Eikenberry Steffen E, Gumel Abba B
Global Security Initiative, Arizona State University, Tempe, AZ, USA.
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA.
J Math Biol. 2018 Oct;77(4):857-933. doi: 10.1007/s00285-018-1229-7. Epub 2018 Apr 24.
Malaria, one of the greatest historical killers of mankind, continues to claim around half a million lives annually, with almost all deaths occurring in children under the age of five living in tropical Africa. The range of this disease is limited by climate to the warmer regions of the globe, and so anthropogenic global warming (and climate change more broadly) now threatens to alter the geographic area for potential malaria transmission, as both the Plasmodium malaria parasite and Anopheles mosquito vector have highly temperature-dependent lifecycles, while the aquatic immature Anopheles habitats are also strongly dependent upon rainfall and local hydrodynamics. A wide variety of process-based (or mechanistic) mathematical models have thus been proposed for the complex, highly nonlinear weather-driven Anopheles lifecycle and malaria transmission dynamics, but have reached somewhat disparate conclusions as to optimum temperatures for transmission, and the possible effect of increasing temperatures upon (potential) malaria distribution, with some projecting a large increase in the area at risk for malaria, but others predicting primarily a shift in the disease's geographic range. More generally, both global and local environmental changes drove the initial emergence of P. falciparum as a major human pathogen in tropical Africa some 10,000 years ago, and the disease has a long and deep history through the present. It is the goal of this paper to review major aspects of malaria biology, methods for formalizing these into mathematical forms, uncertainties and controversies in proper modeling methodology, and to provide a timeline of some major modeling efforts from the classical works of Sir Ronald Ross and George Macdonald through recent climate-focused modeling studies. Finally, we attempt to place such mathematical work within a broader historical context for the "million-murdering Death" of malaria.
疟疾是人类历史上最致命的杀手之一,每年仍导致约50万人死亡,几乎所有死亡都发生在热带非洲的五岁以下儿童身上。这种疾病的传播范围受气候限制,仅限于全球较温暖的地区,因此人为导致的全球变暖(以及更广泛的气候变化)现在有可能改变疟疾潜在传播的地理区域,因为疟原虫和按蚊病媒的生命周期都高度依赖温度,而按蚊幼虫的水生栖息地也强烈依赖降雨和当地水动力。因此,针对复杂、高度非线性的天气驱动的按蚊生命周期和疟疾传播动态,已经提出了各种各样基于过程(或机理)的数学模型,但对于传播的最佳温度以及温度升高对(潜在)疟疾分布的可能影响,得出了有些不同的结论,一些模型预测疟疾风险区域将大幅增加,而另一些模型则主要预测疾病地理范围的转移。更一般地说,全球和局部环境变化推动了恶性疟原虫约1万年前在热带非洲首次成为主要人类病原体,并且这种疾病一直延续至今,有着悠久而深远的历史。本文的目的是回顾疟疾生物学的主要方面、将这些方面形式化纳入数学形式的方法、适当建模方法中的不确定性和争议,并提供从罗纳德·罗斯爵士和乔治·麦克唐纳的经典著作到最近以气候为重点的建模研究等一些主要建模工作的时间线。最后,我们试图将此类数学工作置于疟疾“百万谋杀死亡”这一更广泛的历史背景中。