Superspreading and the evolution of virulence

Superspreading, where a small proportion of a population can cause a high proportion of infection transmission, is well known to be important to the epidemiology of a wide range of pathogens, including SARS-CoV-2. However, despite its ubiquity in important human and animal pathogens, the impact of superspreading on the evolution of pathogen virulence is not well understood. Using theory and both deterministic and stochastic simulations we examine the evolution of pathogen virulence under a range of different distributions of infection transmission for the host. Importantly, for many pathogens, superpreader events may be associated with increased tolerance to infection or asymptomatic infection and when we account for this superspreading selects for higher virulence. In contrast, in animal populations where highly connected individuals, that are linked to superspreader events, also have fitness benefits, superspreading may select for milder pathogens. In isolation, the transmission distribution of the host does not impact selection for pathogen virulence. However, superspreading reduces the rate of pathogen evolution and generates considerable variation in pathogen virulence. Therefore, the adaptation of an emerging infectious disease, that exhibits superspreading, is likely to be slowed and characterised by the maintenance of maladaptive variants. Taken as a whole, our results show that superspreading can have important impacts on the evolution of pathogens.

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Publication Details

Journal
PLoS Computational Biology
Published
2025-10-09
DOI
https://doi.org/10.1371/journal.pcbi.1013517
Primary Topic
Evolution and Genetic Dynamics
Type
article
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article

Superspreading and the evolution of virulence

Mike Boots, Xander O’Neill, P. Signe White, Graham R. Northrup et al.
PLoS Computational Biology
Evolution and Genetic Dynamics
article

Superspreading and the evolution of virulence

Mike Boots, Xander O’Neill, P. Signe White, Graham R. Northrup, Chadi M. Saad-Roy, A. R. White
article en

Abstract

Superspreading, where a small proportion of a population can cause a high proportion of infection transmission, is well known to be important to the epidemiology of a wide range of pathogens, including SARS-CoV-2. However, despite its ubiquity in important human and animal pathogens, the impact of superspreading on the evolution of pathogen virulence is not well understood. Using theory and both deterministic and stochastic simulations we examine the evolution of pathogen virulence under a range of different distributions of infection transmission for the host. Importantly, for many pathogens, superpreader events may be associated with increased tolerance to infection or asymptomatic infection and when we account for this superspreading selects for higher virulence. In contrast, in animal populations where highly connected individuals, that are linked to superspreader events, also have fitness benefits, superspreading may select for milder pathogens. In isolation, the transmission distribution of the host does not impact selection for pathogen virulence. However, superspreading reduces the rate of pathogen evolution and generates considerable variation in pathogen virulence. Therefore, the adaptation of an emerging infectious disease, that exhibits superspreading, is likely to be slowed and characterised by the maintenance of maladaptive variants. Taken as a whole, our results show that superspreading can have important impacts on the evolution of pathogens.

PLoS Computational BiologyVol. 21(10)
University of British Columbia (CA), Miller College (US), Heriot-Watt University (GB), University of Chicago (US), Maxwell Institute for Mathematical Sciences (GB), University of California, Berkeley (US)
Openalex Percentile: Top 70%
Evolution and Genetic Dynamics
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