tetano
Editor, Senior Moderator
Med J Aust
. 2020 Nov 18.
doi: 10.5694/mja2.50845. Online ahead of print.
Modelling the impact of relaxing COVID-19 control measures during a period of low viral transmission
Nick Scott[SUP] 1 [/SUP], Anna Palmer[SUP] 1 [/SUP], Dominic Delport[SUP] 1 [/SUP], Romesh Abeysuriya[SUP] 1 [/SUP], Robyn M Stuart[SUP] 2 [/SUP], Cliff C Kerr[SUP] 3 [/SUP], Dina Mistry[SUP] 3 [/SUP], Daniel J Klein[SUP] 3 [/SUP], Rachel Sacks-Davis[SUP] 1 [/SUP], Katie Heath[SUP] 1 [/SUP], Samuel W Hainsworth[SUP] 1 [/SUP], Alisa Pedrana[SUP] 1 [/SUP], Mark Stoove[SUP] 1 [/SUP], David Wilson[SUP] 1 [/SUP], Margaret E Hellard[SUP] 1 [/SUP]
Affiliations
Abstract
Objectives: To assess the risks associated with relaxing coronavirus disease 2019 (COVID-19)-related physical distancing restrictions and lockdown policies during a period of low viral transmission.
Design: Network-based viral transmission risks in households, schools, workplaces, and a variety of community spaces and activities were simulated in an agent-based model, Covasim.
Setting: The model was calibrated for a baseline scenario reflecting the epidemiological and policy environment in Victoria during March-May 2020, a period of low community viral transmission.
Intervention: Policy changes for easing COVID-19-related restrictions from May 2020 were simulated in the context of interventions that included testing, contact tracing (including with a smartphone app), and quarantine.
Main outcome measure: Increase in detected COVID-19 cases following relaxation of restrictions.
Results: Policy changes that facilitate contact of individuals with large numbers of unknown people (eg, opening bars, increased public transport use) were associated with the greatest risk of COVID-19 case numbers increasing; changes leading to smaller, structured gatherings with known contacts (eg, small social gatherings, opening schools) were associated with lower risks. In our model, the rise in case numbers following some policy changes was notable only two months after their implementation.
Conclusions: Removing several COVID-19-related restrictions within a short period of time should be undertaken with care, as the consequences may not be apparent for more than two months. Our findings support continuation of work from home policies (to reduce public transport use) and strategies that mitigate the risk associated with re-opening of social venues.
Keywords: COVID-19; Infectious diseases; Public policy; Respiratory tract infections; Theoretical models.
. 2020 Nov 18.
doi: 10.5694/mja2.50845. Online ahead of print.
Modelling the impact of relaxing COVID-19 control measures during a period of low viral transmission
Nick Scott[SUP] 1 [/SUP], Anna Palmer[SUP] 1 [/SUP], Dominic Delport[SUP] 1 [/SUP], Romesh Abeysuriya[SUP] 1 [/SUP], Robyn M Stuart[SUP] 2 [/SUP], Cliff C Kerr[SUP] 3 [/SUP], Dina Mistry[SUP] 3 [/SUP], Daniel J Klein[SUP] 3 [/SUP], Rachel Sacks-Davis[SUP] 1 [/SUP], Katie Heath[SUP] 1 [/SUP], Samuel W Hainsworth[SUP] 1 [/SUP], Alisa Pedrana[SUP] 1 [/SUP], Mark Stoove[SUP] 1 [/SUP], David Wilson[SUP] 1 [/SUP], Margaret E Hellard[SUP] 1 [/SUP]
Affiliations
- PMID: 33207390
- DOI: 10.5694/mja2.50845
Abstract
Objectives: To assess the risks associated with relaxing coronavirus disease 2019 (COVID-19)-related physical distancing restrictions and lockdown policies during a period of low viral transmission.
Design: Network-based viral transmission risks in households, schools, workplaces, and a variety of community spaces and activities were simulated in an agent-based model, Covasim.
Setting: The model was calibrated for a baseline scenario reflecting the epidemiological and policy environment in Victoria during March-May 2020, a period of low community viral transmission.
Intervention: Policy changes for easing COVID-19-related restrictions from May 2020 were simulated in the context of interventions that included testing, contact tracing (including with a smartphone app), and quarantine.
Main outcome measure: Increase in detected COVID-19 cases following relaxation of restrictions.
Results: Policy changes that facilitate contact of individuals with large numbers of unknown people (eg, opening bars, increased public transport use) were associated with the greatest risk of COVID-19 case numbers increasing; changes leading to smaller, structured gatherings with known contacts (eg, small social gatherings, opening schools) were associated with lower risks. In our model, the rise in case numbers following some policy changes was notable only two months after their implementation.
Conclusions: Removing several COVID-19-related restrictions within a short period of time should be undertaken with care, as the consequences may not be apparent for more than two months. Our findings support continuation of work from home policies (to reduce public transport use) and strategies that mitigate the risk associated with re-opening of social venues.
Keywords: COVID-19; Infectious diseases; Public policy; Respiratory tract infections; Theoretical models.