Evidence map›Paper›PMID 32385153›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Dynamics in a simple evolutionary-epidemiological model for the evolution of an initial asymptomatic infection stage.

Chadi M Saad-Roy, Ned S Wingreen, Simon A Levin, Bryan T Grenfell

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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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

15 citing papers 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
  2. The evolution of post-infection mortality.Proceedings. Biological sciences · 2024
    Article
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  13. Modeling of COVID-19 propagation with compartment models.Mathematische Semesterberichte · 2021
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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

4 authors.

Chadi M Saad-RoyLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544; csaadroy@princeton.edu slevin@princeton.edu grenfell@princeton.edu.
Ned S WingreenLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544.
Simon A LevinDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544; csaadroy@princeton.edu slevin@princeton.edu grenfell@princeton.edu.ORCID 0000-0002-8216-5639
Bryan T GrenfellDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544; csaadroy@princeton.edu slevin@princeton.edu grenfell@princeton.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogens exhibit a rich variety of life history strategies, shaped by natural selection. An important pathogen life history characteristic is the propensity to induce an asymptomatic yet productive (transmissive) stage at the beginning of an infection. This characteristic is subject to complex trade-offs, ranging from immunological considerations to population-level social processes. We aim to classify the evolutionary dynamics of such asymptomatic behavior of pathogens (hereafter "latency") in order to unify epidemiology and evolution for this life history strategy. We focus on a simple epidemiological model with two infectious stages, where hosts in the first stage can be partially or fully asymptomatic. Immunologically, there is a trade-off between transmission and progression in this first stage. For arbitrary trade-offs, we derive different conditions that guarantee either at least one evolutionarily stable strategy (ESS) at zero, some, or maximal latency of the first stage or, perhaps surprisingly, at least one unstable evolutionarily singular strategy. In this latter case, there is bistability between zero and nonzero (possibly maximal) latency. We then prove the uniqueness of interior evolutionarily singular strategies for power-law and exponential trade-offs: Thus, bistability is always between zero and maximal latency. Overall, previous multistage infection models can be summarized with a single model that includes evolutionary processes acting on latency. Since small changes in parameter values can lead to abrupt transitions in evolutionary dynamics, appropriate disease control strategies could have a substantial impact on the evolution of first-stage latency.

Indexed as

Biological EvolutionDisease ProgressionDisease Transmission, InfectiousModels, BiologicalAsymptomatic InfectionsHost-Pathogen InteractionsHumansVirus Diseasesasymptomatic infection stageevolutionary analysispathogen life history strategies

Identifiers

PMID32385153
PMCPMC7261016

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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.