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<p>Malaria continues to be one of the deadliest diseases. It disproportionately affects the African region and imposes a substantial public health burden. The study aims to investigate the effects of climate variables on malaria in Africa. Spatiotemporal trends analysis for climatic variables and malaria incidence (MI) assessed by Mann-Kendall and Sen’s slope estimator tests. The study employed spatiotemporal correlation analysis to investigate association between climatic variable and malaria incidence. Regression analysis is used to identify impacts of Temperature (T), Rainfall (RF), and Relative Humidity (RH) on malaria occurrence. Results indicate a decline in malaria (MI) and estimated malaria mortality (EMM) in Africa from 2000 to 2019 and increase in 2020. It shows Sub-Saharan African countries had a positive association between RF and MI. T and RF is significantly associated with the mortality rates among individuals aged above 5, while RH exhibited less association with mortality rate. Rainfall significantly affects malaria over other climate factors. Combined effect of RF, RH and T account to 59% MI variation. Every 100&#xa0;m increase in RF increases MI by 0.13%, and RH extreme effect matters significantly. This study indicates climate variables significantly affect malaria transmission in sub-Saharan Africa. Integration of climate monitoring with epidemiological surveillance is important for developing early warning systems and incorporating climatic influences into malaria prevention strategies for Africa.</p>

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Effects of climate change on the transmission of malaria in Africa

  • 期刊论文

  • 发表日期：

    2025年7月29日

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  • Dereba Muleta Megersa,
  • Mulualem Abera,
  • Tizazu Geremew,
  • Rida Zainab,
  • Xiao-San Luo

摘要

Malaria continues to be one of the deadliest diseases. It disproportionately affects the African region and imposes a substantial public health burden. The study aims to investigate the effects of climate variables on malaria in Africa. Spatiotemporal trends analysis for climatic variables and malaria incidence (MI) assessed by Mann-Kendall and Sen’s slope estimator tests. The study employed spatiotemporal correlation analysis to investigate association between climatic variable and malaria incidence. Regression analysis is used to identify impacts of Temperature (T), Rainfall (RF), and Relative Humidity (RH) on malaria occurrence. Results indicate a decline in malaria (MI) and estimated malaria mortality (EMM) in Africa from 2000 to 2019 and increase in 2020. It shows Sub-Saharan African countries had a positive association between RF and MI. T and RF is significantly associated with the mortality rates among individuals aged above 5, while RH exhibited less association with mortality rate. Rainfall significantly affects malaria over other climate factors. Combined effect of RF, RH and T account to 59% MI variation. Every 100 m increase in RF increases MI by 0.13%, and RH extreme effect matters significantly. This study indicates climate variables significantly affect malaria transmission in sub-Saharan Africa. Integration of climate monitoring with epidemiological surveillance is important for developing early warning systems and incorporating climatic influences into malaria prevention strategies for Africa.