Litcius/Paper detail

Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts

Luca Ferretti, Chris Wymant, James Petrie, Daphne Tsallis, Michelle Kendall, Alice Ledda, Francesco Di Lauro, Adam Fowler, Andrea Di Francia, Jasmina Panovska‐Griffiths, Lucie Abeler‐Dörner, Marcos Charalambides, Mark Briers, Christophe Fraser

2023Nature52 citationsDOIOpen Access PDF

Abstract

Abstract How likely is it to become infected by SARS-CoV-2 after being exposed? Almost everyone wondered about this question during the COVID-19 pandemic. Contact-tracing apps 1,2 recorded measurements of proximity 3 and duration between nearby smartphones. Contacts—individuals exposed to confirmed cases—were notified according to public health policies such as the 2 m, 15 min guideline 4,5 , despite limited evidence supporting this threshold. Here we analysed 7 million contacts notified by the National Health Service COVID-19 app 6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had risk similar to that of shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. Whereas most exposures were short (median 0.7 h, interquartile range 0.4–1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4–28). Households accounted for about 6% of contacts but 40% of transmissions. With sufficient preparation, privacy-preserving yet precise analyses of risk that would inform public health measures, based on digital contact tracing, could be performed within weeks of the emergence of a new pathogen.

Topics & Concepts

Interquartile rangeContact tracingCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Transmission (telecommunications)PandemicDemographyPublic health2019-20 coronavirus outbreakMedicineEnvironmental healthPublic health surveillanceStatisticsGeographyComputer scienceVirologyMathematicsTelecommunicationsOutbreakInfectious disease (medical specialty)Internal medicineDiseaseSociologyNursingCOVID-19 Digital Contact TracingCOVID-19 epidemiological studiesMobile Crowdsensing and Crowdsourcing