Diouf Ibrahima, Ndione Jacques-André, Gaye Amadou Thierno
Laboratoire de Physique de l'Atmosphère et de l'Océan-Siméon Fongang, Ecole Supérieure Polytechnique de l'Université Cheikh Anta Diop (UCAD), BP 5085, Dakar-Fann, Dakar 10700, Senegal.
Regional Agency for Agriculture and Food, Lomé 01 BP 4817, Togo.
Trop Med Infect Dis. 2022 Nov 1;7(11):345. doi: 10.3390/tropicalmed7110345.
Malaria is a constant reminder of the climate change impacts on health. Many studies have investigated the influence of climatic parameters on aspects of malaria transmission. Climate conditions can modulate malaria transmission through increased temperature, which reduces the duration of the parasite's reproductive cycle inside the mosquito. The rainfall intensity and frequency modulate the mosquito population's development intensity. In this study, the Liverpool Malaria Model (LMM) was used to simulate the spatiotemporal variation of malaria incidence in Senegal. The simulations were based on the WATCH Forcing Data applied to ERA-Interim data (WFDEI) used as a point of reference, and the biased-corrected CMIP6 model data, separating historical simulations and future projections for three Shared Socio-economic Pathways scenarios (SSP126, SSP245, and SSP585). Our results highlight a strong increase in temperatures, especially within eastern Senegal under the SSP245 but more notably for the SSP585 scenario. The ability of the LMM model to simulate the seasonality of malaria incidence was assessed for the historical simulations. The model revealed a period of high malaria transmission between September and November with a maximum reached in October, and malaria results for historical and future trends revealed how malaria transmission will change. Results indicate a decrease in malaria incidence in certain regions of the country for the far future and the extreme scenario. This study is important for the planning, prioritization, and implementation of malaria control activities in Senegal.
疟疾始终提醒着人们气候变化对健康的影响。许多研究调查了气候参数对疟疾传播各方面的影响。气候条件可通过升高温度来调节疟疾传播，这会缩短寄生虫在蚊子体内的繁殖周期。降雨强度和频率则调节蚊子种群的发育强度。在本研究中，利物浦疟疾模型（LMM）被用于模拟塞内加尔疟疾发病率的时空变化。模拟基于应用于ERA-临时数据的全球气候研究计划强迫数据（WFDEI）作为参考点，以及经过偏差校正的CMIP6模型数据，将历史模拟和未来预测分为三种共享社会经济路径情景（SSP126、SSP245和SSP585）。我们的结果突出显示温度大幅上升，特别是在SSP245情景下塞内加尔东部地区，但在SSP585情景下更为显著。针对历史模拟评估了LMM模型模拟疟疾发病率季节性的能力。该模型显示9月至11月期间疟疾传播高发，10月达到峰值，历史和未来趋势的疟疾结果揭示了疟疾传播将如何变化。结果表明，在遥远的未来和极端情景下，该国某些地区的疟疾发病率将会下降。本研究对于塞内加尔疟疾控制活动的规划、优先级确定和实施具有重要意义。
