Central Annals of Public Health and Research

Research article *Corresponding author Noumedem Anangmo Christelle Nadia, Department of Microbiology, Haematology and Immunology, Faculty Comparative Study of Malaria of Medicine and Pharmaceutical Sciences, University of , P.O. Box 96, Dschang, , Tel: + 237675921280 ; Email : [email protected] Infections and Associated Risk Submitted: 19 June 2020 Accepted: 25 August 2020 Published: 27 August 2020 Factors among Pregnant and Non- Copyright © 2020 Azizi MA, et al. Pregnant Women in the Town OPEN ACCESS

Keywords of Foumbot, Western Region - • Malaria infections • Risk factors Cameroon • Comparative study Mounvera Abdel Azizi1, Noumedem Anangmo Christelle Nadia2*, Yamssi cédric3, Sop Foka Eric Igor1, Ngongang Ouankou Christian4, Simeni Raoul4, Tsila Henri Gabriel1 and Mpoame Mbida1 1Department of Animal Biology, University of Dschang, Cameroon 2Department of Microbiology, Haematology and Immunology, University of Dschang, Cameroon 3Department of Biomedical Sciences, University of Bamenda, Cameroon. 4Department of Internal Medicine and Specialties, University of Dschang, Cameroon

Abstract Background: Malaria is a major public health problem in Cameroon and is the leading cause of morbidity and mortality. This work aimed to assess the malaria situation and associated risk factors among pregnant and non-pregnant women in the town of Foumbot. Methods: This was a cross-sectional study and was carried out in Foumbot sub-Division among pregnant and non-pregnant women coming for ANC and consultation respectively in three selected Health facilities. The sample size required for this study was 180 approximately for each group studied that is pregnant and non-pregnant women and a total of 400 women were recruited for the study. Blood samples of the participants were collected by finger prick for the preparation of thick blood smear and Rapid Diagnostic Test (RDTs). Results: Out of 400 women examined, 108 were infected with the prevalence of 27%. The prevalence was 33.16% and 20.7% in pregnant and non- pregnant women respectively. The rates of malaria infection according to parity were 58.3% 33.3% 29.9% respectively for secundigravidae, primigravidae and multigravidae. According to the place of residence, the prevalence was 46.29% and 19.7% (rural area); 15.75% and 11.11% (urban area) for pregnant and non-pregnant women respectively. Based occupations, the rate of infection were 24.07% and 8.33% (unemployed) among pregnant and non-pregnant women respectively. Measuring the sensitivity and specificity of the diagnostic tool used for this study, Rapid Diagnostic Test was found to have sensitivity of 92.6% and specificity of 99.3%. Regarding predictive values, this study revealed 8 cases of false positive and 2 cases of false negative. Conclusion: The prevalence of infection has not change apart from some false negative and false pasitive recorded. The study also demonstrated that malaria infection associated with pregnancy shows normal symptoms but can also characterized by absence of fever which is the main characteristic of malaria infection. As malaria infection affects the entire immune system, it becomes necessary to integrate antimalarial medication into the management of pregnancy. This will help prevent pregnant and non-pregnant women from running the risk of high parasitaemia and therefore the risk of miss carriage.

INTRODUCTION 216 million clinical infection and 655,000 deaths in 2010 [2] and it remains the most important infection with nearly 81% of Malaria is an infectious disease, transmitted by female cases recorded in Africa. The Population at high risk of infection Anopheles mosquito. It is a febrile and hemolytic erythrocytopathy caused by a protozoan of the genus Plasmodium that infects alternately human and mosquitoes. Plasmodium falciparum, is Children under five years and pregnant women. Sub-Saharan which is the most deadly species of malaria infection and, is women each year and according to the World Health Organization Africa harbors about twenty-five million infected pregnant mainly transmitted in sub-Saharan Africa by Anopheles gambiae (WHO), malaria accounts for more than 10,000 maternal deaths and Anopheles funestus [1]. This diseases account for more than and 200,000 neonatal deaths per year [3].

