A double bootstrap data envelopment analysis model for evaluating malaria spending efficiency in Sub-Saharan Africa

Abstract

Malaria is a major cause of morbidity and mortality in many countries in sub-Saharan Africa. The main objective of this study was to examine malaria spending efficiency and its associated factors in sub-Saharan Africa by employing a two-stage double bootstrap data envelopment analysis (DEA). In the first stage, technical efficiency scores are estimated using the output-oriented variable returns to the scale (VRS) framework. In the second stage, the double bootstrap DEA model is used to identify the environmental variables that affect malaria spending efficiency. We estimate the overall malaria spending efficiency score over the study period. This estimate suggests that malaria treatment and prevention outcomes can improve significantly. We find a significant association between efficiency and education, temperature levels, nurses’ and midwives’ density, and the proportion of children of age five who slept in insecticide-treated bed nets. We conclude that policymakers must not only be concerned with improving educational outcomes but also consider ways to mitigate the effects of climate change and improve access to healthcare services.

Keywords

• Data envelopment analysis
• Double bootstrap
• Malaria spending efficiency
• Environmental factors
• Sub-Saharan Africa