About the Author(s)


Calvin B. Ebai Email symbol
Department of Medical Laboratory Science, Faculty of Health Sciences, University of Bamenda, Bamenda, Cameroon

Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, University of Stellenbosch, Cape Town, South Africa

Flore N. Ngoufo symbol
Department of Medical Laboratory Science, Faculty of Health Sciences, University of Bamenda, Bamenda, Cameroon

Department of Biomedical Science, Faculty of Health Sciences, University of Bamenda, Bamenda, Cameroon

Rene N. Teh symbol
Department of Animal Biology and Conservation, Faculty of Science, University of Buea, Buea, Cameroon

Jerline T.S. Kodjo symbol
Department of Medical Laboratory Science, Faculty of Health Sciences, University of Bamenda, Bamenda, Cameroon

Eminline J. Muyang symbol
Department of Microbiology and Parasitology, Faculty of Science, University of Bamenda, Bamenda, Cameroon

Helen K. Kimbi symbol
Department of Biomedical Science, Faculty of Health Sciences, University of Bamenda, Bamenda, Cameroon

Department of Animal Biology and Conservation, Faculty of Science, University of Buea, Buea, Cameroon

Citation


Ebai CB, Ngoufo FN, Teh RN, Kodjo JTS, Muyang EJ, Kimbi HK. Epidemiology of malaria in pregnant women attending antenatal consultation in Dschang, West Cameroon. J Public Health Africa. 2025;16(1), a1437. https://doi.org/10.4102/jphia.v16i1.1437

Original Research

Epidemiology of malaria in pregnant women attending antenatal consultation in Dschang, West Cameroon

Calvin B. Ebai, Flore N. Ngoufo, Rene N. Teh, Jerline T.S. Kodjo, Eminline J. Muyang, Helen K. Kimbi

Received: 24 Apr. 2025; Accepted: 05 July 2025; Published: 20 Aug. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background: Despite measures, malaria in pregnancy is still reported. It results in maternal illness, anaemia, low birth weight, preterm delivery and both maternal and foetal death.

Aim: To determine the prevalence and density of malaria parasitaemia and identify the associated factors among pregnant women.

Setting: This was a hospital-based study in two health facilities in Dschang, Western Cameroon.

Methods: A cross-sectional study was conducted. A questionnaire was used to collect data on socio-demographics clinical manifestations, environmental factors and prevention measures used. Parasitological tests were carried out using thick and thin blood smears. Data were analysed using Statistical Package for Social Sciences (SPSS), version 22.0.

Results: Out of the 314 participants, 46 (14.6%) were positive for malaria parasitaemia, and the only species identified was Plasmodium falciparum. A multinomial regression model showed that the presence of bushes around houses (odds ratio [OR] = 2.40, p = 0.03) exposes individuals to malaria parasite infection, while the presence of a ceiling (OR = 0.20, p < 0.01), taking intermittent preventive treatment for pregnant women (IPTp) (OR = 0.23, p < 0.01) and having window screens (OR = 0.14, p = 0.01) were protective. Geometric mean parasite density (GMPD) was highest among pregnant women in the second trimester (2190/µL, F = 61.3, p = 0.016), those with more than three gravidities (1022/µL, F = 66.28, p = 0.009), those who presented with sweating (1946/µL, F = 272, p = 0.004) and, unexpectedly, those who were using long-lasting insecticide-treated bed nets (1536/µL; F = 3.32, p < 0.001), compared with their corresponding counterparts.

Conclusion: The prevalence and density of malaria parasite varied with demographics, pregnancy characteristics, clinical manifestations, quality of housing, environmental conditions and malaria prevention methods.

Contribution: An update on malaria among pregnant women. Continuous sensitisation on prevention methods is necessary.

Keywords: epidemiology; prevalence; malaria; pregnant women; risk factors; Dschang; Cameroon.

