ArticleProceedings of the National Academy of Sciences of the United States of America2020
Eco-evolutionary control of pathogens.
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 11 papers.
What it found
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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.
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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.
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Who cites it
11 citing papers in PubMed, 23 citations in OpenAlex.
- Alignment-free prediction of cross-reactivity in influenza A (H3N2) anticipates antigenic drift.PLoS computational biology · 2026Article
- Phase diagrams for biophysical fitness landscape design.bioRxiv : the preprint server for biology · 2026Article
- Stochastic Evolutionary Control in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026Article
- The emergence of Clade IIb and Ib mpox viruses: a state-of-the-art review.Annals of medicine and surgery (2012) · 2026Review
- Effects of plant tissue permeability on invasion and population bottlenecks of a phytopathogen.Nature communications · 2024Article
- Steering and controlling evolution - from bioengineering to fighting pathogens.Nature reviews. Genetics · 2023Review
- Towards evolutionary predictions: Current promises and challenges.Evolutionary applications · 2023Review
- Understanding cellular growth strategies via optimal control.Journal of the Royal Society, Interface · 2023Article
- Strong selective environments determine evolutionary outcome in time-dependent fitness seascapes.Evolution letters · 2022Article
- Drug-induced resistance evolution necessitates less aggressive treatment.PLoS computational biology · 2021Article
- Predicting in vivo escape dynamics of HIV-1 from a broadly neutralizing antibody.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Control can alter the eco-evolutionary dynamics of a target pathogen in two ways, by changing its population size and by directed evolution of new functions. Here, we develop a payoff model of eco-evolutionary control based on strategies of evolution, regulation, and computational forecasting. We apply this model to pathogen control by molecular antibody-antigen binding with a tunable dosage of antibodies. By analytical solution, we obtain optimal dosage protocols and establish a phase diagram with an error threshold delineating parameter regimes of successful and compromised control. The solution identifies few independently measurable fitness parameters that predict the outcome of control. Our analysis shows how optimal control strategies depend on mutation rate and population size of the pathogen, and how monitoring and computational forecasting affect protocols and efficiency of control. We argue that these results carry over to more general systems and are elements of an emerging eco-evolutionary control theory.
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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.