel, apartments and institution staff at quarantine centers. This was a risk factor for easy transmissibility of the virus.

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We also had a challenge of few cars to transport the many travelers per airport landing to the I.Qs. Some of the travelers would get agitated and complained bitterly at the lack of physical distancing which many said was a precursor for transmission of COVID-19. Delayed payment is another issue that affected frontline health workers supporting I.Q. This left the workers dissatisfied with the working conditions but continued to work because of the need for service above self.

Human Resource Factors For the months of July through to September, 2020, we experienced a reduction in the composition of some teams so there arose challenges of unreliable support due to the small numbers of the laboratory teams yet the travelers were so many in those months. The teams got overwhelmed with the work and this derailed the taking off of discharge samples thus unnecessarily extending the stay in quarantine (beyond the known 14 days). The situation was dire in that the travelers grew impatient and wanted to even leave quarantine without the final sample being taken off. We also in the period (June to September, 2020) were faced with a reduction in the number of the technical I.Q staff because the total lockdown had been lifted and some essential workers that were on contract returned to their regular jobs leaving very few people to manage quarantine. This made the running of the daily duties very hard because this was the same time when we had an influx of travelers returning as a result of some countries opening up their air spaces and everyone wanted to come back home, only to meet a small workforce.

System Factors Turnaround time is very important in the effective running of laboratory services. Institutional Quarantine was synonymous with COVID-19 sample collection and any delays in the receipt of laboratory results even if the setting were not quarantine causes duress among the recipients. Unfortunately, this was the case in August and September, 2020 and it caused a number of upheavals in the quarantine centres because discharge from quarantine admission was dependent on a negative PCR result. Unfortunately we had a disparity in result turnaround time from the usual 48 –hours that the travelers expected to 5-10 extra days.

7. Discussion

More Female Returnees Most of the returnees were female estimated. This can be attributed to majority of Ugandan women travel to Asian countries to work as maids. In addition, both there was gender sensitivity while organizing for instance public and private institutional quarantine centers were available making more females to feel comfortable to stay in such institutions. More returnees preferred private I.Q centres due to privacy and safety reasons. However, the availability of low-cost hotels was an additional factor to enable many to return thus making the mandatory Institutional quarantine affordable for them. Similar findings were also noted in a study conducted in Uganda regarding improving institutional quarantine in Uganda as a key measure to combat COVID -19 which reported 54.7% of the returnees being male (Ndejjo et al, 2020). On the contrary, a higher male returnee rate has been reported in other studies from other countries, for example in Nepal, it was reported that 23% of the returnees were female{Phuyal, 2020 #111}

High Recovery Rates Early diagnosis (detection) and treatment have proven to be one of the most efficacious ways to combat the effects of highly infectious diseases like COVID-19 (Adhikari et al., 2020). The follow-up period also showed that none of the returnees that tested positive for COVID-19 died either in quarantine or in hospital following referral from I.Q. The plausibility is that as per the Guidelines of I.Q, testing of the returnees was supposed to be done two times; on arrival (Day Zero), and second (discharge sample) on Day 14 in quarantine. In some cases, an intermediate sample on Day Seven or Eight would be taken off especially if the person had been a contact. This was useful in that detection of disease was timely and all that were found positive, were transferred by government ambulances for case management.

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Another elucidation could be that Uganda’s experience in the fight against other epidemics like Ebola, Marburg, could explain the robust policy and institutional frameworks the country has put in place overtime. (Namara, Nabaho, Karyeija, Nkata, & Lukwago). Additionally, the lessons learnt from other countries where the disease began from like China made Uganda to better prepare for COVID-19 interventions and can explain the 100% recovery rate as was observed in I.Q. This is because there was timely detection and management of the deadly COVID-19 virus among positive returnees. This is additional evidence to the fact that countries like China where COVID-19 originated, had no country to learn from in order to appropriately prepare and institute intervene which could in part explain the many fatalities that were fatalities were registered (Khafaie & Rahim, 2020). Additionally, high recovery was most likely as a result of early detection of cases especially the asymptomatic ones. Immediate isolation of confirmed cases for further management and observation at various treatment centers in-turn was helpful in breaking the transmission chain. Similar findings were reported in a study conducted in China where twice viral tests were done among high risk travelers under I.Q to aid early detection of positives and timely isolation and treatment especially for those that were asymptomatic(Lio et al., 2020)

Most Positives from 1st COVID-19 Samples There were more returnees in quarantine testing positive for their first test (on arrival at the airport or on the first day in quarantine) yet they all had negative travel samples which were always between taken off between 2-5 days prior travel. This could be related to the fact that maybe they took off samples before the virus could be detected by the PCR test. This COVID-19 incubation period was varying from individual to individual and there was no knowledge that kept emerging overtime since the disease was new. This study is in agreement with studies done in Uganda among truck drivers who entered at ground ports of entry and majority could test positive to COVID-19 (Bajunirwe, Izudi, & Asiimwe, 2020). Furthermore, our finding is in line with other studies done in USA and California where most of the returnees tested positive during screening before entering the airport (Dollard et al., 2020) (Bendavid et al., 2020).

More Positives being Male Although majority of the people were asymptomatic, our findings still show that among the symptomatic cases, there were more male returnees turning positive than females yet they were even fewer in number. More male travelers in this follow-up period in I.Q reported signs and symptoms for COVID-19 than their female counterparts. This is no wonder because signs and symptoms increase the odds of one testing positive for COVID-for the disease. This can be examined by the fact that that genetically females are less susceptible to acquire viral infections and reduced cytokine production (Lu et al., 2020). Additionally females have a higher macrophage and neutrophil activity as well as antibody production and response that gives them a protective effect to most viral infections including COVID- 19.Our study findings are in agreement with other studies conducted in Wuhan China where more males tested positive for COVID-19 than female counterparts (Kopel et al., 2020).

Comparing Positive cases by I. Qs Category The data for this follow-up period reported more returnees in private facilities turning positive for COVID-19 than those in public facilities. For the public I.Qs, they were sharing of common places like bathrooms and toilets because rooms were not self-contained, queuing for food, some were sharing rooms, characteristics that are synonymous with home quarantine. Such conditions are risk factors for increased transmissibility of COVID-19.Even when our findings show that there were positive cases in private I.Qs, the number of positive cases in the private I.Qs was equally high. And if the numbers in the private I.Qs were comparable to the public ones, we probably would have had more cases in the public facilities. These findings therefore agree with a study in China that reported a higher likelihood of transmission of COVID-19 in home quarantine( which has similar characteristics with the public I.Qs in our findings(Lio et al., 2020).

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Comparing Positive Cases by Point of Entry For the follow-up period, there were no travelers that used ground crossings to get into the country that tested COVID-19 positive whether for the first, second or third tests. To offer some explanations, it is highly likely that some of the travelers using the airport tested positive because of the way they were transported to the quarantine sites. Travelers were transported by MoH and because of the overwhelming numbers per flight, they used to use same vehicles without appropriate physical distancing. Additionally, considering that those who were going to private I. Qs had different choices, the drivers would make rounds dropping each of the travelers at their respective I. Qs thus increasing the time of contact in case there were some who were positive on the same vehicle. Similarly, a study reported that there was an increased likelihood of travelers contracting COVID-19 in transit after leaving airport to their respective places of abode (Maji, Choudhari, & Sushma, 2020). On the other hand, however, even when there were fewer returnees that reported using ground crossings, there is need to mention that there were none of them tested positive. This could in part be related to the means of transport they used to their I. Qs of choice. They reported that would travel in cars alone and sit in the back seat of the car with just a driver and both had to have their masks on for the whole journey. The sitting arrangement would provide for appropriate physical distancing and the mask protective efficacy for both the driver and returnees. These findings are synonymous with a study in Nepal where 2/3 of travelers reported that they travelled comfortably from the airport and there was no fear of contracting COVID-19 in transit.(Phuyal et al., 2020) Another explanation could be that some of the people got infected on the plane, stopovers, where most reported that there was hardly any physical distancing. Findings from some studies have shown that there (Barnett, 2020; Pavli et al., 2020)

Best Practices and Facilitators for Effective I.Q For any public health intervention, programme or project to succeed, there must be guidelines to provide the basis of all operations for the same and these ultimately culminate into the best practices. COVID-19 being a novel virus, all line ministries and departments including but not limited to health, foreign and internal affairs, aviation, security instituted measures in place to ensure they combat and or mitigate the effects of the viral disease. Coupled with best practices like early detection through testing, timely case management and facilitators like support from stakeholders, financing from Government and her partners, a number of countries Uganda inclusive could easily conclude that I.Q was largely successful and effective in interrupting transmission of I.Q. A study conducted in China provides the same evidence that effective containment of susceptible sections of the population like was the case for this study(high-risk travelers)(Maier & Brockmann, 2020)

Challenges during the Implementation of Quarantine COVID-19 is a novel disease and many countries faced a number of challenges implementing measures to combat and mitigate the pandemic. The case was not any different from Uganda’s experience where a number of challenges were faced in the execution of a number of interventions including I.Q.(Lucero-Prisno, Adebisi, & Lin, 2020; Maqbool & Khan, 2020)Most findings report challenges relating to inadequate supply of PPE, transportation problems for I.Q teams, long laboratory turnaround time.

8. Limitations

We were not able to capture all the information because of operational challenges like lack of transport on some days for the I.Q Teams to access the quarantine sites. The team did not do statistical analyses because the data collected was not intended for research purposes but it is rather for documentation of the I.Q implementation process during follow-up of high risk returnees.

9. Conclusion

It is undeniable that I.Q is one of the interventions across the globe that have proved to effectively interrupt the transmission of highly infectious diseases like COVID. The Ministry of Health should

15 use the experience to revise standard operating procedures and guidelines for managing institutional quarantine in the future with special focus on the challenges that impeded effective implementation of institutional quarantine.

10. Acknowledgements

We take this opportunity to thank the following people and organisations: Ministry of Health, Uganda for recruiting I.Q Teams to support ; Makerere University School of Public health for providing guidance and recommending frontline health workers to support the COVID-19 response; Hotels, Apartments and Government Training Institutions for providing space for quarantine; The travelers who accepted to undergo quarantine and also adhere to SoPs; The Frontline Health Workers for their dedication and commitment to service above self.

References

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Migisha, R., Kwesiga, B., Mirembe, B. B., Amanya, G., Kabwama, S. N., Kadobera, D., . . . Tindyebwa, T. (2020). Early cases of SARS-CoV-2 infection in Uganda: epidemiology and lessons learned from risk- based testing approaches–March-April 2020. Globalization and Health, 16(1), 1-9. Moloney, K. and S. Moloney (2020). "Australian Quarantine Policy: From centralization to coordination with mid‐Pandemic COVID‐19 shifts." Public Administration Review. Namara, R. B., Nabaho, L., Karyeija, G. K., Nkata, J. L., & Lukwago, R. Uganda’s National Response to the COVID-19 Pandemic: Measures and Implications for Public Governance. Good Public Governance in a Global Pandemic, 147. Ndejjo, R., et al. (2020). "Improving quarantine in Uganda as a key measure to combat COVID-19." Olum, R. and F. Bongomin (2020). "Uganda’s first 100 COVID-19 cases: trends and lessons." International Journal of Infectious Diseases 96: 517-518. Pavli, A., Smeti, P., Hadjianastasiou, S., Theodoridou, K., Spilioti, A., Papadima, K., . . . Spanakis, N. (2020). In-flight transmission of COVID-19 on flights to Greece: An epidemiological analysis. Travel medicine and infectious disease, 38, 101882. Phuyal, N., Rajbhandari, B., Shrestha, B., Thapa, M., Budhathoki, L., Magar, K. T., & Singh, P. (2020). Mass Evacuation and Quarantine Stay during COVID-19 Pandemic: An Experience of Nepalese Students Evacuated from Wuhan, China. Nepal Medical Journal, 3(1), 8-12. Sarki, A. M., Ezeh, A., & Stranges, S. (2020). Uganda as a Role Model for Pandemic Containment in Africa: American Public Health Association. Tison, G. H., et al. (2020). "Worldwide effect of COVID-19 on physical activity: a descriptive study." Annals of internal medicine 173(9): 767-770. Tumwesigye, N. M., Biribawa, C., Nyaberi, J. M., Namanda, C., Atukunda, G., & Ayebale, L. (2020). COVID- 19 Lockdowns in Africa. COVID-19 IN THE GLOBAL SOUTH, 149. Weinberger-Litman, S. L., et al. (2020). "A look at the first quarantined community in the USA: Response of religious communal organizations and implications for public health during the COVID-19 pandemic." Journal of religion and health 59(5): 2269-2282. Worldometer (2021). "COVID-19 CORONAVIRUS PANDEMIC." Retrieved 6th January 2021, 2021, from https://www.worldometers.info/coronavirus/.

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Available online at www.asric.org

ASRIC Journal on Health Science 1 (2021) 18-32

a Dept.of ECE, SoEEC, Adama Science and Technology University, Adama, Ethiopia b Alkharj Center for Date Palm Research, Kingdom of Saudi Arabia

Received 30 April 2020; revised 16 June 2021; accepted 30 Feburary 2021

Abstract

The COVID-19 disease started during the period December 2019 in China, and spreads rapidly throughout the world caused death of more than million peoples as per the WHO. Diagnosis of COVID-19 diseases is a very important part in its treatment. A prime reason behind an increase in the number of COVID-19 patients worldwide is the ignorance of people towards treatment in its early stages. This research work proposes a novel Weiner filter based fast and robust Fuzzy C Means (FRFCM) segmentation technique for detection of tissues from COVID-19 image and Deep CNN-WCA model for classification of diseases. As the COVID-19 images are X-Ray images, from which it is difficult to extract the COVID-19 tissues, to avoid such situation we are motivated to apply the proposed FRFCM technique. The segmented images are applied to the, proposed AI based Deep CNN-WCA (Convolutional neural network with water cycle algorithm) for classification of the type of diseased tissues for visual localization by the radiologists. Further, a future central IoT based monitoring system, we are proposing through the proposed artificial intelligence Deep CNN-WCA model to serve the patients affected by COVID-19 which will help doctors to identify and classify the covid-19 diseases with automated system.

Keywords: Fuzzy C Means (FCM); Convolutional Neural Network (CNN); Artificial Intelligence (AI); Water Cycle Algorithm (WCA)

1. Introduction

Due to the COVID-19, the world economy, education system are drastically affected. Corona viruses are categorized as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS) and SARS-CoV. Research evidence suggests that SARS-CoV-2(COVID 19) is the severe stage of infections in chest and lungs. The COVID-2019 epidemic is a member of the family of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). It is difficult for the doctors to identify the presence of virus from the X-Ray image due to its slow growth. The COVID-19 disease started during the period December 2019 in China, and spreads rapidly throughout the world caused death of more than million peoples as per the WHO [1]. According to the report all countries followed lock down to save their peoples from the virus affect. COVID-19 affects drastically in the countries such as Italy, Spain and Iran, US, Germany [2-5] directly. Ethiopia also affected by CORONA-19, but

1Corresponding author. Email addresses: [email protected],+251904433042 (S. Mishra)

18 the cases registered as per the source is much less as compared to other country cases. The patients are admitted to hospitals has to go through the process of CT-Scan image of chest to identify about the virus, but it is difficult for the doctors to get information from the images of chest. The field of medical imaging is gaining importance in determining automated, reliable, fast and efficient diagnosis. Artificial Intelligence (AI) based on a combination of deep-learning algorithms can be utilized to examine corona tissues and detect the region of tissues from the chest images. The imaging method and deep convolutional neural networks (CNNs) are to predict the tissues in an automated fashion due to its fast computational time. The method can also be useful in other surgical procedures, where doctors need to analyse other tissues while operating, including neck, breast, skin and gynecologic surgery. This recent AI technique can be a game-changer in intra-operative COVID- 19 diagnostics. The method can help address the shortage of doctors and radiologists, which sometimes leads to delay in the detection and treatment. Expert doctors often tend to rely on more extensive methods of examination that can be done completed quickly. The proposed new AI tool can help fill the gap in specialization and can help examine and detect signs of COVID tissues much faster than the traditional method which can reduce casualties with timely treatment. Another major benefit of the AI method is that it does not destroy the tissue. The same sample can be used again. The driving force of this research is to create a transparent environment which will help the medical staff to handle the situation in a calm order. As conventional clustering image segmentation is based on FCM(Fuzzy c means) which is efficient for images with simple texture and background, Chen and Zhang [6] employed average filtering and median filtering to obtain the spatial neighborhood as FCM S1 and FCM S2, segmentation. Cai et al. [7] proposed the fast generalized FCM algorithm (FGFCM) which introduced a new factor as a local similarity which performs clustering on gray level histograms. Gong et al. [8] utilized a variable local coefficient instead of the fixed spatial distance, and proposed a variant of the FLICM algorithm (FLICM) which is able to exploit more local context information in images. Guo et al. [8] proposed an adaptive FCM algorithm based on noise detection (NDFCM), where the trade-off parameter is tuned automatically by measuring local variance of grey levels. Despite the fact that NDFCM employs more parameters, it is fast since image filtering is executed before the start of iterations. Motivated by this, in this research work, we improve FCM algorithm, and propose a significantly fast and robust algorithm for image segmentation. The proposed algorithm can achieve good segmentation results for a variety of images with a low computational cost, yet achieve a high segmentation precision. The proposed Weiner- FRFCM employs morphological reconstruction (MR) to smooth images in order to improve the noise- immunity and image detail preservation simultaneously, which removed the difficulty of having to choose different filters suitable for different types of noise in existing improved FCM algorithms. Therefore, the proposed Weiner-FRFCM is more robust than these algorithms for images corrupted by different types of noise. The proposed Weiner-FRFCM modifies membership partition by using a faster membership filtering instead of the slower distance computation between pixels within local spatial neighbors and their clustering centers, which leads to a low computational complexity. Therefore, the proposed Weiner- FRFCM is faster than other FCM based segmentation algorithms. The classification and detection of the brain tumor’s have been presented by the researchers through different classifiers such as SVM,PNN,RBFNN, LLRBFNN[9]etc and found classification results in terms of accuracy and computational time for the cancerous and noncancerous brain tumors. Deepa and Arunadevi [10] have proposed a technique of extreme learning machine for classification of brain tumor from 3D MR images. This method obtained an accuracy of 93.2%, the sensitivity of 91.6%, and specificity of 97.8%. Chaddad [11] has used Gaussian mixture model (GMM) for feature extraction and PCA for the enhancement of the GMM feature extraction process and obtained an accuracy of 97.05% for the T1-weighted and T2-weighted and 94.11% for FLAIR-weighted MR images. Nilesh Bhaskarrao Bahadure et al [12] has presented dice similarity index, which is one of the important parameters to judge the accuracy of any brain tumor segmentation and support vector machine for classification and achieved 96.51% accuracy,94.2% specificity, and 97.72% sensitivity. Mohamed et al [13] proposed CNN (Convolutional neural network) for classification, Wu et al [14] presented the application of deep neural network (DNN) with 20,000 screening mammograms. Kallenberg et al [15] proposed an unsupervised deep learning technique, Geras et al. [16] used deep convolutional neural network for prediction of tissues from MR images, and Zhu et al [17] proposed a

19 deep structural network with end-to-end learning for the segmentation of masses. Further, Wang et al [18] presented a semi-automated detection using DL (Deep learning) to distinguish the micro calcifications and masses. Riddli et al [19] used transfer learning to implement the Faster R-CNN model to classify these lesions into benign and malignant utilizing the MR images. Shen et al [20] presented a deep architecture to pledge weights of full image in an end-to-end fashion. Huynh et al [21] proposed a hybrid method that used both CNN and features of SVM classifier with 5-fold cross- validations for classification. The above CNN based classification involves complex mathematical calculations. Further, it is found form the literature that the CNN too larger computational time for classification for magnetic resonance images. To get rid of such situation, we are motivated to propose a novel Deep CNN-WCA model for classification of COVID-19 diseases to improve the performance of conventional CNN classification. Researchers [22,23] presented AI-based techniques for data acquisition, segmentation, and diagnosis for COVID-19. We considered Kaggle and Github for data- sets containing Chest X-rays. We divide the data sets into two main categories, i.e., (a) SARS-CoV-2 (Covid-19)(b) Non-covid. The rest of the article is organized as follows. Section 2 presents the implementation of research flow diagram, brief details of Covid related images, details of proposed FRFCM segmentation and proposed Deep CNN-WCA model. Section 3 presents the details of segmentation and classification results, In section 4, the discussions of the research are presented, Section 5 provides the concluding remarks for the article followed by references.