Introduction

Malaria is an infectious disease caused by protozoan parasites of the Plasmodium species. It is transmitted by infected female Anopheles mosquitoes when they feed on human blood. The disease remains an important public health problem, particularly in sub-Saharan Africa, including Cameroon with significant economic burden.1 Cameroon is among the 15 countries with the highest malaria burden in the world with 3.0% of all global malaria cases and 1.9% of malaria deaths in 2023.1 Malaria in pregnancy is a severe condition usually leading to maternal illness, maternal anaemia, low birth weight, preterm delivery and both maternal and foetal death.2,3 The occurrence and severity of the disease in pregnancy may be influenced by factors related to socio-demographics, environment, pregnancy, treatment, as well as uptake of control measures.4,5,6 The Cameroon Government within the past decades has taken several measures to eliminate malaria and especially reduce the burden on pregnant women. These measures include free distribution of long-lasting insecticide-treated bed nets (LLINs), intermittent preventive treatment for pregnancy (IPTp) through free distribution of sulfadoxine pyrimethamine (SP) for prophylaxis, as well as health education during visit to antenatal clinic (ANC).7 These measures have been reported to reduce the prevalence of malaria in some settings.8,9 However, there are reports of poor and non-uptake of the prevention measures by some pregnant women,8,10 accounting for the occurrence of malaria in pregnancy reported in some of the recent studies.9,11 Many malaria cases in pregnancy are asymptomatic and if undetected and untreated may lead to severity in disease and sometimes irreversible outcomes for both mother and foetus. Women in their first pregnancies have been reported to be more vulnerable to Plasmodium parasite infection.4,11

Factors influencing the occurrence of malaria vary with geographical settings, and identifying the risk factors within a specific setting is crucial for designing intervention measures towards effective control of the disease. This study aims to determine the prevalence of malaria parasitaemia and to identify the risk factors among pregnant women attending ANC at the Dschang Regional Hospital Annexe and the Saint Vincent de Paul Hospital in Dschang, West Cameroon. The paucity of updated data on malaria in pregnancy in these area, as well as the necessity for continuous monitoring of disease occurrence make this study relevant. This may provide evidence for informed decision-making and support a possible review of policy towards more effective control of malaria among pregnant women.

Research methods and design

Study design

This was a hospital-based cross-sectional study conducted in the month of April 2024. A pretested structured questionnaire was used to collect data on demographics and predisposing factors. Blood samples were collected through finger prick to detect and quantify malaria parasite.

Study setting

This study was carried out at the Dschang Regional Hospital Annexe and the Saint Vincent de Paul Hospital in Dschang. Dschang is the headquarters of the Menoua Division of the West Region of Cameroon. It is a cosmopolitan town with an estimated population of over 99 000 inhabitants. It is located in the western highlands of Cameroon at longitudes 10.036850 W to 10.084987 E and latitudes 5.470937 N to 5.422352 S, at an altitude of about 1380 m above the sea level. Dschang has two seasons like most parts of Cameroon. The rainy season spans from mid-March to mid-November, while the dry season lasts from mid-November to mid-March. Temperatures, during the rainy season, range from 16.1 °C to 26.7 °C, with August being the coldest month, with an average temperature of 18.1 °C. In the dry season, the temperatures range from 17 °C to 33 °C, with February being the hottest month, having an average temperature of 23 °C. The annual rainfall averages 2145 mm. The vegetation is between the savannah and the forest types covered with very dense vegetation. Dschang has both urban and rural settings. Commerce is a major economic activity alongside a very active educational sector. Educational institutions at all levels in both the state and private sectors are present; a good proportion of the population also practise farming. Dschang is endowed with both state-owned and privately owned health facilities with the Regional Hospital Annexe, the highest referral and most equipped in the division. The Saint Vincent de Paul Hospital is a faith-based health facility owned by the Catholic Mission. Both health facilities operate ANC on a daily basis with equipped laboratory services.

Study population and sampling

Enrolment of participants was done in the antenatal units of the two health facilities. A convenience sampling technique was used to recruit pregnant women. Excluded from this study were women who were severely ill with chronic diseases like acquired immunodeficiency syndrome (AIDS) and cancer; those who had not lived in Dschang for up to two months, to avoid persons coming from outside the study area with infections; and those who were undergoing malaria treatment, in order to reduce the chances of false negative results. However, we did not find any pregnant women who were identified into any of these categories during the study. Using Cochran’s formula12 and the malaria prevalence of 10.14% in Cameroon reported by Nlinwe et al.,9 the calculated sample size was 366 participants.

