Evidence map›Paper›PMID 39137891›Full record

ArticleProceedings. Biological sciences2024

Paradoxes in the coevolution of contagions and institutions.

Jonathan St-Onge, Giulio Burgio, Samuel F Rosenblatt, Timothy M Waring, Laurent Hébert-Dufresne

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2024. 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. Homophily within and across groups.Nature communications · 2025
    Article
  2. Article
  3. Article
  4. Paradoxes in the coevolution of contagions and institutions.Proceedings. Biological sciences · 2024
    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

5 authors.

Jonathan St-Onge *Vermont Complex Systems Center, University of Vermont , Burlington, VT, USA.
Giulio Burgio *Departament d'Enginyeria Informatica i Matematiques, Universitat Rovira i Virgili , Tarragona 43007, Spain.
Samuel F RosenblattVermont Complex Systems Center, University of Vermont , Burlington, VT, USA.
Timothy M WaringSchool of Economics, University of Maine , Orono, ME, USA.ORCID 0000-0001-7364-1130
Laurent Hébert-DufresneVermont Complex Systems Center, University of Vermont , Burlington, VT, USA.ORCID 0000-0002-0008-3673

Funding

Using Dengue Controlled Human Infection Model to Identify Adaptive Immune Correlates of ProtectionP20GM125498 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Kristen Pierce · 2018 to 2026
$24.9M
National Science Foundation EPS-2019470NIGMS NIH HHS P20 GM125498NIH HHS 1P20 GM125498-01
6 · The paper itself

Abstract

Epidemic models study the spread of undesired agents through populations, be it infectious diseases through a country, misinformation in social media or pests infesting a region. In combating these epidemics, we rely neither on global top-down interventions, nor solely on individual adaptations. Instead, interventions commonly come from local institutions such as public health departments, moderation teams on social media platforms or other forms of group governance. Classic models, which are often individual or agent-based, are ill-suited to capture local adaptations. We leverage developments of institutional dynamics based on cultural group selection to study how groups attempt local control of an epidemic by taking inspiration from the successes and failures of other groups. Incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation. When groups perceive a contagion as more worrisome, they can invest in improved policies and, if they maintain these policies long enough to have impact, lead to a reduction in endemicity. By looking at the interplay between the speed of institutions and the transmission rate of the contagions, we find rich coevolutionary dynamics that reflect the complexity of known biological and social contagions.

Indexed as

EpidemicsHumanscoevolutioncollective decision-makingcontagionscultural evolutiongroup-based master equationsinstitutions

Identifiers

PMID39137891
PMCPMC11321847

What OpenQuestion holds

Textmetadata
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.