2. Materials and Methods

2.1 Implementation The research flow diagram shown in Fig.1 indicates the step by step accomplishment of the research work. Further the block diagram shows the flow of algorithm application for detection and classification of brain tumor.

COVID-19 Image (Data)

Proposed Weiner-FRFCM for Image Segmentation

Extracted image data input to models

Xception InceptionV3

Proposed AI based CNN- WCA Model SARS-CoV-2(COVID-19)

Classification Of Diseases

Non-Covid

Classification result comparison

Fig.1: Research flow diagram

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2.2 Details of COVID-19 diseases related to patients Coronaviruses are a large family of viruses that are known to cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Infection with SARS coronavirus (SARS-CoV) can cause a severe viral respiratory illness. Since 2004, there have been no reported SARS cases. Research evidence suggests that SARS-CoV spreaded from infected civets to people. The case studies of the COVID-19, we have identified the properties of the COVID-19 virus, associated disease symptoms taken from various sources, to classify the COVID-19 diseases for images. The COVID-19 dataset[24] collected from Kaggle website. We emphasized the statistical significance of these measures for the purpose of detection and classification of COVID-19 diseases also. Fig.2 and Fig.3 shows the images of covid (Pneumonia) and non –covid.

Fig.2 Normal Chest images of four cases (Patients)

Fig.3 Pneumonia COVID-19 images of four cases (Patients)

2.3 Proposed FRFCM Image Segmentation: There are different promising images segmentation methods such as V-Net, U-Net based on convolutional neural networks, which has been applied for 3D Brain tumor image dataset and Breast cancer mammogram datasets. As the available COVID-19 image datasets are X-Ray images, we are motivated to apply the fuzzy factor based FRFCM segmentation algorithm for the purpose of extraction of corona affected tissues form the images. Further, the member partition matrix of FRFCM has been modified to improve the performance of the segmentation algorithm. The improved Weiner- FRFCM technique has shown better segmentation result for covid-19 images. As the FRFCM algorithm is based on morphological reconstruction, it will best suit for COVID-19 X-Ray images to extract the tissues. In this research work, proposed modified FRFCM algorithm distinguishes the performance of segmentation than the other FCM based segmentation. From literature survey, it is observed that, some preliminary segmentation technique have been applied for brain tumor, breast cancer dataset, but FRFCM segmentation techniques yet not applied for COVID-19 image segmentation by the researchers till date. The advantage of FRFCM algorithm is to detect the tissues and at the same time the noise also removed from the COVID-19 images to improve the performance of the segmentation.

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The proposed improved fast and robust FCM segmentation uses a Weiner filter to the modified membership partition matrix of the objective function of FCM algorithm with local information [9]. The objective function of the fuzzy c means algorithm with local information is given by

N c N c m 2 J s   ukv xv  vk  Gkv v1 k1 v1 k1 (1)

Where the fuzzy factor is given by

1 m 2 Gkv   1 ukr xr  vk (2) dvr 1 rNv vr

Where the spatial Euclidean distance between pixels xv and xr is denoted by dvr , N v is the set of neighbours within a window around and represents the neighbours of and ukr is the th neighbours of ukv . With respect to cluster k , xv is the gray value of the k pixel, ukv represents the fuzzy membership value of the vth pixel and N is the total number of pixels in the gray scale image

f  [x1, x2.....xN ], xv is the gray value of pixel, c denotes the cluster centre and m determines the fuzziness of the consequential partition.

To reduce the computational complexity, the membership partition matrix is modified as

 ' log  m 2 Gkv   ukr xr  vk (3) rNv exp(d vr ) 1 vr

Where ukr is the neighbours of ukv ,  is gray value of image and  is the smoothness parameter between 0 and 1. Further, considering the morphological reconstruction operations such as dilation and erosion, the reconstruction of the image is considered as  p , which is given by C  p  Re  f  (4) C Where Re represents the morphological closing reconstruction which is efficient for noise removal and f denotes an original image and reconstruction operators considering morphological closing reconstruction is given by

C   Re  f   R  R f  f  (5) R f  f 

Where  is the erosion operation,  is the dilation operation, c is the closing operation and f represents original image. Further, considering convergence speed of the algorithms and the performance of the partition matrix U we employ a wiener filter. The new membership partition matrix is given by

U l  wienerU  (6)

Update U l according to equation (6) until convergence of objective function in programming.

2.4 Proposed Deep CNN-WCA Model A convolutional neural network consists of an input and an output layer, as well as multiple hidden layers. Though the layers are colloquially referred to as convolutions, this is only by convention.

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Mathematically, it is technically a sliding dot product or cross-correlation. This has significance for the indices in the matrix, in that it affects how weight is determined at a specific index point. The deep CNN-WCA is proposed to reduce the computational time of conventional CNN. We are proposing the WCA(Water cycle algorithm) to optimize the weights of CNN due to the robustness of the optimization capability as compared to accelerated particle swarm optimization, genetic algorithm etc. The water cycle algorithm is a complex mathematical calculation free algorithm based on the process of water cycle in rivers and streams flow in the ocean which permits a search agent to be transposed around the desired solution. Understanding the metaheuristic nature of the algorithms, we are motivated to hybrid the WCA algorithm with CNN to improve the performance of CNN and considered to apply for COVID-19 images for classification. Basically the Deep CNN is modelled with back propagation algorithm for weight optimization. Due to complex mathematical calculation and backward propagation from last layer to first layer during weight optimization consume larger time for classification. To avoid such situation, we are motivated to hybrid WCA with CNN model for weight optimization. The figure below shown is the part of the proposed AI based CNN-WCA model. In this model the weights of the fully connected layer is optimized with a novel water cycle algorithm (WCA) model to improve the performance of Deep CNN.

Fig.4 Deep CNN-WCA model for COVID-19 Classification

The classification model will classify the different categories of diseases such as pneumonia (SARS-CoV-2), and Non-Covid.

2.5 Water Cycle Algorithm (WCA) WCA is a population based stochastic optimization technique inspired by river, sea and stream flow. WCA uses a population of individuals, to search feasible region of the function space. the “water cycle algorithm (WCA)” clones the flow of streams and rivers in the direction of the sea and imitative by the view of process of water cycle. The WCA [27-28] has not been used previously by the researchers for COVID-19 images. In this research work, we are proposing to apply the WCA in the fully connected layer to improve performance of conventional CNN model. The algorithm needs the “generation” of an “initial population” in the form of a matrix of watercourses of size. N Population  D ,where “ D ”is the “dimension”. Therefore, the matrix is formulated which is given as

Sea    River1  River2    River3   y1 y1  y1   1 2 D  (7)   y1 y 2  y 2 Total population      2 2 D  StreamNsr1          StreamN  N pop N pop N pop  sr2  y1 y2  y D  StreamNsr3        StreamN pop 

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The rows of Eqn.(7) represent the size of population as ( NPopulation ) and the columns of Eqn.(7) represents the design variables D . At the beginning, the N Population streams are createdand in the second phase N sr which is the addition of the number of rivers (good individuals or minimum values) are designated as a “sea” and “rivers”. Then, the other remaining population is considered using the subsequent equation:

Nsr  No.of rivers1(sea) (8)

N Stream  N population  N sr (9)      f Rivern   NSn  round  NStream, n  1,2,3 ...Nsr N sr (10)     f Riveri    i1 

Where, NSn represents stream numbers which streams into the definite rivers and sea, and f is the evaluation function in the algorithm. New “positions” for “streams” and “rivers” of WCA have been modified as follows for the weights of fully connected layer as.

WStream l 1  WStream l Rand    WRiver lWStream l W l 1  W l  Rand    W l W l Stream   Stream    Sea   Stream   (11)

WRiver l 1  WRiver l Rand    WSea tWRiver l

With this update equation the algorithm continues till convergence achieved.

2.6 COVID-19 Medical image data-sets Medical images in the form of Chest CT scans and X-rays[25,26] are essential for automated COVID-19 diagnosis. This research followed the article for data [25,26] where COVID-Net, a deep convolutional network for COVID-19 diagnosis based on Chest X-ray images are presented.

3. Results

3.1 Preprocessing Results Data augmentation in machine learning refers to the techniques that synthetically create new examples from a data set by applying possibly stochastic transformations on the existing examples. In the image domain, these transformations can be, for instance, slight translations or rotations, which preserve the perceptual appearance of the original images, but significantly alter the actual pixel values. We performed the experiments on the Chest X-ray image data sets. We resized the 1.3 M images into 227 x 227 pixels, as a compromise between keeping a high resolution and speeding up the training. The pre-processing involves Random Rotations, Random Shifts and Random Flips.

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Fig.5 Output images of Image data augmentation techniques rotation, shifts and flips.

A higher number of images were needed to train a deep learning algorithm. The data augmentation technique was used to increase the number of samples in the dataset. After the data augmentation, we obtained 15,216 samples.

Table-1: Original Images

COVID Non-COVID Training Validation testing Training Validation testing 1252 250 126 1230 250 124 Total: 1628 Total: 1604

Table-2: Data Augmentation Training Validation testing 159,472 160 79,799 Total: 239,431

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3.2 Segmentation Results

(a)

(b)

(c)

(d)

(e) Fig6. Covid-19 Segmentation results of modified FRFCM segmentation

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3.3 Classification Results

Fig7. Classification Covid-19 and Non-Covid results

1 0.8 0.6 0.4 0.2 0 0 20 40 60 80 100

Train Accuracy Val_Accu

Fig.8 InceptionV3Model accuracy results

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1

0.8

0.6

0.4

0.2

0 0 20 40 60 80 100

Train Loss Val-Loss

Fig.9 InceptionV3Model loss results

1

0.8

0.6

0.4

0.2

0 0 20 40 60 80 100

Train Accuracy Val_Accu

Fig.10 XceptionModel accuracy results

8 7 6 5 4 3 2 1 0 0 20 40 60 80 100

Train Loss Val-Loss

Fig.11 Xception Model loss results

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1

0.8

0.6

0.4

0.2

0 0 20 40 60 80 100

Train Accuracy Val_Accu

Fig.12 Deep CNN-WCA Model accuracy results 0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0 0 20 40 60 80 100

Train Loss Val-Loss

Fig.13 Deep CNN-WCA Model loss results

Table-3 Classification accuracy results Model Training Validation Training Validation Computational accuracy accuracy Loss Loss Time in sec InceptionV3 93.0986 91.5259 9.9014 8.4741 4033 Xception 95.2347 92.3879 4.7653 7.6121 3905 Deep CNN-WCA 99.6243 94.1523 0.3757 5.8477 3216

All the values are the average values of 100 epochs

4 Discussion

Fig.5 shows Image data augmentation techniques which includes rotation, shifts and flips. Fig.6 shows the image segmentation by utilizing the proposed modified FRFCM algorithm. The segmentation has been utilized to remove rician noise from the images and the images are fed as input to the Deep CNN-WCA model for classification. Fig.7 shows the classification results of the proposed Deep CNN-WCA model. The Deep CNN-WCA model classifies the images into Covid and non-covid categories. Fig.8 to Fig.13 presents the training accuracy, validation accuracy, training loss and validation loss for inceptionV3 model, Xception model and proposed Deep CNN-WCA model. The computational time and accuracy of classification results are presented in Table-3.

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4.1 Proposed Web Based Application 1. The project can be implemented through IoT system, where the server with software will be taken care by Innovation and Technology support center. 2. Hospitals of all over Africa or state wise will be connected through the server. 3. Hospitals can be connected to the server with an identification number and password provided by the support center. 4. The Deep CNN-WCA model will support the detection and classification task and deliver the report. 5. The customers can access the reports from the hospitals by using there ID and password from the respective hospitals server system.

Fig.14 Web application diagram

4.2 Process of implementation 1. At the first step, we will develop a compact data acquisition system along with the software model design with power backup. 2. Further, the proposed CNN-WCA model and segmentation techniques needs to be tested by the team of doctors and radiologists for patients through the software system as test basis after scan of patients. 3. Finally with real data acquisition and positive results of testing of patients will be taken as reference point, and can be approached for the commercialization as testing kit for COVID related diseases. 4. The kit to be connected to digital scan machine to acquire the images to the system for analysis.

Fig.15 details of data acquisition and report generation

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5. Conclusion

This paper presents a modified FRFCM segmentation to identify the region of tissues and removal of rician noise from the images. The preprocessed images are then fed to novel Deep CNN-WCA model for classification of Covid and Non-covid images. In the architecture of Deep CNN model, the fully connected layer in general plays an important role for classification. The back propagation algorithm generally utilized for weight optimization. In this research work, the meta-heuristic WCA algorithm has been employed for optimization of weights in the fully connected layer. The results of training and testing classification accuracy of the proposed Deep CNN–WCA model outperforms than the inception V3 and Xception model. Also the computational time requirement is less in the proposed Deep CNN model in comparison to the other mentioned models which is presented in Table-3. The simulations for the models are performed using python platform with GPU system.

References

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Available online at www.asric.org

ASRIC Journal on Health sciences 1 (2021) 33-44

a Dept. of Urban and Regional Planning, Ardhi University, Dar es Salaam –Tanzania

Received 31 August 2020; revised 26 May 2021; accepted 13 July 2021

Abstract

This study examines the effectiveness of smart technology in managing the Covid-19 pandemic in Kigali City - Rwanda. Data were collected through interviews by the use of structured questionnaires addressed to 4 administrative officers in the health sector. Also, 32 out 96 residents were randomly selected in each district. Results have shown that Drones (UAVs) were more used by 95% as opposed to Robots and cameras to warn and inform the community to take precautions. In addition, they were used to distribute medical items whereby 500,000 face masks and 1,000,000 gloves were distributed. Also, 43,379 blood samples were collected; other light medical equipment were transported by drones within the city within a period of 3 months saving 158 out of 287 people who had been affected. Limited finance, lack of qualified and skilled personnel to operate drones and robots during these times jeopardized the effectiveness of smart technology. We conclude that the use of smart technology should be a national agenda to improve management of pandemics. This aligns with training of community to handle health crisis during and even after the Covid-19 pandemic. Also, the establishment of the department for innovative ideas to fight current and future pandemics is inevitable.

Keywords: Smart Technology; Covid-19; Developing World; Kigali City

1. Introduction and literature review

Infectious diseases have a long history in human lives and have caused serious fatalities. One of the first known recorded pandemics is the Plague in 542 CE which occurred in the 14th century and claimed millions of lives and the Black Death (McNeill, 1998). Another in the list was Smallpox that killed people in numbers that exceeded those of any who have fought in wars in history. To this date, however, Smallpox is the only disease that human beings have been able to eradicate completely. In the 19th century, Cholera erupted and it remains a concern and still does not have a complete cure (Seshaiyer and McNeely, 2020). Although the foregoing infectious diseases impacted several million people, it was not until the 1918 influenza pandemic and it forms one of the greatest “natural disasters” in the 20th century infectious diseases with a death count estimated to be more than 50 million (ibid). The unexpected urgent rapid spread of global novel H1N1influenza Virus has created the tensions and confusion on the explanation of the Word “Pandemic” since early 2009 (Morens et al., 2020). Following this disaster, several countries and leading organizations increased funding and attention to finding cures for infectious diseases in the form of vaccines and medicines - particularly for those diseases that are

1Corresponding author. Email addresses: [email protected] (D. Mihigo)

33 categorized as re‐emerging infections, those that are spread through sexual transmission such as HIV, those that are spread through vectors such as mosquitoes such as Malaria or Dengue, those that can spread through both sexual and vector transmissions such as Zika, and those which can be spread by viruses, including SARS and MERS (Seshaiyer and McNeely, 2020). Currently, Coronavirus is considered to be the third Pandemic in 21st Century which is among the highly transmissible disease portends worldwide human living. This virus has connection with Wuhan Seafood market in China during the unknown pathogen was discovered by hospitals among a group of Covid-19 patients who are familiar to pneumonia. Originally it was pointed out that patients affected by coronavirus might have been in Wuhan, the place where animals are sold. Finally, Chinese researchers discovered human to human transmissible virus before naming the novel virus Wuhan or 2019 novel Coronavirus or simply the 2019 nCoV (Prasetyo et al., 2020). The Covid‐19 is, however, categorized as a super‐spreader based on the disproportionately fast rate and large (and growing) number of infected persons. For example, data from the SARS outbreak in 2003 showed a spread rate from one to three people on an average, while the super‐spreader Covid‐19 can spread from one to more than 10 people (Trafton, 2020). Furthermore, Seshaiyer and McNeely (2020) note that not only the pandemic spreads quickly having already resulted in at least 3.5 million cases across the world and over 250,000 deaths, it has also impacted the economy, education, workforce, and much more, pointing to its significance for broader questions of sustainable development and societal well-being at a global level. Fighting pandemics is not a new initiative in the world since the eruption of such pandemics. Although effective interventions have occurred for some priority health problems, overall progress towards quality health care for all remains slow. While there has been an increasing consensus that stronger healthcare systems are needed to achieve improved health and wellbeing, little agreement exists on how to strengthen healthcare systems. In the period of 2000‐2015, the United Nations (UN) declared Millennium Development Goals, which attempted to address the importance of basic healthcare coverage (Travis et al., 2004). Moreover, the subsequent 2030 agenda for sustainable development goals (SDGs), established by the UN in 2016, explicitly identified good health improvement and attainment as both an outcome and indicator of progress for the success of the 2030 agenda as a whole (Sachs, 2012; WHO, 2015). The third in the list of seventeen SDGs, “Good Health and Well‐Being” (SDG‐3) refers to the critical need to “ensure healthy lives and promote well‐being for all” for global sustainability and development (UN, 2020). As such, the Covid‐19 pandemic is a particular and immediate concern with regard to SDG‐3, with implications for all of the SDGs (Seshaiyer and McNeely, 2020). Following the eruption of Covid-19 pandemic, WHO provided guidance on how to control and manage the quick spread of the disease which include hand washing, the use of face masks, gloves and social distancing. However, many countries have devised their own ways of detecting the infections and controlling them. This paper investigates how Rwanda in its capital city, Kigali, has used Smart Technology in managing the Covid-19 pandemic. The smart city concept is currently been a pronounced tool to enhance the potential city-level governance systems due to the rapidly growing urban population (Kummitha and Crutzen, 2017; Lee and Lee, 2014). Concerning governance of smart cities, Kummitha (2018) argues that the level of technology adoption is determined either by the technology or by human driven approach which cities adopt. While the techno-driven approach refers to the enhanced use of technologies largely using a top-down method in which governments enforce technologies on cities and citizens, the human driven approach refers to educating and enhancing the potential of communities that help create and promote their own technologies based on the local needs. For the last decade, Europe, North America and China have engaged in transforming their cities into smart cities. Since the identification of the cause of the outbreak of Covid-19 in late 2019 and its pandemic designation in March 2020, research and development activities have been evolving into a broader understanding of the epidemiology of the novel coronavirus as a “super-spreader” of infectious disease. Along with these efforts, several pharmaceutical and non-pharmaceutical interventions for infection prevention and control have been recommended by major health agencies, such as the World Health Organization (WHO) and United States Centers for Disease Control and Prevention (CDC) to mitigate the morbidity and mortality associated with Covid-19 (McNeely and Seshaiyer, 2020). In this paper Chinese Cities are used to underscore how smart technologies have helped control the spread and infection of the Covid-19 pandemic.

