Format

Send to

Choose Destination
PLoS Comput Biol. 2013;9(12):e1003327. doi: 10.1371/journal.pcbi.1003327. Epub 2013 Dec 12.

Heterogeneity, mixing, and the spatial scales of mosquito-borne pathogen transmission.

Author information

1
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.
2
Center for Disease Dynamics, Economics and Policy, Washington, D.C., United States of America.
3
Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America ; Center for Disease Dynamics, Economics and Policy, Washington, D.C., United States of America ; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.

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, 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.

PMID:
24348223
PMCID:
PMC3861021
DOI:
10.1371/journal.pcbi.1003327
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Public Library of Science Icon for PubMed Central
Loading ...
Support Center