Attributing Climate Conditions for Stable Malaria Transmission to Human Activity in sub-Saharan Africa

Abstract:

Temperature and precipitation limit areas of stable malaria transmission, but the effects of climate change on the disease remain controversial. Previously, studies have not separated the influence of anthropogenic climate change and natural variability, despite being an essential step in the attribution of climate change impacts. Ensembles of 2900 simulations of regional climate in sub-Saharan Africa for the year 2013, one representing realistic conditions and the other how climate might have been in the absence of human influence, were used to force a P.falciparium climate suitability model developed by the Mapping Malaria Risk in Africa project. Strongest signals were detected in areas of unstable transmission, indicating their heightened sensitivity to climatic factors. Evidently, impacts of human-induced climate change were unevenly distributed: the probability of conditions being suitable for stable malaria transmission were substantially reduced (increased) in the Sahel (Greater Horn of Africa (GHOA), particularly in the Ethiopian and Kenyan highlands). The length of the transmission season was correspondingly shortened in the Sahel and extended in the GHOA, by 1 to 2 months, including in Kericho (Kenya), where the role of climate change in driving recent malaria occurrence is hotly contested. Human-induced warming was primarily responsible for positive anomalies in the GHOA, while reduced rainfall caused negative anomalies in the Sahel. The latter was associated with anthropogenic impacts on the West African Monsoon, but uncertainty in the RCM’s ability to reproduce precipitation trends in the region weakens confidence in the result. That said, outputs correspond well with broad-scale changes in observed endemicity, implying a potentially important contribution of anthropogenic climate change to the malaria burden during the past century. Results support the health-framing of climate risk and help indicate hotspots of climate vulnerability, providing information to direct control interventions and investment, and allude to climate injustices. Extending methods, such as by using multiple climate and malaria models and investigating trends over longer timescales, would make results more generally applicable and improve their policy relevance.