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1.1 Smart Technology against Covid - 19 in China The interest in the use of smart technologies in China for governance dates back in the early 2000s when the overall shift in the country’s innovation policy began due to rapid urban population (Liu et al., 2011; Ling and Naughton, 2016). For instance, in 2015, the urban population in China accounted for 56% of the total population and given the improved living standards and new employments opportunities in cities, it is expected to increase exponentially in the next two decades to 76% (Wu et al.,2018). In response to the growing population, China has taken an active role building smart cities where technologies have been used significantly to aid urban governance. Mak (2020) estimates that there are about 500 world – class smart cities present in China, Wuhan City being the most affected in the current Covid-19 outbreak. China stated its commitment to building smart cities in the 12th Five- Year Plan published in 2010 which set up a blueprint for the socio, economic and political goals for the next Five Years. The National New Urbanization Plan which came into effect in 2014 and the latest in 2020 has largely taken charge of constructing new smart cities and remodeling existing ones into smart cities (Zhu et al., 2019). In addition, the former premier of China, Li Keqiang, emphasized that smart city and smart technologies are the two major priorities in the development of the country in 2015. The 13th Five-Year Plan takes the smart cities vision even more seriously with the aim of not only promoting them but also creating inter-city infrastructure and partnership building (Dameri et al., 2019).

2. Methods, techniques, studied material and area descriptions

2.1 Overview of the study area

Figure 1: Location Map of Study Area Source: Author, 2020

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Rwanda is facing rapid urbanization and development after 1994 Genocide happened against Tutsi. The City of Kigali, being the main capital of Rwanda and the leading city among Rwandan cities, is also having outstanding changes in terms of infrastructure including technological innovations. These activities are mostly done especially in business areas, construction of new buildings for offices, industrial and tourism areas. All these together conform with the policy of clean city where the city of Kigali is ranking the first cleanest city in Africa. During colonial period the city of Kigali grew slowly where it had only 6,000 inhabitants congested only on a small area of 2.5 km2 at the top of Nyarugenge hill during 1962. Currently, the city of Kigali is the biggest urban cluster of the country whereby in 2012 it had only 1,132,686 people living in the city. According to NSR of 2012 and 2018 the population of Kigali increased up to 1,631,657 in 2017 over the area of 730 km2. Therefore, Kigali city is one of the five provinces located in the middle part of the country between 29o44’0’’E longitude and 29o 43’0’’ latitude. Additionally, the city of Kigali is subdivided into different administrative entities established in 2005; provinces (Intara), districts (Uturere), sectors (Umurenge), cells (Akagali) and villages (Umudugudu). Thus, Kigali is placed at a provincial level and it is divided into three districts namely Nyarugenge, Gasabo and Kicukiro. These districts are further divided into 35 sectors while the sectors are also divided into 161 cells and 1,061 villages (Manirakiza et al., 2019). Fig. 1 shows the selected research study area in Nyarugenge district within Kigali city which are Nyakabanda, Muhima and Kimisagara.

2.2 Data collection procedures and analysis Based on the objectives of this study which is to explore the use of smart technology in the fight of Covid -19 and challenges faced throughout the use of this emerging technology, we used field observations, 32 structured questionnaires and four (4) formal interviews. While field observations aided collection of primary data especially live events particularly on how this technology is physically used to help combat Covid-19, structured questionnaires and formal interviews helped to acquire community points of view on the use of this emerging technology to control and manage the Covid-19 pandemic. In fact, data collection from field observations were intended to support primary data obtained during both formal interview and structure questionnaire. These worked out while gathering data from different smart technologies which were applied during the pandemic in Kigali City. Questionnaires were composed of both open and closed questions administered to Kigali City residents in the three Sectors of Nyakabanda, Muhima and Kimisagara and four (4) Officials in the Rwanda Biomedical Centre (RBC). Regarding ethical issues, considerations were made at each stage in the data collection process. It is for this regard that all Kigali city residents were briefed concerning the objective of the study and confidentiality of their answers before the start of data collection. Additionally, community participation in this research was voluntary; no one was forced to answer questions. Qualitative data were analyzed by generating themes through SPSS and Excel while quantitative data were analyzed by using statistical tools to generate %ages and frequencies.

3. Results

3.1 Socio-demographic characteristics of respondents Results which were obtained from the field revealed that with the study area had people with different backgrounds in terms of their sex, age, marital status, education level and occupation as presented in Fig. 2. Based on their sex, 69% of those who were interviewed were females while males made 31% of the people who were interviewed. Out of these people, 78% were married and the rest 22% were single. In terms of age, the largest group made 42% of the total population had between 39 and 48 years while the smallest group had people with under below 18 years making 6% of the total population. Closely tracked by the largest and smallest groups was those people who had more than 48 years (about 23% of the total population) and a group of people with 19 to 28 years of age (10% of the total population) respectively. Moreover, 19% of all people in the study area had between 29 and 38 years. Education wise, field results have indicated that majority of people (47% of the total population had secondary education, 27% had primary school education, 17% had university education and only 9% had not attained any formal education. These results indicate, therefore, that those who

36 participated in this research were able to give their opinions and had sufficient knowledge of the prevailing Covid- 19 pandemic and how smart technology was used to tackle and manage the disease. According to their occupations the private sector employed more people than any other sector for 57% of people in the study area are employed by the private sector especially as drivers while public employees made 28%. Other people were employed in the service sector especially food shoe makers and repair and hairdressers who comprise 7%. Above all, 5% declared to have not been employed in any category while students made 5% of all people in the study area.

S/N Variable Category Frequency % (%) Total 1 Sex Female 69 69 100 Male 31 31 2 Marital Status Married 78 78 100 Single 22 22 3 Age Under 18 6 6 19-28 10 10 29-38 19 19 100 39-48 42 42 48 above 23 23 4 Occupation Public employees 28 28 Students 3 3 Unemployed 5 5 Service Sector (Shoe makers, Hairdressing) 7 7 100 Private Sector (Drivers etc...) 57 57 5 Education Level None 9 9 Primary Education 27 27 Secondary Education 47 47 100 University Education 17 17

Figure 2: Background Characteristics of the study participants Source: Fieldwork, 2020

3.2 The Discovery of Covid-19 pandemic in Kigali City

Figure 3: Rwanda Covid - 19 Updates Sheet Source: Rwanda Ministry of Health, 2020

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According to the Rwandan Ministry of Health (MOH), the country confirmed the first case of Coronavirus from an Indian person who landed in Kigali City from Mumbai –India on 8th March 2020. During his arrival, the victim had no symptoms but he had to report himself to the health facility on the 13th December. This brought Rwanda to 19th country in Africa to report the presence of Coronavirus. Therefore, since that time until now coronavirus has spread in the entire country and the country has, since then, been taking measures of fighting the pandemic. The situation increased to be worse as days went in and out in as Fig. 3 represents. As it can be seen from the Figure, the number of deaths reached 67 by December 2020 while the affected people by Covid-19 that time were 7,511 and 6,109 people recovered out of 694,450 tested persons. These tests were taken in some of the areas in the city of Kigali.

Kigali City Resident respons on Smart Technology duing Covid-19.

100 TOTAL 94

23 NO 22

77 YES 72

0 20 40 60 80 100 120

Percentage (%) Frequency

Figure 4: Resident Opinion on using Smart Technology to fight Covid-19 Source: Field work, 2020

4. Smart technologies used to fight Covid-19 in Kigali city

4.1 Drone Technology (UAVs) Drone technology is among the emerging technologies which had a big impact in community as well as in the development and disaster risk management. its importance and popularity came into the fore during Covid - 19 era and lockdowns in Rwanda. Results from official interviews with the Ministry of Health and police officers revealed that 95% of all the efforts to combat the pandemic were directed on the use of Drones. In this regard, the Ministry of Health and the Rwandan National Police (see Fig. 5) with the help of Charis UAVs Drone Company in Rwanda started to monitor lockdown situation as well as community awareness of the pandemic. Since drones have the capability to fly a large space and deliver message compared to tradition methods, for instance, the use of cars while people use PA systems (the use of microphones or megaphones), had a substantial contribution to enable the community prevent themselves from and fight against the Covid - 19 pandemic. Apart from the Charis UAVs, the Zip line Rwanda which participated in this event also had a great contribution in the delivery of light medical materials to those people who were affected by Covid – 19. The service was further extended to other places and in hospitals like at the Cancer Hospital in Northern Province to deliver medicines because during these times people couldn’t travel from one place to the other. These imply that Drones were very useful and helpful to save peoples’ lives in Rwanda as it also applied in other countries in Africa, Asia, Europe and America.

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Figure 5: Police Officers during the launch of Drones on Covid-19 Preservative measures Source: The New Times, 2020

4.2 The use of Robots during Covid - 19 In further attempts to fight against the pademic, the country of Rwanda luanched anti-epidemic Robots to increase the fight of Covid-19 especially in treatment centers especially for the delivery of food and medecines to patients (see Fig. 6). It was on 19th May, 2020 where these high technology robots were launched at Kanyinya Covid - 19 treatment centre in partnership with Ministry of ICT and Inovation of Rwanda, Rwandan Ministry of Health and the United Nations Development Programme Rwanda (UNDP). These high technology Robots were manufactured by Zora Bots which is the company specialized in Bots solutions in Belgium.

Figure 6: Launching the anti-epidemic Robots to boost the fight against Covid-19 Source: Rwanda Ministry of Health,2020

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Based on various advanced features of these robots, they helped medical doctors and nurses to monitor, manage and control patients’ temperature, screening and keeping all Covid - 19 patients medical information. For better management and identification of these robots, they were given names including Urumuri, Ngabo, Ikizere, Mwiza and Akazuba. The delivery of food and medecines to patients was not only made in hospitals but also in other places like hotels where people locked themselves or they were locked down by the government or relatives for the sake of not spreading the disease beyond those who had been affected. On the case of deliveries in hotels, the arrangement based on the financial capacity of the owner of the hotel to buy a robot or the customer to hire it from the owner. These robots have capacility to serve between 50 to 150 people per minute. The robots are also capable of capturing data and inform officials on detected abnomalies for better case management as well as timely responses. This increased effeciency during the fight against Covid - 19 and minimized time for health workers being exposed to Covid- 19 patients or infections.

4.3 Thermal fever detection cameras at the airport The cameras are mounted on the ceiling at the Kigali International Airport and they are particularly used during passengers’ arrival and departure to scan and detect fever as Fig. 7 clearly illustrates. After screening, travelers go for Covid-19 test at Covid-19 test center to facilitate or speed up Covid- 19 testing. Social distancing marks are also provided to direct passengers where they must stand while waiting others from checking in and out. Notebooks are used to record travelers’ information during their arrival and departure in order to make sure that each traveler’s information is recorded to avoid any Covid -19 cases which might enter through the airport. Results normally are received at designated hotels booked by passengers before their arrival at Kigali International airport.

Figure 7: Fever Detection at the Airport Source: Field work, 2020

4.4 Road, social distancing and bus cameras Some CCTV cameras are mounted on selected roads within the city as postulated on Fig. 8 to monitor the traffic situation. During Covid - 19 era these cameras also helped to monitor and control community social distancing on the road particularly displaying those who put on and off face masks. Similarly, cameras were installed in the buses. Basically, before the pandemic these cameras were used to monitor rear door passengers, cabs and drivers, rear road and front door passengers as well. But during Covid -19 these cameras contributed a lot where drivers were able to monitor social distancing in the buses and be in better positions to know who wanted to board or get off the bus and automatically open bus doors as opposed to manual operations of doors. This really nailed the concept of smart city where most of urban areas in the near future will be installed cameras on the road, buses

40 and buildings to monitor and give real time information in case needed or to solve city or neighborhood problems.

Figure 8: Community social distancing on roads and in buses Source: Fieldwork, 2020 Source: Taarifa, 2020

4.5 Residents opinions on the use of smart technology Based on Kigali City’s residents’ opinion on how smart technology solutions are helping in the fight against Covid-19 pandemic in the three sectors which are Nyakabanda, Muhima and Kimisagara, 74 out of 96 respondents (nearly 77%) acknowledged that the emerging technology like the use of Drones and Robots had a huge contribution in the health sector during the pandemic as it helped health workers combat this pandemic. In this regard, during household interviews, 90 out of 96 respondents (about 94%) said that the current technology was useful during the pandemic and they opined that the technology must be adopted in other sectors like agriculture, construction and education. Fig. 4 clearly shows the percentage and number of respondents who were in favour or against the application of smart technology in controlling the spread of Covid – 19 and their ideas on whether there is a need to upscale the adoption and application of smart technology in other sectors. They thence, had an opinion the adoption and application of smart technology especially the use of drones in agriculture will help farmers increase their production while monitoring their crops for future better food production.

5. Discussion

The role of smart technology in managing infectious disease in Kigali city complied with the WHO's recommendation to identify, isolate and quarantine those who are infected (WHO, 2020b).

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Like in Chinese cities which were affected by the Covid – 19 pandemic, the Kigali experience shows same traits based on a techno-driven perspective where its well established technological ecosystem has been mobilized to impose technological solutions (see also Hu and Zheng, 2020). Field results from Kigali have generally shown that drones were largely used than robots and other means of controlling the pandemic. They have also revealed how smart technology had positive impact to minimize, control and manage the Covid – 19 as it also had impacts in developed countries including Wuhan city in China, where the genesis of the virus stems from, as well as in other Asia and European countries. Andrelini (2019) and Kummitha (2020) acknowledge that China made use of its well-established surveillance system and placed cities under complete quarantine using a draconian approach to control the spread of the virus particularly serious investments in identifying infected patients. To cement on the importance of cameras to monitor the pandemic, Shenzhen smart city had 159 cameras per every 1,000 residents, while the Shanghai smart city installed 113 cameras, the Tianjin smart city with 93, and the Jinan smart city with 73 cameras, all per every 1,000 people (Kummitha, 2020). Concerning the installation of cameras at the airport, in buses and hotels for controlling social distancing, Kharpal (2020) emphasizes that during the quarantine in China, the government even installed CCTV cameras on apartment doors to ensure that residents would not leave their quarantined houses. Some of these cameras include AI technology and facial recognition to identify people who were infected with the coronavirus (Keegan, 2019). Moreover, the Kigali experience has not shown the use of apps as they are being used in China particularly the Alipay and WeChat and have become popular in China, helping the government to track down those who are infected (Kupfesrchmidt and Cohen, 2020). Such an approach allows citizens to voluntarily come forward to communicate their health data and download dedicated mobile apps to share their health updates and location histories (Kummitha, 2020). In the same line of thought, the Rwandan government has not started using mobile apps as a way of communicating news related to the Covid – 19 pandemic to its citizens as opposed to Chinese and the Western democracies governments. Failure to use multiple technologies might have contributed to the speed at which the pandemic still affects the country and its citizens as a whole taking into account the number of cases in the study area. In this regard, concerning the use of mobile apps by the governments as a tool to control the pandemic, Hollands (2008) and Komninos (2008) provide that in the Western democracies smart technologies (mobile apps inclusive) are used by governments to inform decisions and to find ways in which problems can be addressed. Also, while these countries have freely shared the data about the virus transmission and allowed everyone aware about the growing trends, China has been accused of concealing information from public and international community (Kummitha, 2020).

6. Conclusion and recommendations

This research which aimed at exploring the role of smart technology in managing and controlling infectious diseases, particularly the Covid – 19 pandemic, in developing countries especially in Kigali City. Basing on the results presented, we conclude that the use of emerging or smart technology has been very instrumental in the struggle to fight against the pandemic. While the drones are largely used in the struggle, other technologies especially the use of robots and detections cameras are pivotal. The challenge which emerges is the availability of qualified personnel to operate and apply these technologies. Moreover, other contemporary and easy to apply technologies especially mobile apps which may be used by the government to inform its people about the spread have never put into practice in Rwanda. This makes it difficult for citizens to get current information about the pandemic, making them respond or find solutions later than it would be if they had prior information. Above all, Rwanda has not established formal structures and instruments to mainstream the adoption and application of smart technology in the country. As such, it lacks qualified professionals to spearhead smart technology and link it to the citizens. Basing on these conclusions we argue that for better controlling and managing infectious diseases and pandemic threats, first, the adoption and application of smart technology must be a national agenda. This will also include the application of mobile apps so that the government can use them to collect data about the pandemic and actively share the information with its citizens. This will not only apply to controlling and managing pandemics like Covid -19 but any other type of pandemic which

42 might arise after coronavirus and also in various sectors such as agriculture. Secondly, the establishment of department in charge of innovative ideas to fight current and future pandemic is inevitable. This goes hand in hand with training the community to solve health crisis during and even after Covid-19 pandemic. Lastly, in order to speed the implementation of the Smart City Concept, the establishment of the institution in charge of financial assistance during pandemics like Covid - 19 is highly recommended.

