This study describes the development the COVID-19 Symptom Tracker mobile application launched in the UK on March 24, 2020 and the US on March 29, 2020 that has more than 2.25 million users to date.
The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. Mobile phone applications or web-based tools facilitate self-guided collection of population-level data at scale, the results of which can then be rapidly redeployed to inform participants of urgent health information. Although several digital collection tools for COVID-19 symptoms have been developed and launched in the U.S., these applications have largely been configured to offer a single assessment of symptoms or have been developed for researchers to report patient-level information on behalf of participants already enrolled in clinical registries. While these approaches offer critical public health insights, they are not tailored for the type of scalable longitudinal data capture that epidemiologists need to perform comprehensive, well-powered investigations to address this public health crisis.
To meet this challenge, this study describes the establishment of an international collaboration, the Coronavirus Pandemic Epidemiology (COPE) consortium, comprised of leading investigators from several large clinical and epidemiological cohort studies. COPE co-developed a COVID-19 Symptom Tracker mobile app in partnership with in-kind contributions from Zoe Global Ltd, a digital healthcare company and academic scientists from King’s College London. By leveraging the established digital backbone of an application used for personal nutrition studies, the COVID Symptom Tracker was launched in the UK on March 24, 2020, and in the US on March 29th, 2020.
A preliminary snapshot of the first 1.6 million users in the UK over the first five days of use confirms the variability in symptoms reported across suspected COVID-19 cases and is useful for generating and testing broader hypotheses.
This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge.