ArticleeLife2025
A within-host infection model to explore tolerance and resistance.
Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Hazard curvature makes within-host variability costly for survival.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Tolerance to persistent cell-fusing agent virus infection in Aedes aegypti mosquitoes correlates with maintenance of lipid reserves.BMC biology · 2026Article
- Shielded by the dead: how killed bacteria shape the dynamics and evolution of innate immunity.bioRxiv : the preprint server for biology · 2026Article
- Layers of immunity: Deconstructing theeLife · 2025Article
- Pathogen-induced damage in Drosophila: Uncoupling disease tolerance from resistance.PLoS pathogens · 2025Article
- Pathogen growth and virulence dynamics drive the host evolution against coinfections.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Virulence decomposition for bifurcating infections.Proceedings. Biological sciences · 2023Article
- A Toll pathway effector protectsProceedings of the National Academy of Sciences of the United States of America · 2023Article
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Authors and funding
8 authors.
Funding
Abstract
How are some individuals surviving infections while others die? The answer lies in how infected individuals invest into controlling pathogen proliferation and mitigating damage, two strategies respectively called resistance and disease tolerance. Pathogen within-host dynamics (WHD), influenced by resistance, and its connection to host survival, determined by tolerance, decide the infection outcome. To grasp these intricate effects of resistance and tolerance, we used a deterministic theoretical model where pathogens interact with the immune system of a host. The model describes the positive and negative regulation of the immune response, consider the way damage accumulate during the infection and predicts WHD. When chronic, infections stabilize at a Set-Point Pathogen Load (SPPL). Our model predicts that this situation can be transient, the SPPL being then a predictor of life span which depends on initial condition (e.g. inoculum). When stable, the SPPL is rather diagnostic of non-lethal chronic infections. In lethal infections, hosts die at a Pathogen Load Upon Death (PLUD) which is almost independent from the initial conditions. As the SPPL, the PLUD is affected by both resistance and tolerance but we demonstrate that it can be used in conjunction with mortality measurement to distinguish the effect of disease tolerance from that of resistance. We validate empirically this new approach, using
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Registered trials
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.