Evidence map›Paper›PMID 41902992›Full record

ArticleJournal of mathematical biology2026

Emergence of microbial host dormancy during a persistent virus epidemic.

Jochen Blath, András Tóbiás

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Jochen Blath *Institute of Mathematics, and C3S - Center for Critical Computational Studies, Goethe-Universität Frankfurt, Robert-Mayer-Straße 10, 60325, Frankfurt am Main, Germany.
András Tóbiás *Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Műegyetem rakpart 3., H-1111, Budapest, Hungary. tobias@cs.bme.hu.ORCID http://orcid.org/0000-0003-4881-2553

Funding

Magyar Tudományos Akadémia János Bolyai Research ScholarshipMinistry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund STARTING 149835
6 · The paper itself

Abstract

We study a minimal stochastic individual-based model for a microbial population challenged by a persistent (lytic) virus epidemic. We focus on the situation in which the resident microbial host population and the virus population are in stable coexistence upon arrival of a single new "mutant" host individual. We assume that this mutant is capable of switching to a reversible state of dormancy upon contact with virions as a means of avoiding infection by the virus. At the same time, we assume that this new dormancy trait comes with a cost, namely a reduced individual reproduction rate. We prove that there is a non-trivial range of parameters where the mutants can nevertheless invade the resident population with strictly positive probability (bounded away from 0) in the large population limit. Given the reduced reproductive rate, such an invasion would be impossible in the absence of either the dormancy trait or the virus epidemic. We explicitly characterize the parameter regime where this emergence of a host dormancy trait is possible, determine the success probability of a single invader and the typical amount of time it takes the successful mutants to reach a macroscopic population size. We conclude this study by an investigation of the fate of the population after the successful emergence of a dormancy trait. Heuristic arguments and simulations suggest that after successful invasion, either both host types and the virus will reach coexistence, or the mutants will drive the resident hosts to extinction while the virus will stay in the system.

Indexed as

EpidemicsHost Microbial InteractionsModels, BiologicalVirus DiseasesComputer SimulationHost-Pathogen InteractionsHumansMathematical ConceptsMutationStochastic ProcessesCoexistenceDormancyFounder controlHost–virus systemInvasionVirus epidemic

Identifiers

PMID41902992
PMCPMC13032982

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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.