Responding to the second wave
Covid-19 has changed course, and so should we
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Illustration: Ajay Mohanty
Through 2020, it felt like the epidemic was gradually subsiding. We have a second wave of Covid-19 on our hands. This appears to reflect a combination of new variants, reduced social distancing, and difficulties of the data. Lockdowns are a blunt instrument and should be avoided. Firms need to strategise for 2021 and 2022 in this modified reality. The most important levers are better data and ending state control of vaccination.
The disease spread rapidly in early 2020. By July/August, seroprevalence studies were showing that a substantial proportion of India had developed antibodies. Evidence in Bombay suggested that the rich had been able to hide in their homes while the poor had developed immunity. There was a tantalising prospect that from here, the rich would jump to vaccination and the story would subside. But in the tug of war between vaccines, variants, and behaviour, we may have a second wave.
Data problems: The standard data on the number of tests and positives is problematic. The event of testing is a non-random one. Last year, for some months, the government monopolised testing, and only opened up to private testing with a lag. There were shortages of tests. The epidemic was raging in the poor, and they often don’t test. Hence, the testing data last year missed out on a lot of sickness, as is seen in the mismatch between the testing data and the seroprevalence data.
Today, the disease is spreading in the rich, who are more likely to get tested. Capacity constraints have been removed through private testing. We hear reports of stress in health care system capacity, which is also consistent with the fact that the rich are more likely to seek health care.
Non-random testing has been the bane of the conventional Covid-19 data in India, and the present situation is a nice example of why this data should be approached with caution. The only useful data on Covid-19 in India is that obtained from random samples of households.
The disease spread rapidly in early 2020. By July/August, seroprevalence studies were showing that a substantial proportion of India had developed antibodies. Evidence in Bombay suggested that the rich had been able to hide in their homes while the poor had developed immunity. There was a tantalising prospect that from here, the rich would jump to vaccination and the story would subside. But in the tug of war between vaccines, variants, and behaviour, we may have a second wave.
Data problems: The standard data on the number of tests and positives is problematic. The event of testing is a non-random one. Last year, for some months, the government monopolised testing, and only opened up to private testing with a lag. There were shortages of tests. The epidemic was raging in the poor, and they often don’t test. Hence, the testing data last year missed out on a lot of sickness, as is seen in the mismatch between the testing data and the seroprevalence data.
Today, the disease is spreading in the rich, who are more likely to get tested. Capacity constraints have been removed through private testing. We hear reports of stress in health care system capacity, which is also consistent with the fact that the rich are more likely to seek health care.
Non-random testing has been the bane of the conventional Covid-19 data in India, and the present situation is a nice example of why this data should be approached with caution. The only useful data on Covid-19 in India is that obtained from random samples of households.
Illustration: Ajay Mohanty
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