Data collection
Administration of questionnaire

A standardised, pretested questionnaire was used to collect data on demographics, such as age, sex, level of education and profession; predisposing factors, including clinical and environmental aspects; history of pregnancy and the use of malaria prevention measures. Pregnancy age was divided into three trimesters, following the WHO prescriptions (1st: 0–13 weeks, 2nd: 14–26 weeks and 3rd: 27–40 weeks).13 The questionnaire was administered in English, Pidgin and French, depending on the participant’s preference. This was done with the assistance of healthcare personnel (nurses and midwives) on duty, as the women took rounds during their ANC consultation.

Blood specimen collection and laboratory procedures

For detection and identification of Plasmodium species, capillary blood was collected from either the ring finger or the middle finger using a sterile lancet after disinfection with 70% ethyl alcohol. Excluding the first drop, three drops of blood were collected; two drops were placed on clean, grease-free microscope slides at separate points and used to prepare thick and thin blood smears. The third drop of blood was used to perform a white blood cell count using the improved Neubauer counting chamber, following standard procedures. The blood smears were air dried and the thin smear fixed with absolute methanol. Both smears were stained with 10% Giemsa stain for 10 min and examined under a light microscope (Olympus, New York, United States), using the oil immersion objective, following standard operating procedures. The thick blood smears were used for parasite detection and quantification using the formula:

while the thin blood smears were used for species identification.14

Data analysis

Data was entered in a Microsoft Excel spreadsheet and exported into the Statistical Package for Social Sciences (SPSS), version 22.0. Descriptive statistics were presented as frequencies and percentages. Fisher’s exact test and the Chi-square test were used to compare prevalence of malaria among groups; odds ratios (OR) were used to identify factors associated with malaria parasitaemia, while logistic regression model was used to determine risk factors. A one-way analysis of variance (ANOVA) test was used to compare geometric mean parasite densities (GMPDs) at 95% confidence interval (CI). The level of significance was set at p < 0.05.

Ethical considerations

The ethical clearance for this study was obtained from the Institutional Review Board/Ethics Committee of the Faculty of Health Sciences, University of Bamenda (No. 2024/0343H/UBa/IRB of 05 April 2024). Administrative authorisation was obtained from the Director of the Dschang Regional Hospital Annexe as well as from the Director of Saint Vincent de Paul Hospital Dschang. Participants were informed about the objectives, procedures, benefits and inconveniences of the study. Those who agreed to take part in the study gave written informed consent. Confidentiality of participants was ensured by use of codes on all documents; no names were used. Participation in the study was completely free and voluntary; participants had the right to quit at any time without facing any consequences.

Results

Socio-demographic characteristics of the study participants

A total of 314 participants – 212 (64.3%) from the Regional Hospital Annexe and 102 (35.7%) from the Saint Vincent De Paul Hospital – were admitted into the study. The age range was from 17 years to 40 years, with the median age being 26 years. The age group 17–25 years was the most represented (n = 144, 45.9%). Most of the women were married (n = 191, 60.8%), 146 (46.5%) had attained secondary education, and 107 (34.1%) were in business (Table 1).

TABLE 1: Socio-demographic characteristics of the study population.
Prevalence of malaria parasite
Prevalence of malaria parasite with respect to socio-demographic characteristics

Out of 314 participants, 46 (14.6%) were positive for malaria parasitaemia and the only species identified was Plasmodium falciparum. Comparing the prevalence of malaria parasitaemia between participants using Fisher’s exact test (FET), a significant statistical difference was observed with respect to the level of education (FET = 7.88, p = 0.04), with the highest prevalence detected among those with no formal education (30.0%). A similar observation was found with respect to the occupation, with the highest prevalence observed among farmers (n = 6, 33.3%; FET = 11.25, p = 0.02) (Table 2).

