Publications & Reports

Modelling the impact of reducing control measures on the COVID-19 pandemic in a low transmission setting.

Scott N, Palmer A, Delport D, Abeysuriya R, Stuart R, Kerr CC, Ministry D, Klein D, Sacks-Davis R, Heath K, Hainsworth S, Pedrana A, Stoové M, Wilson D, Hellard ME


This is a preprint version of an article submitted for publication in the Medical Journal of Australia. Changes may be made before final publication.

Objectives: We assessed coronavirus disease 2019 (COVID-19) epidemic risks associated with relaxing a set of physical distancing restrictions.

Design: An agent-based model, Covasim, was used to simulate network-based transmission risks in households, schools, workplaces, and a variety of community spaces (e.g. public transport, parks, bars, cafes/restaurants) and activities (e.g. community or professional sports, large events).

Setting: The model was calibrated to the COVID-19 epidemiological and policy environment in Victoria, Australia, between March and May 2020, at a time when there was low community transmission.

Participants: Model-simulated Victorian population.

Intervention: From May 2020, policy changes to ease restrictions were simulated (e.g. opening/closing businesses) in the context of interventions that included testing, contact tracing (including via a smartphone app), and quarantine.

Main outcome measure: Simulated epidemic rebound following relaxation of restrictions.

Results: Policy changes leading to the gathering of large, unstructured groups with unknown individuals (e.g. bars opening, increased public transport use) posed the greatest risk of epidemic rebound, while policy changes leading to smaller, structured gatherings with known individuals (e.g. small social gatherings) posed least risk of epidemic rebound. In the model, epidemic rebound following some policy changes took more than two months to occur. Model outcomes support continuation of working from home policies to reduce public transport use, and risk mitigation strategies in the context of social venues opening.

Conclusions: Care should be taken to avoid lifting sequential COVID-19 policy restrictions within short time periods, as it could take more than two months to detect the consequences of any changes.

Keywords: agent-based model, COVID-19, COVIDSAFE Australia, smartphone contact tracing app, networks, policy change, physical distancing

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