7. Acknowledgements

We would like to extend appreciation to Kigali city professionals and residents for providing data for this paper. In particular, a note of vote goes to the Rwanda Biomedical Center Team for the cooperation offered during field data collection. Likewise, all Ardhi University lecturers and various research teams in the School of Spatial Planning and Social Sciences, Department of Urban and Regional Planning for their contributions.

References

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Available online at www.asric.org

ASRIC Journal on Health Sciences 1 (2021) 45-62

a Dept. of Biochemistry, Faculty of Life Sciences, University of Ilorin, Ilorin, Nigeria b Dept. of Anatomy, Basic Medical Sciences, University of Ilorin, Ilorin, Nigeria c Biological Sciences Department, Achievers University Owo, Ondo, Nigeria d Dept. of Microbiology, Faculty of Life Sciences, University of Ilorin, Ilorin, Nigeria e Biochemistry Unit, Dept. of Science Laboratory Technology, Federal Polytechnic Ilaro, Ogun State, Nigeria

Received 11 February 2020; revised 30 June 2021; accepted 30 July 2021

Abstract

Pfizer researchers reported in 2018 that lipophilic efficiency (LipE) is an important metric that is increasingly being applied to medicinal chemistry drug discovery programs. In this perspective, drug discovery examples have been strictly applied when adopting LipE to guide medicinal chemistry lead optimization toward candidate drugs with exceptional efficacy and safety in vivo potential, especially when guided by optimization based on physicochemical properties. In general, most medicinal chemists only consider potency and try to increase it during hits and lead optimization or when studying the structure-activity relationship. It should be noted that lipophilicity should be considered in conjunction with potency variations to ensure both the safety (drug- likeness) and the efficacy of the candidate drug. Therefore, the aim of this study is to identify successful potential leads against 3CL-pro and optimize them for maximum potency and safety in COVID-19 treatment with a design strategy approach. 3CL-pro inhibitors with lipophilic efficacy and related bioactivity data were obtained from the Chembl database and analyzed based on relationship between LipE and logP (lipophilic). The 2D physicochemical descriptors of the compounds were calculated. Quantitative Structural-Activity Relationships (QSAR) model was built and bioactivities of novel compounds were predicted while molecular mechanism was inferred by docking assay. Based on analysis, 80 novel compounds were found, 6 of the novel compounds (36, 37, 46, 47, 77 and 79) revealed an increase in both LipE and potency with logP decrease, which makes them better alternatives to existing 3CL-pro inhibitors in the treatment of COVID-19.

Keywords: COVID-19; Lipophilic; QSAR model; 3CL-pro inhibitors; drug

1. Introduction

From a global public health and socioeconomic perspective, there is an urgent expectation to come- up with a rapid intervention that includes effective vaccines and antiviral drugs to stop the spread of the current pandemic virus [1] designated as coronavirus disease 2019 (COVID-19), broadcasted by the

1Corresponding author. Email addresses: [email protected] (G.A. Oche)

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World Health Organization a pandemic [2, 3]. The infection inhibits the liver, respiratory and central nervous systems, the digestive system of humans and animals. Thus the resent name, SARS-CoV-2 agreed upon by scientist due to 82% similarity with the known Severe Acute Respiratory Syndrome- Coronavirus (SARS-CoV) [4-6]. The SARS-CoV-2 principle protease (Mpro), also identified as chymotrypsin-like (3CL) protease (3CLpro), is a non-structural protein playing crucial role through cleavage of the virus-encoded polyproteins for replication and maturation (Coro 21). By so doing, it is rendered as an alluring quarry for the upshot of efficacious antiviral drugs against SARS-CoV-2 virus [7, 8]. The 3CLpro homodimer enzyme (EC: 3.4.22.69; optimal activity at pH 7.5 and 42 ° C) is largely maintained amid members of Coronaviridae with approximately 40-44% sequence homology. It has three structural segments consisting of domain I (residue 8 - 101) and domain II (residue 102 - 184), with the pair having beta-barrel motifs representing the catalytic region of chymotrypsin, as well as domain III (residue 185 - 200), having helical structure participating in the protein dimerization and enzyme activation [9-13]. A valid approach necessary to design potent drugs for SARS-CoV-2 infection requires the interaction mechanism of protein-ligand. These protein-ligands exhibit an important role in structure-based drug design, while enhancing steric compatibility of drug agents is an effective strategy for generating energy-efficient binding of drug agents to target receptors [14]. Leeson and Springthrope [16] initially proposed ligand lipophilicity efficiency (LLE or LipE) [15]. And various studies conducted on this ligand have proofed it to be an effective and direct means of evaluating the quality of research compounds. Safety of the compounds is accessed by relating lipophilicity and potency. LipE tries to maximize acceptable minimum lipophilicity per unit in vitro or in basic terms, to enhance the activity while sustaining low lipophilicity [16]. LipE is estimated as logP (or log D) minus logarithm of ligand potency (pKd, pKi or pEC50) [17]. Practically, instead of measuring log P, the computed value of clog P is commonly adopted together with the most pertinent in vitro strength to predict in vivo efficacy [18]. LipE can be adopted to recognize small sized molecules which would otherwise be overlooked due to its low potency and lipophilic value. This is advantageous in view of the fact that size and lipophilicity are largely increased following lead optimization. Thus using small quantity of LipE, makes less lipophilitic compounds a beneficial starting point [17, 19, 20]. In recent time, LipE has gained popularity as a direct and important method to modulate lipophilicity, with examples to show for its use in drug optimization. Some notable examples worth mentioning include; CB2 agonists [24], CB2 agonists/CB1 agonists [25], soluble epoxide hydrolase inhibitors [35], twofold PI3K/mTOR inhibitors [27], HIV non-nucleoside reverse transcriptase inhibitors [28], ATP-competitive Akt inhibitors [26], design of a potent cyclin-dependent kinase 2 (CDK2) inhibitor [21, 22] and protein kinase B inhibitor [23] (see [29, 30] for review). Hence this study aims to select successful leads as starting points towards optimization to design more potent and drug-like clinical candidates as inhibitors of 3CL-pro.

2.0 Materials and methods 2.1 Collection of data and dataset groundwork The trivial name, source, lipophilic efficiency metrics (LipE), experimental lipophilicity (AlogP) and biological activities (IC50) of 3CLpro inhibitors were obtained from the ChEMBL database. A total of 15 coronavirus 3C-like proteinase Inhibitors were retrieved on the basis of avail chemical structures with corresponding bioactivities (IC50) (Figure 1). Bioactivities (IC50) were subsequently adjusted to pIC50 adopting the expression pIC50 = (-log (IC50 X)). 3CLpro inhibitors chemical structures were downloaded from the ChEMBL database as smiles which were then changed to (2D) SDF format on DataWarrior v5.0.0. [31].

2.2 Analysis of Lipophilic efficiency The lipophilic efficiency of retrieved dataset in relation to their corresponding potency (pIC50) and lipophilicity (logP) was carried out using DataWarrior v5.0.0

2.3 2D QSAR study The potency of a compound must be quantified by molecular descriptors in order to build a QSAR model [32] and so based on this, CDK descriptor version 1.0 was adopted for the computation of

46 varied descriptors in the following groups: Hybrid features, Constitutional properties, Topological properties, Electronic properties and Geometric descriptors. The computed properties were organized in a matrix format. These computed properties were preprocessed to determine the correlation coefficient cut-off of 0.99 based on a variance cut-off of 0.0001 and take-away invariables (constant column) by using JFrameVWSP version 1.0. The dataset of 28 molecules retrieved from literature [33] was separated into the test and training dataset by adopting Kennard-Stone method [34] QSAR model validation is essential to assess how reliable a developed model is [35]. This is usually achieved by evaluating the internal stability and predictive ability of the QSAR models. In this study, the QSAR model developed was authenticated using leave-one-out (LOO) method to achieve internal validation. This was performed by removing a molecule, creating and authenticating the model against the individual molecule for all the Q2 (rCV2) values and documented. Equation (1) was used to calculate rCV2 (cross-validation regression coefficient) to describe the internal stability of the model.

2 YY 2  obs pred  rCV 1 2 (1) YYobs  

Where Y in the stated equation represents the training dataset average activity value. Ypred and Yobs stands for the predicted and observed activity values correspondingly. It is worthy of note that, rCV greater than 0.5 proposes a realistically robust model [36]. Sequel to the process of internal validation, QSAR model’s high predictive power was projected from an external test set of compounds not applied in building the QSAR model. The predictive 2 2 capacity or external validation obtained was determined by predictive R (Rpred ) based on equation (2).

2 YY 2  pred test  test  r prod 1 2 (2) YYtest   training 

Y(test) and Ypred(test) is the observed activity and predicted values for test set compounds respectively. Y(training) is the average bioactivity of compound in the training set. 2 QSAR model (Rpred ) greater than 0.6 is the acceptable predictive power for the test set molecules [37-39]. MLR method was used to develop QSAR model from the dataset to exam potential leads against 3CLpro inside a training dataset (28 compounds). CDK algorithm was used to calculate the total molecular descriptor (108) for individual compound.

2.4 Molecular docking The three-dimension crystal structure of (PDB: 1uj1) from the protein databank was retrieved to prepare the target SARS coronavirus 3C-like proteinase (3CLpro) [40]. Discovery studio 2017R2 was employed to remove all heteroatoms while Pymol tool for non-essential water molecules. Subsequent to receptor and ligands preparation, this study utilized PyRx, AutoDock Vina option based on scoring functions to perform molecular docking analysis. PyRx, AutoDock Vina exhaustive search docking function was used for the analysis. Upon successful minimization process, the resolution of the grid box was centered at 76.0065 ×-11.5107 × 18.0445 on the x, y and z axes correspondingly at grid dimension 25x 25 x 25 Å to specify the binding site (Figure 1).

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Figure 1: Raw data with corresponding bioactivities (IC50) 3.0 Results and Discussion

Figure 2 shows the relationship between potency (pIC50), lipophilicity (logP) and lipophilic efficiency (LipE) of 3CL-pro inhibitors, which is useful in lead selection and optimization as discussed in the section below:

3.1 Iso-LipE 3CLpro inhibitors Multiple combinations of pIC50 and logP can lead to the same LipE. On this account, having the knowledge of LipE alone for molecule is not informative [50]. It is necessary to interpret 3CLpro inhibitors in the LipE plot format, to give insight into required procedure for optimization-oriented designs. Based on our analysis, compound 2 had a pIC50 value of 5 with a measured logP of 6.01, resulting in a LipE of -1.01 (Figure 3). Although compound 8 is slightly less potent with a pIC50 value of 4.82, it had a logP of 5.84 which resulted in a comparable lipophilic efficiency of -1.02. If we consider only the potency, compound 2 ought to appear superior to compound 8. These two compounds are comparably attractive and isoefficient for follow-up. In addition, taking into consideration that both compounds 2 and 8 have logP values of 6.01 and 5.84 respectively, which exceed the required optimum for ADME (Absorption, Distribution, Metabolism, and Excretion) properties (logP: ≤ 5), none is considered a better starting place than the other. Also, compound 11 had a pIC50value of 4.4 with a measured logP of 5.06, resulting in a lipophilic efficiency of -0.66 while compound 15, with similar potency of pIC50 valueof 4, had a logP of 4.67 resulting in a similar lipophilic efficiency of -0.67 (Figure 3). Given that compound 11 had a logP of 5.06 which exceed the required optimum for ADME properties (logP: ≤ 5), compound 15 is a better starting place. In fact, both compounds are isopotent i.e they have similar pIC50 values. This highlights the essence of analyzing LipE changes in the context of logP for selecting a lead compounds [41].

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Figure 2: Relationship between pIC50 and logP of 3CL-pro inhibitors in relation to their respective LipE

Figure 3: Isoefficient 3CL-pro inhibitors

3.2 Iso-potent Efficiency Changes of 3CLpro inhibitors Unlike compound 2 and 8; 11 and 15, the compounds with comparable pIC50 can have different LipE. Not realizing logP would make then look alike but then again, the compounds with lower logP will possess a higher lipophilic efficiency [42]. This is an isopotent efficiency change. It is illustrated by the potency of compounds 6 and 8; 13 and 14, in which reduction in LipE are seen while pIC50 is sustained, which lead to an increase in LipE (Figure 4).Compounds 6 and 8; 13 and 14 are same in terms of pIC50, irrespective of logP ranging from 3 to 6. Of all these compounds, 13 have appreciably high LipE when compared with the other compounds, thus presenting it a valuable lead which would have been lost in the subset of equipotent compounds without a LipE-based analysis.

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Figure 4: Isopotent 3CL-pro inhibitors

3.3 Isolipophilic LipE Changes of 3CL-pro inhibitors Invariant logP in relation with pIC50 changes throughout a set of derivatives resulting in isolipophilic modifications of LipE. Generally, isolipophilic variation in efficacy occurs with twosome of enantiomers, even though they are not limited to such examples [42]. This is observed in compound 12 and 13 in which an increase in LipE are observed while lipophilicity is maintained. This resulted in an insignificant increase in potency (Figure 5). Compound 12 and 13 are same in terms of their logP values, despite pIC50 values of 4.35 and 4.22 respectively. 12 possessed slightly higher LipE, making it an indispensable lead. Because logP remain the same, assessment of isolipophilic LipE variations cannot be distinguished from a potency-centric analysis.

Figure 5: Isolipophilic 3CL-pro Inhibitors At the same time, decreasing logP and improving potency results in a very large increase in lipophilic efficiency [42-44]. This was achieved by generating novel compounds based on structural modification of the starting chemical entity. Therefore, in a search for a starting chemical specie from our dataset, Compound 1 (with the lowest logP value) and 10 (with the highest potency) reveals an efficiency increase (3-fold) of -0.78 and 2.29 respectively with potency and logP decrease (figure 6). Given that compound 1 had a logP of 6.03 which is over what is optimal for ADME properties (logp: ≤ 5), compound 10 with logP value of 2.11 is a better starting chemical entity.

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Figure 6: 10-1 showing an efficiency Increase decrease in potency and logP

Quantitative structural-activity relationship analysis (QSAR) is a successful method that has been adopted in reasonable drug design and in understanding drug action mechanism. Bioactivities of compounds are rated as a function of various physicochemical properties in QSAR studies. This makes clear how the variation of biological activity is based on alteration in the chemical structures [45]. These physicochemical properties are quantified in the form of descriptors. Given this, we designed a set of new compounds from compound 10 with a de novo design approach using DataWarrior v5.0.0. DataWarrior adopted an evolutionary method that mimics nature by randomly transforming known molecular configurations having small changes to establish novel generations with possibly better structures. Each generation of molecules are tested for robustness with a set of modifiable principles and the most auspicious structures serve as a starting point for subsequent generation. The mutation algorithm executes vicissitudes such as bond order changes, ring aromatisations, replacing an atom, atom insertions, substituent migrations just to mention a few. Every structure to be mutated is firstly evaluated for all possible mutations concerning how extensively the alteration will increase or decrease the drug-likeness. Mutations with alteration in the required direction are assigned a higher probability than mutations that reduce drug-likeness. Mutations that would create high ring tension are eliminated from the list. Based on this approach, 81 structures were created that retain the scaffold of compound 10 with the corresponding fitness scores (Figure 7). Compound 17 of the second generation holds the highest fitness scores (0.98817), which makes it closest to the original structure (compound 10, fitness score = 1,000).

Figure 7: Novel compounds generated based on the structure of the parent molecule (compound 10) (a = Compound 10; b = Compound 17)

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Tsai et al., (2006) [33] discovered 28 novel family of SARS-CoV Protease Inhibitors with their corresponding IC50 values and shared the same scaffold as compound 10 (Figure 8). In order to predict the bioactivities of the newly generated datasets, a QSAR model was built from the 28 datasets having the same scaffold as the novel compounds.

Figure 8: Retrieved chemical structures with same scaffold as compound 10 To analyze the multiplicity of the testing and training set, the Principal Component Analysis approach (PCA) was adopted and the PCA was executed with structural descriptors evaluated for the entire data set. This approach helped to identify homogeneities in the total data, as well as to describe the spatial location of the samples to help in dividing the data into train and test sets. The PCA result revealed three main components (PC1, PC2 and PC3), elucidated as 99.998% of the entire variables which are as follows: PC1 = 41.975%, PC2 = 33.541% and PC3 = 24.482%. Given that the first three principal components can account for most of the variables, the different score plot is a dependable exemplification of the spatial allotment of points for the whole data. The compounds distribution over the initial three principal components space is shown by the plot of PC1, PC2 and PC3 (Figure 9) with PC1 and PC2 covering the largest variability in the total data (Figure 10). This number revealed that the samples of the test and training sets appear to be uniformly strewed in the three-dimensional space and consequently, it was possible to divide the dataset. In addition, the compounds in the training sets are represented in the whole dataset.

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Figure 9: Analysis of the primary component of the test and train sets

Figure 10: Analysis of principle component with PC1 and PC2

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The next step after analyzing the separation of the dataset into the test and training set was to identify and choose the major factors that are most important for the SARS-CoV protease inhibition activity of the 28 new inhibitors. Genetic algorithm (GA) was applied as the method for selecting variables to select only the most important (relevant) combinations to obtain the model with the utmost predictive power by employing training dataset. The three (3) most important descriptors according to the GA approach, are SCH-5, C1SP3 and khs.ddsN based on the variance cut-off of 0.01 and inter correlation cut-off of 0.9. In this study, these descriptors have been shown to be related to the studied biological response and are described in Table 1. In general, the quality of a model is described by its predictability in a QSAR study. The techniques adopted in this study were performed to correlate physicochemical descriptors of 28 3CL- pro inhibitors from their inhibitory training set. Physicochemical descriptors were taken as individual variables and the inhibitory activity of the 3CL-pro target was taken as dependent variables. The data set of 28 compounds was divided into training set of 19 compounds in order to create and test the model. The datasets were subsequently utilized to construct the model and a test set of 9 compounds, which were used to test the structured model. The resulting linear equation based on the MLR is as follows (equation 3):

pIC50  4.52085  0.2233  0.2688  0.08067 C 1 SP 3 (3)  4.92257  0.79286 SCH  5  0.51868  0.18816 khs . ddsN

R2 (regression coefficient) = 0.82776, SEE (standard error of estimate) = 0.28645, Q2 (cross-validation regression coefficient) =0.6468, SDEP (standard deviation of error of prediction) = 0.3829 r2 (LOO) ((Leave out one cross validation) = 0.7077 PRESS (predicted residual sum of squares) = 1.23081 2 F (variance ratio) = 24.02849 (DF: 3, 15), r pred (external predictive power) = 0.80913

Equation (5) suggests that the model established with GA-MLR presented an excellent tetragonal correlation coefficient (R2) value with both internal and external predictive power (r2pred) having excellent values. The developed QSAR model derived by GA-MLR showed a noteworthy connection between dependent variable (pIC50 values) and the carefully chosen descriptors (independent variables). An 82.8% correlation exists among the activity and selected descriptors in the training dataset, determined based on value of the regression (R2=0.82776). Meanwhile, the value of the cross- validation regression coefficient (Q2 = 0.6468) put forward ~64.7% prediction exactitude of this QSAR model. Figure 11 shows the predicted and observed biological activities of the training and test datasets. Figure 12 is the predicted pIC50 plot versus the experimental pIC50 which revealed that there is a good agreement between the predicted and experimental activity values.

