School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia.
The Kids Research Institute Australia, Perth Children's Hospital, Nedlands, Australia.
Malar J. 2024 Oct 10;23(1):306. doi: 10.1186/s12936-024-05122-7.
Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control. Previous work has developed mathematical models and global maps for the suitability of temperature for malaria transmission. In this paper, existing temperature-based models are extended to include two other important bioclimatic factors: humidity and rainfall. This model is combined with fine spatial resolution climatic data to produce a more biologically-realistic global map of climatic suitability for Plasmodium falciparum malaria. The climatic suitability index developed corresponds more closely than previous temperature suitability indices with the global distribution of P. falciparum malaria. There is weak agreement between the Malaria Atlas Project estimates of P. falciparum prevalence in Africa and the estimates of suitability solely based on temperature (Spearman Correlation coefficient of ). The addition of humidity and then rainfall improves the comparison ( when humidity added; when both humidity and rainfall added). By incorporating the impacts of humidity and rainfall, this model identifies arid regions that are not climatically suitable for transmission of P. falciparum malaria. Incorporation of this improved index of climatic suitability into geospatial models can improve global estimates of malaria prevalence and transmission intensity.
气候条件是疟疾传播强度的关键决定因素，其通过影响寄生虫和其蚊子媒介来实现。将气候条件与疟疾传播相关联的数学模型可用于开发疟疾气候适宜性的空间图。这些地图是量化人类疟疾分布和负担的努力的基础，使监测和控制得到改进。先前的工作已经开发了用于疟疾传播温度适宜性的数学模型和全球地图。在本文中，现有的基于温度的模型扩展到包括另外两个重要的生物气候因素：湿度和降雨。该模型与精细的空间分辨率气候数据相结合，生成了更符合生物学实际的全球按蚊疟疾病媒气候适宜性地图。开发的气候适宜性指数与按蚊疟疾病媒的全球分布更为吻合，与先前的温度适宜性指数相比，与按蚊疟疾病媒的全球分布更为吻合。非洲疟疾地图项目对恶性疟原虫流行率的估计与仅基于温度的估计之间存在较弱的一致性（Spearman 相关系数为 ）。湿度和降雨的加入改善了这种比较（湿度加入时为 ；湿度和降雨均加入时为 ）。通过纳入湿度和降雨的影响，该模型确定了干旱地区不适合传播恶性疟原虫疟疾。将这种改进的气候适宜性指数纳入地理空间模型可以提高疟疾流行率和传播强度的全球估计。
