Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study.

ABSTRACT:

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 2.8 million app users in England provided 120 mill

SUBMITTER: Varsavsky T 

PROVIDER: S-EPMC7605586 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature