News Release

COVID-19 symptom tracker smartphone app could predict outbreak hotspots

Peer-Reviewed Publication

American Association for the Advancement of Science (AAAS)

Daily symptoms logged by more than two and a half million users of the COVID-19 Symptom Tracker, a mobile application launched in March 2020, suggest the tool could help to predict geographical hotspots of COVID-19 incidence up to a week in advance of official public health reports. The app, which enables users to self-report data on COVID-19 exposure and infection, was developed by the Coronavirus Pandemic Epidemiology (COPE) Consortium - a multinational collaboration composed of leading COVID-19 investigators collectively studying "the largest and most diverse patient population assembled to-date," the authors write. Although an increasing number of digital collection tools for COVID-19 are being developed and launched, they are not often tailored for the type of scalable longitudinal data capture that epidemiologists need. Here, David Drew and colleagues launched their mobile app - in the U.K. on March 24, 2020, and in the U.S. five days later - among several large epidemiology cohorts that have previously gathered longitudinal data on lifestyle, diet and health factors and genetic information. Their app also tracked information from healthcare workers, including work hazards from personal protective equipment shortages. Drew and colleagues looked at data on symptoms from individuals who reported results to the Tracker within the initial launch period. Positive tests for the disease were often predicted by combinations of three or more symptoms, including fatigue and cough, followed by diarrhea, fever, and loss of smell. Based on this symptom data, Drew and colleagues developed a weighted prediction model. With data from a subset of users in Southern Wales, they successfully predicted two spikes in the number of confirmed COVID-19 cases in advance of public health authorities, showing the tool's predictive power. The results point to mobile technology as a resource for providing the real-time epidemiological information that scientists have struggled to gain from qPCR nucleic acid testing. Because the launch of the app began in cohorts for which longitudinal data was previously gathered, it will also allow the researchers to investigate long-term outcomes of COVID-19, they say. The authors note the app has limitations, including not representing a random sampling of the population.


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