Predicting Malaria Prevalence at the Regional and Local Level: A Case Study in the Ashanti Region

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Abstract Type: Poster Abstract

Abstract

Malaria remains a leading cause of morbidity and mortality in Ghana, and it accounts for a significant proportion of outpatient visits, hospital admissions, and childhood deaths. In the Ashanti region, Up to one-third of all clinic visits and at least 25% of hospital admissions are associated with the disease, underscoring the significant effect of malaria in the region.
This study determines spatial patterns of malaria incidence at the local and regional levels. It evaluates the relative contributions of different predictor variables to malaria prevalence by combining remotely sensed data (such as rainfall, vegetation indices, land surface temperature, proximity to roads, and proximity to waterbodies) with household surveys and regional health data and identifies how these predictor variables vary on both levels using boosted regression trees (BRTs).
The results of this study will help inform public health intervention policies by prioritizing influential risk factors at the local and regional levels, contributing to more targeted malaria control strategies in Ghana.