TABLE 2: Prevalence of malaria parasite with respect to socio-demographic characteristics.
Factors associated with malaria parasitaemia
Pregnancy-related factors

Although the prevalence of malaria parasitaemia was highest among pregnant women in the first trimester (n = 11, 19.9%), there was no significant statistical difference (χ2 = 1.41, p = 0.49). With respect to gravidity, women at gravida 1 were most infected (n = 21, 17.4%), but the difference was not statistically significant (χ2 = 1.17, p = 0.56) (Table 3).

TABLE 3: Prevalence of malaria with respect to trimester of pregnancy and gravida.
Clinical and environmental factors

Participants presenting with the following clinical manifestations were at higher odds of being infected with malaria parasite than their corresponding counterparts: fever (OR = 6.34, 95% CI: 2.93–13.74, p < 0.01), headache (OR = 3.28, 95% CI: 1.72–8.23, p < 0.01) and muscle pain (OR = 4.82, 95% CI: 2.51–9.26, p < 0.01). Similarly, participants with the presence of bushes around their houses (OR = 3.10, 95% CI: 1.50–6.33, p = 0.001), those with mud house type (OR = 1.98, 95% CI: 1.02–3.83, p = 0.04) and those with holes on the walls of their houses (OR = 2.60, 95% CI: 1.26–5.25, p = 0.008) were at a higher risk of having malaria than their corresponding counterparts. The results also show that those who had a ceiling had a lower prevalence of malaria compared to those who did not (OR = 0.2, 95% CI: 0.11–0.44, p < 0.01), indicative of a protective effect of the ceiling against malaria infection (Table 4).

TABLE 4: Prevalence of malaria with respect to clinical and environmental factors.
Malaria prevention methods

It was observed that the prevalence of malaria parasite was lower among pregnant women who took IPTp than their counterparts who did not take (OR = 0.33, 95% CI: 0.16–0.70, p = 0.002). In the same light, a lower prevalence of malaria parasite was observed among participants who had window screens than those who did not have (OR = 0.84, 95% CI: 0.80–0.88, p = 0.02). This is indicative of a protective effect of both methods (Table 5).

TABLE 5: Prevention measures associated with malaria parasite prevalence.
Determination of the risk factors of malaria parasitaemia

From the results of a multiple logistic regression model done using the environmental and prevention methods that were associated with malaria parasitaemia (p < 0.05), it was observed that the presence of bushes around the house (OR = 2.40, p = 0.03) exposes to malaria parasite infection, while the presence of a ceiling (OR = 0.20, p < 0.01), taking IPTp (OR = 0.23, p < 0.01) and having window screens (OR = 0.14, p = 0.01) were protective against malaria parasite infection (Table 6).

TABLE 6: Multinomial regression model for risk factors of malaria parasitaemia.
Variation of parasite density with pregnancy-related factors, clinical manifestations and prevention methods

Assessing the variation of parasite density using one-way ANOVA, it was observed that there was a significant statistical difference in GMPDs with respect to trimester of pregnancy (F = 61.3; p = 0.016); with the second trimester having the highest (2191/µL). A similar observation was obtained with respect to gravidity (F = 66.28; p = 0.009) with participants who had more than three pregnancies having the highest GMPD (1023/µL). Participants manifesting with sweating (1242/µL; F = 272; p = 0.004) and, surprisingly, those who used LLINs (1536/µL; F = 175.3; p < 0.001) had higher GMPDs than their corresponding counterparts (Table 7).

TABLE 7: Comparing parasite density with respect to trimesters of pregnancy, clinical manifestations and malaria prevention methods.

Discussion

Given that malaria continues to be a public health problem despite the continuous efforts by several stakeholders, vulnerable groups such as pregnant women continue to remain significantly affected by the disease. This study was carried out to assess the prevalence and risk factors of malaria parasitaemia in pregnant women. The prevalence of malaria parasite in this study was 14.6%. This figure of prevalence is higher than 5.06% reported in 2021 in Foumban, a district in the same region,15 as well as the 10.14% prevalence reported in 2022 in Foumbot, also within the same region and in Bamenda, which has similar environmental factors like the study site.9 These discrepancies could be because of variabilities in the implementation of control measures between health facilities, individual factors like immune status, and the differences in the demographic characteristics of the study populations. However, the prevalence of malaria parasitaemia found in this study is lower than the 39.6% reported by Elime et al.16 in Ndop, Cameroon; the 17.8% reported by Jugha et al. in the Mount Cameroon Region,17 and the 20.8% reported by Almaw et al. in Ethiopia.18 This could be because of an improvement in the overall implementation of preventive measures against malaria.

