‘Covid situation changed due to rise of fast-spreading mutated variants’

Amid the second wave of the Covid-19 pandemic, Ashutosh Sharma, secretary, department of science and technology, spoke to Vishwa Mohan on strategies to control spread of infection and protect livelihoods. Excerpts from the interview:
Did the scientific community and the DST anticipate the kind of situation India is facing right now?
At the time the first wave was tapering, sero surveys such as the fifth serological survey in Delhi, conducted between January 15 and January 23, to detect Covid-19 antibodies showed 56.13% of the 28,000 people sampled tested positive. Such a situation should in general reduce the number of future transmissions. But the situation changed due to the rise of mutated variants that could spread more rapidly with greater impact, and large-scale laxity in observation of protective measures induced by fatigue due to the long-term social and economic restrictions.
While many mutations were being observed all along the trajectory of the pandemic, scientific understanding of the transmissibility and impact of mutations of concern is still continuing. It is for these and other reasons that the scale, speed, intensity and ferocity of the situation we witness today could not have been foreseen by scientific panels that were directly monitoring the situation.
There was a lot of buzz around the Covid-19 second wave much before it actually hit India. Was there any concrete scientific evidence to foresee it or its intensity?
Of course, there are always varying perspectives and debates about many possibilities for the future evolution of a pandemic and on balanced strategies to contain its rise while keeping in view justifiable demands to preserve livelihoods. This is a problem that all countries have grappled with. I have examined predictions that globally respected models were making at that time. But there was no concrete scientific evidence by the end of March to early April to foresee its speed and intensity.
Is there any prediction on how long this second wave will continue?
As one can expect, there are several differing predictions. For example, models developed at University of Michigan (US), Ashoka University and the SUTRA model indicate per day peak cases of around 8 lakh, 5-6 lakh and 4 lakh respectively within a window of early May to late May. The models seem to indicate around two months after the peak to reach levels comparable to those seen at the end of the first wave.
However, fidelity of longterm predictions depends on the adherence to appropriate behaviour — masking, ventilation, distancing, testing, surveillance, isolation, vaccination etc and on having no further game-changing mutations.
When should we expect the third wave?
About the third wave and beyond, the future is not so much about predicting it, but actively imaging, inventing and shaping it. We do have the power to write our chosen destiny by shared objectives and shared responsibilities reflecting measures we put in motion today. There is no iron hand of mathematics or any other science pushing us on a preordained path.
Do you think India should go for inoculation irrespective of age criteria, considering growing instances of infections among children during this second wave?
In an ideal setting with unlimited supply, one should implement near universal immunisation. However, in a supply constrained situation, a pragmatic strategy must factor in Covid-19 risk profiles and the system capacity. Risk is partly related to age, partly to the job profile and partly to serious co-morbidities. In the vaccination strategy being pursued, each of these risks is addressed. In a largescale vaccination programme, prioritisation must be done in a way which is unequivocal, clear, actionable, transparent and minimises the risk to the entire population as a whole.
Does the country have the capacity for a universal vaccination programme?
Production and acquisition of vaccines in India are being ramped up by several measures, including supply of raw material, excess inventory and relaxation of certain intellectual property norms, allowing the import of foreign-approved vaccines with plans for some of them to be manufactured in India, and more new vaccines being developed in India rapidly.
What are the limitations of mathematical models when we look at fast-changing scenarios in terms of testing or reporting gaps in certain states and non-adherence to Covid-appropriate behaviour by the general public?
Any mathematical model of a pandemic spread is neither a crystal ball that foretells future with accuracy, nor a law of nature like Newton’s laws of motion. Predictions of a model depend crucially on the prevailing inputs such as the behaviour of the virus and people, and when they change significantly, the model needs recalibration. There have been models by top scientists globally, published in the top scientific journals, which over-estimated the peak disease and death burden of the first wave in India by as much as 1,000%. Nevertheless, it is well recognised that models are useful in testing scenarios and identifying major departures in the behaviour of people and viruses.