Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/87643
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorZhao, Sen_US
dc.creatorStone, Len_US
dc.creatorGao, DZen_US
dc.creatorMusa, SSen_US
dc.creatorChong, MKCen_US
dc.creatorHe, DHen_US
dc.creatorWang, MHen_US
dc.date.accessioned2020-07-16T04:00:12Z-
dc.date.available2020-07-16T04:00:12Z-
dc.identifier.issn2305-5839en_US
dc.identifier.urihttp://hdl.handle.net/10397/87643-
dc.language.isoenen_US
dc.publisherAME Publishing Companyen_US
dc.rights© Annals of Translational Medicine. All rights reserved.en_US
dc.rightsThis is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Zhao S, Stone L, Gao D, Musa SS, Chong MKC, He D, Wang MH. Imitation dynamics in the mitigation of the novel coronavirus disease (COVID-19) outbreak in Wuhan, China from 2019 to 2020. Ann Transl Med 2020 ; 8(7) : 448 is available at https://dx.doi.org/10.21037/atm.2020.03.168en_US
dc.subjectCoronavirus disease 2019 (COVID-19)en_US
dc.subjectMathematical modellingen_US
dc.subjectImitation gameen_US
dc.subjectFinal epidemic sizeen_US
dc.subjectReproduction numberen_US
dc.titleImitation dynamics in the mitigation of the novel coronavirus disease (COVID-19) outbreak in Wuhan, China from 2019 to 2020en_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume8en_US
dc.identifier.issue7en_US
dc.identifier.doi10.21037/atm.2020.03.168en_US
dcterms.abstractBackground: The coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China on December 2019 in patients presenting with atypical pneumonia. Although 'city-lockdown' policy reduced the spatial spreading of the COVID-19, the city-level outbreaks within each city remain a major concern to be addressed. The local or regional level disease control mainly depends on individuals self-administered infection prevention actions. The contradiction between choice of taking infection prevention actions or not makes the elimination difficult under a voluntary acting scheme, and represents a clash between the optimal choice of action for the individual interest and group interests.en_US
dcterms.abstractMethods: We develop a compartmental epidemic model based on the classic susceptible-exposed-infectious-recovered model and use this to fit the data. Behavioral imitation through a game theoretical decision-making process is incorporated to study and project the dynamics of the COVID-19 outbreak in Wuhan, China. By varying the key model parameters, we explore the probable course of the outbreak in terms of size and timing under several public interventions in improving public awareness and sensitivity to the infection risk as well as their potential impact.en_US
dcterms.abstractResults: We estimate the basic reproduction number, R-0, to be 2.5 (95% CI: 2.4-2.7). Under the current most realistic setting, we estimate the peak size at 0.28 (95% CI: 0.24-0.32) infections per 1,000 population. In Wuhan, the final size of the outbreak is likely to infect 1.35% (95% CI: 1.00-2.12%) of the population. The outbreak will be most likely to peak in the first half of February and drop to daily incidences lower than 10 in June 2020. Increasing sensitivity to take infection prevention actions and the effectiveness of infection prevention measures are likely to mitigate the COVID-19 outbreak in Wuhan.en_US
dcterms.abstractConclusions: Through an imitating social learning process, individual-level behavioral change on taking infection prevention actions have the potentials to significantly reduce the COVID-19 outbreak in terms of size and timing at city-level. Timely and substantially resources and supports for improving the willingness-to-act and conducts of self-administered infection prevention actions are recommended to reduce to the COVID-19 associated risks.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAnnals of translational medicine, Apr. 2020, v. 8, no. 7, 448en_US
dcterms.isPartOfAnnals of translational medicineen_US
dcterms.issued2020-04-
dc.identifier.isiWOS:000527389200030-
dc.identifier.pmid32395492-
dc.identifier.eissn2305-5847en_US
dc.identifier.artn448en_US
dc.description.validate202007 bcwhen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Othersen_US
dc.description.pubStatusPublisheden_US
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