With respect to the levels of education, pregnant women with no formal education were most infected. This is most likely a consequence of lack of knowledge about the disease, and also the poor understanding of the importance and use of prevention measures. There is evidence that maternal education is a cost-effective intervention to reduce malaria infection.19 Concerning the occupation, farmers were most infected. This is likely because of their exposure to sites closer to vector hideouts and breeding sites, but also could be because of pig-rearing, which is common in the area, because mosquitoes are attracted to the animals for blood meal.20 Except for the levels of education and the occupation, there was no association observed between malaria parasitaemia and all other socio-demographic characteristics, including health facility. This similarity in prevalence could be an indication of the general efforts made by the government and other stakeholders to fight against malaria, especially among pregnant women and children below five years. Earlier studies have, however, shown associations between malaria parasitaemia and socio-demographic factors.21,22 The gaps may have been closed over time by a scale-up in prevention measures.

No significant statistical difference in prevalence was observed with respect to trimester and gravida. This could also be because of a scale-up in prevention measures. However, the highest prevalence was observed among the women in their first trimester and the primigravida. Similar results have been reported in other studies.4,11 This could be because of their lower levels of adaptive immunity.

Fever, headache and muscle pain were found to be associated with malaria parasitaemia in the studied participants. Malaria is characterised by sequential rupture of infected red blood cells (RBCs).23 During the rupture of RBCs, trophozoites and malaria pigment haemozoin are released into the blood circulation causing an immune response that results in synchronised bouts of fever corresponding to the moments of rupture.24 Prior to the occurrence of fever, there is usually a sensation of cold, which results in shivering to generate heat. This also results in an increase in the body temperature.25 Concerning headache, infected RBCs develop adhesiveness to both infected and non-infected RBCs; this results in sequestration of RBCs in the blood vessels, sometimes blocking microcirculation, including those in the brain and the skeletal muscles,26 which leads to hypoxia and impairment of tissue function. Also, there is the release of inflammatory cytokines because of the presence of malaria parasites, which stimulate the pain receptors in the tissues.27 These two processes could be a possible explanation for the headache and muscle pain observed in the malaria-infected participants in this study.

Furthermore, the presence of bushes around houses, houses fabricated with mud, the presence of holes on walls and the absence of a ceiling were associated with malaria parasitaemia. This confirms the findings in other studies too.28 Bushes around the house provide hideouts for the mosquito vector, thereby bringing them closer to the human host for infection. Holes on the walls are common in houses constructed with mud, and together with the absence of a ceiling they provide entry of mosquitoes ad libitum, thereby increasing the chances of malaria parasite transmission to the occupants.

Malaria prevention measures remain the key to the elimination or eradication of the disease. In this study, participants who failed to take IPTp (SP) were at higher risk of having malaria. The different components of sulfadoxine pyrimethamine (SP) are folate inhibitors. Sulfadoxine inhibits the activity of dihydropteroate synthase, an enzyme that catalyses the condensation of para-aminobenzoic acid (PABA) with 6-hydroxymethyl-7,8-dihydropterin pyrophosphate to form 7,8-dihydropteroate, a crucial step in the biosynthesis of folate, an essential molecule for the cell growth and division in parasites and other microorganisms.29 Pyrimethamine inhibits dihydrofolate reductase (DHFR), which plays a crucial role as an essential enzyme in the folate pathway, necessary for the synthesis of nucleotides required for deoxyribonucleic acid (DNA) replication and cell division. So, inhibiting DHFR disrupts the parasite’s ability to produce vital building blocks for its growth and survival,29 thus limiting the chances of establishing the disease.

