Spatiotemporal patterns and climate-induced macroeconomic burden of malaria in sub-Saharan Africa

Abstract

Background: The global malaria burden is characterized by economic, geographical, and climatic disparities, especially in sub-Saharan Africa (SSA). Moreover, meteorological factors have become increasingly important to understand the malaria burden in SSA in the context of climate change.

Methods: Value of Statistical Life Year (VSL) and machine learning are proposed to jointly assess the weather-induced economic burden of malaria in SSA from 2000 to 2022. Geographic information systems (GIS) are employed to examine the spatial autocorrelation of malaria burden and address the issues of spatiotemporal heterogeneity. Finally, the uncertainty in the relationship between weather patterns and malaria burden was tested for robustness using Bayesian statistics.

Results: Malaria mortality in SSA has decreased by 30 per 100,000 incidences annually from 2000 to 2022. The macroeconomic burden of malaria accounts for 1.58% of the total GDP in SSA, equating to USD 497.06 billion (95% CI, [418.38, 553.56]), with weather conditions contributing 60% of the economic burden. The climate-related macroeconomic burden of malaria mortality varies dramatically across regions, with East Africa bearing the highest cost at USD 195.90 billion, followed by Central Africa (57.36 billion), West Africa (30.43 billion), and Southern Africa (1.81 billion). Besides, there is notable autocorrelation and spatial heterogeneity in malaria patterns. East Africa has a high malaria burden and is climate vulnerable. For every 1 °C increase in temperature in SSA, the number of malaria incidences will rise by 16.30 [95% Credible Interval (CrI), (13.88, 18.61)] per 1,000 incidences, while malaria-related deaths per 100,000 incidences will increase by 5.79 [95% CrI, (4.90, 6.74)].

Conclusions: Rising temperatures have increased the burden of malaria, especially in East and Central Africa. Climate change also indirectly increases the economic burden associated with malaria, which could put enormous pressure on government health budgets. Therefore, local governments in East Africa should adopt measures to cope with climate warming and allocate resources rationally to achieve the goal of malaria elimination by 2030.

Keywords: Climate change; Economic burden; GIS; Malaria mortality.

Fig. 1

Spatial clustering of malaria mortality in SSA from 2000 to 2022

Fig. 2

Spatial distributions of VSL and the economic burden of malaria mortality in 2000 and 2022

Fig. 3

The influence of meteorological factors on malaria burdens based on Bayesian statistics. The light blue area indicates the 97.5% uncertainty range for the meteorological factors