ArticleGeoJournal2023
Spatial modelling of malaria prevalence associated with geographical factors in Houet province of Burkina Faso, West Africa.
Article in GeoJournal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Variance partitioning reveals contrasting random effect contributions to the density and species composition of malaria-transmitting mosquitoes in western Burkina Faso.Parasites & vectors · 2026Article
- Mapping the COVID-19 pandemic in Burkina Faso: spatial patterns, socioeconomic factors, and public health implications.International journal of health geographics · 2026Article
- How do recurrent malaria infections occur in clinical cohorts: a mathematical modelling study to support study planning.Malaria journal · 2025Article
- Spatiotemporal patterns and climate-induced macroeconomic burden of malaria in sub-Saharan Africa.BMC public health · 2025Article
- Malaria hotspots and risk factors among children under-five years of age across eight West African countries: A geospatial analysis of DHS data.MalariaWorld journal · 2025Article
- Impact of Climate Variability and Interventions on Malaria Incidence and Forecasting in Burkina Faso.International journal of environmental research and public health · 2024Article
- Relative effects of climate factors and malaria control interventions on changes of parasitaemia risk in Burkina Faso from 2014 to 2017/2018.BMC infectious diseases · 2024Article
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Authors and funding
6 authors.
Funding
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Abstract
Malaria is a permanent threat to health in western Burkina Faso. Research has shown that geographical variables contribute to the spatial distribution in its transmission. The objective of this study is to assess the relationship between malaria prevalence and potential explanatory geographical variables in the Houet province in Burkina Faso. Statistics on malaria prevalence registered by health centres in the Houet province in 2017 and potential geographical variables identified through a literature review were collected. An Ordinary Least Squares (OLS) regression was used to identify key geographical variables and to measure their association with malaria while the Getis Ord Gi* index was used to locate malaria hotspots. The results showed that average annual temperature, vegetation density, percentage of clay in the soil, total annual rainfall and distance to the nearest waterbody are the main variables associated with malaria prevalence. These variables account for two-thirds of the spatial variability of malaria prevalence observed in Houet province. The intensity and direction of the relationship between malaria prevalence and geographical factors vary according to the variable. Hence, only vegetation density is positively correlated with malaria prevalence. Average temperature, for soil clay content, annual rainfall and for distance to the nearest water body are negatively correlated with the disease prevalence. These results show that even in an endemic area, malaria prevalence has significant spatial variation. The results could contribute to the choice of intervention sites, as this choice is crucial for reducing the malaria burden. Supplementary Information: The online version contains supplementary material available at 10.1007/s10708-022-10692-7.
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