Cite this article: Azizi MA, Christelle Nadia NA, Cédric Y, Eric Igor SF, Christian NO, et al. (2020) Comparative Study of Malaria Infections and Associated Risk Factors among Pregnant and Non-Pregnant Women in the Town of Foumbot, Western Region - Cameroon. Ann Public Health Res 7(2): 1094. Azizi MA, et al. (2020)

10°45’ east. Foumbot is located in the so-called tropical Sudano- the outbreak of malaria infection. Malaria is a major public health Guinean climatic region characteristic of the whole western problem.Cameroon It is is the located leading in an cause epidemiological of morbidity zone in conducive the country. to region. This climate has two seasons: a rainy season from mid- Although there are few areas where malaria is still hyper-endemic to mid-March. March to mid-November and a dry season from mid-November in(especially people’s in lifestyle, forest areas), sanitation the measureslevel of malaria and greater endemicity access has to Sampling method stabilized and has become meso-endemic due to improvements The study was conducted between February and April 2019 and concerned mostly pregnant and non-pregnant women who inhealth Cameroon services. in In 2010, urban indicates areas, malaria that malaria infection is isresponsible hypoendemic. for: 35-40%The declaration of total ofdeaths the national in hospital politic facilities; for the 50%fight againstof morbidity malaria in children under 5 years of age; 40-45% of medical consultations; received prenatal and curative consultations respectively in Bonnethe three Samaritaine. selected HealthThe sample facilities: size Foumbotneeded for District this study Hospital, was and 40% of annual household expenditure on health. Protestant Hospital of Baïgom and a Private Hospital called 30% of hospitalizations; 57% of hospital days; 26% of sick leave and the estimated sample size for each group studied was approximatelycalculated according 198 and to a the total formula number put 400 in pregnant place by and LORENZ non- are particularly susceptibility to P. falciparum infection. This Pregnant women living in areas where malaria is endemic pregnant women were recruited for the study. abortion, increased perinatal mortality and reduced birthweight. susceptibility is commonly associated with premature delivery, Z2. P . q 1.9622 × 0.5 × 0.4 n≥ n = I 2 0.052 pregnancyPregnancy makes causes women several more physiological susceptible changesto malaria that infection make women more vulnerable, by weakening the immune system, Inclusion and Exclusion Criteria addition, infected erythrocytes of P. falciparum can be secreted and increases their risk of illness, severe anaemia and death. In Inclusion criteria: Only pregnant and non-pregnant women age between 14-45years and accepted to sign the free informed placenta from ensuring its function appropriately [4]. into the intravillus spaces of the placenta, thus preventing the consent form were included in the study. In Cameroon, as in most countries south of the Sahara, malaria Exclusion criteria: Was excluded those who do not belong is a public health problem. The disease is endemic, mainly caused to this age group and those that refused to sign the informed by Plasmodium falciparum consent form. Also those that were under treatment with anti- , and transmission is high [5]. However, malaria medications were equally excluded. the problem link to the coverage after free insecticide-treated net Data collection plan distribution interventions and its use among women persists [6]. The failure to reduce malaria morbidity and mortality levels can be explained firstly by a gap between official recommendations Data collection was conducted over the period from March to and the therapeutic practices of the population, i.e. the low level addressed to pregnant and non-pregnant women. The information April 2019. Data was collected using a structured questionnaire of adherence by the population to preventive and curative control protocols. Malaria control programs have paid little attention to that lack of attention to socio-cultural factors has been the main was obtained through interview by the principal investigator. social, behavioural and economic factors: “there is consensus reasons for the failure of early malaria control programmes” After signing the informed consent form, the participants gave a [7]. The dramatic increase in malaria morbidity and mortality drop of blood obtained through finger prick for the determination can be partly explained by the lack of consideration of social of malaria parasite. Then the Rapid Diagnostic TestP. falciparum(RDT) test. used in this work was SD BIOLINE Malaria which detects the work aimed to assess the malaria situation and associated risk histidine rich protein II (HPR-II) antigen specific to factorsand behavioural among pregnant aspects and in thenon-pregnant fight for malaria women control. in the town This malariaThe choice infections of this are test due can this be malaria justified parasite by the [8]. epidemiological Thus the thick profile of the disease. Indeed, in Cameroon, 98% of recorded intensity of malaria among pregnant and non-pregnant women of Foumbot. More specifically, to determine the prevalence and malaria infection. blood smear was used for the microscopic and quantification of compared to microscopy in the diagnosis of the disease and to Parasitological test determineliving in the the town factors of Foumbot that promote ;to assess malaria the reliabilitytransmission of the in eachRDT group of women in the town of Foumbot. MATERIALS AND METHODS The Rapid Diagnostic Test (RDT) was taken out of its pouch alcoholand placed swab on anda flat, pricked dry surface. on the The side test with device a sterilewas labeled single-use with Study site the patient’s code. The patient’s fingertip was cleaned with the

