Controlling COVID-19 via test-trace-quarantine

Abstract

COVID-19 containment efforts in the United States so far have largely focused on physical distancing, including school and workplace closures. However, these interventions have come at an enormous societal and economic cost. Here, we use an agent-based model, calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region, to investigate the feasibility of alternative control strategies, focusing on "test-trace-quarantine": a combination of (a) routine testing of primarily symptomatic individuals, (b) tracing and testing their known contacts, and (c) placing their contacts in quarantine. We assess the requirements for implementing this strategy, including its robustness to low compliance, delays, and other factors such as variability in overall transmission rates. We find that for the Seattle setting, if mask compliance remains high and schools remain closed, realistic levels of testing and tracing are sufficient to maintain epidemic control under a return to full workplace and community mobility.

Schools are not islands: Balancing COVID-19 risk and educational benefits using structural and temporal countermeasures

“…We modeled schools to match age mixing patterns between students within elementary schools, middle schools, and high schools [10] (see Appendix A for more details on the school network structures). Key inputs and assumptions of our modeling approach have been documented in our methodology papers [16,17]. The Covasim model is fully open source and is available for download via GitHub and the Python Package Index; more information is available at https://covasim.org.…”

The potential contribution of face coverings to the control of SARS-CoV-2 transmission in schools and broader society in the UK: a modelling study

“…Transmission model Analogous to our recently published work [28], we modelled the spread of COVID-19 using Covasim, a stochastic individual-based model of SARS-CoV-2 transmission across a population. Development and implementation details can be found at http://docs.covasim.org with the methodology outlined in [36]. The model was previously applied to explore different scenarios of schools reopening in the UK [28], explore the epidemic spread in Australia [37] and explore different non-pharmaceutical interventions for epidemic control in Seattle, USA [36].…”

“…Development and implementation details can be found at http://docs.covasim.org with the methodology outlined in [36]. The model was previously applied to explore different scenarios of schools reopening in the UK [28], explore the epidemic spread in Australia [37] and explore different non-pharmaceutical interventions for epidemic control in Seattle, USA [36]. The code used to run all simulations contained in this paper is available from https://github.com/Jasminapg/Covid-19-Analysis.…”

“…A growing number of modelling studies have evaluated the impact of face coverings on the COVID-19 epidemic [32][33][34][35][36][37][38][39]. While the overall message from these models is that, as lockdown measures are relaxed, masks are likely to be effective if they are worn by a large percentage of the population, they often optimistically assumed that a large proportion of transmission events could be prevented with face masks by overestimating their efficacy and guided by evidence of the impact of masks on influenza transmission reduction [15]; hence their results are likely to overestimate impact.…”

“…Our recent work [28], which used the detailed individual based model called Covasim [36], highlighted that adequate TTI is needed to prevent a secondary epidemic wave when broader society including schools reopen in the UK. Here, we extend this work by calibrating Covasim, illustrated in Figures 1A-B, to recent data, to August 28, 2020 rather than June 17, 2020 as in [28], taking in consideration the slower-than-anticipated reopening of society in the UK during July and August, and to explore whether extending mandatory mask use to secondary school students alongside its existing use in some community settings could contribute to reducing the risk of COVID-19 wave resurgence later this year.…”