Geostatistical analysis and mapping of malaria risk in children under 5 years old in Togo

Authors

Keywords:

malaria, risk, geostatic, health

Abstract

The objective of this research is to analyze the geostatistical and cartographic determinants of malaria risk among children under 5 years of age in Togo. Using a geostatistical model and data from the 2017 MIS survey in Togo, the results reveal that children of uneducated mothers have a higher malaria prevalence than those of educated mothers. The general trend observed is that households living in urban areas have a lower prevalence of malaria compared to those living in rural areas. The prevalence of malaria among children under five years old decreases with increasing household wealth. Malaria prevalence was also positively associated with vegetation index and minimum temperature. Thus, these results suggest the need for effective and efficient public health interventions in high-risk areas. In addition, the determinants of malaria spatial distribution identified in this study together with the established malaria risk maps could be used in the implementation of malaria control programs and policies to define priority intervention areas.

References

Abeku, T. A., Hay, S. I., Ochola, S., Langi, P., Beard, B., de Vlas, S. J., & Cox, J. (2004). Malaria epidemic early warning and detection in African highlands. Trends in Parasitology, 20(9), 400–405.
View in Google Scholar

Afoakwah, C., Deng, X., & Onur, I. (2018). Malaria infection among children under-five: The use of large-scale interventions in Ghana. BMC Public Health, 18(1), 1–13.
View in Google Scholar

Amoah, B., Giorgi, E., Heyes, D. J., van Burren, S., & Diggle, P. J. (2018). Geostatistical modelling of the association between malaria and child growth in Africa. International Journal of Health Geographics, 17(1), 1–12.
View in Google Scholar

Awine, T., Malm, K., Bart-Plange, C., & Silal, S. P. (2017). Towards malaria control and elimination in Ghana: Challenges and decision making tools to guide planning. Global Health Action, 10(1), 1381471.
View in Google Scholar

Bakai, T. A., Atcha-Oubou, T., d’Almeida, S., Ekouevi, D. K., Tchadjobo, T., Kusiaku, K., ..., Essébio, D. (2017). Mise en place d’un réseau sentinelles national de surveillance du paludisme au Togo. Revue d’Épidémiologie et de Santé Publique, 65, S92–S93.
View in Google Scholar

Chikodzi, D. (2013). Spatial modelling of malaria risk zones using environmental, anthropo-genic variables and geographical information systems techniques. Journal of Geosciences and Geomatics, 1(1), 8–14.
View in Google Scholar

Diggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C, 47(3), 299–350.
View in Google Scholar

Djadou, K. E., Batalia, H., Akolly, D. E., Djadou, J. A., Agbéko, F., Douti, N. K., ..., Atakouma, Y. (2020). Paludisme grave de l’enfant de 1 a 59 mois au CHR de Tsevie. Journal de La Recherche Scientifique de l’Université de Lomé, 22(3), 671–681.
View in Google Scholar

Djagadou, K. A., Tchamdja, T., Kaaga, L. Y., Tchala, A., Balaka, A., & Djibril, M. A. (2019). Utilisation de la moustiquaire impregnee d’insecticide dans la zone urbaine d’Agoe-Nyive au Togo. Journal de La Recherche Scientifique de l’Université de Lomé, 24(1), 98–100.
View in Google Scholar

Ejigu, B. A. (2020). Geostatistical analysis and mapping of malaria risk in children of Mo-zambique. PloS One, 15(11), e0241680.
View in Google Scholar

Ejigu, B. A., & Wencheko, E. (2021). Spatial prevalence and determinants of malaria among under-five children in Ghana. Epidemiology. https://doi.org/10.1101/2021.03.12.21253436
View in Google Scholar

Geleta, G., & Ketema, T. (2016). Severe malaria associated with Plasmodium falciparum and P. vivax among children in Pawe Hospital, Northwest Ethiopia. Malaria Research and Treatment.
View in Google Scholar

Gemperli, A., Sogoba, N., Fondjo, E., Mabaso, M., Bagayoko, M., Briët, O. J. T., ..., Vounatsou, P. (2006). Mapping malaria transmission in West and Central Africa. Tropical Medicine & International Health, 11(7), 1032–1046.
View in Google Scholar

Kabaghe, A. N., Chipeta, M. G., McCann, R. S., Phiri, K. S., Van Vugt, M., Takken, W., ..., Terlouw, A. D. (2017). Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi. PLoS One, 12(2), e0172266.
View in Google Scholar

Kumi-Boateng, B., Stemn, E., & Mireku-Gyimah, D. (2015). Modelling of malaria risk areas in Ghana by using environmental and anthropogenic variables–A spatial multi-criteria approach. Ghana Mining Journal, 15(2), 1–10.
View in Google Scholar

Kumi-Boateng, B., & Ziggah, Y. Y. (2017). Horizontal coordinate transformation using ar¬tificial neural network technology—a case study of Ghana geodetic reference network. Journal of Geomatics, 11(1), 1–11.
View in Google Scholar

Malaria Indicator Survey (MIS). (2017). Enquête sur les indicateurs do paludisme au Togo.
View in Google Scholar

Ministère de l’Économie et des Finances. (2019). Rapport de performance du PA-RGFP 2018-2020 à fin décembre 2018.
View in Google Scholar

Nyarko, S. H., & Cobblah, A. (2014). Sociodemographic determinants of malaria among under-five children in Ghana. Malaria Research and Treatment, 304361. http://doi.org/10.1155/2014/304361
View in Google Scholar

Nzabakiriraho, J. D., & Gayawan, E. (2021). Geostatistical modeling of malaria preva¬lence among under-five children in Rwanda. BMC Public Health, 21(1), 369. https://doi.org/10.1186/s12889-021-10305-x
View in Google Scholar

OMS. (2018). Rapport annuel de performance 2018 du MSHP.
View in Google Scholar

OMS. (2019). Le Rapport sur le paludisme dans le monde 2019 en un clin d’oei.
View in Google Scholar

QUIBB. (2006). Profil de la pauvreté et de la vulnérabilité au Togo. Rapport.
View in Google Scholar

QUIBB. (2015). Rapport du questionnaire Unifié des Indicateurs de Base du Bien-Être 174.
View in Google Scholar

Roberts, D., & Matthews, G. (2016). Risk factors of malaria in children under the age of five years old in Uganda. Malaria Journal, 15(1), 1–11.
View in Google Scholar

Rudasingwa, G., & Cho, S. I. (2020). Determinants of the persistence of malaria in Rwanda. Malaria Journal, 19(1), 36.
View in Google Scholar

Stanton, M. C., & Diggle, P. J. (2013). Geostatistical analysis of binomial data: Generalised linear or transformed Gaussian modelling?. Environmetrics, 24(3), 158–171.
View in Google Scholar

Teklehaimanot, A., & Mejia, P. (2008). Malaria and poverty. Annals of the New York Academy of Sciences, 1136(1), 32–37.
View in Google Scholar

Thomas, A., Bakai, T. A., Atcha-Oubou, T., Tchadjobo, T., & Voirin, N. (2020). Implementation of a malaria sentinel surveillance system in Togo: A pilot study. Malaria Journal, 19(1), 1–11.
View in Google Scholar

Thuilliez, J., d’Albis, H., Niangaly, H., & Doumbo, O. (2017). Malaria and education: Evidence from Mali. Journal of African Economies, 26(4), 443–469.
View in Google Scholar

Yankson, R., Anto, E. A., & Chipeta, M. G. (2019). Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana. Malaria Journal, 18(1), 1–12.
View in Google Scholar

Published

2022-06-30

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Articles