Participants who did not have window screens were also at risk of infection. Window screens reduce the chances of the vector getting into the house to bite and transmit the parasite. The multiple logistic regression model confirmed the presence of bush around houses, the non-uptake of IPTp, the absence of a ceiling and window screens as the risk factors for malaria in the study population. Effective use of preventive measures has been reported to be protective against malaria transmission in several studies.9,28

Assessing the variation of GMPDs revealed significant statistical differences with respect to trimester of pregnancy, gravida, sweating and the use of LLINs. The highest values were found among participants in the second trimester, while the lowest values were observed in the first trimester. Inasmuch as the prevalence of malaria parasitaemia was higher among women in the first trimester, there is a possibility that improved immunity in preparation for pregnancy provides a general non-specific defence against infectious agents, including malaria parasite, as reported in some studies.30,31

A similar phenomenon was observed when comparing GMPDs with respect to gravida. Participants with more than three pregnancies had higher parasite densities than their counterparts with lesser pregnancies. These findings are unexpected given that reports have shown that women with higher gravida have greater specific immunity to malaria parasite and so will more likely eliminate malaria parasites than pregnant women with lower gravida.32 However, the results obtained here could be because of variabilities in the immunity of the individuals. Similar results were obtained in the study by Emmanuel et al.33 in Nigeria.

Higher GMPDs were also recorded in participants who presented with sweating compared to their counterparts. In a classical malaria bout, following the hot stage, there is usually profuse sweating, which is then followed by a reduction or drop in temperature and exhaustion, so this confirms sweating as a typical manifestation of malaria. Geometric mean parasite density was unexpectedly higher in participants who reported using mosquito bed nets. There could be a possible neglect on the part of these individuals, who may believe that because they slept under nets, they are not exposed to malaria, while failing to consider exposure when out of the net. This may expose them to multiple mosquito bites that could result in higher parasite densities in their blood.

Limitation

This study did not ensure species confirmation of malaria parasite by polymerase chain reaction (PCR).

Conclusion

The prevalence of malaria parasitaemia was associated with some demographic factors which included the levels of education and the occupation, as well as clinical factors, including fever, headache and muscle pain. The presence of bushes around houses, holes on walls, the absence of ceiling and non-uptake of IPTp were the risk factors for malaria. Geometric mean parasite densities varied significantly with pregnancy trimester, gravida, presence of profuse sweating and the use of LLINs. Some clinical signs may serve as predictors of malaria infection during pregnancy. Continuous sensitisation of pregnant women on the consistent use of prevention methods is essential.

Acknowledgements

The authors are grateful to the participants who agreed to be part of this study. They also want to thank the authorities of Dschang Regional Hospital Annex and the Saint Vincent de Paul Hospital in Dschang for authorising the study in their facilities.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors’ contributions

C.B.E. conceived the study. C.B.E., F.N.N., J.T.S.K. and E.J.M. described the methodology and carried out the investigations. C.B.E. and R.T.N. did the data analysis. C.B.E. and J.T.S.K. provided the resources. C.B.E. wrote the original draft of the article. All authors reviewed the article, read and approved the final version. C.B.E. and H.K.K. supervised the project.

Funding information

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

Data for this study are available on reasonable requests from the corresponding author, C.B.E.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

