Journal article
Contact-number-driven virus evolution: a multi-level modeling framework for the evolution of acute or persistent RNA virus infection
- Abstract:
- Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.6MB, Terms of use)
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- Publisher copy:
- 10.1371/journal.pcbi.1011173
Authors
- Publisher:
- Public Library of Science
- Journal:
- PLoS Computational Biology More from this journal
- Volume:
- 19
- Issue:
- 5
- Article number:
- e1011173
- Place of publication:
- United States
- Publication date:
- 2023-05-30
- Acceptance date:
- 2023-05-10
- DOI:
- EISSN:
-
1553-7358
- ISSN:
-
1553-734X
- Pmid:
-
37253076
- Language:
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English
- Keywords:
- Pubs id:
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1357294
- Local pid:
-
pubs:1357294
- Deposit date:
-
2023-09-09
Terms of use
- Copyright holder:
- Sunagawa et al.
- Copyright date:
- 2023
- Rights statement:
- © 2023 Sunagawa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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