Beyond the “Contact Tracing” App
Why we need to shift the focus,if mobile technology is ever going to help in the fight against COVID
As a mathematician, it amazes me how much computing power fits on our mobile phones today. Like other “Gen Z” digital natives, I grew up watching people dream up and build technologies that have transformed our social lives, work lives and everything in between.
Yet in a time when humanity desperately needs innovation more than ever, the application of mobile technologies in the fight against COVID-19 has been weak and fragmented.
We have technology literally at our fingertips that could be utilized to help us through this pandemic, but governments around the world have barely managed to develop even a contact tracing app.
Back in March I spent a weekend building an app for the COVID-19 pandemic. The Estonian government had called for the startup community to come together as part of a 48-hour hackathon to build solutions in response to the many challenges posed by the coronavirus crisis.
We developed our Corona-tracker app before anyone was even talking about contact tracing apps. At the time, very little was known about the virus or how the general population would react to the lockdown restrictions.
Having founded a digital health startup a few months prior to the whole COVID-19 situation, we had swiftly adapted parts on our core technology in response to these challenges.
However, in the day following the hackathon, Google and Apple decided to ban any coronavirus-related apps not created by official government or public health/research entities.
While I respect their desire to minimize the spread of misinformation, a blanket ban is an extreme measure.
Many laws exist to protect users of apps that process personal data and/or operate in a health context (especially in the European Union, where I reside), and startups and developers operating in the digital health space are well-versed in these rules.
The decision taken by Apple and Google to instead hastily enact their own regulatory system carried the implication that many pandemic-response apps built by small startups or independent teams of developers would never see the light of day.
These developer teams usually consist of highly competent people — often with PhDs in artificial intelligence, cyber security or computational biology, among other things — who could have contributed much-needed solutions towards alleviating the challenges brought on by this pandemic.
Especially in times of urgency, these groups are highly effective at executing great solutions without suffering the kind of bureaucratic inertia experienced by governments and other public institutions.
Despite our project being born as part of a government-run hackathon, the Estonian government told us they were working on their own coronavirus app and didn’t need our input (which has seen months of delays and still hasn’t been released).
Likewise, the universities that we tried to reach out to were uninterested in collaborating with a startup, even though we offered them our time and technology for free in the hope it could aid their research efforts.
Fast forward five months later and we can see the consequences of such decisions embodied in the “contact tracing” app.
Many governments have hyped this technology as an automated process for identifying recent contacts of an individual infected with COVID-19, so that those people can in turn get tested or self-isolate and prevent further spread of the disease.
It sounds promising in theory, but widespread media coverage of contact tracing app failures around the world have portrayed the implementation of this technology as a chaotic disaster. This has involved everything from privacy concerns to the fact that the underlying bluetooth technology doesn’t actually work properly.
Some have scrutinized the organizational failure of governments to deliver a timely and effective app. Others have examined the eerie power of big tech as an inhibitor to developing a successful solution.
But all this focus on contact tracing apps has missed a key point: the use of mobile technologies in the fight against COVID-19 should go above and beyond just contact tracing.
Don’t get me wrong, digital contact tracing is a very important problem that needs to be solved, but it’s one among many problems we face today that mobile technologies can help solve.
Our smartwatch data, for example, could help us understand the impact of lockdown measures on our physical and mental wellbeing.
As my home country Australia braces itself for another wave of lockdown, I could see this being useful for informing the development of targeted interventions for helping communities through the periods of isolation and remote work/schooling.
Another app could reduce pressure on our healthcare systems by enabling doctors to remotely monitor patients recovering from COVID-19 at home.
We’ve seen a surge in the popularity of telemedicine recently, but a more cohesive solution could integrate wearables and self-reported symptom logs for additional context and automatic triaging of the most at-risk cases.
Ironically, I’ve published research in the area of mathematics that deals with how things move and spread in an interconnected population. In mathematics, this discipline is called network science and its associated algorithms and models convey many interesting insights about the dynamics of epidemiological processes, like the spread of a virus.
This type of modelling has been used to help improve the predictive power of the SIR model — the epidemiological model that has informed much government decision-making throughout this pandemic.
Researchers have also looked at network science methods in helping to determine who should get a vaccine first when it becomes available, to optimize its effectiveness in achieving herd immunity in as few doses as possible.
An emerging subfield called network medicine has the potential to transform the prevention and treatment of diseases through the development of new algorithms for analyzing biological networks (e.g. protein-protein interactions and metabolic pathways).
Network science is most effective in practice when it utilizes a rich stream of real-time data — the type of data that is available from our smartphones and wearable devices.
I’d even prototyped a network science-based algorithm for digital contact tracing, but this was never to come to fruition because we were not allowed to release our app on the app stores.
I’m sure many other developers have their own stories of projects they’ve been working on during this pandemic. However, without good systems in place for executing these ideas, too many promising projects end up lost as archived fragments of code.
In this pandemic, time costs us lives and economic destruction. As my team’s own experience demonstrates, big tech is impeding the development of solutions, and governments and universities are not doing enough to collaborate with startups or other groups capable of rapidly responding to the crisis.
The mobile devices we carry around with us everyday could be doing more to get us through this pandemic, but change needs to occur at an institutional level if this is ever going to happen.