References

  1. Venkatesan P. WHO world malaria report 2024. Lancet Microbe. 2025;6(4):101073. https://doi.org/10.1016/j.lanmic.2025.101073
  2. Chua CLL, Khoo SKM, Ong JLE, Ramireddi GK, Yeo TW, Teo A. Malaria in pregnancy: From placental infection to its abnormal development and damage. Front Microbiol. 2021;12:777343. https://doi.org/10.3389/fmicb.2021.777343
  3. Tako EA, Zhou A, Lohoue J, Leke R, Taylor DW, Leke RF. Risk factors for placental malaria and its effect on pregnancy outcome in Yaounde, Cameroon. Am J Trop Med Hyg. 2005;72(3):236–242. https://doi.org/10.4269/ajtmh.2005.72.236
  4. Dosoo DK, Chandramohan D, Atibilla D, et al. Epidemiology of malaria among pregnant women during their first antenatal clinic visit in the middle belt of Ghana: A cross sectional study. Malar J. 2020;19(1):381. https://doi.org/10.1186/s12936-020-03457-5
  5. Lingani M, Zango SH, Valea I, et al. Prevalence and risk factors of malaria among first antenatal care attendees in rural Burkina Faso. Trop Med Health. 2022;50(1):49. https://doi.org/10.1186/s41182-022-00442-3
  6. Tilaye T, Tessema B, Alemu K. High asymptomatic malaria among seasonal migrant workers departing to home from malaria endemic areas in northwest Ethiopia. Malar J. 2022;21(1):184. https://doi.org/10.1186/s12936-022-04211-9
  7. MINSANTE: Note d’Information 2eme Campagne Nationale de Distribution Gratuite de 12 350 000 de MILDA [Information Note: 2nd National Campaign for the Free Distribution of 12,350,000 LLINs]. Yaounde: Ministere de la Sante Publique du Cameroun; 2016.
  8. Antonio-Nkondjio C, Ndo C, Njiokou F, et al. Review of malaria situation in Cameroon: Technical viewpoint on challenges and prospects for disease elimination. Parasit Vectors. 2019;12(1):501. https://doi.org/10.1186/s13071-019-3753-8
  9. Nlinwe NO, Nchefor FG, Takwi NB. Impact of long lasting insecticidal nets on asymptomatic malaria during pregnancy, in a rural and urban setting in Cameroon. Parasite Epidemiol Control. 2022;18:e00265. https://doi.org/10.1016/j.parepi.2022.e00265
  10. Kamga SLS, Ali IM, Ngangnang GR, et al. Uptake of intermittent preventive treatment of malaria in pregnancy and risk factors for maternal anaemia and low birthweight among HIV-negative mothers in Dschang, West region of Cameroon: A cross sectional study. Malar J. 2024;23(1):6. https://doi.org/10.1186/s12936-023-04816-8
  11. Ebai CB, Yamssi C, Ngoufo FN, et al. Malaria parasite density and anaemia in pregnant women attending antenatal consultation in the Regional Hospital Bamenda, Cameroon. Int J Res Rep Hematol [serial online]. 2023;6(2);264–274. [cited 2024 Apr 18]. Available from: https://journalijr2h.com/index.php/IJR2H/article/view/133
  12. Cochran WG. Sampling techniques. 2nd ed. John Wiley & Sons; New York, 1963.
  13. WHO. Hemoglobin concentration for the diagnosis of anemia and assessment of severity. Vitamins and minerals nutrition information system [homepage on the Internet]. 2011 [cited 2024 Mar 15]. Available from: https://www.who.int/publications/i/item/WHO-NMH-NHD-MNM-11.1
  14. Cheesbrough M. District laboratory practice in tropical countries. 2nd ed. Cambridge: Cambridge University Press; 2005.
  15. Celestine KMN, Hirma T-NK, Nadia NAC, Symphorien E, Jerome A. Malaria and anemia among pregnant women in the Foumban Health District: West-Cameroon. J Biosci Med. 2024;12(12):305–314. https://doi.org/10.4236/jbm.2024.1212024
  16. Elime FA, Nkenyi NR, Ako-Egbe L, Njunda A, Nsagha D. Malaria in pregnancy: Prevalence and risk factors in the Mamfe Health District, Cameroon. J Adv Med Med Res. 2019;30(1):1–11. https://doi.org/10.9734/jammr/2019/v30i130161
  17. Jugha VT, Anchang JA, Taiwe GS, Kimbi HK, Anchang-Kimbi JK. Association between malaria and undernutrition among pregnant women at presentation for antenatal care in health facilities in the Mount Cameroon region. PLoS One. 2023;18(10):e0292550. https://doi.org/10.1371/journal.pone.0292550
