Your browser doesn't support javascript.
Engagement and adherence trade-offs for SARS-CoV-2 contact tracing.
Lucas, Tim C D; Davis, Emma L; Ayabina, Diepreye; Borlase, Anna; Crellen, Thomas; Pi, Li; Medley, Graham F; Yardley, Lucy; Klepac, Petra; Gog, Julia; Déirdre Hollingsworth, T.
  • Lucas TCD; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • Davis EL; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • Ayabina D; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • Borlase A; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • Crellen T; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • Pi L; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • Medley GF; MathSys CDT, University of Warwick, Coventry, UK.
  • Yardley L; Centre for Mathematical Modelling of Infectious Disease and Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK.
  • Klepac P; School of Psychology, University of Southampton, Southampton, UK.
  • Gog J; School of Psychological Science, University of Bristol, Bristol, UK.
  • Déirdre Hollingsworth T; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Philos Trans R Soc Lond B Biol Sci ; 376(1829): 20200270, 2021 07 19.
Article in English | MEDLINE | ID: covidwho-1309689
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
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'.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Contact Tracing / Pandemics / COVID-19 / Models, Theoretical Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Philos Trans R Soc Lond B Biol Sci Year: 2021 Document Type: Article Affiliation country: Rstb.2020.0270

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Contact Tracing / Pandemics / COVID-19 / Models, Theoretical Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Philos Trans R Soc Lond B Biol Sci Year: 2021 Document Type: Article Affiliation country: Rstb.2020.0270