bloodlancet collected provided was in thethen kit transferred using a capillary to the round pipette sample or a single-well. 4 The study was conducted in Foumbot sub-Division found in use collection handle (5µl) provided, blood was drawn. The total Division, of Cameroon and is located 25km result was interpreted within a minimum of 15 minutes (within betweenfrom the Regional Latitude and 5°10’ 48km and from 5°35’ the then Longitude town. 10°30’ It occupies and 30drops minutes of diluent maximum): were added vertically to the square test well. The a surface area of about 579km². It is half the alluvial plain of Noun

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-The presence of a single colored band (“C” Control Line) in with an overall prevalence of 27%. Among non-pregnant women, the -Tresult window indicates a negative result. 198 were examined and 41 positive cases were recorded giving an infection prevalence of 20.7%. Among the 202 pregnant he presence of two colored bands (“P. f” Test Line and “C” (p<0.05) (Figure 1). regardless of the order in which the bands appear. The test is women, we registered a prevalence of infection of 33.16% Control Line) in the result window indicates a positive result, Prevalence of malaria with respect to parity (pregnant women) considered positive even if the test line is pale/fine. If the control reanalyzedstrip (Control using Line a new“C”) kit.does not appear in the results window, Table 1 shows the distribution according to parity, with the result is reported as invalid. In the latter case, the sample is The thick drop was used for the microscopic and parasitological diagnosis of malaria. The technique was performed as follows: a slight fluctuation in the proportion between primigravida, secongravida and multigestation. Despite this slight difference therePrevalence is no significant of malaria difference with (p>0.05). respect to marital status The identification number was marked on each slide. The third finger of the left hand was disinfected with an alcohol swab, free of any inflammation. The excess alcohol was wiped off with pregnantTable 2 women. shows that There single is therefore and married a relationship women have between 8.33% dry cotton wool. The disinfected part of the finger pulp was plasmodiumand 53.70% prevalenceinfection and compared marital to status single in and pregnant married women non- centrepricked of with a blade. a sterile Using vaccinostyle. the angle of anotherThe first blade, drop we of proceededblood was removed with dry cotton wool. The second drop was placed in the was spread in a circle of about one centimeters in diameter. The (p<0.05). Likewise in non-pregnant women, there is a significant markedto mechanical blades defibrination were placed by in acollection circular motion boxes forso that drying, the bloodaway fluctuation between single and married women. This distribution allows us to say that the prevalence is significant (p<0.05): pregnant women without employees were fromThe flies single-time and dust. (30 minutes) Giemsa 3% staining technique was chosen. After drying, the slides were arranged one by one the majority in our sample, with a prevalence of 24.07%, followed in a staining tray. The Giemsa solution was poured into the tray, taking care to immerse all the slides. The thin discolouring film theywas removed were exposed with buffered to the rack water for drying.(pH=7.2). The slides were then rinsed with tap water and the tank was moved slightly. Finally,

