Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America ; Department of Entomology, University of California, Davis, California, United States of America.
Center for Disease Dynamics, Economics and Policy, Washington, D.C., United States of America.
PLoS Comput Biol. 2013;9(12):e1003327. doi: 10.1371/journal.pcbi.1003327. Epub 2013 Dec 12.
The Ross-Macdonald model has dominated theory for mosquito-borne pathogen transmission dynamics and control for over a century. The model, like many other basic population models, makes the mathematically convenient assumption that populations are well mixed; i.e., that each mosquito is equally likely to bite any vertebrate host. This assumption raises questions about the validity and utility of current theory because it is in conflict with preponderant empirical evidence that transmission is heterogeneous. Here, we propose a new dynamic framework that is realistic enough to describe biological causes of heterogeneous transmission of mosquito-borne pathogens of humans, yet tractable enough to provide a basis for developing and improving general theory. The framework is based on the ecological context of mosquito blood meals and the fine-scale movements of individual mosquitoes and human hosts that give rise to heterogeneous transmission. Using this framework, we describe pathogen dispersion in terms of individual-level analogues of two classical quantities: vectorial capacity and the basic reproductive number, R0. Importantly, this framework explicitly accounts for three key components of overall heterogeneity in transmission: heterogeneous exposure, poor mixing, and finite host numbers. Using these tools, we propose two ways of characterizing the spatial scales of transmission--pathogen dispersion kernels and the evenness of mixing across scales of aggregation--and demonstrate the consequences of a model's choice of spatial scale for epidemic dynamics and for estimation of R0, both by a priori model formulas and by inference of the force of infection from time-series data.
罗斯-麦克唐纳模型主导了蚊媒病原体传播动力学和控制理论一个多世纪。该模型与许多其他基本人口模型一样,做出了数学上方便的假设,即种群是充分混合的;也就是说,每只蚊子都有可能同等地叮咬任何脊椎动物宿主。这个假设引发了关于当前理论的有效性和实用性的问题,因为它与普遍的经验证据相矛盾,即传播是异质的。在这里,我们提出了一个新的动态框架,它足够现实,可以描述人类蚊媒病原体传播的异质性的生物学原因,又足够易于处理,可以为开发和改进一般理论提供基础。该框架基于蚊子吸血和个体蚊子和人类宿主的微观运动的生态背景,这些因素导致了异质传播。使用这个框架,我们根据两个经典数量的个体水平类似物来描述病原体的扩散:媒介能力和基本繁殖数 R0。重要的是,这个框架明确考虑了传播中总体异质性的三个关键组成部分:异质暴露、混合不良和宿主数量有限。使用这些工具,我们提出了两种描述传播空间尺度的方法——病原体扩散核和聚合尺度上混合的均匀性——并通过先验模型公式和从时间序列数据推断感染力度来演示模型选择空间尺度对流行动态和 R0 估计的影响。