Evolution of an asymptomatic first stage of infection in a heterogeneous population

Author:

Saad-Roy Chadi M.1ORCID,Grenfell Bryan T.23,Levin Simon A.2,van den Driessche P.4,Wingreen Ned S.5

Affiliation:

1. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA

2. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA

3. Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA

4. Department of Mathematics and Statistics, University of Victoria, Victoria, British Columbia, Canada

5. Department of Molecular Biology, Princeton University, Princeton, NJ, USA

Abstract

Pathogens evolve different life-history strategies, which depend in part on differences in their host populations. A central feature of hosts is their population structure (e.g. spatial). Additionally, hosts themselves can exhibit different degrees of symptoms when newly infected; this latency is a key life-history property of pathogens. With an evolutionary-epidemiological model, we examine the role of population structure on the evolutionary dynamics of latency. We focus on specific power-law-like formulations for transmission and progression from the first infectious stage as a function of latency, assuming that the across-group to within-group transmission ratio increases if hosts are less symptomatic. We find that simple population heterogeneity can lead to local evolutionarily stable strategies (ESSs) at zero and infinite latency in situations where a unique ESS exists in the corresponding homogeneous case. Furthermore, there can exist more than one interior evolutionarily singular strategy. We find that this diversity of outcomes is due to the (possibly slight) advantage of across-group transmission for pathogens that produce fewer symptoms in a first infectious stage. Thus, our work reveals that allowing individuals without symptoms to travel can have important unintended evolutionary effects and is thus fundamentally problematic in view of the evolutionary dynamics of latency.

Funder

Centers for Disease Control and Prevention

James S. McDonnell Foundation

Natural Sciences and Engineering Research Council of Canada

National Institutes of Health

Gift from Google, LLC

National Science Foundation

C3.ai Digital Transformation Institute and Microsoft Corporation

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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