Evidence map›Paper›PMID 26415861›Full record

ArticleBMC public health2015

Spontaneous social distancing in response to a simulated epidemic: a virtual experiment.

Adam Kleczkowski, Savi Maharaj, Susan Rasmussen, Lynn Williams, Nicole Cairns

Abstract read
In one paragraph

Article in BMC public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  12. One model to rule them all? Modelling approaches across OneHealth for human, animal and plant epidemics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Review
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.

Adam KleczkowskiComputing Science and Mathematics, School of Natural Sciences, University of Stirling, Stirling, UK. ak@cs.stir.ac.uk.
Savi MaharajComputing Science and Mathematics, School of Natural Sciences, University of Stirling, Stirling, UK. savi@cs.stir.ac.uk.
Susan RasmussenSchool of Psychological Sciences and Health; University of Strathclyde, Glasgow, UK. s.a.rasmussen@strath.ac.uk.
Lynn WilliamsSchool of Social Sciences, University of the West of Scotland, Paisley, UK. lynn.williams@uws.ac.uk.
Nicole CairnsSchool of Psychological Sciences and Health; University of Strathclyde, Glasgow, UK. nicole.cairns.2013@uni.strath.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/M008894/1
6 · The paper itself

Abstract

backgroundStudies of social distancing during epidemics have found that the strength of the response can have a decisive impact on the outcome. In previous work we developed a model of social distancing driven by individuals' risk attitude, a parameter which determines the extent to which social contacts are reduced in response to a given infection level. We showed by simulation that a strong response, driven by a highly cautious risk attitude, can quickly suppress an epidemic. However, a moderately cautious risk attitude gives weak control and, by prolonging the epidemic without reducing its impact, may yield a worse outcome than doing nothing. In real societies, social distancing may arise spontaneously from individual choices rather than being imposed centrally. There is little data available about this as opportunistic data collection during epidemics is difficult. Our study uses a simulated epidemic in a computer game setting to measure the social distancing response.

methodsTwo hundred thirty participants played a computer game simulating an epidemic on a spatial network. The player controls one individual in a population of 2500 (with others controlled by computer) and decides how many others to contact each day. To mimic real-world trade-offs, the player is motivated to make contact by being rewarded with points, while simultaneously being deterred by the threat of infection. Participants completed a questionnaire regarding psychological measures of health protection motivation. Finally, simulations were used to compare the experimentally-observed response to epidemics with no response.

resultsParticipants reduced contacts in response to infection in a manner consistent with our model of social distancing. The experimentally observed response was too weak to halt epidemics quickly, resulting in a somewhat reduced attack rate and a substantially reduced peak attack rate, but longer duration and fewer social contacts, compared to no response. Little correlation was observed between participants' risk attitudes and the psychological measures.

conclusionsOur cognitive model of social distancing matches responses to a simulated epidemic. If these responses indicate real world behaviour, spontaneous social distancing can be expected to reduce peak attack rates. However, additional measures are needed if it is important to stop an epidemic quickly.

Indexed as

Computer SimulationEpidemicsHumansModels, PsychologicalModels, TheoreticalRisk-TakingSocial BehaviorSocial Isolation

Identifiers

PMID26415861
PMCPMC4587782

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LicenceCC BY
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Registered trials

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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.