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DC Field | Value | Language |
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dc.contributor.author | Kleczkowski, Adam | en_UK |
dc.contributor.author | Maharaj, Savi | en_UK |
dc.contributor.author | Rasmussen, Susan | en_UK |
dc.contributor.author | Williams, Lynn | en_UK |
dc.contributor.author | Cairns, Nicole | en_UK |
dc.date.accessioned | 2016-01-19T00:32:29Z | - |
dc.date.available | 2016-01-19T00:32:29Z | - |
dc.date.issued | 2015-09-28 | en_UK |
dc.identifier.other | 973 | en_UK |
dc.identifier.uri | http://hdl.handle.net/1893/22307 | - |
dc.description.abstract | Background: Studies 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. Methods: Two 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. Results: Participants 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. Conclusions: Our 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. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | BioMed Central | en_UK |
dc.relation | Kleczkowski A, Maharaj S, Rasmussen S, Williams L & Cairns N (2015) Spontaneous social distancing in response to a simulated epidemic: a virtual experiment. BMC Public Health, 15, Art. No.: 973. https://doi.org/10.1186/s12889-015-2336-7 | en_UK |
dc.rights | © 2015 Kleczkowski et al. Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. | en_UK |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_UK |
dc.subject | Epidemics | en_UK |
dc.subject | Social distancing | en_UK |
dc.subject | Agent-based models | en_UK |
dc.subject | Participatory simulation | en_UK |
dc.subject | Virtual experiment | en_UK |
dc.title | Spontaneous social distancing in response to a simulated epidemic: a virtual experiment | en_UK |
dc.type | Journal Article | en_UK |
dc.identifier.doi | 10.1186/s12889-015-2336-7 | en_UK |
dc.identifier.pmid | 26415861 | en_UK |
dc.citation.jtitle | BMC Public Health | en_UK |
dc.citation.issn | 1471-2458 | en_UK |
dc.citation.volume | 15 | en_UK |
dc.citation.publicationstatus | Published | en_UK |
dc.citation.peerreviewed | Refereed | en_UK |
dc.type.status | VoR - Version of Record | en_UK |
dc.contributor.funder | Biotechnology and Biological Sciences Research Council | en_UK |
dc.author.email | savi@cs.stir.ac.uk | en_UK |
dc.citation.date | 28/09/2015 | en_UK |
dc.contributor.affiliation | Mathematics | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.contributor.affiliation | University of Strathclyde | en_UK |
dc.contributor.affiliation | University of the West of Scotland | en_UK |
dc.contributor.affiliation | University of Strathclyde | en_UK |
dc.identifier.isi | WOS:000361795600004 | en_UK |
dc.identifier.scopusid | 2-s2.0-84942511270 | en_UK |
dc.identifier.wtid | 587992 | en_UK |
dc.contributor.orcid | 0000-0003-1384-4352 | en_UK |
dc.contributor.orcid | 0000-0002-0674-6044 | en_UK |
dc.date.accepted | 2015-09-23 | en_UK |
dcterms.dateAccepted | 2015-09-23 | en_UK |
dc.date.filedepositdate | 2015-10-06 | en_UK |
dc.relation.funderproject | Risks of Animal and Plant Infectious Diseases Through Trade (RAPID trade) | en_UK |
dc.relation.funderref | BB/M008894/1 | en_UK |
rioxxterms.apc | paid | en_UK |
rioxxterms.type | Journal Article/Review | en_UK |
rioxxterms.version | VoR | en_UK |
local.rioxx.author | Kleczkowski, Adam|0000-0003-1384-4352 | en_UK |
local.rioxx.author | Maharaj, Savi|0000-0002-0674-6044 | en_UK |
local.rioxx.author | Rasmussen, Susan| | en_UK |
local.rioxx.author | Williams, Lynn| | en_UK |
local.rioxx.author | Cairns, Nicole| | en_UK |
local.rioxx.project | BB/M008894/1|Biotechnology and Biological Sciences Research Council|http://dx.doi.org/10.13039/501100000268 | en_UK |
local.rioxx.freetoreaddate | 2015-10-06 | en_UK |
local.rioxx.licence | http://creativecommons.org/licenses/by/4.0/|2015-10-06| | en_UK |
local.rioxx.filename | Maharaj et al_BMC Public Health_2015.pdf | en_UK |
local.rioxx.filecount | 1 | en_UK |
Appears in Collections: | Computing Science and Mathematics Journal Articles |
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Maharaj et al_BMC Public Health_2015.pdf | Fulltext - Published Version | 2.46 MB | Adobe PDF | View/Open |
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