The stained, dried slides were examined under a 100 objective Baigom.microscope (100 x immersion objective) in the laboratory of the District Hospital of Foumbot and the Protestant Hospital of Data Management and Statistical analysis analyzed using Statistical Packages for Social Science (SPSS) software.The data The tests collected used were were the entered Chi square into and Excel the Fisher 2010 andtest when the theoretical numbers are below 5. The different tests above were used to evaluate the parameters sought such as the Figure 1 prevalence according to age, religion, ethnicity was made by the Overall prevalence with respect to status. use of the Chi square in a 95% confidence interval. The DUNCAN Table 1: test was used to check for significant differences between these Parity Pregnant X² P bothdifferent types parameters of analyses andwas thetested KRUSKAL at 5%. In WALLIS this work test we was included used Prevalence of malaria with respect to parity. Primigeste 20 (33,3%) 4,33 0,11 400to determine women in the consultation, intensities. randomlyThe statistical assigned. confidence The age level of thefor participants ranged from 14-45 years, with the mean age among Secondhand 7 (58,3%) pregnant women being 25.14 ± 5.81 and among non-pregnant Multigeste 40 (29,9%) women being 29.22 ± 8.27. Pregnant and non-pregnant women representing 61.40% and 53.5% were Muslim, 46.5% and 37.6% Table 2: Status RESULTS Prevalence of malaria with respect to marital status. were Christian, and 1% and 0% were of other faiths, respectively. Marital status pregnant Not pregnant X P Overall prevalence Single 9(8,33%) 6(5,55%) 3,7 0,04 The study was carried out on a sample size of 400 women Married 58(53,70%) 35(32,40%)

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Table 5: by business- women with a prevalence of 15.74%, pregnant Prevalence of malaria accordingStatus to ethnicity. farmers with a prevalence of 14.81%, pregnant employed Ethnic Groups pregnant Not pregnant X2 P women with a prevalence of 5.55% and pregnant students with Bamiléké 23(34,32%) 9(21,95%) 5,63 0,06 a prevalence of 1.85%. In contrast to non-pregnant women, who 6.48%, farmers 19.44%, employed 2.77%, and students 0.92%, Bamoum 37(55,22%) 26(63,41%) have a prevalence of 8.3% among unemployed women, Business Others 7(10,44%) 6(14,63%) respectivelyPrevalence as of it malariacan be seen infections on table 3. by grade level Table 6:

Table 4 shows that the prevalence of malaria among Prevalence of malaria Statusaccording to hospitals. pregnant women in primary, secondary and university education Location Pregnant Non pregnant X2 P is 25%, 36.11% and 0.92%, respectively, while among non- BS 5(7,46%) 10(24,39%) 2,97 0,22 pregnant women, for the same levels of schooling, we obtained 51(76,11%) 16(39,02%) 24%, 13.88% and 0%, respectively. However, we note that the prevalence of pregnant women at the secondary level is double HDFHPB 11(16,41%) 15(36,58%) that of non-pregnant women (p>0.05). There is a relationship betweenPrevalence the level of malaria of education infections and malaria according infection. to ethnic groups non-pregnant women have the following prevalence 31.5% and 18.52% respectively. Among Christian women, they are 29.62% and non-pregnant women. It appears from this table that and 19.44% respectively. Prevalence does not differ according to pregnantTable 5 and presents non-pregnant the prevalence Bamoum by ethnicity women among were thepregnant most religionPrevalence (P>0.05 of malaria Infections according to the Place of Residence infected with prevalence of 55.22% (Pregnant) and 63.44% (Non - pregnant). Although there is a slight fluctuation between the in rural areas is 49.29% and in urban areas 15.75%; among non-pregnantprevalence among Bamileke pregnant and andother non-pregnant women, there Bamoun is also women, a large Table 8 shows that the prevalence among pregnant women it does not vary according to ethnicity (p>0.05). In pregnant and non-pregnant women living in rural and urban areas it is 19.7 Prevalence of malaria infections according to women’s residence (p<0.05). fluctuation but does not vary by ethnicity (p>0.05). % and 11.11% respectively. This prevalence varies according to hospitals Prevalence of malaria infections according to age group

