Evidence map›Paper›PMID 40262640›Full record

ArticleJournal of the Royal Society, Interface2025

The complex interplay between risk tolerance and the spread of infectious diseases.

Maximilian M Nguyen, Ari S Freedman, Matthew A Cheung, Chadi M Saad-Roy, Baltazar Espinoza, Bryan T Grenfell, Simon A Levin

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Integrated framework to study genomic surveillance of selective sweeps in multivariants dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Marginal notes, June 2025. Artificial Stupidity.Journal of medical microbiology · 2025
    Article
  4. 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

7 authors.

Maximilian M NguyenLewis-Sigler Institute, Princeton University, Princeton, NJ, USA.ORCID 0000-0002-4378-5050
Ari S FreedmanDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.ORCID 0009-0004-3742-9043
Matthew A CheungProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA.ORCID 0009-0007-9358-3338
Chadi M Saad-RoyMiller Institute for Basic Research in Science, University of California Berkeley, Berkeley, CA, USA.ORCID 0000-0002-2217-3071
Baltazar EspinozaBiocomplexity Institute, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0002-6280-3277
Bryan T GrenfellDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
Simon A LevinDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.ORCID 0000-0002-8216-5639

Funding

Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California BerkeleyArmy Research OfficeGift from William H. Miller IIINational Science FoundationPrinceton Catalysis InitiativePrinceton Precision Medicine
6 · The paper itself

Abstract

Risk-driven behaviour provides a feedback mechanism through which individuals both shape and are collectively affected by an epidemic. We introduce a general and flexible compartmental model to study the effect of heterogeneity in the population with regard to risk tolerance. The interplay between behaviour and epidemiology leads to a rich set of possible epidemic dynamics. Depending on the behavioural composition of the population, we find that increasing heterogeneity in risk tolerance can either increase or decrease the epidemic size. We find that multiple waves of infection can arise due to the interplay between transmission and behaviour, even without the replenishment of susceptibles. We find that increasing protective mechanisms such as the effectiveness of interventions, the fraction of risk-averse people in the population and the duration of intervention usage reduce the epidemic overshoot. When the protection is pushed past a critical threshold, the epidemic dynamics enter an underdamped regime where the epidemic size exactly equals the herd immunity threshold and overshoot is eliminated. Finally, we can find regimes where epidemic size does not monotonically decrease with a population that becomes increasingly risk-averse.

Indexed as

Communicable DiseasesEpidemicsModels, BiologicalHumansepidemic sizeheterogeneous behaviourintervention adoption and usagerisk tolerance

Identifiers

PMID40262640
PMCPMC12014228

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.