Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Brisbane 4006, Australia.
School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
Environ Res. 2018 Apr;162:203-210. doi: 10.1016/j.envres.2017.12.021. Epub 2018 Jan 30.
The proportion of imported malaria cases in China has increased over recent years, and has presented challenges for the malaria elimination program in China. However, little is known about the geographic distribution and environmental suitability for malaria transmission under projected climate change scenarios.
Using the MaxEnt model based on malaria presence-only records, we produced environmental suitability maps and examined the relative contribution of topographic, demographic, and environmental risk factors for P. vivax and P. falciparum malaria in China.
The MaxEnt model estimated that environmental suitability areas (ESAs) for malaria cover the central, south, southwest, east and northern regions, with a slightly wider range of ESAs extending to the northeast region for P. falciparum. There was spatial agreement between the location of imported cases and area environmentally suitable for malaria transmission. The ESAs of P. vivax and P. falciparum are projected to increase in some parts of southwest, south, central, north and northeast regions in the 2030s, 2050s, and 2080s, by a greater amount for P. falciparum under the RCP8.5 scenario. Temperature and NDVI values were the most influential in defining the ESAs for P. vivax, and temperature and precipitation the most influential for P. falciparum malaria.
This study estimated that the ESA for malaria transmission in China will increase with climate change and highlights the potential establishment of further local transmission. This model should be used to support malaria control by targeting areas where interventions on malaria transmission need to be enhanced.
近年来，中国输入性疟疾病例比例有所增加，给中国消除疟疾规划带来了挑战。然而，对于在预计的气候变化情景下疟疾传播的地理分布和环境适宜性，人们知之甚少。
我们使用基于疟疾存在记录的最大熵模型，制作了环境适宜性地图，并研究了地形、人口统计学和环境风险因素对中国间日疟原虫和恶性疟原虫疟疾的相对贡献。
最大熵模型估计，疟疾的环境适宜区（ESA）覆盖了中国的中部、南部、西南部、东部和北部地区，而恶性疟原虫的 ESA 范围稍宽，延伸到东北地区。输入性疟疾病例的位置与疟疾传播的环境适宜区之间存在空间一致性。在 2030 年代、2050 年代和 2080 年代，间日疟原虫和恶性疟原虫的 ESA 在西南、南部、中部、北部和东北地区的某些地区预计会增加，而在 RCP8.5 情景下，恶性疟原虫的增加幅度更大。温度和 NDVI 值对间日疟原虫的 ESA 定义影响最大，而温度和降水对恶性疟原虫疟疾的影响最大。
本研究估计，随着气候变化，中国疟疾传播的 ESA 将增加，并强调了可能会出现进一步的本地传播。应使用该模型来支持疟疾控制，针对需要加强疟疾传播干预的地区。
