COVID-19 epidemic modelling for policy decision support in Victoria, Australia 2020–2021
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Published:2023-05-27
Issue:1
Volume:23
Page:
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ISSN:1471-2458
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Container-title:BMC Public Health
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language:en
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Short-container-title:BMC Public Health
Author:
Scott Nick,Abeysuriya Romesh G,Delport Dominic,Sacks-Davis Rachel,Nolan Jonathan,West Daniel,Sutton Brett,Wallace Euan M,Hellard Margaret
Abstract
Abstract
Background
Policy responses to COVID-19 in Victoria, Australia over 2020–2021 have been supported by evidence generated through mathematical modelling. This study describes the design, key findings, and process for policy translation of a series of modelling studies conducted for the Victorian Department of Health COVID-19 response team during this period.
Methods
An agent-based model, Covasim, was used to simulate the impact of policy interventions on COVID-19 outbreaks and epidemic waves. The model was continually adapted to enable scenario analysis of settings or policies being considered at the time (e.g. elimination of community transmission versus disease control). Model scenarios were co-designed with government, to fill evidence gaps prior to key decisions.
Results
Understanding outbreak risk following incursions was critical to eliminating community COVID-19 transmission. Analyses showed risk depended on whether the first detected case was the index case, a primary contact of the index case, or a ‘mystery case’. There were benefits of early lockdown on first case detection and gradual easing of restrictions to minimise resurgence risk from undetected cases. As vaccination coverage increased and the focus shifted to controlling rather than eliminating community transmission, understanding health system demand was critical. Analyses showed that vaccines alone could not protect health systems and need to be complemented with other public health measures.
Conclusions
Model evidence offered the greatest value when decisions needed to be made pre-emptively, or for questions that could not be answered with empiric data and data analysis alone. Co-designing scenarios with policy-makers ensured relevance and increased policy translation.
Funder
Burnet Institute
Department of Health, State Government of Victoria
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health
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