SHINE Case Study: COVID-19 Policy Options
SHINE has made a leading contribution to COVID-19 policy making.
In collaboration with colleagues at the University of Melbourne’s Transport Health and Urban Design Research Lab (THUD) , we developed an agent-based model for quantifying the impact of policy options like elimination , suppression and mask wearing. This model was successfully used to underpin the Victorian Government’s Roadmap out of lockdown in 2020.
SHINE then linked the agent-based model (as a ‘special’ example of an intervention model) to our PMSLT model to estimate the health gains and costs (including GDP costs) of various policy response options, including:
- for elimination and suppression strategies in Victoria in 2020 as published in JAMA Health Forum
- for varying speeds of vaccine program roll out in Pakistan and Armenia for the Asia Development Bank.
COVID-19 Pandemic Tradeoffs is the ongoing platform of modelling. 100s of scenarios are modelled of how infection rates, hospitalisation and death rate, and – critically – time in lockdown vary by policy scenarios (vaccination coverage, border policies impacting the number of vaccinated but infected arrivals per day, and in-country suppression policies). The latest iteration of this modelling is summarized in the 2022 Will Be Better report.
We initiated the Australian COVID-19 Modelling Initiative that showcases outputs from many COVID-19 modelling groups in Australia.
As 2022 approaches, modelling of COVID-19 policy options continues to be important. Our Pandemic Tradeoffs modelling is ideally suited to examining:
- optimal booster programs
- optimal border policies
- optimal use of innovations such as mass rapid antigen testing.
We are ‘open for business’ for clients who want modelling of scenarios; contact us at firstname.lastname@example.org with queries.
For further information about this research, please contact the research group leader.
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