STEERING AHEAD

In the age of Artificial Intelligence and Big Data, technology can indeed provide us with pointers to steer in the prevailing uncertainty. As the world gasps for an economic breath, earnestly developing a cure for the virus, it is the data in our hands that must influence our future steps. The transmission curve that India projected would be deadly for us had forced our hand to an early imposition of lockdown when cases hovered around 320. More than six weeks and two lockdown extensions

later, a tally of around 56,000 cases appears to be a better outcome than the grievous projection in case of no lockdown. While the lockdown has indeed helped in flattening the curve, it has not succeeded in breaking the transmission chain. Cases have kept on adding, and since the beginning of May, the figures have climbed to record levels. One reason to explain the rise is the dynamic increase in testing carried out by states. As has been the word of advice from the World Health Organisation, India ramped up its testing capacity to reach 75,000 tests per day since May 3 from less than 4,000 on April 1. Heeding to the experience of nations such as South Korea and Germany — who have exhibited better control over the situation than other developed nations — has allowed India to identify its own situation from a fair lens. A low average mortality rate of nearly 3.3 per cent and an average recovery rate of nearly 29 per cent shows that the infection has been under control relative to the catastrophic outcome of the kind that US and European nations suffered. Increased testing has also begun showing the infection penetration in states, better shaping decisions to combat the virus. Since testing more provides the chance to discover more positive cases, the notion explains the steep rise in cases in Tamil Nadu recently. The state widened the screening net to reach around 2,800 tests per million population, second only to Delhi (around 4,600). In fact, the top five states with most cases are also those with the most testing per million population figures. Collectively, Maharashtra (17,974 cases), Gujarat (7,013), Delhi (5,980), Tamil Nadu (5,409) and Rajasthan (3,322) account for more than 70 per cent of cases in the country. So the notion that more testing will reveal more cases and hence provide a better picture of the situation does get some validation through these figures. The concern is more for states which have moderately high cases and shallow testing figures. Madhya Pradesh (3,252) has nearly as many cases as Rajasthan, but while Rajasthan has conducted more than 2,100 tests per million, MP has only done 840. Same goes for Uttar Pradesh which has a little more than 3,000 cases but has conducted nearly 570 tests per million population. At 358 test per million, testing has been meagre for West Bengal as well though cases appear to be half of that in UP. The underlying concern for such states with

low-testing per million is that they are yet to identify the spread of the virus. With clarity over the spread, decisions to open up the economy amidst the pandemic can be taken with more accuracy.

The lockdown has been a boon in arresting the massive spread and tuning the healthcare infrastructure to brace the impact of Covid-19. But it has not managed to effectively break the transmission chain. Resuming business as usual without breaking the chain could prove disastrous, recording a spike in cases in June and July. Big data is, therefore, necessary to take a call on the transition to normalcy that India aspires to undertake post-may 17. A graded risk assessment and each state’s capacity to test, trace and treat should be elicited on the table before taking any decision. The trends and patterns as well as social discipline would prove decisive in lifting the lockdown.