Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application

Varsavsky, Thomas; Graham, Mark S.; Canas, Liane S.; Ganesh, Sajaysurya; Puyol, Joan Capdevila; Sudre, Carole H.; Murray, Benjamin; Modat, Marc; Cardoso, M. Jorge; Astley, Christina M.; Drew, David A; Nguyen, Long H.; Fall, Tove; Gomez, Maria F; Franks, Paul W.; Chan, Andrew T.; Davies, Richard; Wolf, Jonathan; Steves, Claire J.; Spector, Tim D.; Ourselin, Sebastien

BACKGROUND: As many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention. METHODS: We performed modelling on longitudinal, self-reported data from users of the COVID Symptom Study app in England between 24 March and 29 September, 2020. Combining a symptom-based predictive model for COVID-19 positivity and RT-PCR tests provided by the Department of Health we were able to estimate disease incidence, prevalence and effective reproduction number. Geographically granular estimates were used to highlight regions with rapidly increasing case numbers, or hotspots. FINDINGS: More than 2.6 million app users in England provided 115 million daily reports of their symptoms, and recorded the results of 170,000 PCR tests. On a national level our estimates of incidence and prevalence showed similar sensitivity to changes as two national community surveys: the ONS and REACT studies. On a geographically granular level, our estimates were able to highlight regions before they were subject to local government lockdowns. Between 12 May and 29 September we were able to flag between 35–80% of regions appearing in the Government’s hotspot list. INTERPRETATION: Self-reported data from mobile applications can provide a cost-effective and agile resource to inform a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance. FUNDING: Zoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimer’s Society.