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The effects of social structure and sex-biased transmission on macroparasite infection

Published online by Cambridge University Press:  25 September 2008

S. E. PERKINS ,
M. F. FERRARI  and
P. J. HUDSON
S. E. PERKINS*
Affiliation:
Center for Infectious Disease Dynamics, 208 Mueller Laboratory, Penn State University, State College, PA 16803, USA
M. F. FERRARI
Affiliation:
Center for Infectious Disease Dynamics, 208 Mueller Laboratory, Penn State University, State College, PA 16803, USA
P. J. HUDSON
Affiliation:
Center for Infectious Disease Dynamics, 208 Mueller Laboratory, Penn State University, State College, PA 16803, USA
*
*Corresponding Author: Dr. Sarah Perkins, Center for Infectious Disease Dynamics, 208 Mueller Laboratory, Penn State University, State College, PA 16803, USA. Tel: (001) 814-863-2099. Fax: (001) 814-865-9131. E-mail: [email protected]
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Summary

Mathematical models of disease dynamics tend to assume that individuals within a population mix at random and so transmission is random, and yet, in reality social structure creates heterogeneous contact patterns. We investigated the effect of heterogeneity in host contact patterns on potential macroparasite transmission by first quantifying the level of assortativity in a socially structured wild rodent population (Apodemus flavicollis) with respect to the directly-transmitted macroparasitic helminth, Heligmosomoides polygyrus. We found the population to be disassortatively mixed (i.e. male mice mixing with female mice more often than same sex mixing) at a constant level over time. The macroparasite H. polygyrus has previously been shown to exhibit male-biased transmission so we used a Susceptible-Infected (SI) mathematical model to simulate the effect of increasing strengths of male-biased transmission on the prevalence of the macroparasite using empirically-derived transmission networks. When transmission was equal between the sexes the model predicted macroparasite prevalence to be 73% and infection was male biased (82% of infection in the male mice). With a male-bias in transmission ten times that of the females, the expected macroparasite prevalence was 50% and was equally prevalent in both sexes, results that both most closely resembled empirical dynamics. As such, disassortative mixing alone did not produce macroparasite dynamics analogous to those from empirical observations; a strong male-bias in transmission was also required. We discuss the relevance of our results in the context of network models for transmission dynamics and control.

Keywords

social networksassortative mixingHeligmosomoides polygyrusApodemus flavicollismacroparasite transmissionhelminthssex-biased transmission
Type
Research Article
Information
Parasitology , Volume 135 , Special Issue 13: Mathematical modelling of parasitic infections: from data and parameter estimation to evolutionary implications , November 2008 , pp. 1561 - 1569
Copyright
Copyright © 2008 Cambridge University Press

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