Table 6 shows a significant fluctuation by the site. For example, among pregnant women at the Foumbot District The table 9 below shows the prevalence of malaria by age Hospital, the prevalence rate is 47.22%. This prevalence varies significantlyPrevalence depending of malaria on infectionsthe site (p>0.05). according to religion group. Plasmodial infection varies little with age in non-pregnant pregnantwomen as andopposed non-pregnant to pregnant women women. with We rates have of found 38.50% that andthe 21-27 age groups seem to have the highest prevalence in both pregnant women by religion. It shows that Muslim pregnant and Table 7 shows the prevalence among pregnant and non- 20.80% respectively. In contrast, among non-pregnant women, Table 3: the 28-34 age groups had the lowest prevalence, which was 7.50%. However, the difference was not significant across age Prevalence of malaria byStatus occupation. groups in both pregnant (p>0.05) and non-pregnant women Occupation pregnant Not pregnant X2 P (p>0.05Prevalence of plasmodial infections as a function of Business 17(15,74%) 7(6,48%) 14,24 0,002 sleeping time (bed time) Grower 16(14,81%) 21(19,44%) 6(5,55%) 3(2,77%) We will first note that 74.5% of the women surveyed said EmployedStudent 2(1,85%) 1(0,92%) which 68.9% actually use it. Usual bedtime and the risk of the Unemployed 26(24,07%) 9(8,33%) occurrencethey had received of plasmodial an insecticide-treated infections were assessedmosquito and net, the of

of plasmodial infections is always higher among pregnant and Table 4: non-pregnantresults are presented women in going Table to 10. bed We after found 10 that p.m. the with prevalence rates of Prevalence of malaria accordingStatus to the level of education. Level of study Pregnant Not pregnant X2 P pregnant women going to bed before 10 p.m. with rates of 36% and 48% respectively, while among pregnant and non- Primary 27(25%) 26(24%) 12,11 0,002 Secondary 39(36,11%) 15(13,88%) 32.8% and 16.8% respectively. Bedtime significantly affected 1(0,92%) 0(0%) the prevalence of plasmodial infections in non-pregnant women (p˂0, 05). However, in pregnant women, the difference was not University significant (p>0.05), ddl=1 Ann Public Health Res 7(2): 1094 (2020) 4/9 Azizi MA, et al. (2020)

the infection is higher in pregnant women than in non-pregnant Table 7: women (p<0.05). Prevalence of malaria Statusby religion. Religion Pregnant Not pregnant X2 P Average intensity of plasmodial infection according Christian 32(29,62%) 21(19,44%) 3,74 0,15 to the place of residence Muslim 4(31,5%) 20(18,52%) Figure 4 shows the distribution of the intensity of plasmodial Other 1(0,92%) 0(0%) infection according to the place of residence. It shows that the mean intensity of infection in pregnant and non-pregnant women

Table 8: of residence. varies little according to residence (p>0.05). It is slightly higher Prevalence of malaria the population according to the place women. Status in pregnant women living in rural areas than in non-pregnant Residence Pregnant Not pregnant X2 P Average intensity of plasmodial infection according 50(74,62%) 29(70,73%) 26,5 0,0 to the level of study

UrbanRural 17(25,37%) 12(29,26%)

Figure 5 gives us the distribution of the intensity of the Table 9: plasmodial infection as a function of the level of study. It shows Status was recorded in pregnant women and none in non-pregnant Prevalence of malaria the population by age group. that except for the university level where a very high intensity Age range Pregnant Not pregnant between pregnant and non-pregnant women according to the 14-20 53(26,2%) 27(13,6%) women (p<0.05), the average intensity of infection varies little 21-27 78(38,6%) 72(36,4%) 28-34 54(26,7%) 53(26,8%) level of study (Primary & Secondary). Table 10: 17(8,4%) 46(23,2%) time). Population prevalence of malaria with respect to sleeping time (bed ≤ 35 Result GE Prevalence of malaria infections according to waking Status Hours Negative Positive Total X² P hours Before 10 pm 144(83,26) 29(16,8) 173(100) 12,98 0,00 N.pregnant Usual wake-up times and the risk of the occurrence of After 10 pm 133(52) 12(48) 25(100) Before 10 pm 119(67,2) 58(32,8) 177(100) 0,10 0,74 Pregnant presented in Table 11. The results show that non-pregnant After 10 pm 16(64) 9(36) 25(100) plasmodial infections were evaluated and the results are and pregnant women who get up before 5 a.m. have the Table 11: highest malaria prevalence with rates of 38.50% and 48.10% Population prevalence of malariaResult by waking hours. respectively. However, statistical analysis revealed that malaria Status Hours Negative Positive Total X² P prevalence does not differ significantly according to the time of Before 5 A.M 24(61,5) 15(38,5) 39(100) 9,32 0,002 N.pregnant getting up only in non-pregnant women (p>0.05). Pregnant and After 5 A.M 133(83,6) 26(16,46) 156(100) non-pregnant women who get up after 5 A.M. have a prevalence Before 5 A.M 14(51,9) 13(48%) 27(100) 3,15 0,07 Pregnant of 16.46% and 30.9% respectively, and therefore the prevalence After 5 A.M 121(69,1) 54(30,9) 175(100) differs significantly between pregnant women getting up before 5Average a.m. and those intensity gets up of after plasmodial 5 a.m. (p˂0, infection 05). according to the profession

