Estimating the impact of test–trace–isolate–quarantine systems on SARS-CoV-2 transmission in Australia
Freya M. Shearer,
James M. McCaw,
Gerard E. Ryan,
Tianxiao Hao,
Nicholas J. Tierney,
Michael J. Lydeamore,
Logan Wu,
Kate Ward,
Sally Ellis,
James Wood,
Jodie McVernon,
Nick Golding
Affiliations
Freya M. Shearer
Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia; Telethon Kids Institute, Perth, Australia; Corresponding author at: Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
James M. McCaw
Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia; School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia
Gerard E. Ryan
Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia; Telethon Kids Institute, Perth, Australia
Tianxiao Hao
Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia; Telethon Kids Institute, Perth, Australia
Nicholas J. Tierney
Telethon Kids Institute, Perth, Australia
Michael J. Lydeamore
Department of Econometrics and Business Statistics, Monash University, Melbourne, Australia
Logan Wu
Walter and Eliza Hall Institute, Melbourne, Australia
Kate Ward
Public Health Response Branch, NSW Ministry of Health, Australia
Sally Ellis
Public Health Response Branch, NSW Ministry of Health, Australia
James Wood
School of Population Health, The University of New South Wales, Sydney, Australia
Jodie McVernon
Department of Infectious Diseases at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia; Victorian Infectious Diseases Reference Laboratory Epidemiology Unit at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Australia
Nick Golding
Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia; Telethon Kids Institute, Perth, Australia; Curtin University, Perth, Australia; Corresponding author.
Background:: Australian states and territories used test–trace–isolate–quarantine (TTIQ) systems extensively in their response to the COVID-19 pandemic in 2020-2021. We report on an analysis of Australian case data to estimate the impact of test–trace–isolate–quarantine systems on SARS-CoV-2 transmission. Methods:: Our analysis uses a novel mathematical modelling framework and detailed surveillance data on COVID-19 cases including dates of infection and dates of isolation. First, we directly translate an empirical distribution of times from infection to isolation into reductions in potential for onward transmission during periods of relatively low caseloads (tens to hundreds of reported cases per day). We then apply a simulation approach, validated against case data, to assess the impact of case-initiated contact tracing on transmission during a period of relatively higher caseloads and system stress (up to thousands of cases per day). Results:: We estimate that under relatively low caseloads in the state of New South Wales (tens of cases per day), TTIQ contributed to a 54% reduction in transmission. Under higher caseloads in the state of Victoria (hundreds of cases per day), TTIQ contributed to a 42% reduction in transmission. Our results also suggest that case-initiated contact tracing can support timely quarantine in times of system stress (thousands of cases per day). Conclusion:: Contact tracing systems for COVID-19 in Australia were highly effective and adaptable in supporting the national suppression strategy from 2020–21, prior to the emergence of the Omicron variant in November 2021. TTIQ systems were critical to the maintenance of the strong suppression strategy and were more effective when caseloads were (relatively) low.
