Tracking SARS-CoV-2 with phone app data offers insight into proximity and duration risk factors

Researchers at the University of Oxford, UK, have discovered how the rate of time exposed to a person who has been in contact with COVID-19 is linked to the risk of infection. They found that duration of exposure to people who have been in contact with COVID-19 increases the risk of infection more than proximity.

In the article “Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts”, published in NatureThe Oxford team analyzed data from the NHS COVID-19 app in England and Wales to understand the likelihood of SARS-CoV-2 transmission after exposure.

The study analyzed 7 million COVID-19 contacts from the app between April 2021 and February 2022, involving 23 million hours of exposure and 240,000 positive tests reported. Contacts were assessed based on proximity, duration and contagiousness scores calculated by the app, which were then used to estimate transmission risk.

The app used the privacy-preserving Exposure Notification framework to record Bluetooth signal strength measurements between smartphones to estimate proximity.

Below 1 meter, the proximity score remains constant and decreases inversely to the square of the distance above 1 meter. Duration was assessed in half-hour blocks during which close contact with COVID-19 occurred.

Exposure data was skewed toward shorter, lower-risk public encounters, while transmissions occurred over a wide range of risk levels, with durations ranging from one hour to several days.

Household and recurring contacts accounted for a lower percentage of COVID-19 contacts recorded in the apps, but were responsible for a greater number of transmissions due to longer durations and greater proximity within households.

Duration of exposure played the most critical role in predicting transmission. Short exposures demonstrated linear growth in reported transmission probability at a rate of 1.1% per hour. After a few hours, this increase in the probability of transmission slowed as the probability of infection continued to increase.

There are some limitations to analyzing app data to reconstruct infection risk. There is potential sample bias by only having access to data generated by individuals sufficiently concerned to participate in a risk and traceability application. This could limit calculations of transmission risk to a segment of the population more likely to take recommended precautions in the presence of others.

The app’s data also relies on individuals self-reporting their positive COVID-19 test results, a step that an unknown percentage of app users may miss. If the app were considered to offer an exposure risk tool to avoid COVID-19, contracting COVID-19 could end some users’ interest in the app, including any self-reporting of COVID-19. ‘infection.

Despite the limitations, the app’s data and study analysis provide a rare glimpse into millions of interactions, enabling the best version of risk observations available. The study validated the accuracy and epidemiological relevance of the app’s risk score calculations, finding a strong correlation between the metrics recorded by the app (proximity, duration) and the actual likelihood of reported transmissions.

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