Evidence map›Paper›PMID 40100637›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Epidemic evolutionarily stable strategies within an age-structured host population.

Andreas Eilersen, Ottar N Bjørnstad, Ruiyun Li, Sebastian J Schreiber, Zeyuan Pei, Nils Chr Stenseth

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Epidemic evolutionarily stable strategies within an age-structured host population.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Andreas EilersenTheoretical Biology Group, Department of Environmental Systems Science, ETH Zürich, Zürich 8092, Switzerland.ORCID 0000-0003-1451-7564
Ottar N BjørnstadDepartment of Entomology, Pennsylvania State University, University Park, PA 16802.ORCID 0000-0002-1158-3753
Ruiyun LiCentre for Ecological and Evolutionary Synthesis, Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo 0371, Norway.
Sebastian J SchreiberDepartment of Evolution and Ecology, University of California, Davis, CA 95616.
Zeyuan PeiCentre for Pandemics and One-Health Research, Sustainable Health Unit, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo 0316, Norway.
Nils Chr StensethCentre for Ecological and Evolutionary Synthesis, Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo 0371, Norway.ORCID 0000-0002-1591-5399

Funding

Danmarks Grundforskningsfond (DNRF) DNRF170EC | ERC | HORIZON EUROPE European Research Council (ERC) 740704National Science Foundation (NSF) DEB22043076NordForsk 104910Research Council of Norway 312740
6 · The paper itself

Abstract

To understand infectious disease dynamics, we need to understand the inextricably intertwined nature of the ecology and evolution of pathogens and hosts. Epidemiological dynamics of many infectious diseases have highlighted the importance of considering the demographics of the societies in which they spread, particularly with respect to age structure. In addition, the waves of the recent COVID-19 pandemic driven by variant replacements at an unprecedented speed show that it is vital to consider the evolutionary aspects. The classic trade-off theory of virulence addresses aspects of pathogen evolution, but here we explore in more detail the possibility of society-specific evolutionarily stable strategies (ESS) during an unfolding pandemic. Theory posits the existence under some conditions of an ESS representing the evolutionary endpoint of change. By using a demographically realistic model incorporating infection rates that vary with age, we outline which evolutionary scenarios are plausible. Focusing on the rate of infection and duration of infectivity, we ask whether an ESS exists, what characterizes it, and as a result which long-term public-health consequences may be expected. We demonstrate that the ESS of an evolving pathogen depends upon the background age-dependent frailty and mortality rates. Our findings shed important light on the plausible long-term trajectories of highly evolvable novel pathogens.

Indexed as

Biological EvolutionCOVID-19SARS-CoV-2Age FactorsHumansPandemicsdemographicsepidemiologyevolutionmodellingtrade-off

Identifiers

PMID40100637
PMCPMC11962425

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.