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Figure 11: Experimental and Predicted bioactivities of the Train and Test set

Table 1: GA selected descriptors with their corresponding description

S/N Descriptors Description Contribution 1 C1SP3 Singly bound carbon bound to one other Negative Contribution carbon 2 SCH-5 Simple chain, order 5 Positive Contribution 3 khs.ddsN Description not available in the database Negative Contribution

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Figure 12: The predicted pIC50 values using MLR modeling against the experimental (observed) pIC50 values The three descriptors for the best model (GA-MLR) used for PC1–PC2 loadings plot is shown in Figure 13. For the loadings, it was affirmed that the compounds with greater biological activity values, situated on the right side presented a larger influence on the SCH-5 descriptor located on the same side as in Figure 8. Conversely, compounds with lesser biological activity values on the left side have extra distinct contributions from the other descriptors (mostly from khs.ddsN and C1SP3).

Figure 13: PC1–PC2 loadings plot using the three descriptors for the best model (GA-MLR) The Y randomization test performed to guarantee that there are no random correlations was used in this study to validate the recognized QSAR model and also to ensure that the selected descriptors are not random. Therefore, results of the model should be of low statistical quality. Random MLR models created was done randomly by rearranging the dependent variable while maintaining the individual variables. The recently built QSAR models will predictably have significant R2 and Q2 low values for

56 more than a few trials, thus confirming that developed QSAR models are robust. Approximately hundred trials of Y-randomization were conducted in this study which gave lesser values for R2 and Q2, thereby authenticating the initial model (the established GA-MLR model) (Figure 14).

Figure 14: R2 train and Q2LOO values following numerous Y-randomization tests for GA-MLR

The residue for the predicted values of pIC50 for the training and test sets against the experimental pIC50values is plotted as presented in Figure 15. It was observed that the model did not indicate relative and systematic error at all, since the propagation of the residues on the horizontal lines is random.

Figure 15: The residual against the experimental pIC50 by adopting GA-MLR Furthermore, QSAR model was utilized to envisage the bioactivities of the novel compounds from their respective 2D physicochemical properties (SCH-5, khs.ddsN and C1SP3). The compound in generation 0 represents the parent molecule (compound 10), and has a predicted pIC50 value of 4.49. Twenty compounds across generation 3-10 have a predicted pIC50 values higher than the parent molecule, which makes them more potent than the parent molecule (Figure 16). From the predicted pIC50 we computed LipE and clogP for each of the novel compounds using Datawarrior v5.0.

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Figure 16: De novo synthesized compounds with higher predicted bioactivities

Increase in LipE can be attained by modifying the ligand to impact lipophilicity, potency or both. The biggest assured impact of LipE frequently occurs when adjustments improve potency and concurrently lower lipophilicity [33]. Based on our design strategy, 6 of the novel compounds (36, 37, 46, 47, 77 and 79) revealed an increase in both LipE and potency with logP decrease (Figure 17).

Figure 17: Optimized compounds based on bioactivities, logP and LipE In order to have a better understanding of the molecular mechanism underlying the action of the unique compounds selected on the basis of their bioactivities and LipE, molecular docking was employed in this study. In the present study, the six selected compounds and their parent molecule were docked into the binding pocket of SARS coronavirus 3C-like proteinase for their inhibitory (antagonistic) (Figure 18a and b) properties. Compound 77 showed a better binding affinity, -

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7.4kcal/mol, when compared with the parent molecule (compound 10; -7.3kcal/mol) and thus is considered as the lead compound (Figure 19).

Figure 18: (a) Grid box within which the ligand binds 76.0065 * -11.5107 * 18.0445 along the x, y and z axes correspondingly (b) Compounds within binding pockets

Figure 19: Binding affinities of selected 3CL-pro inhibitors The highest binding energy of -7.4kcal/mol attributed to compound 77 is considered to be as a result of chemical interactions at the receptor’s active site (Figure 20a) which includes: Five (5) hydrogen bonds involving GLN110, ASN151 and HIS246 residues; Three (3) hydrophobic interactions involving VAL104, LEU202 and ILE249 residues. However, that of compound 10 serving as the reference molecule presents the following chemical interactions at the binding pocket (Figure 20b): Four (4) hydrogen bonds involving ASN151, ASP295 and THR111 residues with two (2) hydrophobic interactions involving ILE249 and PRO293. Therefore, the consequence of higher binding affinity of compound 77 within SARS coronavirus 3C-like proteinase drug-able pocket is due to the presence of more hydrophobic interactions and more hydrogen bonds when compared to compound 10. Hydrogen (H)-bonds potentiates varied cellular functions by accelerating molecular interactions. In order words, hydrogen bonds are considered to be facilitators of protein-ligand binding [48, 49]. Previous studies have shown that interdependent receptor-ligand H-bond pairings potentiate high- affinity binding, which corresponds to an increase in binding affinity [50]. Additionally, ASN151 was predicted to be universally implicated in hydrogen bonding with the ligands within SARS coronavirus 3C-like proteinase drug-able pocket.

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Figure 20: 3D and 2D interactions (a) compound 77 (b) compound 10

Conclusion

This study has maximized the combination of LipE and logP to select potent leads against SARS coronavirus 3C-like proteinase Inhibitors and to optimize these leads based on changes in their physicochemical properties in order to discover highly efficient and reliable clinical candidates for the cure of COVID-19. Six novel compounds (36, 37, 46, 47, 77 and 79) were suggested for further in vitro and preclinical testing based on their predicted efficiencies values and potency.

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[30] Meanwell, N.A., 2011. Improving drug candidates by design: a focus on physicochemical properties as a means of improving compound disposition and safety. Chemical research in toxicology, 24(9), pp.1420-1456. [31] O'Boyle, N.M., Banck, M., James, C.A., Morley, C., Vandermeersch, T. and Hutchison, G.R., 2011. Open Babel: An open chemical toolbox. Journal of cheminformatics, 3(1), p.33. [32] Mahabeleshwar, G.H. and Kundu, G.C., 2003. Tyrosine kinase p56lck regulates cell motility and nuclear factor κB-mediated secretion of urokinase type plasminogen activator through tyrosine phosphorylation of IκBα following hypoxia/reoxygenation. Journal of Biological Chemistry, 278(52), pp.52598-52612. [33] Tsai, K.C., Chen, S.Y., Liang, P.H., Lu, I.L., Mahindroo, N., Hsieh, H.P., Chao, Y.S., Liu, L., Liu, D., Lien, W. and Lin, T.H., 2006. Discovery of a novel family of SARS-CoV protease inhibitors by virtual screening and 3D-QSAR studies. Journal of medicinal chemistry, 49(12), pp.3485-3495. [34] Paul, M.K. and Mukhopadhyay, A.K., 2004. Tyrosine kinase–role and significance in cancer. International journal of medical sciences, 1(2), p.101. [35] Roy, K., Das, R.N., Ambure, P. and Aher, R.B., 2016. Be aware of error measures. Further studies on validation of predictive QSAR models. Chemometrics and Intelligent Laboratory Systems, 152, pp.18- 33. [36] Veber, D.F., Johnson, S.R., Cheng, H.Y., Smith, B.R., Ward, K.W. and Kopple, K.D., 2002. Molecular properties that influence the oral bioavailability of drug candidates. Journal of medicinal chemistry, 45(12), pp.2615-2623. [37] Yadav, D.K. and Khan, F., 2013. QSAR, docking and ADMET studies of camptothecin derivatives as inhibitors of DNA topoisomerase‐I. Journal of Chemometrics, 27(1-2), pp.21-33. [38] Yadav, D.K., Kumar, S., Saloni, H.S., Kim, M.H., Sharma, P., Misra, S. and Khan, F., 2017. Molecular docking, QSAR and ADMET studies of withanolide analogs against breast cancer. Drug Design, Development and Therapy, 11, p.1859. [39] Kumar Yadav, D., Kalani, K., Khan, F. and Kumar Srivastava, S., 2013. QSAR and docking based semi-synthesis and in vitro evaluation of 18 β-glycyrrhetinic acid derivatives against human lung cancer cell line A-549. Medicinal Chemistry, 9(8), pp.1073-1084. [40] Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N. and Bourne, P.E., 2000. The protein data bank. Nucleic acids research, 28(1), pp.235-242. [41] Brockunier, L.L., He, J., Colwell Jr, L.F., Habulihaz, B., He, H., Leiting, B., Lyons, K.A., Marsilio, F., Patel, R.A., Teffera, Y. and Wu, J.K., 2004. Substituted piperazines as novel dipeptidyl peptidase IV inhibitors. Bioorganic & medicinal chemistry letters, 14(18), pp.4763-4766. [42] Johnson, T.W., Gallego, R.A. and Edwards, M.P., 2018. Lipophilic efficiency as an important metric in drug design. Journal of medicinal chemistry, 61(15), pp.6401-6420. [43] Johnson, T.W., Tanis, S.P., Butler, S.L., Dalvie, D., DeLisle, D.M., Dress, K.R., Flahive, E.J., Hu, Q., Kuehler, J.E., Kuki, A. and Liu, W., 2011. Design and synthesis of novel N-hydroxy- dihydronaphthyridinones as potent and orally bioavailable HIV-1 integrase inhibitors. Journal of medicinal chemistry, 54(9), pp.3393-3417. [44] Freeman-Cook, K.D., Hoffman, R.L. and Johnson, T.W., 2013. Lipophilic efficiency: the most important efficiency metric in medicinal chemistry. Future Medicinal Chemistry, 5(2), pp.113-115. [45] Bayat, Z. And Yazdan Abad, M.F., 2011. Quantitative Structure-Property Relationship (Qspr) Study Of Kovats Retention Indices Of Some Of Adamantane Derivatives By The Genetic Algorithm And Multiple Linear Regression (Ga-Mlr) Method. Petroleum & Coal, 53(2). [46] Sander, T., Freyss, J., von Korff, M. and Rufener, C., 2015. DataWarrior: an open-source program for chemistry aware data visualization and analysis. Journal of chemical information and modeling, 55(2), pp.460-473. [47] Cramer, R.D., 1993. Partial least squares (PLS): its strengths and limitations. Perspectives in Drug Discovery and Design, 1(2), pp.269-278. [48] Salentin, S., Haupt, V.J., Daminelli, S. and Schroeder, M., 2014. Polypharmacology rescored: Protein– ligand interaction profiles for remote binding site similarity assessment. Progress in biophysics and molecular biology, 116(2-3), pp.174-186. [49] Sawada, T., 2012. Chemical insight into the influenza a virus hemagglutinin binding to the sialoside revealed by the fragment molecular orbital method. Open Glycoscience, 5(1). [50] Chen, D., Oezguen, N., Urvil, P., Ferguson, C., Dann, S.M. and Savidge, T.C., 2016. Regulation of protein-ligand binding affinity by hydrogen bond pairing. Science advances, 2(3), p.e1501240.

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Available online at www.asric.org

ASRIC Journal on health Sciences 1 (2021) 63-82

a Dept. of Biochemistry, Faculty of Basic Medical Sciences, College of Medicine, University of Ibadan, Nigeria b Dept. of Biochemistry, Faculty of Basic Medical Sciences, College of Medicine, University of Lagos, Nigeria c Dept. of Biochemistry, Federal University of Technology Nigeria

Received 22 April 2020; revised 22 March 2021; accepted 20 May 2021

Abstract

Introduction: Since the outbreak of Covid-19 identified around December 2019 which is rapidly expanding with confirmed cases in over 210 countries. Global incidence is on a ravaging increase and with new cases reported daily which has imposed threat to global health and economy. Some of the notable symptoms include dry cough, cold, fever and respiratory distress alongside inflammation. Methods: In order to curtail the community spread and reduce the incidence of new cases of Covid-19 we reviewed some medicinal foods, leafs and spices that has chemoprophylaxis and potent pharmacological activities. Results and Discussion: The anti-inflammatory, anti-viral, anti-bacterial, antioxidant, anti-pyretic and inhibition of viral replication properties against the SARS-COV-2 (Severe acute respiratory syndrome coronavirus 2) symptoms and elucidate their bioactive compounds with their mechanism of action and suggest possible preventive roles they play in the abating the spread of the Covid-19 and reduce the cases globally in a bid of raising the immune system function and possible abate the development of symptoms and general health function. Conclusion: In this present review, we presented the preventive potentials of some medicinal foods, natural products, and their role in abating the community spread of Covid-19 globally as well as the enhancement of immunity. Keywords: Frugal Chemoprophylaxis; COVID-19; Medicinal foods; Bioactive compounds; Pharmacological properties; Mechanism of action; Proventive benefits.

1. Introduction

The outbreak of a novel coronavirus disease; a respiratory syndrome, referred to as COVID-19, was first recognized in Wuhan, China, in December 2019. The causative agent for this deadly viral infection is a coronavirus known as SARS-CoV-2. COVID-19 is demonstrated by fever, dry cough, persistent pressure in the chest, and shortness of breath (Huang et al., 2020; CCDC, 2020). There are several symptoms of coronavirus infection, such as sore throat, running nose, cough, sneezing, fever, viral conjunctivitis, loss of smell and taste and severe pneumonia (Chen et al., 2020; Li et al., 2020; Xia et al., 2020) Sneezing, runny nose, and symptoms similar to the common cold are observed in only 5% of patients. The novel coronavirus-related pneumonia COVID-19 has continued to disseminate, with the current case count close to 75,704,857 cases, and more than 1,690,061 deaths according to the World Health Organization (WHO) as of 21st December, 2020 (WHO, 2020). The mortality rate of COVID-19 is about 7% which varies by countries and regions is less than that of SARS (severe acute respiratory syndrome), which has a mortality rate of 9.6%, and less than that of MERS (Middle East respiratory syndrome), up to 34.4% deaths. Individuals already suffering from

1Corresponding author. Email addresses: [email protected] Phone: +2348133577788 (J.O. Teibo)

63 cardiovascular disease, hypertension, respiratory disease, or diabetes are at a high risk of mortality. Age and gender-specific variations in the death rate have also been reported (WHO, 2020). The disease became pandemic within a few months of its emergence, indicating a high transmission ability as compared with SARS and MERS (Munster et al., 2020; Guan et al., 2020). COVID-19 can last for up to 6 weeks depending upon the individual’s immunity and the disease intensity. A variable incubation period has been reported for the infection to establish completely; a second exposure to the viral inoculum may decrease the incubation time (Munster et al., 2020). An incubation time of 3 to 27 days (average 14 days) has been reported by different sources (WHO, 2020; Bai et al., 2020; Lauer et al., 2019). This incubation period is considerably longer than that required by SARS or MERS (Lessler et al., 2009; Backer et al., 2020). SARS-CoV-2 has an airborne route of transmission, whereby small aerosols spread in the surrounding air by the coughing and sneezing of infected individuals. These fine airborne droplets, harboring viral particles, can be directly inhaled by nearby healthy individuals (Liu et al., 2020). The viral particles can stick to the fingertips and invade the healthy individuals by contact of contaminated hands with the nose, eyes, or mouth. Hence, hand hygiene is an expedient precaution to reduce SARS-CoV-2 transmission (Yang, 2020). The infection mechanism of both the SARS and COVID-19 viruses involve an interaction with the angiotensin- converting enzyme 2 (ACE2) and cleavage of the viral spike protein by a serine protease (Zhao et al., 2019; Prabakaran et al., 2004). To have a better understanding of respiratory infectious disease transmission for pathogenesis and epidemiological spread of disease, a model for respiratory emissions was established and it was found that droplets containing the virus can be as small as 1 micron and a multiphase turbulent gas cloud from a human sneeze exhibited the property to travel great distance (7–8 m) (Bourouiba, 2020). This suggests that the gas cloud with its pathogen payload can span a certain space in a few seconds. The pathophysiology of SARS-CoV-2 infection closely resembles that of SARS-CoV infection, with aggressive inflammatory responses strongly implicated in the resulting damage to the airways (Wong et al., 2004). Therefore, disease severity in patients is due to not only the viral infection but also the host response. Giving a high rate of community spread, there is a need to change the public health policy from containment to mitigation of transmission amongst community, and determine the extent to which mild disease is contagious in the community, particularly among less vulnerable young adults for acquisition of SARS-CoV-2 infection (Spellberg et al., 2020). The constant and rapid spread of novel coronavirus SARS-CoV-2 and its ability to disseminate from human to human has prompted researchers to identify existing medicinal foods that are frugal and could have suitable preventive benefits on the novel coronavirus-related pneumonia COVID-19. Chemoprophylaxis refers to the administration of medication or natural substance for the purpose of preventing a disease or infection. The choice of chemoprophylaxis agent is dependent on if the benefits outweighs the potential harm and if it is cost effective. Since these medicinal foods possess bioactive compounds with potent pharmacological activities such as anti-inflammatory, anti-viral, anti-bacterial, antioxidant, anti-pyretic, and inhibition of viral replication properties against the SARS-COV-2 symptoms, therefore in this review, we elucidated their various bioactive compounds with their mechanism of actions. Again, we suggest possible preventive roles they play in abating the spread of the Covid-19 and reducing the cases globally perhaps by bolstering the immune system.

2. Medicinal Foods, Leafs and Spices

These are foods that do not only provide nutrient for the body but also confers medicinal and health promoting benefits. There are many examples of these medicinal foods. In this review, we would be examining foods, leafs and spices like onion, bitter cola, bitter leaf, alligator pepper, turmeric, ginger, garlic and nutrients like zinc, ascorbic acid.

2.1 Onion (Allium Liliaceae) Onions are members of the Allium genus of flowering plants that also includes garlic, shallots, leeks and chives. These vegetables contain various vitamins, minerals and potent plant compounds that have been shown to promote health in many ways. In fact, the medicinal properties of onions have

64 been recognized since ancient times, when they were used to treat ailments like headaches, heart disease and mouth sores (Nemeth and Piskula, 2007).

2.1.1 Biochemical composition of Onion

Onions (Figure 1) contain 89% water, 1.5% protein, and vitamins B1, B2, and C, along with potassium and selenium. Polysaccharides such as fructosans, saccharose, and others are also present, as are peptides, flavonoids (mostly quercetin), and essential oil. Methods for the qualitative assessment of the flavonoids have been detailed, and quercetin glycosides have been shown to be heat stable and transferable to cooking water (Lanzotti, 2006).

