Evidence map›Paper›PMID 31932981›Full record

ArticleBulletin of mathematical biology2020

The Timing and Nature of Behavioural Responses Affect the Course of an Epidemic.

Rebecca C Tyson, Stephanie D Hamilton, Aboubakr S Lo, Bert O Baumgaertner, Stephen M Krone

Open access · bronzeAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

17 citing papers in PubMed, 35 citations in OpenAlex.

  1. Review
  2. Article
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  5. Heterogeneous risk tolerance, in-groups, and epidemic waves.Frontiers in applied mathematics and statistics · 2024
    Article
  6. Article
  7. Article
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  10. Misinformation can prevent the suppression of epidemics.Journal of the Royal Society, Interface · 2022
    Article
  11. Article
  12. Article
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  14. Article
  15. Coupling Epidemiological Models with Social Dynamics.Bulletin of mathematical biology · 2021
    Article
  16. Article
  17. 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 at 3 institutions in 3 countries.

Rebecca C TysonMathematics, Irving K. Barber School of Arts and Sciences Unit 5 BLDG SCI, University of British Columbia Okanagan, 1177 Research Road, Kelowna, BC, V1V 1V7, Canada. rebecca.tyson@ubc.ca.
Stephanie D HamiltonMathematics, Irving K. Barber School of Arts and Sciences Unit 5, University of British Columbia Okanagan, 1177 Research Road, Kelowna, BC, V1V 1V7, Canada.
Aboubakr S LoENSTA ParisTech, 828 Boulevard des Maréchaux, 91120, Palaiseau, France.
Bert O BaumgaertnerDepartment of Politics and Philosophy, University of Idaho, 875 Perimeter Drive, MS 3165, Moscow, ID, 83844-3165, USA.
Stephen M KroneDepartment of Mathematics, University of Idaho, 875 Perimeter Drive, MS 1103, Moscow, ID, 83844-1103, USA.
University of British Columbia · CAUniversity of Idaho · USÉcole Nationale Supérieure de Techniques Avancées · FR

Funding

Sequence-structure-function relationships in human visual photopigmentsP20GM104420 · NIGMS · UNIVERSITY OF IDAHO · PI VAN LEUVEN, JAMES · 2015 to 2024
$22.9M
6 · The paper itself

Abstract

During an epidemic, the interplay of disease and opinion dynamics can lead to outcomes that are different from those predicted based on disease dynamics alone. Opinions and the behaviours they elicit are complex, so modelling them requires a measure of abstraction and simplification. Here, we develop a differential equation model that couples SIR-type disease dynamics with opinion dynamics. We assume a spectrum of opinions that change based on current levels of infection as well as interactions that to some extent amplify the opinions of like-minded individuals. Susceptibility to infection is based on the level of prophylaxis (disease avoidance) that an opinion engenders. In this setting, we observe how the severity of an epidemic is influenced by the distribution of opinions at disease introduction, the relative rates of opinion and disease dynamics, and the amount of opinion amplification. Some insight is gained by considering how the effective reproduction number is influenced by the combination of opinion and disease dynamics.

Indexed as

EpidemicsHealth BehaviorModels, BiologicalAttitudeAttitude to HealthBasic Reproduction NumberCommunicable DiseasesComputer SimulationDisease SusceptibilityHumansMathematical ConceptsModels, PsychologicalDisease-behaviour modelEpidemiologyOpinion dynamicsOrdinary differenntial equationsProphylactic behaviour

Identifiers

PMID31932981
PMCPMC7223272
OpenAlexW2999695270

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.