Researchers at the University of Oxford, U.K., have made a significant breakthrough in understanding the dynamics of COVID-19 transmission by investigating the relationship between exposure time and infection risk. The findings, detailed in the paper “Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts,” published in Nature, shed light on the crucial role duration of exposure plays in the likelihood of SARS-CoV-2 transmission.Â
The Oxford team utilized information from the NHS COVID-19 app in England and Wales, examining 7 million COVID-19 contacts recorded between April 2021 and February 2022. This extensive dataset involved 23 million hours of exposure and 240,000 reported positive tests. Contacts were evaluated based on proximity, duration, and infectiousness scores calculated by the app, providing insights into the factors influencing transmission risk.Â
The app employed the privacy-preserving Exposure Notification framework, utilizing Bluetooth signal strength between smartphones to estimate proximity. The study revealed that, below 1 meter, the proximity score remained constant, decreasing at the inverse square of the distance above 1 meter. This distinction in proximity measurements laid the foundation for understanding the impact of exposure duration on transmission risk.Â
Duration of exposure emerged as a key determinant of transmission risk. The data showed that household and recurring contacts, despite constituting a smaller percentage of COVID-19 contacts, were responsible for more transmissions due to longer durations and closer proximity in household settings. The exposure data, skewed towards shorter and lower-risk public encounters, highlighted the complexity of transmission dynamics.Â
The study demonstrated that short exposures exhibited linear growth in the probability of reported transmission at a rate of 1.1% per hour. However, as exposure duration increased, the growth rate slowed, indicating that the likelihood of infection continued to climb after a few hours. This insight into the temporal dynamics of transmission risk provides valuable information for understanding and mitigating the spread of the virus.Â
While the app data offered a unique glimpse into millions of interactions, the study acknowledged certain limitations. One limitation is the potential sample bias inherent in relying on data generated by individuals who are concerned enough to use a risk and traceability app. This bias may impact the generalizability of transmission risk calculations to a segment of the population more likely to adhere to recommended precautions.Â
Another potential limitation is the reliance on individuals self-reporting COVID-19 positive test results. The study acknowledged the possibility of omissions by some app users, especially if obtaining COVID-19 could lead to a decrease in user engagement with the app, including reporting infections. Despite these limitations, the study emphasized that the app data provided a valuable and extensive source for observing and analyzing transmission risk.Â
The University of Oxford’s research offers a deeper understanding of the factors influencing COVID-19 transmission, with exposure duration playing a pivotal role. The study’s reliance on real-world app data, despite its limitations, provides a unique perspective into millions of interactions, allowing for valuable observations and risk calculations.
The findings underscore the importance of considering both proximity and duration in assessing transmission risk, offering insights that can inform public health measures and strategies to mitigate the spread of SARS-CoV-2.Â
Journal Reference Â
Luca Ferretti et al, Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts, Nature (2023). DOI: 10.1038/s41586-023-06952-2. Â