Fig. 1: Picture of Onion adopted from the internet (www.shutterstock.com)

Onion contains numerous sulfur compounds, including thiosulfinates; cepaenes; S-oxides; S- dioxides; mono-, di-, and trisulfides; and sulfoxides. When the onion bulb is minced or crushed, cysteine sulfoxides are released from cellular compartments and make contact with the enzyme alliinase from the adjacent vacuoles. Hydrolysis results in the release of reactive intermediate sulfenic acid compounds and then the various sulfur compounds which can be utilized as a potential preventive property on the novel Covid-19 virus (Arnault and Auger, 2006).

2.1.2 Potential Mechanisms of Pharmacological Uses of Onion and its Potential Use as Chemoprophylaxis against Covid-19 Anti-inflammatory effects: Animal and in vitro data shows that compounds derived from onion have exerted anti-inflammatory and antihistamine effects in vitro and in animal models (Griffiths et al., 2002). Antimicrobial effects: In vitro studies have shown onion possesses antibacterial (example is Helicobacter pylori), antiparasitic, and antifungal activity (Elnima et al., 1983). Clinical applications for this activity have not been determined, and use as a food preservative is limited by the strong odor and instability of sulfur compounds (Griffiths et al., 2002). 2.1.3 Dosing An average daily dose of 50 g of fresh onion, or 20 g of dried onion has been suggested for a variety of uses (Nathan and Scholten, 1999; WHO, 1999).

2.1.4 Possible Adverse Reactions of Onion Ingestion of onion and onion extract appears to be relatively safe (Nathan and Scholten, 1999; WHO, 1999). Excessive consumption of onion has been associated with GI upset (burning sensation and diarrhea), flatulence, and changes in intestinal flora (Suleira et al., 2015). Onion seeds have been reported as occupational allergens, but frequent contact with onion rarely causes allergic reaction

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(Navarro et al., 1995). Certain sulfur compounds, such as propanethial-S-oxide, escape from onion in vapor form and hydrolyze to sulfuric acid when cut, causing eye irritation and lacrimation (Chan et al., 2020).

2.2 Bitter Kola (Garcinia kola) Garcinia kola (bitter kola) is a dicotyledonous plant belonging to the family of plants called Guttiferae. It is a perennial crop growing in the forest, distributed throughout West and Central Africa (Iwu, 1993). G. kola is also found distributed in the forest zone of Sierra Leone, Ghana, Cameroon and other West African countries. In Nigeria, it is common in the South Western States and Edo State (Otor et al., 2001). It is a medium sized evergreen tree, about 15-17m tall and with a fairly narrow crown. The leaves are simple, 6-14cm long and 2-6cm across, shiny on both surfaces and spotted with resin glands. The small flowers are covered with short, red hairs (Iwu, 1993). The fruit is a drupe of 5-10cm in diameter and weighs 30-50g. It is usually smooth and contains a yellow-red pulp. The fruit changes color during maturation from green to orange, and each fruit contains 1-4 seeds (Juliana et al., 2006). Garcinia kola (Figure 2) has been referred to as a “wonder plant” because every part of it has been found to be of medicinal importance (Dalziel, 1937). It is also called bitter cola, male kola due to the reported aphrodisiac properties. It is commonly called “Orogbo” in Yoruba language, Aku ilu‟ in Igbo language and Namijin goro‟ in Hausa language (Dalziel, 1937).

Fig. 2 : Picture of bitter kola adopted from the internet (www.9jafoods.com)

2.2.1 Biochemical constituents The phytochemical compounds isolated from G. kola include tannins, saponins, alkaloids, cardiac glycosides (Ebana et al., 1991). Other phytochemical compounds isolated from G. kola seeds are biflavonoids such as kolaflavone and 2-hydroxybi-flavonols. Two new chromanols, garcioic and garcinal, together with tocotrienol were reported isolated from G. kola (Terashima et al., 2020; Morabandza et al., 2013) had also determined the chemical composition of Garcinia kola Heckel (Clusiaceae) mesocarp.

2.2.2 Traditional Uses and Medicinal Values Garcinia kola is chewed extensively in Southern Nigeria as a masticatory and it is readily served to visitors, especially among the Igbo tribe in Eastern Nigeria, as a sign of peace and acceptance of visitors. The root of the plant is used as favourite bitter chew-sticks in West Africa (Otor et al., 2001). The stem bark is used in folklore remedies as a purgative among the natives of Eastern Nigeria and the latex is externally applied to fresh wounds to prevent sepsis, thereby assisting in wound healing. It is also popular among the people of Nigeria for nervous alertness and induction of insomnia. Garcinia kola is highly valued for medicinal use. This plant has been referred to as a wonder plant‟ because every part of it has been found to be of medicinal importance (Dalziel, 193). The seeds are chewed as an aphrodisiac or used to cure cough, dysentery, chest colds, liver disorders, diarrhoea, laryngitis, bronchitis, and gonorrhea (Adesina et al., 1995). The seed is used to prevent and relieve colic; it can also be used to treat headache, stomach ache and gastritis (Ayensu, 1978). It has also been reported for

66 the treatment of jaundice, high fever, and as purgative (Iwu, 1989). In Sierra Leone, the roots and bark are taken as a tonic for sexual dysfunction in men. The bark is also added into palm wine to improve its potency (Iwu et al., 1990). Traditional medicine practitioners in Nigeria, particularly in the Ogoni area use a decoction of Garcinia kola stem bark for the treatment of dysmenorrhoea, fever, inflammation and burns (Adesina et al., 1995). "Bitter kola is anti-poison and helps to detoxify the system, it has the ability to repel evil men and spirits, it could sound superstitious but it works (Iwu, 1989). 2.2.3 Possible Mechanism of action of Garcinia kola as Chemoprophylaxis agent against Novel Covid-19

2.2.3.1 Anti-microbial properties Adegboye, et al. (Adegboye et al., 2008) had investigated the in vitro antimicrobial activities of crude extract of Garcinia kola against some bacterial isolates comprising of both Gram-positive and Gram negative organisms. In another study, the antimicrobial interaction between Garcinia kola seed (GKS) and gatifloxacin (GAT), a fourth generation fluoroquinolone was evaluated by a modification of the checkerboard technique using Bacillus subtilis and Staphylococcus aureus as the test organisms (Ofokansi et al., 2008). The results showed that the effect of combination of the methanol extract of GKS with gatifloxacin was dependent not only on the ratio of combination but also on the test organism employed for the evaluation. Overall, the combined antimicrobial effect of the interaction between GKS and gatifloxacin was predominantly synergistic against B.subtilis (Ofokansi et al., 2008).The antimicrobial activity of five solvent extracts of Garcinia kola seeds had also been investigated against 30 clinical strains of H. pylori and a standard control strain, NCTC 11638, using standard microbiological techniques (Collise et al., 2011). In vitro anti-Vibrio activities of methanol and aqueous extracts of Garcinia kola seeds against 50 Vibrio isolates obtained from wastewater final effluents in the Eastern Cape Province, South Africa were also investigated (Penduka et al., 2011). The bioactivity of G. kola seeds was also assessed on Streptococcus pyogenes, Staphylococcus aureus, Plesiomonas shigelloides and Salmonella typhimurium (Seanego et al., 2012). Trichomona cidal effects of G. kola nuts were also investigated (Gabriel and Emmanuel, 2011). Esimone et al. (Esimone et al., 2002) also investigated the effect of Garcinia kola seed extract (100 mg/kg) on the pharmacokinetic and antibacterial effects of ciprofloxacin hydrochloride (40 mg/kg).

2.2.3.2 Hepatoprotective and Anti-oxidant activities The hepatoprotective effect of Garcinia kola seed extract against paracetamol induced hepatotoxicity had been investigated in rats which their results showed that the hepatoprotective effect of the extract may be due to inhibition of cytochrome P-450 which normally converts paracematol to the toxic intermediate N-acetyl-p-benzoquinoneimine (NAPQI) (Akintonwa and Essien, 1990). The protective effects of Garcinia kola against a dose of Carbon-Tetrachloride (CC14)-induced liver damage in experimental rats were also investigated which from the results observed there was a significant decrease in liver marker enzymes and lipid peroxides (matthew and Blessing, 2007). Antioxidant potentials of five fractions (ME1–ME5) of methanolic extract of Garcinia kola seeds was also studied in which moreloflavone and GB2a very abundant compounds in the seeds of this plant, could be responsible, at least in part, for the antioxidant potential of its crude extract (Tebekeme, 2009).

2.2.4 Other studies on Garcinia kola and its health benefits Anti-ulcer potential and proton pump inhibitory activity of kolaviron (KV) isolated from Garcinia kola. Heckel had been evaluated using different ulcer models and was suggested to emerge as a potent anti-ulcer compound (Onasanwo et al., 1990). Garcinia kola (Heckel) seed extract evaluated in albino Wistar rats possess significant anti-pyretic activity, which justified its ethnomedicinal use (Kakjing et al., 2014). Garcinia kola 0.5% aqueous solution eye drop significantly reduces intraocular pressure (IOP) as compared to baseline (Adebukunla et al., 2010). Comparative study on the efficacy of Garcinia kola in reducing some heavy metal accumulation in liver of Wistar rats was also carried out. Garcinia kola has the highest hepatoprotective effect to Cd followed by Hg and least protection against

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Pb toxicity in rats and its administration was beneficial in reducing heavy metal accumulation in the liver (Nwokochaa et al., 2011). Administration of Garcinia kola for a period of six weeks in rabbits elicited no observable histo- pathological effects on the histology of the liver (Charity et al., 2012). Garcinia kola had been shown to enhance erythropoiesis in rabbits and rats and as well has no long term significant toxicological implication (Unigwe and Nwakpu, 2009). In another study, Garcinia kola significantly reduced tissue damage induced by lipopolysaccharide (LPS) (Okoko and Ndoni, 2009). Daily administration of Garcinia kola (G. kola) in growing Wistar rats for a period of 70 days showed a depressive effect on appetite and water intake with resultant poor feed utilization efficiency and mass gain of rats in a dose dependent manner. Plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities were elevated (P<0.05) but histological examinations of liver, heart and lungs of experimental rats revealed no alterations. The extract enhanced sexual interest (libido) of the male rats but did not necessarily improve their fertility rate (King et al., 2006).

2.3 Zinc Zinc essentiality was established in 1869 for plants, in 1934 for experimental animals and in 1961 for humans (King et al., 2006). A syndrome of anemia, hypogonadism and dwarfism was reported in a 21-year-old Iranian farmer in 1961 who was subsisting on a diet of unrefined flat bread, potatoes, and milk (Prasad et al., 1963). Shortly after, a similar syndrome was observed in Egyptian adolescents who had similar dietary history to that of the Iranians, mainly subsisting on bread and beans (Sandstead et al., 1967).

2.3.1 Biochemical and Physiologic Functions: Although, zinc-dependent biochemical mechanisms in physiologic functions have received extensive study, clear relationships have not been fully established. Zinc is ubiquitous within cells in contrast to iron, which is contained in defined cellular components and has defined physiological roles. The role of zinc in biology can be grouped into three general functional classes, namely catalytic, structural and regulatory functions (Cousins et al., 1996). Zinc is released from food as free ions during digestion. These liberated ions may then bind to endogenously secreted ligands before their transport into the enterocytes in the duodenum and jejunum (Turnlund et al., 1984). Specific transport proteins may facilitate the passage of zinc across the cell membrane into the portal circulation. With high intakes, zinc is also absorbed through a passive paracellular route. The portal system carries absorbed zinc directly to the liver, and then released into systemic circulation for delivery to other tissues. About 70% of the zinc in circulation is bound to albumin, and any condition that alters serum albumin concentration can have a secondary effect on serum zinc levels. Although, serum zinc represents only 0.1% of the whole body zinc, the circulating zinc turns over rapidly to meet tissue needs (Tubek, 2007).

2.3.2 Possible Mechanism of action of Zinc as Chemoprophylaxis agent against Novel Covid-19 Diarrhea: Diarrhea is characteristically, although not inevitably, a prominent feature of acrodermatitis enteropathica. (Hambidge, 2001). Plausible explanations for a link between zinc deficiency and diarrhea include impairment of the immune system and of intestinal mucosal cell transport (Ghishan, 1984). A causal relationship between zinc deficiency and diarrhea is indicated by the beneficial effects of zinc supplements and concurrent increase in growth velocity (Brown et al., 1998). Pneumonia: Community zinc supplementation studies in children have demonstrated a substantial and statistically significant reduction in the prevalence of pneumonia in developing countries (Bhutta et al., 1999), this makes its effective in treatment of pneumonia complications which results from Covid-19. Malaria: It is uncertain to what extent oral supplementation with zinc can reduce episodes of malaria in endemic areas. According to some studies, malaria also appears to be reduced by zinc supplementation (Shankar et al., 2000) However, there are studies showing no effect of zinc supplementation against malaria (Veenemans et al., 2011). Further studies are required to establish this effect.

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2.4 Alligator Pepper (Aframomum melegueta) This plant is a member of the ginger family (Zingiberaceae) and is wildly cultivated in tropical areas of Africa, mostly in West Africa. Aframomum melegueta (Grains of Paradise) has names such as grains of paradise, Atare (in Yoruba), chitta (Hausa), is one seed with many healing power and of great benefits to mankind (Figure 3). The seeds of the plant are used to flavor foods and as components of traditional African medicine. Alligator pepper has been reported to have anti-ulcer, anti-microbial, anti-nociceptive, anti-plasmodial, hepatoprotective and anticancer activities (El-Halawany et al., 2014).

Fig. 3: Aframomum melegueta (Alligator pepper) adopted from internet (www.e-time.com)

Traditionally, Aframomum Melegueta is mixed with other herbs for the treatment of common ailments such as body pains, diarrhoea, sore throat, catarrh, congestion and rheumatism in West Africa, Nigeria (Ajaiyeoba and Ekundayo, 1999). Diabetes, a major underlying disease of people afflicted with covid-19 might also be combated by Aframomum melegueta. A myriad of compounds found in Aframomum melegueta such as 6-paradol, 6-shagaol, 6-gingerol, oleanolic acid and acarbose exert an anti-diabetic effect by inhibiting enzymes such as α-amylase and α-glucosidase. These enzymes are responsible for digestion and break down of carbohydrates and polysaccharides from food into simple sugars to increase blood glucose levels. Among the compounds, 6-gingerol and oleanolic acid are more effective in inhibiting the enzymes (Mohammed et al., 2017). Aframomum melegueta is suitable for consumption by diabetic patients; its consumption will help a diabetic patient stay healthy (Venugopal and Liu, 2012).

The ethanolic seed extract and stem bark of Aframomum melegueta contains phytochemicals such as tannins, saponins, flavonoids, steroids, terpernoids, cardiac glycosides and alkaloids that possess antimicrobial and anti-inflammatory effects (Doherty et al., 2010; Okwe, 2005; Okoli et al., 2007). These compounds which are natural antioxidant are believed to scavenge free radicals and offer protections against viruses, allergens, microbes, platelet aggregation, tumors, ulcers and hepatotoxins (chemical liver damage) in the body. To support this claim of anti-inflammatory properties of Aframomum melegueta, Ilic et al. (Ilic et al., 2014) reported that ethanolic Aframomum melegueta extract inhibited cyclooxygenase-2 (COX-2). Compounds that inhibit COX-2 activity are capable of reducing inflammatory responses. The most active COX-2 inhibitory compound in the Aframomum melegueta extract was [6]-paradol, while [6]-shogaol was found to inhibit expression of a pro- inflammatory gene, interleukin-1 beta (IL-1β) (Osuntokun et al., 2017).

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2.5 Turmeric (Curcuma longa) Turmeric (Curcuma longa L.) belongs to the family of ginger (Zingiberaceae) and natively grows in India and Southeast Asia. The plant’s rhizomes contain several secondary metabolites including curcuminoids, sesquiterpenes, and steroids (Omosa et al., 2017), with the curcuminoid curcumin being the principal component of the yellow pigment and the major bioactive substance. It has been used as traditional medicine from ancient time, especially in Asian countries. Plants as a rich source of phytochemicals with different biological activities including antiviral activities are in interest of scientists (Jassim and Naji, 2003). It has been demonstrated that curcumin as a plant derivative has a wide range of antiviral activity against different viruses. Inosine monophosphate dehydrogenase (IMPDH) enzyme due to rate-limiting activity in the de novo synthesis of guanine nucleotides is suggested as a therapeutic target for antiviral and anticancer compounds. Among the 15 different polyphenols, curcumin through inhibitory activity against IMPDH effect in either noncompetitive or competitive manner is suggested as a potent antiviral compound via this process (Dairaku et al., 2010). Furthermore, protein molecules encoded by the SARS-CoV-2 genome are potential targets for chemotherapeutic inhibition of viral infection and its replication. These intriguing targets include the spike protein (S), which mediates the entry of the virus, the SARS-CoV-2 main protease (3CL protease), the NTPase/helicase, the RNA-dependent RNA polymerase, the membrane protein (M) required for virus budding; the envelope protein (E) which plays a role in coronavirus assembly (Stadler et al., 2003; Lai, 2005; Holmes, 2003) and the nucleocapsid phosphoprotein (N) that relates to viral RNA inside the virion and possibly other viral protein-mediated processes (Gallagher and Buchmeier, 2001). With such a drastic increase in molecular and biochemical information about various components of the SARS-CoV-2 and their cellular targets, it is important and timely to again evaluate anti-SARSCoV-2 activities of various turmeric phytocompounds. It is to be noted that in vitro studies have positively demonstrated effective antiviral properties of curcumin against enveloped viruses such as Dengue virus (DENV), influenza virus and emerging arboviruses like the Zika virus (ZIKV) or chikungunya virus (CHIKV) (Chen et al., 2013; Munaya 2013) which are similar to the SARS-CoV-2 an enveloped virus.

