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Countering the next wave of COVID-19 -Yamini Aiyar, Jishnu Das, Partha Mukhopadhya and Shamindra Nath Roy

-The Hindu

It requires co-ordination across States and districts, based on real-time analysis of data

As the focus shifts to a possible third wave, it is important for India to ask how it can marshal its resources better. Can we leverage the advantages of our size and federal character?

Delhi’s experience is instructive. As the first wave abated, hospitalisation for COVID-19 patients plummeted. By January 2021, Delhi was using less than 20% of its bed capacity for COVID-19 patients. It then made the fateful decision, at the beginning of February, to reduce bed capacity back to its usual level of just above 5,000. The decision paid off till mid-March and then the system collapsed. As the second wave hit, bed occupancy went from 33% to over 90% in the first three weeks of April. The government responded rapidly, ramping up bed capacity (faster than what was seen in China or New York City) to more than the previous peak, but it could not keep up with the surge. Equally, as the surge subsided over an 18-day period, utilisation of government hospital beds went rapidly back to 30%, even as infections spread to many other areas with a shortage of key infrastructure. The fact is that it is extremely hard to ramp up capacity in response to the kind of surge that we saw in April 2021, and next to impossible to staff the additional capacity adequately. It is also true that all governments are under pressure to scale down capacity, if augmented capacity remains unused for a long period of time.

Elastic health infrastructure

Delhi’s experience highlights two important issues. First, COVID-19 waves require the health infrastructure to be elastic (i.e. expand and contract based on need) and often over a very short period. Second, demand for COVID-19-specific health infrastructure is spatially varied. If cities, districts and States see in surge in cases at different points in time, does health capacity at a location need to be fixed or can it vary over time and across geography?

Preparing for the third wave thus requires us to think differently about health infrastructure, and focus on where we need to build capacity locally and where we can move capacity in response to a surge.

The response depends, in part, on the geography of COVID-19. When we look at the data, we uncover one key fact: in the second wave, COVID-19 returned to many of the districts affected in the first wave, a group that we call the ‘permanently at risk’ districts. There were 145 districts that accounted for 75% of the cases during the first wave. Strikingly, the same districts accounted for up to 80% of cases during the second wave. Of these, 45 districts accounted for 50% of the cases during the first surge and even more in the initial days of the second. The characteristics of these districts in terms of population size, density and mobility make them susceptible to rapid spread. An epidemiological question is why this happens if such districts have herd immunity, from prior infection and vaccination. One answer, as shown in models developed by the Tata Institute of Fundamental Research, is that if vaccination is only partly efficacious, as recent CMC Vellore results indicate, even limited reinfection and a more transmissible variant can lead to a large surge — and a potential third wave in the ‘permanently at risk’ districts. These ‘permanently at risk’ districts thus need reserve capacity and resources to be expanded to track and detect potential surges at an early stage.

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