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, and Ragonnet, Romain (2021) Understanding how Victoria, Australia gained control of its second COVID-19 wave. Nature Communications, 12. 6266.
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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.
| Item ID: | 73127 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 2041-1723 |
| Copyright Information: | © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
| Date Deposited: | 10 May 2022 21:49 |
| FoR Codes: | 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490102 Biological mathematics @ 30% 42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 70% |
| SEO Codes: | 20 HEALTH > 2004 Public health (excl. specific population health) > 200404 Disease distribution and transmission (incl. surveillance and response) @ 80% 20 HEALTH > 2002 Evaluation of health and support services > 200205 Health policy evaluation @ 20% |
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