2.6 Bitter Leaf (Vernonia amygdalina) Vernonia amygdalina (Del.) commonly called bitter leaf is the most widely cultivated species of the genus Vernonia which has about 1,000 species of shrubs (Munaya 2013). Bitter leaf is a seedless plant, green in colouration with a characteristic odour and bitter taste. It has different names such as ‘Omjunso’ in East Africa especially Tanzania, ‘Ewuro’ in yoruba, Etidot (Ibibio), Ityuna (Tiv), Oriwo (Edo), Chusa-doki Shiwaka (Hausa), and ‘Omubirizi’ in south- western Uganda. Vernonia amygdalina is known as food and medicinal plants used in Asia and Africa (West Africa) due to its pharmacological effects which include antioxidant, anti-inflammatory, anti-diabetes, anticancer, anti-malaria etc. One major properties of considering Vernonia amygdalina in the management of covid-19 is its antioxidants property. Antioxidants inhibit deleterious effects of free radicals that are capable of deteriorating lipid biomembranes in the human body. Researchers in the field of medical sciences have observed free radical scavenging ability and antioxidant property in Vernonia amygdalina. Vernonia amygdalina has been documented to possess antioxidant properties which correlates to its medicinal properties. Antioxidant activities of bioactive compounds isolated from Vernonia amygdalina leaves have been established from various studies (Igile et al., 1994; Farombi and Owoeye, 2011; Ho et al., 2012; Udochukwu et al., 2015). Farombi and Owoeye (Farombi and Owoeye, 2011) observes phytochemicals compounds such as saponins and alkaloids, terpenes, steroids, coumarins, flavonoids, phenolic acids, lignans, xanthones, anthraquinones, edotides, sesquiterpenes extracted and isolated from Vernonia amygdalina to elicit various biological effects in humans including cancer chemoprevention. The chemoprophylaxis properties of Vernonia amygdalina was attributed to their abilities to scavenge free radicals, induce detoxification, inhibit stress response proteins and interfere with DNA binding activities of some transcription factors.

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2.7 Black Seeds (Nigella sativa) Nigella sativa, commonly known as black seed is native to Southern Europe, North Africa and Southwest Asia and it is cultivated in many countries in the world like Middle Eastern Mediterranean region, South Europe, India, Pakistan, Syria, Turkey, Saudi Arabia (Khare, 2004). N. sativa is regarded as a valuable remedy for various ailments, the seeds, oil and extracts have played an important role over the years in ancient Islamic system of herbal medicine. Bukhari reported that Holy Prophet Muhammad (peace be upon him) told “There exists, in the black grains, health care of all the diseases, except death” (Gheznavi et al., 1988). Many studies have been carried out to affirm the acclaimed medicinal properties emphasized on different pharmacological effects of N. sativa seeds such as antioxidant, anti-bacterial, anti-tussive, anti-lipid peroxidative (Hosseinzadeh et al., 2007; Hosseinzadeh et al., 2008), gastroprotective , anti- anxiety (El-Abhar et al., 2003; Bin et al., 2014), anti-inflammatory, anti-cancer, immunomodulatory, anti-tumor properties (Shafi et al., 2009; Salem, 2005; Majdalawieh et al., 2010) and hepatoprotective effect (Khan, 1999).

Fig. 4: Nigella sativa plant and seeds adopted from Sabana et al. (2012)

It should be noted that the seeds of N. sativa are the source of the active ingredients of this plant. Thymoquinone (TQ), dithymquinone (DTQ), which is believed to be nigellone, thymohydroquinone (THQ), and thymol (THY), are considered the main phytochemicals of the seed (Omar et al., 1999). N. sativa seeds (Figure 4) contain other ingredients, including nutritional components such as carbohydrates, fats, vitamins, mineral elements, and proteins, including eight of the nine essential amino acids (Chun et al., 2002; Correa et al., 1986). The potential immunomodulatory and immunotherapeutic potentials of N. sativa seed active ingredients, most especially TQ will show a promising therapy in managing covid-19 virus.

1.8 Ginger (Zingiber Officinale Roscoe) Ginger, with the botanical name Zingiber Officinale Roscoe a commonly used spice and belongs to the family Zingiberaceae (Singh and Singh, 2019). Its local names are Ata-ile, Jinja, and Cithar among the Yoruba, Igbo and Hausa folks of Nigeria respectively (Nwauzoma and Dappa, 2013). Commonly, ginger can be found in subtropical and tropical Asia, Africa, Far East Asia, China, and India (Tanaka et al., 2015). It can be used as a component in curry powder, sauces, ginger bread, and ginger- flavoured carbonated drinks and also in the preparation of dietaries for its aroma and flavour (Durak et al., 2015). Investigations, reveal that ginger possesses several biological properties such as anti- inflammatory and anti-oxidative, antimicrobial, neuroprotective, cardiovascular protective, antidiabetic and anti-nausea, antiemetic activities and chemo-protective effects (Chung, 2019; Beristain-Bauza et al., 2019; Sahin et al., 2019; Ilkhanizadeh et al., 2016; Mele, 2019; Amar et al.,

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2019). Its main bioactive components are 6-gingerol, 6-shogaol which are phenolics, thus accounting for its various bioactivities (Sahardi and Makpol, 2019). Till date, there are no antiviral therapeutics that specifically target human corona viruses, and thus completely eradicating the pandemic. Even though several potential vaccines have been developed, such as recombinant attenuated viruses, live virus vectors, or individual viral proteins expressed from DNA plasmids (Fehr and Pelman, 2015). However, none have been yet approved for use. The limitation with the use of vaccines is a propensity of the viruses to recombine, thereby posing a problem of rendering the vaccine useless and potentially increasing the evolution and diversity of the virus into a more virulent form (Wang et al., 1993). It therefore implies that a preventive approach could be a better option.

2.8.1 Possible Mechanism of action of Ginger against Corona virus Virus–receptor interactions play a key regulatory role in viral host range, tissue tropism, and viral pathogenesis (Maginnis, 2018). Many α-coronaviruses utilize amino-peptidase N (APN) as their receptor (Reguera et al., 2012), SARS-CoV and HCoV-NL63 use angiotensin- converting enzyme 2 (ACE2) as their receptor (Li et al., 2020), MHV enters through CEACAM1 (Li, 2014), and the recently identified MERS-CoV binds to dipeptidyl-peptidase 4 (DPP4) to gain entry into human cells (Raj et al., 2013). Following receptor binding, the viruses then proceeds into the cytosol of the host. A possible mechanism of preventing access of the viruses into the host’s cell could be the inhibition of microbial binding to cellular receptors. In the antimicrobial mechanism of ginger, inhibition of receptor binding has been identified as a major mechanism.

2.8.2 Angiotensin converting enzyme-2 (ACE-2) binding Hitherto, ACE-2 has been associated with an obscure function, not until in recent times with the widespread of the corona virus disease (COVID-19). It is now established as a protein being recognized by various corona viruses to gain entry into hosts cell (Li et al., 2020) suggesting it to be a therapeutic target in the treatment of the disease. We propose that both ACE receptor antagonism and agonism can be an effective mechanism of ginger in its chemopreventive strategy against corona viruses. These claims are supported by a recent report of Cava et al. (Cava et al., 2020), who demonstrated through computational methods that anti-ACE 2 compounds could be effective in blocking the replication of SARS-CoV variant. Moreover, Huentelman et al. (Huentelman et al., 2004) also used docking methods to predict the inhibitory ability of small molecules against ACE 2 enzymes, and possibly inhibiting SARS corona virus S protein mediated cell fusion, and high binding affinity was scored. In addition, different bioactive compounds in ginger have been shown to have different effects on ACE2. One mechanism is through ACE 2 inhibition. A study by Alu’datt et al. (Alu’datt et al., 2016) in the bid to evaluate the anti-hypertensive activity of ginger, demonstrated that its methanolic extract has excellent inhibitory activity on ACE 2 at an extraction temperature and time of 400C and 6 hours respectively. To further corroborate our hypothesis, 3-3’-digallate, a phenolic compound present in ginger was found to interact with ACE2 receptor in a recent computational modelling studies (Zhang et al., 2019). Taken together, we suggest that the intake of ginger, might be beneficial for both prevention and treatment of the pandemic COVID-19 corona virus. Below (Figure 5) is a proposed inhibitory mechanism of action of Ginger against ACE-2 in its chemoprophylaxis strategy.

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Fig. 5: Ginger is able to inhibit ACE-2, thereby preventing the binding of the corona virus to the protein.

1.9 Garlic (Allium sativum L.) Garlic (Allium sativum L.) is a widely consumed spice in the world, and it contains diverse phytochemicals such as organosulfur compounds, saponins, phenolic compounds, and polysaccharides (Diretto et al., 2017; Szychowski et al., 2018; Bradley et al., 2016; Wang et al., 2018). However, its major bioactive compounds (figure 6) are the organosulfur compounds including allicin, alliin, diallyl sulfide, diallyl disulfide, diallyl trisulfide, ajoene, and S-allyl-cysteine (Shang et al., 2019). It has been reported that garlic and its constituents exhibit different bioactivities such as anti-carcinogenic, antioxidant, anti-diabetic, renoprotective, anti-atherosclerotic, antibacterial, antifungal, and antihypertensive activities.

Fig. 6: Structures of some bioactive compounds in garlic excerpted from Shang et al. (2019)

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From the foregoing, worthy of relevance to our subject matter among the bioactivities of garlic is its antiviral properties. We suggest that this could be due in part to its anti-inflammatory and antioxidative abilities. The antiviral potential of garlic extracts has been demonstrated against influenza virus and entero-virus, HIV virus, herpes simplex type 2, dengue virus, Infectious Bronchitis virus, Newcastle Disease virus (Sharma, 2019; Bezerra et al., 2018; Weber et al., 1992; Hall et al., 2016; Shojai et al., 2016; Harazem et al., 2019).

2.9.1 Possible Mechanisms of action of Garlic against Corona virus Major challenges in treating viral diseases are the development of resistance in the virus against the antiviral drugs, due to the high mutation rate of the viral RNA Polymerase (Elena and Sanjuan, 2005) and some of the antiviral drugs can also induce negative side effects in the body (Bindu and Anusha, 2011). Therefore, it is necessary to find alternative therapies in natural plants and their products, out of which garlic stands out significantly, because of its robust pharmacological bioactive components as stated above. Below is a possible mechanism of action of garlic for the prevention and treatment of the human corona virus.

2.9.1.1 Blocking of the attachment of the virus with cell membranes through protein inhibition Following receptor binding, the corona virus then fuses with the cell membrane (Fehr and Perlman, 2015). Coronaviruses are enveloped positive-stranded RNA viruses that replicate in the cytoplasm. To deliver their nucleocapsid into the host cell, they rely on the fusion of their envelope with the host cell membrane, which is mediated by the spike (S) glycoprotein, a class I fusion protein (Sandrine et al., 2012). Inhibition of this protein by peptide inhibitors is an important mechanism of antiviral drugs. These molecules could stabilize the viral envelope protein or alter its conformation, thereby blocking oligomerization or the conformational changes required for fusion (Teissier et al., 2011). Using the S- HR1 and S-HR2 sequence in the protein as a target, Liu et al. (Liu et al., 2009), Lu et al. (Lu et al., 2014) and Xia et al. (Xia et al., 2019) have previously designed and developed several potent fusion inhibitors against the Severe Acute Respiratory Syndrome corona virus (SARS-CoV), the Middle East Respiratory Syndrome (MERS-CoV) and the Human corona virus (H-coV) respectively. Antimicrobial compounds from garlic have been shown to react with viral envelope and inhibit the penetration and exponentiation of influenza virus in animals using hemagglutination (HA), methyl tetrazolium (MTT) cytotoxity assay and RT-PCR (Mehrbod et al., 2013). Interestingly, allicin and quercetin, which are bioactive compounds of garlic were found to exhibit inhibitory action on the COVID-19 Mpro protease, thereby demonstrating similar binding affinity when compared to other potent peptide inhibitors such as Nelfinavir and lopinavir in an in silico study of protein-protein docking (Khaerunnisa et al., 2019). Furthermore, it was demonstrated by Weber et al. (Weber et al., 1992) that treatment of different bioactive components of garlic against different viral strains led to the inhibition of viral adsorption or penetration. Taken together, we suggest that through this mechanism, garlic could prevent the attachment of the corona virus to the host’s cellular machinery.

2.10 Vitamin C (Ascorbic acid) Vitamin C or ascorbic acid (AA), a water-soluble vitamin was first isolated in 1923 by Hungarian biochemist and Nobel laureate Szent-Gyorgyi and synthesized by Howarth and Hirst (Haworth et al., 1933). Humans cannot synthesize ascorbic acid as they lack an enzyme called gulonolactone oxidase. It plays an important role in bone formation, wound healing and the maintenance of healthy gums, metabolic functions including the activation of the B vitamins, folic acid, the conversion of cholesterol to bile acids and the conversion of the amino acid, tryptophan, to the neurotransmitter, serotonin. As an antioxidant that protects body from free radical damage (Chambial et al., 2013).

2.10.1 Therapeutic Roles It is used as therapeutic agent in many diseases and disorders. Vitamin C protects the immune system, reduces the severity of allergic reactions and helps to fight off infections. Large doses of vitamin C have been widely used in the treatment and prevention of a large number of disorders like diabetes, atherosclerosis, common cold, infertility, cataracts, glaucoma, macular degeneration, stroke, heart diseases, neurodegenerative diseases, cancer etc.

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2.10.2 Dietary Sources Vitamin C is commonly found in fruits and vegetables. Fruits containing vitamin C, includes; Guava, red pepper, orange, grape fruit, strawberries, banana, Brussels sprouts, pawpaw, tomatoes, mango etc. (Schlueter et al., 2010). Milk, eggs, cheese, and nuts are also rich sources of vitamin C.

2.10.3 Deficiency Ascorbic acid deficiency gives rise to the appearance of scurvy, which is more common in developed countries. Symptoms develop with plasma levels below 0.15 mg/dL. Scurvy is characterized by the presence of weakness, joint pain or skin lesions in form of petechias, gum bleeding, ease of developing bruises or delay in wound healing. The most characteristic skin manifestations are purpuric perifollicular hyperkeratotic papules and the presence of kinky hair (Valdes, 2006).

2.10.4 Toxicity Vitamin C is generally safe and well tolerated, even in large doses. The IOM set the Tolerable Upper Intake Level for oral vitamin C ingestion at 2 g daily for adults based on gastrointestinal disturbances observed in some individuals at higher doses. High amounts of vitamin C intake have been associated with an increased risk of kidney stones, although the evidence is mixed and inconsistent. The current recommendation is to avoid vitamin C supplementation in those susceptible to kidney stone formation. Vitamin C consumed with iron could increase the risk of iron overload in susceptible individuals. Patients with these conditions should not avoid eating fruit and vegetables but limit their intake of iron instead. Vitamin C has been reported to cause hemolysis in individuals with glucose-6-phosphate dehydrogenase deficiency, but these reports have not been substantiated (Lykkesfeldt et al., 2014).

2.10.5 Possible Mechanisms of action of Vitamin C against Corona virus

2.10.5.1 Improve host’s immune responses to combat diseases Vitamin C (Ascorbic acid) has been reportedly found to exhibit many of its therapeutic functions, partly due to it been able to improve the body’s immune responses through a number of mechanisms. We therefore opine that through this physiological response, it would prove to be effective as a chemo-preventive alternative to antiviral drugs against COVID 19 corona virus. Vitamin C plays important roles in immune function and the modulation of host resistance to infectious agents, reducing the risk, severity, and duration of infectious diseases as supplementation of vitamin C was found to improve components of the human immune system such as antimicrobial and natural killer cell activities, lymphocyte proliferation, chemotaxis, and delayed-type hypersensitivity (Wintergerst et al., 2006). Vitamin C contributes to immune defense by supporting various cellular functions of both the innate and adaptive immune system. It supports epithelial barrier function against pathogens and promotes the oxidant scavenging activity of the skin, thereby potentially protecting against environmental oxidative stress (Lauer et al., 2013; Valacchi et al., 2016) Vitamin C accumulates in phagocytic cells, such as neutrophils, and can enhance chemotaxis, phagocytosis, generation of reactive oxygen species, and ultimately microbial killing (Carr et al., 2017). It is also needed for apoptosis and clearance of the spent neutrophils from sites of infection by macrophages, thereby decreasing necrosis/netosis and potential tissue damage. (Sharma et al., 2004). Based on this established premises, we suggest that Vitamin C consumption can serve as a prophylactic measure against the pandemic. It is therefore necessary that diet formulations with adequate vitamin C supplement should be given more attention by different regulatory agencies in the local and international communities, while the populace should consume more of foods that are rich in this vitamin as we have afore mentioned.

3. Conclusion

Coronavirus is a respiratory viral infection of global health concern because the virus is contagious and may cause life-threatening respiratory infection and severe pneumonia in humans. The

75 pathophysiology of SARS-COV-2 infection, is associated with aggressive inflammatory responses which uncontrolled inflammation inflicts multi-organ damage leading to organ failure, especially of the cardiac, hepatic and renal systems and most patients with this infection who progressed to renal failure eventually death.

In this review, some medicinal foods were elucidated which include ginger, garlic, onion, bitter kola, alligator pepper, black seed, turmeric, bitter leaf, zinc and vitamin C which possess potent pharmacological activities which include anti-inflammatory, anti-viral, anti-pyretic properties, inhibition of viral replication properties against the symptoms displayed by SARS-COV-2 infection. These frugal medicinal foods offer great chemoprophylactic benefits and can play potent roles in the prevention and curtailing of the community spread of COVID-19 as it bolsters immunity and defence of the body system coupled with its cost effectiveness and availability features.

We hereby recommend that further research should be done to evaluate the protective roles of these medicinal foods on COVID-19 infection as well as promote the development of drugs and improved plant medicines as this outcome can prepare the global populace against subsequent global outbreak of viruses.

Acknowledgment(s)

We are grateful to God Almighty and the Chemoprophylaxis team for their input in this work.

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Available online at www.asric.org

ASRIC Journal on Health Sciences 1 (2020) 83-91

a School of Natural Resources, The Copperbelt University, Kitwe, Zambia b Department of Biological Sciences, Egerton University, Egerton, Kenya c Dept. of Applied Community Development Studies, Egerton University Egerton, Kenya

Received 11 February 2020; revised 30 June 2021; accepted 30 July 2021

Abstract

Since the first case of the novel COVID-19 was recorded in Kenya on 13 May, 2020, the increase in positive cases, transformation into community transmission, and emergence of more epicenters, depicts a disconcerting trend despite the multi-phased government-driven mitigations. Hence the urgent need for more robust mechanisms to track and map COVID-19, and design targeted mitigations. Such interventions include GIS- mapping systems coupled with multivariate analysis, to evaluate the internal dynamics based on prevalence, control measures, responses and successes to combat COVID-19. We applied GIS and statistical analyses to map the 100-day disease pattern, outlined country’s preparedness and COVID-19 projections post-100 days. Results indicate an average daily testing capacity of 11% and a corresponding daily detection rate of 7%. Between March-June 2020, the cumulative 122,418 tests reported 4,783 positive cases. The highest figure (2,816) was reported in June against 57,744 tests conducted. These figures represent 0.26% tested and 0.01% positive cases respectively of the country’s population. Nairobi, Mombasa and Busia counties were identified as ‘hot-spots’. Despite the growing pressure to re-open businesses and public facilities due to socioeconomic challenges, the government should carefully review and rely on expert opinion and initiate sector-specific strategies in combating COVID-19 under the ‘new normal’.

