Malaria risk mapping among children under five in Togo

Abstract

Malaria is a major health threat in sub-Sahara Africa, especially for children under five. However, there is considerable heterogeneity between areas in malaria risk reported, associated with environmental and climatic. We used data from Togo to explore spatial patterns of malaria incidence. Geospatial covariate datasets, including climatic and environmental variables from the 2017 Malaria Indicator Survey in Togo, were used for this study. The association between malaria incidence and ecological predictors was assessed using three regression techniques, namely the Ordinary Least Squares (OLS), spatial lag model (SLM), and spatial error model (SEM). A total of 171 clusters were included in the survey and provided data on environmental and climate variables. Spatial autocorrelation showed that the distribution of malaria incidence was not random and revealed significant spatial clustering. Mean temperature, precipitation, aridity and proximity to water bodies showed a significant and direct association with malaria incidence rate in the SLM model, which best fitted the data according to AIC. Five malaria incidence hotspots were identified. Malaria incidence is spatially clustered in Togo associated with climatic and environmental factors. The results can contribute to the development of specific malaria control plans taking geographical variation into consideration and targeting transmission hotspots.