Contact tracing apps help reduce COVID infections, data shows


Contact tracing apps detect when two users are close to each other.Credit: Dan Kitwood/Getty

Since the start of the COVID-19 pandemic, dozens of countries have deployed digital apps that attempt to identify those exposed to the SARS-CoV-2 coronavirus and stop transmission. But proof that these “contact tracing” apps work has been hard to come by, as most collect limited data to protect user privacy. Now, studies from a handful of countries are showing growing evidence that apps can help prevent infections and are a valuable public health tool.

“This data is really appreciated, especially when it comes to decision making – should we adopt the app or not?” says epidemiologist Viktor von Wyl from the University of Zurich, who evaluated the Swiss app SwissCovid.

Researchers say contact-tracing apps alone won’t be enough to bring the pandemic under control. But the results show that they are useful, provided they have adequate political support and are properly integrated into public health systems.

Contact tracing apps are installed on smartphones, and many involve the Google/Apple Exposure Notification (GAEN) system, which uses the phone’s Bluetooth signal to detect when two app users are near each other. – usually within 2 meters of each other for more than 15 minutes. Users are notified if someone they have come into contact with tests positive. The exposed user can then be tested or quarantined, which should help prevent further transmission.

The GAEN system prevents health authorities from collecting personal information about app users or their devices, helping to address privacy concerns raised early in the pandemic. (Not all contact-tracing apps do this. Singapore’s TraceTogether app has drawn criticism because the data it collects could be used by police in criminal investigations.)

Emerging evidence

On February 9, British researchers published an assessment1 of the National Health Service (NHS) COVID-19 app, which was launched in England and Wales at the end of September. The evaluation, which has not yet been peer-reviewed, found that the app sent 4.4 exposure notifications for each user who tested positive for SARS-CoV-2 and agreed to the app notifying their contacts. . This was more than double the average of 1.8 contacts notified via manual contact tracing.

The team then used two methods – a mathematical model and a statistical comparison of neighborhoods that differed in app usage – to estimate that the app could have helped avert more than 224,000 infections between October and December 2020. The model assumed that around 61% of people who received an exposure notification and were ordered to quarantine for up to two weeks followed that advice. This is slightly lower than the results of a survey from January 132 in the UK, which found that around 80% of people directed to quarantine did so.

So far, the app has been downloaded to over 21 million phones, with around 16.5 million regular users. That’s about 28% of the population, or 49% of people with compatible phones. “The numbers in the UK are good, but not yet impressive,” says mathematician Luca Ferretti from the University of Oxford, UK, who worked on the analysis. The team estimates that every 1% increase in the number of app users – beyond a minimum of 15% – reduces the number of infections by 0.8 to 2.3%.

But von Wyl says it’s hard to conclude infections and deaths were averted because people used the app. “Having people tipped off by exposure notification doesn’t mean they wouldn’t have ended up on the manual contact tracing radar,” he says.

Still, the UK team’s results mirror what other groups have found. A pilot study3 Spain’s Radar Covid app, conducted in the Canary Islands in July and released last month, also found that the app notifies around twice the number of people exposed to simulated infections, compared to manual contact tracing. And an evaluation of the SwissCovid app, published in pre-publication in February4, found that the app increased the number of people in quarantine in Zurich by 5% last September, and that 17% of those people tested positive.

Von Wyl says that while the numbers may seem small, the contribution is significant. “Avoiding a case now, or a transmission now, potentially prevents further transmissions downstream,” he says.

Digital contact tracing is particularly effective in identifying contacts who do not live together. Von Wyl and his team calculated that non-family contacts notified of an exposure by the SwissCovid app entered quarantine one day earlier than those notified via manual contact tracing.5. The NHS COVID-19 app also shortened the time to quarantine by 1-2 days, says infectious disease modeler Christophe Fraser from the University of Oxford, who led the evaluation.

Crucial integration

But the researchers identified barriers to an app’s effectiveness, such as the quality of the app’s integration into the local healthcare system.

In Switzerland, for example, users of the SwissCovid app who test positive receive a code from their local health authority or doctor which they must then enter into the app to alert their close contacts. This makes the system manual rather than automatic, says von Wyl. When COVID-19 infections spiked in late 2020, overwhelmed health officials had less time to generate those codes, von Wyl says. “It’s a bottleneck,” he adds.

A similar situation exists in Spain, says Lucas Lacasa, a mathematician of complex systems at Queen Mary University of London, who led the Canary Islands pilot project. There are 17 autonomous communities across Spain, and not all of them are promoting the use of Covid Radar or quickly issuing a code to people using the app who have tested positive, Lacasa says. This means that notifications are not always sent to app users who may have been exposed to an infection. “It’s very disappointing,” he said.

The NHS COVID-19 app, on the other hand, automatically issues codes to users who test positive, so they can initiate the notification process on their phone.

Build a better app

One way the apps could improve is how they measure exposure risk, says Joanna Masel, an evolutionary biologist at the University of Arizona in Tucson who is leading a pilot study.6 of the COVID Watch app at the university. “The techs really focused on the distance aspect,” says Masel, who is also chief scientist at WeHealth, a California utility company that is managing the development of COVID Watch.

She would like to see apps that can predict the risk of exposure based on how infected a person is. For example, apps could embed information about whether a user has a more infectious variant of the virus — if that information is available — as well as whether the exposure occurred indoors or outdoors.

But von Wyl cautions against expanding an app’s functions beyond what the public will accept. “It’s a fine balance between adding more information, or taking more information out of it, but possibly losing more users because privacy fears have increased,” he says.


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