DIGITAL CONTACt tracing FOR SARS-cov-2

In March 2020 we published a proposal to slow the spread of SARS-CoV-2 (the virus causing COVID-19) by doing contact tracing digitally: using proximity-detecting mobile phone apps. Since then we—a group of scientists at Oxford University’s Nuffield Department of Medicine, mainly led by Professor Christophe Fraser—have published a variety of studies investigating this novel public health investigation further. This website provides links and summaries for our work.

Tabs at the top navigate between pages about specific topics.

Published peer-reviewed articles:

• In Ferretti & Wymant et al, Science 2020 we provided the initial proposal for digital contact tracing for SARS-CoV-2 based on evidence from mathematical modelling. See the app proposal page for more details. See also the corresponding blog post.
• In Parker et al, Journal of Medical Ethics 2020 we discussed the ethics of digital contact tracing in greater detail than in the original proposal. See the corresponding blog post.
• In Altmann et al, JMIR Mhealth Uhealth 2020 we conducted and examined user surveys about user acceptance of digital contact tracing. See the corresponding blog post.
• In Kendall et al, Lancet Digital Health 2020 we analysed epidemiological changes on the Isle of Wight in May 2020 when a Test and Trace programme was introduced, including a first version of the NHS COVID-19 App. See also the corresponding blog post.
• In Colizza et al, Nature Medicine 2021 we enumerated epidemiological and public-health requirements for digital contact tracing apps and their evaluation.
• In Hinch & Probert et al, PLoS Computational Biology 2021 we presented OpenABM-Covid19: an open-source individual-based model developed specifically to model the COVID-19 epidemic and different non-pharmaceutical interventions including digital contact tracing. See also the corresponding blog post.
• In Wymant & Ferretti et al, Nature 2021 we estimated the epidemiological impact of the NHS COVID-19 App on the epidemic in England and Wales, concluding that it prevented several hundred thousand cases and saved several thousand lives in its first three months. See the epi impact page for more details.
• In Abueg & Hinch et al, npj Digital Medicine 2021, working with Google Research, we modelled how much digital contact tracing and manual contact tracing combined could reduce infections and deaths in three counties in Washington State. See also the corresponding blog post.
• In Kendall et al, Nature Communications 2023 we estimated how the epidemiological impact of the NHS COVID-19 App varied over its first year in operation, concluding that it prevented over a million infections.
  

Reports, preprints etc:

• Our report to NHSX, using OpenABM-Covid-19 to estimate the efficiency of a COVID-19 contact tracing app in different scenarios, see also the corresponding blog post.
• A discussion of the epidemiological requirements that need to be met to design successful COVID-19 contact tracing apps.
• A discussion of the advantages and disadvantages of the centralised versus the decentralised system for COVID-19 contact tracing apps.
• The blueprint for the risk-scoring algorithm of the NHS COVID-19 contact tracing app.
• A study on how the infectious period of COVID-19 relates to the date of infection and the date of symptom onset. Ferretti et al, medRxiv 2020, see also the corresponding blog post.
• Evidence of the impact of our work was gathered in this REF CASE STUDY.

Other COVID-19 work by our team, beyond digital-contact tracing:

• In Lythgoe & Hall et al, Science 2021 we analysed SARS-CoV-2 intrahost diversity and what this means for the transmission of minority variants. See the sequencing page for more details.
  
• In both Hinch et al, PTRSA 2022 and Panovska-Griffiths et al, PTRSA 2022 we estimated the fitness advantage of different viral variants and the impact of different interventions to slow viral spread.