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dc.contributor.authorRahmandad, Hazhir
dc.contributor.authorLim, Tse Yang
dc.contributor.authorSterman, John
dc.date.accessioned2021-07-20T14:36:23Z
dc.date.available2021-07-20T14:36:23Z
dc.date.issued2021-01
dc.identifier.issn0883-7066
dc.identifier.issn1099-1727
dc.identifier.urihttps://hdl.handle.net/1721.1/131112
dc.description.abstractEffective responses to the COVID-19 pandemic require integrating behavioral factors such as risk-driven contact reduction, improved treatment, and adherence fatigue with asymptomatic transmission, disease acuity, and hospital capacity. We build one such model and estimate it for all 92 nations with reliable testing data. Cumulative cases and deaths through 22 December 2020 are estimated to be 7.03 and 1.44 times official reports, yielding an infection fatality rate (IFR) of 0.51 percent, which has been declining over time. Absent adherence fatigue, cumulative cases would have been 47 percent lower. Scenarios through June 2021 show that modest improvement in responsiveness could reduce cases and deaths by about 14 percent, more than the impact of vaccinating half of the population by that date. Variations in responsiveness to risk explain two orders of magnitude difference in per-capita deaths despite reproduction numbers fluctuating around one across nations. A public online simulator facilitates scenario analysis over the coming months.en_US
dc.language.isoen
dc.publisherWileyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1002/sdr.1673en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceSSRNen_US
dc.titleBehavioral dynamics of COVID‐19: estimating underreporting, multiple waves, and adherence fatigue across 92 nationsen_US
dc.typeArticleen_US
dc.identifier.citationRahmandad, Hazhir et al. "Behavioral dynamics of COVID‐19: estimating underreporting, multiple waves, and adherence fatigue across 92 nations." System Dynamics Review 37, 1 (January 2021): 5-31. © 2021 System Dynamics Societyen_US
dc.contributor.departmentSloan School of Managementen_US
dc.relation.journalSystem Dynamics Reviewen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-07-19T12:32:15Z
dspace.orderedauthorsRahmandad, H; Lim, TY; Sterman, Jen_US
dspace.date.submission2021-07-19T12:32:19Z
mit.journal.volume37en_US
mit.journal.issue1en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusComplete


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