Google and Apple's Contact-Tracing API Doesn't Work on Public Transport, Study Finds

This finding is the latest example of mounting skepticism among experts regarding the effectiveness of the technology.
Image:  FABRICE COFFRINI/AFP via Getty Images

Covid-19 contact-tracing apps that rely on an API developed by Apple and Google and bluetooth technology cannot accurately measure the distance between users on public transport, a recently released study from Trinity College Dublin has found.

The researchers of the study first tested the API on a group of volunteers who switched seats every fifteen minutes in a Dublin tram. They then ran the collected data through the detection rules of the Swiss, German, and Italian contact-tracing apps to see how often they correctly identified contact between users. Based on this, they found that the chance of an accurate detection was “similar to that of triggering notifications by randomly selecting from the participants in our experiments, regardless of proximity.”


So, no better than random.

This finding is the latest example of mounting skepticism among experts regarding the effectiveness of the technology underlying the apps which have been widely released–but less widely used–by governments across Europe and more recently the United States.

Most contact-tracing apps in Europe and the United States use Apple and Google’s exposure notification API, which in turn relies on in-built wireless Bluetooth technology to estimate the distance between two users and whether they’ve been in contact. What actually constitutes ‘contact’ is set by the developers of whichever app calls the API, but it’s usually defined as being within 2 meters (~6.5 feet) of another user for at least 15 minutes. Once a user uploads a positive test result to a contact-tracing app, it notifies all contacted users and lets them know that they’ve been at risk of infection.

While that sounds nice in theory, experts say that the reality is much more complicated.

“What we see is that even tiny changes in the orientation of the handset can make a big difference,” dr. Doug Leith, one of the authors of the study, told Motherboard over the phone. “Even something as simple as having a phone facedown or faceup on a table can have a surprisingly strong effect. In environments like a tram, Bluetooth for contact-tracing simply doesn’t work.”

That’s also because Bluetooth signals reflect off of the metallic walls and objects of the tram in the same way light reflects off mirrors and therefore artificially strengthening some signals, while weakening others.


"Given this study (and others like it)—it's concerning to me that so many public health agencies and schools are rushing out to deploy a technology that introduces significant risks of abuse and manipulation," Ashkan Soltani, former Chief Technologist for the Federal Trade Commission, told Motherboard. "I think it’s another example of tech determinism—introducing untested technologies under the utopic vision that they’re going to solve the world’s ails whereas the reality is that the solutions themselves introduce new problems with even greater concerns (like voter manipulation).  See: social media, user generated content, and a host of other ails."

With cases surging in countries like the Netherlands, France, and the UK, governments have argued that contact-tracing apps can help to ease the load on overburdened manual contact-tracing systems by identifying cases of exposure in areas where traditional methods have struggled, like crowded public spaces.

But, if the Bluetooth signals lack robustness in the way the study suggests, then there’s reason to be skeptical about contact-tracing apps in other spaces as well. In crowded shopping streets, for example, Bluetooth signals can be absorbed by human bodies, Leith says, and variables like whether a phone is in or out of a user’s pocket can make a substantial difference.

He’s also both disappointed in a lack of transparency on behalf of governments regarding the efficacy of these apps.

“Given this is unproven technology–and that’s just a factual statement–and we are essentially doing population-level experiments, governments should be gathering enough data after deployment to actually know ‘do they work.’ The incredible thing is that basically nobody has done that. Many places are using these apps just on faith, and there’s a very good chance that they don’t work.”