intensityFigure of2 gives infection us the indistribution pregnant of and the intensity non-pregnant of plasmodial women infection according to the occupation. It shows that the average intensityvaries little of withinfection the other of 2164 occupations compared except to 1123 for in female non-pregnant farmers womenwhere the (p<0.05). infection is higher in pregnant women with an average Average intensity of plasmodial infection according to the hospitals infection according to the sampling site. It shows that the mean intensityFigure of3 gives infection us the indistribution pregnant of and the intensity non-pregnant of plasmodial women Figure 2

Average intensity of infection by occupation. varies little with the other sites except for Bon samaritin in which Ann Public Health Res 7(2): 1094 (2020) 5/9 Azizi MA, et al. (2020)

single women, a higher intensity of infection is observed in non- pregnantAverage women intensity compared of plasmodium to pregnant womeninfection (p˂0,05). according to religion

Figure 7 gives us the distribution of the intensity of plasmodial infection according to religion. It shows that the average intensity of infection varies according to religious affiliation. Among amongChristian Muslim women, women. pregnant Among women women have a ofhigher other intensity religious of denominations,infection than non-pregnant only pregnant women. women Thewere situation infected isand reversed with a lower intensity of infection than the other two groups. Average intensity of infection according to ethnic groups Figure 3

Average intensity of infection as a function of hospitals. plasmodial infection according to ethnicity. It shows that among the FigureBamilekes 8 givesand others, us the pregnant distribution women of were the more intensity infected of

inthan two non-pregnant statuses. women. However, among the Bamounes, a small variation in the average intensity of infection was observed Average intensity of plasmodial infection by age group Figure 9 shows the distribution of the intensity of plasmodial

infection according to age group. It shows that the average intensity of infection varies little in all age groups, both pregnant

Figure 4 residence. Average intensity of malaria infection as a function of

Figure 6

Average intensity of infection as a function of marital status.

Figure 5

Average intensity of infection as a function of grade level. Average intensity of plasmodium infection according to marital status plasmodial infection according to marital status. It shows that Figure 6 gives us the distribution of the intensity of Figure 7 the average intensity of infection in pregnant and non-pregnant women varies little among married women. In contrast, among Average intensity of infection by religion. Ann Public Health Res 7(2): 1094 (2020) 6/9 Azizi MA, et al. (2020)

by those concerned and also to agriculture, which remains

the dominant activity for these populations. This result is in agreement with that obtained by the ENIPT [11,12], which also women.had a malaria This resultprevalence highlights of 27.8%. the Among fact that pregnant a large women number the of pregnantprevalence women is higher are than indeed the carriers overall prevalenceof the malaria of (33.16%) parasite in their blood. These results are similar to those obtained by

pregnant women (33.16%) was higher than among non-pregnant WHO [13], and [14]. The prevalence of malaria infection among

comparedwomen (20.7%). to 22.3% Our amongresults non-pregnantare similar to womenthose of [16,17]Dao [15] also in Mali, who reported a prevalence of 36% among pregnant women Figure 8 groups.. made the same observation. Indeed, pregnant women are in a Average intensity of plasmodial infection according to ethnic bystate the of climaticimmunodeficiency conditions which of the increases town of their Foumbot, vulnerability which are to malaria. This level of malaria prevalence could also be explained and non-pregnant women. The exception is the 28-34 age group,

isfavourable an important to the factor proliferation in the multiplication of mosquitoes of mosquito amplified breeding by the inComparison which non-pregnant of the microscopic women have a resultshigher intensity. with the TDR practice of agriculture, which remains a dominant activity that

