🪧 What do we want? 🪧
Help balancing work and family life!

🪧 When do we want it? 🪧
School pick-up time!

Christmas and the Euros were associated with big increases in spread, driven by synchronised (likely inter-generational) meet-ups across England and/or Wales. Excess transmissions on Euro match days accounted for 29% of all app-recorded transmissions during the month-long tournament scim.ag/86t

Plus the data captured fine-grained insights into the drivers of transmission, including the effects of day-of-the-week, setting (longer vs more fleeting contact), and geographical region.

Analysis of app data provided a leading indicator of the reproduction number R, available at least 5 days earlier than other estimates. This provided valuable situational awareness for policy makers.

Finally, app data provided near real-time insights into the drivers of the epidemic. We could see if a wave was driven by an increase in contact rates or infectiousness.
doi.org/10.1126/scie...

"Whereas most exposures were short (median 0.7 h, interquartile range 0.4–1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4–28). Households accounted for about 6% of contacts but 40% of transmissions."

By analysing 7 million contacts captured by the app, we (a) concluded the app was good at measuring "riskiness" of contact, and (b) quantified for the first time the "riskiness" of contacts according to distance and duration. doi.org/10.1038/s415...

App usage declined as vaccines (happily!) did most of the life-saving work, but it continued to help reduce pressure on the NHS. Each week in 2022, 30-60% of nationally-registered positive tests were reported via the app and 1000s of contacts were traced.
bdi-pathogens.shinyapps.io/NHS-COVID-19...

Impressive achievements for a new technology built rapidly during a pandemic by teams who had largely never met before 🏆

Frequent, rapid updates were required to maintain it in line with national policy changes 💪👏

And of course huge thanks to the >18 million users who made it such a success ✨🙏

The app's popularity and accuracy made it effective: a user getting an alert was always at least twice as likely to be infected as a person randomly selected from the population. At its peak, a notified app user was 77 (CI 54, 106) times more likely to be infected than a not-notified app user.

Later, we performed an analysis of the app's first year. Central estimates: it averted 1 million cases, 44k hospitalisations and 10k deaths. Plenty of uncertainty in the estimates owing to the privacy-preserving, minimal data collection.
doi.org/10.1038/s414...

Approximately one case was averted for each case consenting to notification of their contacts. We showed that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis).

We found that over its first three months of operation the NHS COVID-19 app reduced the number of cases by something in the region of 14% or 25%, depending on the method of attribution.
doi.org/10.1038/s415...

The NHS COVID-19 app for England and Wales was launched in September 2020. It featured local area info, QR check-ins for public venues, symptom checker, access to testing and results, and Bluetooth-based contact tracing. Within days there were >10 million users.

A contact tracing app was launched in May 2020 on the Isle of Wight, England. We performed a preliminary analysis of its effectiveness. There was limited data available, but it looked promising.
doi.org/10.1016/S258...

In many countries, this was the motivation for developing digital contact tracing. An Agent-Based Model called OpenABM-Covid19 helped refine details of how tracing could/should work by modelling realistic household sizes, age-based interactions, smartphone ownership etc.
doi.org/10.1371/jour...

It began in Christophe Fraser's group in Oxford, Feb/Mar 2020. Since ~half of all COVID-19 infections were from people without symptoms (including pre- and asymptomatic), we showed that contact tracing would need to be quick and scalable to be effective. Full details: www.science.org/doi/10.1126/...

I spent most of the last few years working on digital contact tracing, first at the Big Data Institute at @universityofoxford.bsky.social then @warwickstats.bsky.social, working closely with the UK Health Security Agency 📱

Then a year on maternity leave 👶

Both roles were an absolute privilege!