Lucas, Tim CD; Davis, Emma L; Ayabina, Diepreye; Borlase, Anna; Crellen, Thomas; Pi, Li; Medley, Graham F; Yardley, Lucy; Klepac, Petra; Gog, Julia; +1 more... Déirdre Hollingsworth, T; (2021) Engagement and adherence trade-offs for SARS-CoV-2 contact tracing. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 376 (1829). 20200270-. ISSN 0962-8436 DOI: https://doi.org/10.1098/rstb.2020.0270
Permanent Identifier
Use this Digital Object Identifier when citing or linking to this resource.
Abstract
Contact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from self-reporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritized. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies which increase the average duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced self-reporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.
Item Type | Article |
---|---|
Faculty and Department |
Faculty of Public Health and Policy > Dept of Global Health and Development Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
Research Centre |
Covid-19 Research Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 34053257 |
Elements ID | 161394 |
Download
Filename: Engagement and adherence trade-offs for SARS-CoV-2 contact tracing.pdf
Licence: Creative Commons: Attribution 3.0
Download