Keywords: COVID-19; Community transmission; GIS mapping; Hot-spots; Social distancing; Mitigations; Public-health awareness

1. Introduction

The first case of a pneumonia-like disease of unknown etiology, later identified as the Novel Coronavirus (2019-nCoV) disease, was traced back to Wuhan City in Hubei Province of China on 31st December, 2019. In under 5 days from detection, China had reported 44 case-patients and by 20th January, 2020, the confirmed cases had risen to 278 (WHO, 2020d). The first case of the COVID-19 disease in Africa was reported in Egypt by the country’s Minister of Health and Population from a 33- year old foreign national on 14th February 2020 (Africa CDC, 2020). Since then, all the 54 countries in Africa have recorded surges in active cases, significant recoveries and deaths (UNDP Africa, 2020). As at 20th June, 2020, the cumulative cases and deaths in Africa had reached 216,999 and 4,874 respectively, representing 2.49 and 1.06% of global incidents respectively (WHO, 2020c). In the same period, the proportion of COVID-19 cases and deaths in Europe represented 31and 43% respectively against the global figures (WHO EURO, 2020). The African Union Commission responded to the

1Corresponding author. Email addresses: [email protected] (K.O. Ouma)

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COVID-19 pandemic by collaborating with the Africa Centre for Disease Control (Africa CDC) and the WHO to invest in preparedness and management of COVID-19. Since the first case of the novel COVID-19 was confirmed in Kenya on 13 May, 2020 (MoH, 2020), the government progressively enforced multi-staged initiatives (KNBS, 2020), and as advised by the WHO (2020a), to mitigate the pandemic using “black-box” precautionary-measures (MoH/NERC, 2020c). However, the exponential increase in positive cases (Aluga, 2020), transformed into community transmission, and the emergence of more epicenters depicted a disconcerting trend. This was despite the partial lock-downs in four counties considered as “hot-spots” (MoH/NERC, 2020a), public health awareness campaigns (NERCC and MoH/NERC, 2020) and availability of personal protective and hygiene equipment, such as face masks and hand sanitisers to health care providers (MoH/NERC, 2020b) and the general public. This called for more robust mechanisms to track and map COVID-19 in Kenya, and design adaptive mitigations based on scenario analysis. Such applications include GIS-mapping coupled with multivariate analysis, to evaluate the internal dynamics based on prevalence, control measures, responses and successes towards the “plateauing” the COVID-19 curve. The objective of this study was to employ complementary GIS techniques to map COVID-19 in Kenya to identify patterns, hot-spots and evaluate the effectiveness of the multi-agency approach to combat the pandemic. Similar studies elsewhere have revealed the effectiveness and potential applications of GIS in predicting, preventing and dealing with pandemics (e.g. Datta, 2020; SuperMap, 2020). We hypothesised that GIS-based mapping would enhance the country’s targeted responses and result in increased efficiency in managing the COVID-19 pandemic compared to the “black-box” approach initially adopted. The study also aimed at evaluating the socioeconomic impacts of government interventions during the initial 100 days of COVID-19 in Kenya.

2. Materials and methods

2.1 Description of Study area Kenya is located between 34° E – 42° E and 05° N – 5° S in the Eastern region of sub-Saharan Africa, with 580,876 km2 land area (Fig. 1) occupied by 47.6 million persons. The capital city’s Nairobi County hosts approximately 9.1% (4.4 million) of this population. Administratively, the country is divided into 47 counties spreading across 8 regions; Coast, Western, North-Eastern, Nyanza, Central, Rift Valley, Eastern and Nairobi (KNBS, 2019).

2.2 Data collection and analysis Data collection and verification: The study used data collected between 13th March and 20th June, 2020 from various repositories including the WHO (WHO COVID-19 situation reports), John Hopkins University COVID-19 Resource Center (JHU COVID-19 RS), UNDP Africa (UNDP Africa situation reports), Africa CDC (Africa CDC COVID-19 Dash board) and Global COVID-19 watch platforms (e.g. worldometers, Corona Tracker). At the national level, multiple online such as the Ministry of Health Kenya website (COVID-19 situation reports) and press releases (MoH daily briefs), the National Emergency Response Committee (NERC) on COVID-19 updates (NERC on COVID-19), the Kenya National Bureau of Statistics (2019-KPHC Vol 1), independent citizens observatories, media-houses, and social media platforms (e.g. MOH Kenya twitter page) were accessed. Desktop studies: The relevant data and information from these sources was collated, cross-checked and cross-compared for similarity (Pickvance, 2005) to ensure accuracy of data used for GIS-mapping, statistical and trend analyses and reporting. GIS data and mapping: The cumulative confirmed cases by county was used to generate the 100th- day COVID-19 spectral map of Kenya and classified based on the “no-case” to “hotspot” level using QGIS software (QGIS.org, 2020). A similar classification scheme was followed to identify, map and monitor the three most impacted counties, from 01 May, 2020, the start of county-based COVID-19 reporting by the National Emergency Response Committee on COVID-19 to 20 June, 2020, which marked day 100 of the disease surveillance period in Kenya. Data analysis: Descriptive analysis was conducted to evaluate testing capacity, identify trends and projections of COVID-19 pandemic in the initial 100-day period. The trend and exponential behaviour of the confirmed cases was visualized to depict the likely scenario post-100 days in the country. The

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GIS outputs for the three “hot-spot” counties were also studied to give a reflection of the “hot-spot” transition pattern in counties susceptible to exponential increase in COVID-19 cases based on either their proximity to border entry/exit points or neighbouring hot-spots areas within the country.

Fig. 1: A spectral map Kenya showing the cumulative county-wise cumulative distribution of confirmed COVID-19 cases across the 47 counties as at 20 June, 2020 (day 100).

3. Results and Discussion

3.1 The COVID-19 patterns and projections Based on the data collected and verified, statistical analyses revealed an almost similar and predictable pattern on the occurrence of COVID-19 in the country compared to previously reported cases globally. There was a relatively flat and slow rise in confirmed daily cases in the first 28-35 days possibly dues to the low testing capacity, quarantine enforcement on immigrants over March-April, 2020 period. The next 21 days in May, 2020 were characterized by an exponential increase in confirmed daily cases perhaps due to increased interaction with persons and facilities handling COVID-19 and transformation into community transmission of the disease (Fig. 2). The increase confirms the assertions in a previous study on the COVID-19 situation in Kenya (Aluga, 2020). The government had also upscaled the daily screening and contact-tracing capacity compared to the previous period (Fig. 3a) and which corresponded with the numbers of confirmed COVID-19 patients in the country. For instance, in June 2020, the 57,744 tests also produced the highest number of positive cases. However, April 2020 recorded the highest percent rise in testing and confirmed case scenarios of 2,142 and 471% respectively (Fig 3c). This improvement coincided with the acquisition of testing kits, personal protective equipment (PPE), trained personnel and laboratory facilities by the government. April, 2020 also marked start of the rising phase of the exponential COVID-19 curve in Kenya. The numerous public awareness campaigns by the government agencies and the private sector organisations, coupled with the free mass-testing of the public may also have contributed to the increased number of tests between April and June, 2020. Generally, during the initial 100-day period, a total of 122,418 persons (0.26% of total population) had been tested for the SARS-nCOV-2 virus (Fig. 3a). Respectively, 4,783 were confirmed positive for COVID-19 (Fig. 3b). The average testing

85 capacity through the period stood at 11% (1,224 tests per day) with an approximately 7% (47 persons) daily increase in the number of confirmed cases. In Figure 4, the cumulative cases of positive patients observed in figure 3b over the 100-days depicted a trend which also corresponded to the exponential equation y=13.31exp0.0645x, where y is the cumulative number of positive COVID-19 cases and x the day from the first detection. If the hypothetical situation remains, then for instance, on day 150, the total positive cases will be expected to reach 211,825 and 5,328,156 by the 200th day, unless targeted interventions and other natural factors come into play to flatten the curve. However, the trend and projections in figure 4 may only be a rough indicator of the potential prevalence of COVID-19 in the country since the results represent a dismal 0.26% of Kenya’s 47.6 million persons.

6000

5000

Tested +ve cases

4000

3651 3000 329134033365 3255 3102 3077 3177 3167 29592892 3043 27112831 2833 2820 26212567 2640 2518 2000 2293 22732419 210021002198 2112 2247 Test & Postive Postive & Test cases 1933 16111516 15741518 1000 1330 1434 1486 1195 1139 1108 1096 946 101210771075 922 1056 978 7481 69172 234 380662 362 372 530 696 305 308504 491 766 674 694 803 704 450 545668 589508777 883 581 841 0 13 16 19 22 25 28 31 03 06 09 12 15 18 21 24 27 30 03 06 09 12 15 18 21 24 27 30 02 05 08 11 14 17 20 Mar/2020 Apr/2020 May/2020 Jun/2020 Date

Fig. 2: The trend of daily COVID-19 tests and confirmed cases in Kenya during the initial 100-day (13 March - 20 June, 2020) monitoring period.

(a) (b)

(c) 2,132 2,000 %change-tests %change +ve cases

1,500

1,000 Percent 471 366 500 255 - - 16 79 - Mar-20 Apr-20 May-20 Jun-20 Month

Fig. 3: Figures (a)-(c) showing the transformation in the testing and detection capacity during the 100-day COVID-19 pandemic in Kenya. Figure (d) gives the exponential increase in the cumulative positive cases over the same period.

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8,000 y = 13.31e0.0645x ; R² = 0.8898 Total +ve Expon. ( Total +ve )

6,000

4,000 Positive cases Positive

2,000

- 0 20 40 60 80 100 No. of days since case 1

Fig. 4: The cumulative number of confirmed COVID-19 cases and the corresponding exponential increase in Kenya in the initial 100-day (13th March-20th June 2020) surveillance period.

3.2 Hot-spot detection and mapping According to the MoH/NERC (2020b) April 01, 2020 report, there was cumulative 81 COVID-19 cases since 13 March, 2020 while 1,675 contacts were under surveillance. The disease had unpredictably spread to eight counties some of which were likely to hot-spots. Figure 5 shows the changing patterns of COVID-19 for three counties with the highest reported cases considered over May-June 2020 COVID-19 surveillance period. Nairobi and Mombasa counties are the two major international flights entry-exit points while Busia county’s proximity to Uganda is a key entry-exit point via road. In the first 15 days (May 1-15) of the county-level COVID-19 surveillance (Figure 5a), Nairobi county recorded over 800 confirmed cases although Mombasa county was quickly drawing concern to the NERC/MoH team with a rapid increase in confirmed cases up to 575. The border county of Busia had the lowest figure of 288 cases possibly due to the lock-downs and travel restriction enforced by the government in the first two counties during the 100-days phase. The cases in Busia could have arisen from authorised movement of persons providing essential services during the lock-downs or cross-border contacts. In the 16th-31st May, 2020 phase of the monitoring (Figure 5b), the cumulative COVID-19 cases were relatively lower in all the three counties. Nairobi and Mombasa counties fell within the 103-153 range while Busia county recorded positive cases below the 100 mark. A plausible explanation for this trend could be the upscaled containment measures given that the COVID-19 disease pattern was getting more understood over time. The increased public awareness campaigns, changes in social behaviour of the citizenry and cessation of travels into and within the country. In general, the 100-day scenario mapping isolated the three counties as hot-spots with positive COVID-19 cases between 1275 and 2272 (Figure 1). The implication of the trend is evidenced in the gradual rise in cases in neighbouring counties of the three epicenters. For instance, from the same classification scheme in figure 1, the three counties (Kajiado, Kiambu and Machakos) bordering Nairobi city county Central Kenya recorded extremely high cumulative number of COVID-19 cases between 22-177. Furthermore, Kilifi and Kwale counties, neighbouring Mombasa county, also reported positive COVID-19 cases of up to 60, classified as high, in the same time-frame. This brings to light the essence of counties instituting mitigations to manage the imminent spread of COVID-19 in the event the travel restrictions and lock-downs in the hot-spot counties are eventually lifted. Such mitigations include highly efficient surveillance and contract-tracing systems as reiterated by the WHO that will enhance the control of the spread of the disease (WHO, 2020a). As suggested by

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Smith (2020b), information about the pandemic will be crucial in preparing countries to better manage COVID-19 and reduce transmission by creating informed public communications and education strategies.

(a) 1-15 May, 2020

(b) 16th – 31st May, 2020

(c) 1st – 20th June, 2020 Fig. 5: Spectral maps for the three hot-spot counties in Kenya (Nairobi, Mombasa and Busia) for three time- steps, (a) 1st-15th May 2020, (b) 16th-31st May 2020, and (c) 1st-20th June, 2020, as observed during the 100- day monitoring period based on the disaggregated county-based statistics by the country’s Ministry of Health.

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3.3 Sectoral pressures: Social and economic dynamics Since the first reported case of COVID-19 in Africa, governments all over the continent have taken different approaches in implementing a raft of measures to curb the spread of the disease within their borders (Deloitte, 2020). In Kenya, among the measures taken include quarantines, curfews, full or partial lockdowns, and social distancing in areas where contact is common such as shopping places, eateries, transport vehicles, and markets. These restrictions have also affected social gatherings such as church services, family gatherings, weddings, parties and funerals. A total shut down of learning institutions due to concerns about ability to control movement and contagion has also brought physical learning to a screeching halt. Directives on wearing of masks in public always, handwashing and regular use of sanitizers also changed aspects of social behaviour for many. Eateries and bars allowed to offer take out services only were subjected to stringent hygiene and distancing certifications in order to stay open (Deloitte, 2020).

3.3.1 Commerce and Industry The ban on international and local air travel, partial lockdowns and social distancing measures have seen many people forced to take unpaid leave. Disruptions in foreign trade has caused huge losses in some sectors and driven others to near collapse. The flower, vegetable and fruit industries in Kenya, livestock producers and exporters, and poultry farmers are experiencing loss of income and face imminent collapse. International and local leisure as well as conference tourism has also suffered due to travel bans and social distancing rules. Many employees have taken pay cuts due to revenue losses across the economic sector (Deloitte, 2020). The pandemic has also hit the region at a time when agriculture is already facing challenges dealing with desert locust invasion which has compromised food security in some places. The impact on agriculture may not be felt as immediately as on other sectors since rural areas were not as badly hit as urban areas where food is still available due to recent harvests. However, industries supported by agriculture and economies that rely heavily on food imports will suffer should the prevailing situation remain. The threat to food security could increase if production suffers due to changes in production rules. In Kenya, a survey conducted between May and June, 2020 indicated that nearly 78.8% of the households experienced increase in food prices due to shortages caused by the COVID-19 situation in the country (KNBS, 2020). In response, nearly 42% of households had reduced expenditure on non- essential items or services while 21.6% were mainly worried about food security which also negatively impacted trading and business activities (KNBS, 2020). In order to cushion businesses and individuals from the COVID-19 onslaught, the Kenyan government instituted tax based and fiscal measures as follows (PSCU, 2020): Reduction of the turnover tax rate from the current 3% to 1% for all Micro, Small and Medium Enterprises (MSMEs); reduction of VAT to 14% from 16% and disbursement of accumulated VAT refunds of KES 10 billion; a 100% tax relief for persons earning up to KES 24,000 monthly; reduction of the highest income tax band from 30% to 25%; reduction of corporate rate tax from 30% to 25%; reduction of the Central Bank of Kenya lending rate from 7.25% to 7%; increased maximum tenure for repurchase agreements; lowered cash reserve ratio for banks; flexibility in loan provisioning requirements for performing loans; appropriated KES 10 bn in cash transfers to the elderly, orphans and other vulnerable groups; and a 20-80% voluntary salary reduction for senior government officials. These targeted interventions were to cushion Kenyans against the socioeconomic impacts of the COVID-19 pandemic.

3.3.2 Education, science and technology Owing to closure of all learning institutions in Kenya, there have been negative impacts on education such as exposure to undernutrition for learners who come from schools where meals are offered free of charge. There has also a lag in learning outcomes for those in remote areas or areas where access to electricity or internet is constrained a well as those with low initial digital skills (Areba, 2020). Moreso, students are anxious, especially those at the terminal stages and expect undertake various forms of summative evaluation (UNESCO and IESALC, 2020). About 17% of households with students reported challenges in accessing distance or self-learning during the pandemic (KNBS, 2020). Cases of bad behaviour such as substance abuse and involvement in sex are on the rise with concern being voiced over the high numbers of teenage pregnancies. Child abuse,

89 gender based and domestic violence is also on the rise (KNBS, 2020). Students studying abroad were either forced to return home and have not resumed their studies or were stuck abroad where they underwent difficult conditions. Returned students are facing psychological insecurity which may cause them to resign from their studies or facing cancellations of their scholarships due to economic impacts of the pandemic on the countries offering them (UNESCO and IESALC, 2020). To date, the re- opening of learning institutions in the country is uncertain. The KNUT/UASU/KHRC (2020) evaluation report recommend an “inclusive and comprehensive data-driven process of ascertaining how schools, teachers, non-teaching staff, students and communities are coping with closures and the pandemic”. Further suggested in the report is that resumption of learning should largely be determined by the status and evolution of the pandemic, and as advised by the Ministry of Health in Kenya.

Health and psychosocial aspects Sub-Saharan Africa is characterized by high poverty, weak institutions, armed conflict and crowding in urban areas (WFP, 2020). The resultant conditions are those of undernutrition, low literacy levels, adverse underlying health conditions and poor access to services. These have been exacerbated by lockdown measures instituted to curb the COVID-19 pandemic causing disruptions to food, water and medication access. Dense populations in urban areas where the pandemic first entered these economies has had adverse effects on mitigation measures (Smith, 2020a), especially in informal settlements where WASH is a chronic challenge. Adopting some of the measures such as hand washing, work from home orders and social distancing rules has proved impossible due to lack of access to clean water, the nature of their employment (casual/low skilled labour and petty trade) and size and distribution of dwellings. Closure of eateries, micro and small enterprises and entertainment places has led to job losses for these populations. Reduced spending power may mean nutritional insecurity for many Kenyans. In case of infection, this increases the risk of poor outcomes as it compromises the immune system of the individual.

4. Conclusion

Evidence from the 100-day scenario shows the current and projected negative economic, social and health impacts of COVID-19 in Kenya. The exponential pattern of the disease warrants proactive multi-targeted measures and more ‘accurate’ responses to flatten the COVID-19 curve. The supportive role of GIS in monitoring and management of the COVID-19 pandemic in Kenya is viable in to enhance targeted and timely cross-sectoral interventions. The government should priorities expert- based knowledge, including multivariate and geospatial analysis, during decision-making for increased effectiveness in combating this pandemic. This will minimize the negative economic impacts on human and capital resource use, and restore normalcy in the shortest reasonable time under the ‘new normal’.

Acknowledgement

The authors wish to acknowledge the respective public and private institutions for providing online, the relevant reference datasets and information during manuscript preparation. We also acknowledge the invaluable contribution from the anonymous reviewers of the manuscript.

References

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