The route to release for the NHS COVID-19 app was not a smooth one, to say the least. Initially hailed as one of the key weapons in the government's armoury to reduce the rate of infection, the app suffered a number of delays as the NHS was torn between developing its own centralised technology and relying on a decentralised approach developed by Apple and Google.
After a number of technical challenges, the latter approach was adopted and the general public was urged to download and use the application for checking into venues and receiving alerts for when coming into contact with someone who had tested positive for the novel Coronavirus.
The government, the Alan Turing Institute and Oxford University have today released its latest research into how the COVID-19 app is being used and how its release has helped break the chain of infection across the UK. The results are largely more positive than many may have been anticipating.
For example, the analysis suggests that approximately 600,000 cases have been prevented by the app since September. This compares to a total of 3.96 million positive cases of the virus since testing began last March.
As we know, any case prevented potentially saves a string of other cases occurring, given the highly transmissible nature of COVID-19. Over 1.7 million users across England and Wales have been advised to isolate by the NHS COVID-19 app following close contact with someone who has gone on to test positive.
The fastest time that users were notified of having made contact with an at-risk individual was 15 minutes. Although the research states that sometimes this timeframe was a "matter of hours".
The app itself has been downloaded 21.63 million times, representing 56% of the eligible population aged 16+ with a smartphone. The research released today indicates that for every 1% increase in app users, the number of coronavirus cases in the population can be reduced by 2.3%.
Commenting on the findings, Health and Social Care Secretary Matt Hancock said:
The NHS COVID-19 app is an important tool in our pandemic response. We know it has instructed hundreds of thousands of at-risk people to self-isolate since it launched in September - including me - and this analysis shows it has been hugely effective at breaking chains of transmission, preventing an estimated 600,000 cases.
Isolating and knowing when you have been at risk of catching coronavirus is essential to stopping the spread of this virus, and the app is the quickest way to notify you if you are at risk.
I want to thank all those who have played their part by downloading and using the app, and urge those who haven't to take the simple step to protect your communities and loved ones and download it.
A deeper dive
The researchers also found that over 3.1 million test results have been entered into the app across England and Wales, of which 825,388 were positive. This is a combination of both tests booked through the app and test results manually entered.
In addition to this, figures show that users checked into a venue over 103 million times since the app's release, where a total of 253 venues were identified as ‘at risk' as a result of an outbreak since 10th December. This triggers a ‘warn and inform' response to users who also checked into those venues.
The Alan Turing Institute also highlighted some interesting findings, when mapping the app data alongside policy interventions from the government. It states:
There are definite patterns in these data: outside of national lockdowns, Saturday was the day of most check-ins, while Monday was the lowest. During December, check-ins in higher tier areas were lower than in lower tier areas, as one might expect. There was a significant drop in check-in count data during Wales' firebreak and England's second national lockdown, that is, November to early December - as expected. Check-in data also acts as a (loose) indicator of social mobility.
The impact of local and national restrictions can be clearly seen; a relaxation of restrictions in tier one and tier two areas has resulted in an increase in check-ins. The difference between tier one (e.g. Cornwall) and tier two areas is also clear. Wales and England's tier three areas saw little change in check-in activity during this period.
The Institute also estimates that the app has sent an average of 3.2 notifications to isolate per index case, or 4.4 notifications per index case who consented to being contact traced. In addition, the app was able to signal changes in case rates in areas across the UK five to seven days ahead of a change in case rates from testing data.
The researchers involved are now looking at how the app data can be used to influence policy decisions, as we continue to navigate our way out of the COVID-19 crisis. The Alan Turing Institute said:
Data from the app may also have an important role to play in wider policy development and operational planning. For example, we can use the space-time statistical analysis to help to characterise "what is a safe distance?", given unique distance-related data that the app is able to generate. This could also help to reshape policy, as necessary, helping inform future guidance relating to social distancing in specific contexts. This is an ongoing research exploration.
We have just finished producing preliminary research into the potential for a mobile device to infer whether an encounter takes place indoors or outdoors. This information could help to inform the risk calculation, and potentially wider public policy.
The key takeaway here should be that the NHS COVID-19 App is a useful tool in the government's fight against the novel Coronavirus - not a silver bullet. The app has demonstrated its effectiveness, according to this research, in helping reduce infections in England and Wales. The key lesson from the broader contact tracing story in the UK is that technology is a useful enabler in a broader human-centred approach to informing people of their risk. Some things just can't and shouldn't be automated.