grounds through cultivation techniques that develop water accumulation points in the fields. the Ofthick the drop 400 as subjects the reference examined method, for malaria, Table XII 102 presents were RDT the positive and 108 were microscopically positive. Considering plasmodiumThis study parasitaemia. demonstrates This that indicates during a the strong first relationship and second pregnancy, pregnant women are particularly vulnerable to comparative result of the two diagnostic techniques. We have parasite intensity decreasing as the number of pregnancies identified 2 false -positive results (RDT +/ Microscopic -) and 8 between parity and malaria infection, with average levels of false- negative results (RDT -/ Microscopic +) in this study. Only the 2 false- positives were of interest in this study. increases, confirming that primigravidae remain undoubtedly The RDT used in this study has a sensitivity, specificity, the most vulnerable. We found that malaria prevalence is not positive predictive value and negative predictive value of 92.6%, age-specific. The same observation was made by [18], who 99.3%, 0.7% and 7.4% respectively Table 12. mentioned that age had no significant relationship with malaria. The residence would have an impact on malaria. Our results The sensitivity of this RDT was evaluated according to parasitaemia classes. We noted that the sensitivity of the RDT decreases along with parasitemia. For parasitemia ≤ 500µl the sensitivityDISCUSSION is 95.45% and 100% for parasitemia. which demonstrates that pregnant and non-pregnant women Almost all of the women surveyed were on chemoprevention, the geographical accessibility of these facilities. Other studies carriedhave good out access in urban to health and peri-urban facilities, which areas is had also made facilitated the same by conducted in Yaoundé [9] and Madagascar [10] where 80% of womenobservation. regularly Among attended these their studies, prenatal we consultation can mention (ANC) those and the number of ANCs performed by these women was directly related to the geographical accessibility of the health facilities and Figure 9 by these women was directly related to the geographical Average intensity of plasmodial infection by age group. not to their level of education. The number of ANCs performed Table 12: education. It thus appears that the accessibility of health facilities playsaccessibility a determining of the healthrole in facilitiesthe success and of notthe tonew their programme level of Test Comparison of RDT andResult microscopic Microscopy results. Negative Positive Total N 290 8 298 developed by WHO which advocates directly observed treatment of malaria in pregnant women. P 2 100 102 (DOT) with Sulfadoxine-Pyrimethamine (SP) for the prevention (27%). In this RDT Total 292 108 400 The fairly high overall malaria prevalence study could be due to the poor practice of prevention methods Ann Public Health Res 7(2): 1094 (2020) 7/9 Azizi MA, et al. (2020)

corroborate those obtained by Part (18) which showed that

either direction increase or decrease the sensitivity of the RDTs. urban areas were (15.75%) and non-pregnant women (11.11%). malaria is mainly a rural disease. Pregnant women living in Beyond the epidemiological contexts, several other reasons may explain the low sensitivity of the RDT. to sensitization, easy access to impregnated mosquito nets and in our study is higher than that reported by [27] who found This low rate observed in the urban environment may be due the efforts made to combat this scourge. The results show that 96.7%.Specificity: This difference As for specificity, could be explainedit is 99.3%. by This the valuepersistence obtained of religion has no impact on malaria. These results are contrary to that of the WHO [28] which showed that the presence of certain an etiological interpretation guide frequently taken into account several antigens in the blood. This result is in agreement with those obtained by [19], which showed that religious affiliation is rheumatoid factors at high levels in the body and the persistence in the study of behavioural determinants related to diseases. of several antigens in the blood are at the origin of the variation It does not emerge exclusively from spiritual motives but also in specificity. factorsignificantly in cultural influences practices, social forms contingencies. of social In organization this sense, and we have considered religious denomination as a differentiating Positive predictive value: Our results revealed 2 cases of false positive, or 0.7%. This rate is lower than those obtained by WHO behavioral norms that can influence malaria transmission. This [29,30] and which found a positive predictive value of 4% and 17.1% respectively. These cases of false-positive could be due Muslims.shows no This significant trend is relationshipearlier contrary between to our malariahypothesis prevalence because to the persistence of proteins in the blood, as several authors weand thought religious that, affiliation. contrary Indeed, to this Christians result, Muslim are more women malarial who than are [29] and [31] have recognized. In addition, other factors such as temperature and low parasitaemia have been cited as causes of generally assumed to be out of the nets at a certain time of vector false positives. activity (prayers at 7:30 pm and 5 am) are the most malarious. Negative predictive value: The study revealed 8 cases of false knowAs this the study factors did notthat take could into justify account this behavioural result. factors within negatives, or 7.4%. The 8 cases of false negatives corresponded the populations of both religions, it is rather difficult to really detectto cases the of diseaselow parasitaemia. in case of parasitaemia This value is washigher determined than that byfound the WHOby [32] in itswho detection found a threshold value of 3.6%.indicated The in capacity the results of the of productRDT to Anthropogenic behavior in the occurrence of malaria after inLong-Lasting three hospitals Insecticidal and during Net (LLIN) mass coverage. distribution, During compared our study, to 74.5% of respondents said they received free impregnated nets evaluations, i.e. 200 parasites/L of blood. Based on the diagnostic performance evaluation criteria of the thick blood smear and the 68.9% who did not receive them. The prevalence of infection SDCONCLUSION BIOLINE Malar RDT among those who received is 25.5% compared to 31.1% among At the end of our work, which aimed to compare malaria those who did not. However, the relationship between the use infections and associated risk factors in pregnant and non- of LLINs and the carrying of malaria parasites reveals that there pregnant women in the town of Foumbot, it appears that malaria sameis no significantrisk of being difference infected betweenwith Plasmodium subjects sleeping as those on without. LLINs is indeed present and that pregnant women are generally more and those who do not. Moreover, subjects with LLINs have the affected by malaria than non-pregnant women. Furthermore, we

