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Modelling the impact of reducing control measures on the COVID-19 pandemic in a low transmission setting
Nick Scott; Anna Palmer; Dominic Delport; Romesh Abeysuriya; Robyn Stuart; Cliff C Kerr; Dina Mistry; Daniel J Klein; Rachel Sacks-Davis; Katie Heath; Samuel Hainsworth; Alisa Pedrana; Mark Stoove; David P Wilson; Margaret Hellard.
Affiliation
  • Nick Scott; Burnet Institute
  • Anna Palmer; Burnet Institute
  • Dominic Delport; Burnet Institute
  • Romesh Abeysuriya; Burnet Institute
  • Robyn Stuart; Burnet Institute
  • Cliff C Kerr; Institute for Disease Modelling
  • Dina Mistry; Institute for Disease Modelling
  • Daniel J Klein; Institute for Disease Modelling
  • Rachel Sacks-Davis; Burnet Institute
  • Katie Heath; Burnet Institute
  • Samuel Hainsworth; Burnet Institute
  • Alisa Pedrana; Burnet Institute
  • Mark Stoove; Burnet Institute
  • David P Wilson; Burnet Institute
  • Margaret Hellard; Burnet Institute
Preprint in English | medRxiv | ID: ppmedrxiv-20127027
ABSTRACT
AimsWe assessed COVID-19 epidemic risks associated with relaxing a set of physical distancing restrictions in the state of Victoria, Australia - a setting with low community transmission - in line with a national framework that aims to balance sequential policy relaxations with longer-term public health and economic need. MethodsAn agent-based model, Covasim, was calibrated to the local COVID-19 epidemiological and policy environment. Contact networks were modelled to capture transmission risks in households, schools and 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). Policy changes that could prevent or reduce transmission in specific locations (e.g. opening/closing businesses) were modelled in the context of interventions that included testing, contact tracing (including via a smartphone app), and quarantine. ResultsPolicy changes leading to the gathering of large, unstructured groups with unknown individuals (e.g. bars opening, increased public transport use) posed the greatest risk, while policy changes leading to smaller, structured gatherings with known individuals (e.g. small social gatherings) posed least risk. In the model, epidemic impact 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, such as >30% population-uptake of a contact-tracing app, physical distancing policies within venues reducing transmissibility by >40%, or patron identification records being kept to enable >60% contact tracing. ConclusionsIn a low transmission setting, 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. These findings have implications for other settings with low community transmission where governments are beginning to lift restrictions.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Prognostic study / Rct Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Prognostic study / Rct Language: English Year: 2020 Document type: Preprint
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