Spatial modelling of malaria prevalence associated with geographical factors in Houet province of Burkina Faso, West Africa

• Published in: GeoJournal 2023, Vol.88 (2), p.1769-1783
• Main Authors: Millogo, Abdoul Azize, Yaméogo, Lassane, Kassié, Daouda, de Charles Ouédraogo, François, Guissou, Charles, Diabaté, Abdoulaye
• Format: Article
• Language: English
• Subjects: Annual rainfall; Averages; Clay; Clay soils; Density; Disease hot spots; Distance; Environmental Management; Geography; Health facilities; Health problems; Health risks; Human diseases; Human Geography; Life Sciences; Literature reviews; Malaria; Morbidity; Precipitation; Prevalence; Rainfall; Social Sciences; Soil temperature; Spatial analysis; Spatial distribution; Spatial variations; Statistical methods; Temperature; Variables; Vector-borne diseases; Vegetation; Water bodies
• ISSN: 1572-9893; 0343-2521; 1572-9893
• DOI: 10.1007/s10708-022-10692-7

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.