Can India Replicate China's and South Korea's Hi-Tech Response to COVID-19
Electronic Frontier Foundation (eff.org) graphic created by EFF Senior Designer Hugh D'Andrade to illustrate EFF's work against mass surveillance.
The main driving fuel behind China's Data Science models that proved to be so effective was Data Collection. China is a world leader when it comes to collecting personal data because of its undemocratic nature. China used text monitoring algorithms and GPS tracking functions to effectively monitor people. It has also used face localization methods with its road-side video cameras to monitor the movement of its people and link it to their personal identities. Another decisive activity in China's response action has been that it has been linking the ID of its people with a specific color (like green, yellow) to organize the self-quarantine measures. Basically, based on its algorithm's results, it assigns people a color that depicts the degree of threat that they serve in the spread of the virus.
Criticisms of the undemocratic nature of these strategies that rely on public labeling and surveillance should be raised, but the fact of the matter remains that the public needs to be protected from the virus today in order for them to enjoy their rights to privacy tomorrow (although, civil liberties of this kind remain negligible in China.) The health of the state's economy, and in turn, the livelihood of its people depends on the spread of the virus. If certain rights have to be suspended in order to curtail the spread, it should be implemented. All this aside, just simple measures like regular temperature scans, setting up of testing booths have also proved to be efficient.
South Korea, on the other hand, which done much less surveillance than China, but still quite a lot, has also managed the "flatten the curve" of the spread. The MERS outbreak in South Korea in 2015 had prepared the government to tackle a similar threat efficiently. From the get-go, South Korea has been conducting massive amounts of tests, by partnering with national Bio-Tech companies. It has been setting up live message alerts to the public, which inform them of where and when an active case in their vicinity has developed so that they can act accordingly. They have achieved this by rapid contact-tracing.
It will no doubt, be difficult to implement the exact strategy in India because first of all, there is no single complete application like WeChat in India, that binds the people's ID with their locations. But what Indian can do is that it can use deep learning models and create Neural Networks that analyze the spread of COVID-19 in other countries and predict on that basis, certain hot-spots in India where COVID-19 could spread rapidly. If India is able to create a model which utilizes existing data from countries like Italy, China, and the USA, and predict hot-spots where an outbreak could be massive (like Mumbai, Siwan in Bihar), then they will be able to effectively clamp down on the movement in that particular area rather than the whole country, since economically India is not in a position to afford a nationwide lockdown. Another thing that India can do is use the census data, and other surveys in recent years to derive which communities and social groups are most vulnerable to COVID-19 and help them financially, and mentally. People with automobiles in India are financially stable and can be requested by the government to provide detailed logs of where they have visited and what all they have done with the help of in-built vehicle GPS, which can then be used by the authorities to take efficient measures in places that experience large traffic. All this though is just speculation, and due to the unpredictable nature of the virus, any sort of arithmetic model has a high chance of being greatly incorrect.