Are contact-tracing apps helping tame the pandemic?
Contact-tracing apps are not the silver bullet they are sometimes pitched as, and they don’t always zealously protect civil liberties as they should
PremiumThe number of coronavirus cases worldwide is nearing 18 million, with 700,000 deaths, and public health systems in many countries are struggling to cope with the pandemic. A few nations have launched contact-tracing apps to support other measures such as lockdowns and physical distancing in an effort to slow the spread of the virus.
Governments collecting personal data of individuals for a public-health objective is not new. West African countries did it during the 2014 Ebola virus outbreak, South Korea during the MERS outbreak in 2015. But the ongoing coronavirus pandemic is the first public-health crisis where data collection by governments seeks to leverage digital technologies, big data and algorithm-driven decision-making on a universal scale.Contact-tracing apps are where all this comes together.
The MIT Technology Review's Covid Tracing Tracker has data on 47 such apps, and it paints a diverse picture in approach, timing, adoption and privacy. The data shows that such apps are not the silver bullet they are sometimes pitched as and they don’t always zealously protect civil liberties as they should.
There are, broadly speaking, two approaches to contact-tracing apps: centralised and decentralized.
Under the centralised approach, typically, all information of infected people and their contacts is stored on a central server with the government for matching contacts and alerting people at risk. Further, besides the user, the central server also tracks information on the location and people the user has met. Under the decentralised approach, apps store data within a user’s phone, leaving users in charge of their personal data. These apps only send the ID of the user in an anonymous format to a central database once the user is confirmed positive, while the matching is done on user phones.
Of the 47 countries in the MIT database, information on centralisation or decentralisation is available for 42. Of these, 17 have chosen the centralised approach. These include India’s Aarogya Setu, France’s StopCovid and Australia’s COVIDSafe. Decentralised apps include Germany’s Corona-Warn, Italy’s Immuni and Ireland’s COVID Tracker. The centralised set has seen greater adoption. The median population penetration of contact-tracing apps from the centralised set was nearly five times that of the decentralised set.
With 100 million installations, India’s Aarogya Setu—a requirement in several public places—is the world’s most downloaded contact-tracing app. As a share of population, however, that number is just 7.4%. That ranks India 12th of the 30 countries for which such data is available in the MIT database. Countries with relatively smaller populations have managed greater penetration levels, including Singapore (37%), Australia and Norway (26% apiece).
Most countries have seen their case growth rate reduce post the introduction of such an app. Yet, the role of these apps in controlling the spread of the virus is difficult to ascertain quantitatively, as they were mostly accompanied by stricter lockdowns.
Of the 30 countries for which complete data was available in the MIT database, 19 countries have registered at least 10,000 confirmed cases of coronavirus. Of the top 10 among these by app penetration, nine have shown a decline in rate of case growth since their app launch, as compared to the 30-day period before the app launch.
Equally, a before-app and after-app comparison shows that seven of these 10 countries increased the severity of their lockdown. This includes high app-penetration countries such as Qatar (91%), as well as low app-penetration ones such as Indonesia and India (around 7%).
A June 2020 Economic & Political Weekly article by lawyer-academic Kritika Bhardwaj highlights the restricted scope of contact-tracing apps, especially in a developing-country context like India. They depend on self-reporting by individuals. This depends on large-scale testing, on which India has lagged peers. Further, such apps run on smartphones, which most Indians don’t have.
Then, there is the prickly issue of data privacy. Data-privacy policies of countries taking the decentralised approach did well in MIT’s review, with nine out of 10 countries scoring a maximum 5 on the parameters it had set for protection. By comparison, the average score for countries following the centralised approach was 2.5. India’s Aarogya Setu scored 2, indicating that data safeguards are weak compared to those in most other countries.
Bharadwaj, in the same piece, says that India lacks a “well-defined legal regime for public health". Aarogya Setu, for instance, “collects a large amount of personal information from users when they sign up, and constantly builds on this by collecting location and Bluetooth data in real time. This allows the app to create a social graph of a person’s interactions."
Further, under the current terms, Aarogya Setu can be used beyond contact tracing for other covid-related aspects and the time period specified for user data to be deleted can be extended. Such barriers have reined in adoption of contact-tracing apps and reduced their effectiveness.
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