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Researchers at the University of Oxford in the UK have discovered how the proportion of time spent in contact with someone who has had coronavirus infection is associated with the risk of infection. They found that the duration of contact with an individual exposed to COVID-19 increased the risk of infection more than proximity.
In the paper “Digital measurement of SARS-CoV-2 infection risk from 7 million contacts”, Naturea team from the University of Oxford analyzed data from the NHS COVID-19 app in England and Wales to understand the likelihood of SARS-CoV-2 transmission following infection.
The study analyzed 7 million COVID-19 contacts from the app from April 2021 to February 2022, including 23 million hours of exposure and 240,000 positive tests. Contains a report. Contacts were evaluated based on proximity, duration, and infectiousness scores calculated by the app and used to estimate infection risk.
The app utilized a privacy-preserving exposure notification framework to record Bluetooth signal strength measurements between smartphones and estimate proximity.
Below 1 meter, the proximity score remained constant and decreased with the inverse square of distance above 1 meter. Periods were assessed as 30-minute blocks in which close contact with COVID-19 occurred.
Although exposure data were biased toward shorter, lower-risk public encounters, infections occurred at a wide range of risk levels and ranged in duration from an hour to several days.
Although household and regular contacts account for a small proportion of COVID-19 contacts recorded in the app, they are more likely to be the source of infection due to the longer duration and proximity of household contacts. It became.
Duration of exposure played the most important role in predicting infection. It was demonstrated that for short exposures, the reported probability of infection increases linearly at a rate of 1.1% per hour. After several hours, the increase in the probability of infection slowed as the probability of infection continued to rise.
Analyzing app data to reconstruct infection risk has some limitations. There may be a sample bias in that risk and traceability apps only have access to data generated by individuals interested enough to participate. This may limit infection risk calculations to a portion of the population who are more likely to take recommended precautions when in the presence of others.
The app’s data also relies on individuals self-reporting positive COVID-19 tests, but it’s unclear what percentage of app users can skip this step. If an app is deemed to provide an infection risk tool to avoid COVID-19, some individuals may be infected with COVID-19, including through self-reporting of infection. Users may lose interest in your app.
Despite its limitations, the app’s data and survey analysis provides a glimpse into millions of interactions, giving you the best version of risk observations available. This study examined the accuracy and epidemiological relevance of the app’s risk score calculation, showing a strong correlation between the measurements recorded in the app (proximity, duration) and the reported actual probability of infection. It turns out that there is.
For more information:
Luca Ferretti et al., Digital measurement of SARS-CoV-2 infection risk from 7 million contacts, Nature (2023). DOI: 10.1038/s41586-023-06952-2
Magazine information:
Nature
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