  18. Almaw A, Yimer M, Alemu M, Tegegne B. Prevalence of malaria and associated factors among symptomatic pregnant women attending antenatal care at three health centers in north-west Ethiopia. PLoS One. 2022;17(4):e0266477. https://doi.org/10.1371/journal.pone.0266477
  19. Masuda K. Length of maternal schooling and children’s risk of malaria infection: evidence from a natural experiment in Uganda. BMJ Glob Health. 2020;5(2):e001729. https://doi.org/10.1136/bmjgh-2019-001729
  20. Mwalugelo YA, Mponzi WP, Muyaga LL, et al. Livestock keeping, mosquitoes and community viewpoints: A mixed methods assessment of relationships between livestock management, malaria vector biting risk and community perspectives in rural Tanzania. Malar J. 2024;23(1):213. https://doi.org/10.1186/s12936-024-05039-1
  21. Poespoprodjo JR, Fobia W, Kenangalem E, et al. Adverse pregnancy outcomes in an area where multidrug-resistant plasmodium vivax and Plasmodium falciparum infections are endemic. Clin Infect Dis. 2008;46(9):1374–1381. https://doi.org/10.1086/586743
  22. Ayoola OO, Whatmore A, Balogun WO, Jarrett OO, Cruickshank JK, Clayton PE. Maternal malaria status and metabolic profiles in pregnancy and in cord blood: Relationships with birth size in Nigerian infants. Malar J. 2012;11(1):75. https://doi.org/10.1186/1475-2875-11-75
  23. Soni S, Dhawan S, Rosen KM, Chafel M, Chishti AH, Hanspal M. Characterization of events preceding the release of malaria parasite from the host red blood cell. Blood Cells Mol Dis. 2005;35(2):201–211. https://doi.org/10.1016/j.bcmd.2005.05.006
  24. Parroche P, Lauw FN, Goutagny N, et al. Malaria hemozoin is immunologically inert but radically enhances innate responses by presenting malaria DNA to Toll-like receptor 9. Proc Natl Acad Sci USA. 2007;104(6);1919–1924. https://doi.org/10.1073/pnas.0608745104
  25. Huynh BT, Fievet N, Gbaguidi G, et al. Malaria associated symptoms in pregnant women followed up in Benin. Malar J. 2011;10(1):72. https://doi.org/10.1186/1475-2875-10-72
  26. Franke-Fayard B, Fonager J, Braks A, Khan SM, Janse CJ. Sequestration and tissue accumulation of human malaria parasites: Can we learn anything from rodent models of malaria?. PLoS Pathog. 2010;6(9):e1001032. https://doi.org/10.1371/journal.ppat.1001032
  27. Wiwanitkit V. Headache and malaria: A brief review. Acta Neurol Taiwan. 2009;18(1):56–59.
  28. Kimbi HK. Environmental factors and preventive methods against malaria parasite prevalence in rural Bomaka and Urban Molyko, Southwest Cameroon. J Bacteriol Parasitol. 2012;4(1):1000162. https://doi.org/10.4172/2155-9597.1000162
  29. Aponte JJ, Schellenberg D, Egan A, et al. Efficacy and safety of intermittent preventive treatment with sulfadoxine-pyrimethamine for malaria in African infants: A pooled analysis of six randomised, placebo-controlled trials. Lancet. 2009;374(9700):1533–1542. https://doi.org/10.1016/S0140-6736(09)61258-7
  30. Plaks V, Birnberg T, Berkutzki T, et al. Uterine DCs are crucial for decidua formation during embryo implantation in mice. J Clin Invest. 2008;118(12):3954–3965. https://doi.org/10.1172/JCI36682
  31. Shimada S, Nishida R, Takeda M, et al. Natural killer, natural killer T, helper and cytotoxic T cells in the decidua from sporadic miscarriage. Am J Reprod Immunol. 2006;56(3):193–200. https://doi.org/10.1111/j.1600-0897.2006.00417.x
  32. Suliman MA, Tamomh AG, Younis OY, et al. Malaria infection and associated risk factors in pregnant women attending antenatal care clinics in Al Jabalian Locality, White Nile state, Sudan. Ann Parasitol. 2021;67(3):499–504.
  33. Emmanuel BN, Chessed G, Erukainure FE, Ekeuhie JC, Philips V. Prevalence of malaria parasite and its effects on some hematological parameters amongst pregnant women in Yola, Nigeria. J Umm Al-Qura Univ Appl Sci. 2023;10(1):200–210. https://doi.org/10.1007/s43994-023-00092-z


Crossref Citations

No related citations found.