The effectiveness of ITNs in reducing transmission and thus or religion but rather according to parity, profession, residence duration.malaria morbidity Paradoxically, has been the observed comparison in somebetween endemic areas areas with andnote physiologicalthat its prevalence status does (pregnant not vary and according non-pregnant) to age group and [20] and [21]. However, the observations were only of short anddifferent [23]. transmissionIt has been shown rates did that not reducing show a significanttransmission difference will, in women’s behaviour in terms of bedtime and waking hours. The thein the long occurrence term, only of shift severe the malariaage of onset in Tanzania of malaria and and Kenya thus [22] the forRDT the can diagnosis be used for of thediagnostic disease as because well as the microscopy margins ofbecause error this level of sensitivity has led us to say that this test can be used combinedage of premunition with the use [24]. of However, impregnated good mosquito patient management nets with a are quite negligible compared to microscopy. The evaluation of with antimalarial drugs, with at least two effective molecules, remainsanthropogenic quite behaviour high among in women women reveals in the that town despite of Foumbot. the high term. coverage of the population with LLINs, the prevalence of malaria 100% coverage rate could reduce malaria morbidity in the long inHowever, the blood in of an a subject epidemiological must lead framework to appropriate that treatment consists in of avoiding the disease and treating it, the presence of Plasmodium The sensitivity, specificity, positive predictive value, negative order to reduce the risk of transmission to others. In this sense, predictive value of a test is parameters used to measure the intrinsic value of a test in relation to a reference. inthe this epidemiological population. parameters evaluated in this study must be Sensitivity: The result reveals a sensitivity of 92.6% with followed in order to avoid the occurrence of a malaria epidemic the TDR. This result is contrary to those obtained by [25]; [26] ETHIC APPROVAL AND CONSENT TO PARTICIPATE context,who obtained which is sensitivities not always ofidentical 96.3% for and these 94.7% different respectively. regions, This difference in sensitivity could be due to the epidemiological To carry out this research, an Ethical Clarence was obtained and also to the level of endemicity of the disease, which could in from the “Comite National D’ethique De La Recherche Pour La Ann Public Health Res 7(2): 1094 (2020) 8/9 Azizi MA, et al. (2020)

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Cite this article Azizi MA, Christelle Nadia NA, Cédric Y, Eric Igor SF, Christian NO, et al. (2020) Comparative Study of Malaria Infections and Associated Risk Factors among Pregnant and Non-Pregnant Women in the Town of Foumbot, Western Region - Cameroon. Ann Public Health Res 7(2): 1094.

Ann Public Health Res 7(2): 1094 (2020) 9/9