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Antigenic Diversity, Transmission Mechanisms, and the Evolution of Pathogens

Overview of attention for article published in PLoS Computational Biology, October 2009
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Title
Antigenic Diversity, Transmission Mechanisms, and the Evolution of Pathogens
Published in
PLoS Computational Biology, October 2009
DOI 10.1371/journal.pcbi.1000536
Pubmed ID
Authors

Alexander Lange, Neil M. Ferguson

Abstract

Pathogens have evolved diverse strategies to maximize their transmission fitness. Here we investigate these strategies for directly transmitted pathogens using mathematical models of disease pathogenesis and transmission, modeling fitness as a function of within- and between-host pathogen dynamics. The within-host model includes realistic constraints on pathogen replication via resource depletion and cross-immunity between pathogen strains. We find three distinct types of infection emerge as maxima in the fitness landscape, each characterized by particular within-host dynamics, host population contact network structure, and transmission mode. These three infection types are associated with distinct non-overlapping ranges of levels of antigenic diversity, and well-defined patterns of within-host dynamics and between-host transmissibility. Fitness, quantified by the basic reproduction number, also falls within distinct ranges for each infection type. Every type is optimal for certain contact structures over a range of contact rates. Sexually transmitted infections and childhood diseases are identified as exemplar types for low and high contact rates, respectively. This work generates a plausible mechanistic hypothesis for the observed tradeoff between pathogen transmissibility and antigenic diversity, and shows how different classes of pathogens arise evolutionarily as fitness optima for different contact network structures and host contact rates.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 4%
United States 4 4%
Kenya 1 <1%
Australia 1 <1%
Brazil 1 <1%
France 1 <1%
India 1 <1%
Vietnam 1 <1%
Afghanistan 1 <1%
Other 1 <1%
Unknown 95 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 29%
Student > Ph. D. Student 19 17%
Professor 12 11%
Student > Bachelor 11 10%
Student > Master 10 9%
Other 22 20%
Unknown 5 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 45%
Medicine and Dentistry 12 11%
Biochemistry, Genetics and Molecular Biology 8 7%
Mathematics 6 5%
Immunology and Microbiology 4 4%
Other 19 17%
Unknown 13 12%