Abstract
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, . 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 , both by a priori model formulas and by inference of the force of infection from time-series data.
Highlights
IntroductionDynamic models of mosquito-borne pathogens are being used in scientific research to investigate the mechanisms and processes underlying transmission and in policy research to give advice about malaria elimination and global malaria eradication [1,2,3,4], stratification of a country to improve disease control [5,6,7,8,9], strategies for managing the evolution of resistance to insecticides and antimalarial drugs [10,11], and ideal properties, potential impact, and delivery strategies for new vaccines, drugs, and vector control technologies [5,12,13,14]
Rather than serving as a focal point for calibration, our purpose was to design a model that is flexible enough that it can serve as a tool for conducting experiments in silico to identify the biological details that are most relevant for transmission dynamics and disease control
Because here we are concerned only with dynamics within a patch, we focus on the matrix Sp, which is obtained by deleting all rows and columns of S that correspond to blood-feeding habitats outside of the focal patch p
Summary
Dynamic models of mosquito-borne pathogens are being used in scientific research to investigate the mechanisms and processes underlying transmission and in policy research to give advice about malaria elimination and global malaria eradication [1,2,3,4], stratification of a country to improve disease control [5,6,7,8,9], strategies for managing the evolution of resistance to insecticides and antimalarial drugs [10,11], and ideal properties, potential impact, and delivery strategies for new vaccines, drugs, and vector control technologies [5,12,13,14]. Mass action assumes that encounters in a very large population are so well mixed that different types interact randomly and in direct proportion to their densities. Whereas this assumption may be suitable for modeling infectious diseases in some contexts, it is important to know when the mass-action assumption breaks down. We develop a new mathematical framework capable of assessing the appropriateness of the mass-action paradigm at different spatial scales and investigating the biological heterogeneities underpinning these scaling relationships
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