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Understanding how Victoria, Australia gained control of its second COVID-19 wave.
Trauer, James M; Lydeamore, Michael J; Dalton, Gregory W; Pilcher, David; Meehan, Michael T; McBryde, Emma S; Cheng, Allen C; Sutton, Brett; Ragonnet, Romain.
  • Trauer JM; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. james.trauer@monash.edu.
  • Lydeamore MJ; Central Clinical School, Monash University, Melbourne, VIC, Australia.
  • Dalton GW; Victorian Department of Health, Government of Victoria, Melbourne, VIC, Australia.
  • Pilcher D; Victorian Department of Health, Government of Victoria, Melbourne, VIC, Australia.
  • Meehan MT; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
  • McBryde ES; Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD, Australia.
  • Cheng AC; Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD, Australia.
  • Sutton B; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
  • Ragonnet R; Victorian Department of Health, Government of Victoria, Melbourne, VIC, Australia.
Nat Commun ; 12(1): 6266, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1493105
Preprint
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ABSTRACT
During 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria's second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage. Estimates of the risk of death in those aged ≥75 and of hospitalisation were higher than international estimates, reflecting concentration of cases in high-risk settings. We estimated significant effects for each of the calibrated time-varying processes, with estimates for the individual-level effect of physical distancing of 37.4% (95%CrI 7.2-56.4%) and of face coverings of 45.9% (95%CrI 32.9-55.6%). That the multi-faceted interventions led to the dramatic reversal in the epidemic trajectory is supported by our results, with face coverings likely particularly important.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Diagnostic study Limits: Adolescent / Adult / Humans / Middle aged / Young adult Country/Region as subject: Oceania Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2021 Document Type: Article Affiliation country: S41467-021-26558-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Diagnostic study Limits: Adolescent / Adult / Humans / Middle aged / Young adult Country/Region as subject: Oceania Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2021 Document Type: Article Affiliation country: S41467-021-26558-4