Franzke Christian L E, Parihar Ruchi Singh
Center for Climate Physics Institute for Basic Science Busan South Korea.
Department of Integrated Climate System Sciences Pusan National University Busan South Korea.
Geohealth. 2025 Jun 19;9(6):e2025GH001356. doi: 10.1029/2025GH001356. eCollection 2025 Jun.
The spread of malaria is a major health burden, which affects many people in Africa, depends on climate but also socio-economic conditions. Thus, it is important to gauge the impact of anthropogenic global warming on malaria and attribute anthropogenic causes. Here we compute the Time Of Emergence of vector density and of the entomological inoculation rate (EIR) in the SSP3-7.0 scenario using 50 bias-corrected members of Community Earth System Model version 2 Large Ensemble simulations. This reveals that vector density, which depends on climate conditions, and EIR, which depends on both climate and population density, will rise significantly and permanently above the pre-industrial background variability due to anthropogenic causes in Africa. Both the vector density and EIR have areas, mainly in central Africa, where anthropogenic causes have already significantly changed, and many more areas will experience anthropogenic caused changes in the period 2030-2050 and toward the end of this century. Our simulations also show clear evidence that extremes of vector density and EIR increase in the future by almost 100%, suggesting that major malaria epidemic outbreaks will become much more likely. We also perform simulations with constant population and with no global warming which partly reveal underlying malaria dynamics. Our results highlight the need to prepare for an expansion and intensification of the malaria burden if no health interventions are being taken.
疟疾的传播是一项重大的健康负担，影响着非洲许多人，它不仅取决于气候，还取决于社会经济条件。因此，评估人为全球变暖对疟疾的影响并确定人为原因很重要。在这里，我们使用社区地球系统模型版本2大集合模拟的50个偏差校正成员，计算了SSP3-7.0情景下病媒密度和昆虫接种率（EIR）的出现时间。这表明，由于非洲的人为原因，依赖气候条件的病媒密度和依赖气候及人口密度的EIR将显著且永久地高于工业化前的背景变率。病媒密度和EIR都有一些区域，主要在中非，人为原因已经使这些区域发生了显著变化，在2030年至2050年期间以及本世纪末，还会有更多区域将经历人为导致的变化。我们的模拟还清楚地表明，未来病媒密度和EIR的极值将增加近100%，这表明疟疾大规模流行爆发的可能性将大大增加。我们还进行了人口不变且无全球变暖情况下的模拟，这部分揭示了潜在的疟疾动态。我们的结果强调，如果不采取健康干预措施，就需要为疟疾负担的扩大和加剧做好准备。
