Background: One of the major causes of malaria-related deaths in Sub-Saharan African countries is the limited accessibility to quality care. In these countries, malaria control activities are implemented at the health district level. However, malaria indicators are often regionally representative. This paper provides an approach for estimating health district-level malaria readiness indicators from survey data designed to provide regionally representative estimates.
Methods: A binomial hierarchical Bayesian spatial prediction method was applied to Service Availability and Readiness Assessment (SARA) survey data to provide estimates of essential equipment availability and readiness to provide malaria care at the health district level. Predicted values of each indicator were adjusted by the type of health facility, location, and population density. Then, a health district composite readiness profile was built via hierarchical ascendant classification.
Results: All surveyed health-facilities were mandated to manage malaria. The spatial distribution of essential equipment and malaria readiness was heterogeneous. Around 62.9% of health districts had a high level of readiness to provide malaria care and prevention during pregnancy. Low-performance scores for managing malaria were found in big cities located in the central and Haut-Bassins regions. The health districts with low coverage for both first-line antimalarial drugs and rapid diagnostic tests were Baskuy, Bogodogo, Boulmiougou, Nongr-Massoum, Sig-Nonghin, Dafra, and Do.
Conclusion: We provide health district estimates and reveal gaps in basic equipment and malaria management resources in some districts that need to be filled. By providing local-scale estimates, this approach could be replicated for other types of indicators to inform decision-makers and health program managers and to identify priority areas.