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Govt’s infection fatality claim shows India missing 23 infections for every reported Covid case -Abantika Ghosh

-ThePrint.in

Niti Aayog member Dr V.K. Paul says govt estimates that India has an infection fatality rate of 0.05%. But there's no sero survey data after January to back this claim.

New Delhi: India could be missing 23 infections for every reported Covid-19 case in the country, according to estimates shared by NITI Aayog member (health) Dr V.K. Paul Thursday.

Rejecting mortality numbers published in The New York Times, Dr Paul said the government estimates that India has an infection fatality rate of 0.05%.

With the country having reported 3,15,235 deaths till Thursday morning, this would mean that the total infections in the country stand at 63,04,70,000, against a total figure of 2,73,69,093 cases. This means India is undercounting infection by a factor of 23.

In epidemiological terms, a case is an infection that has been detected using a test and is likely symptomatic. An infection is the presence of a virus in a person without the outward manifestations of the disease or a positive laboratory report.

“The (NYT) estimates have been done ad hoc and without any basis; there are two parts — quoted cases is what percentage of viral infections. Because this virus infects a large number of people only some people get symptoms. This is well-known. There is a universe where infection is not known — if it is to be ascertained, every day or every week the entire population needs to be tested…saying that the infection is 10-15 times of reported, it doesn’t bother,” Dr Paul said.

He added that the problem arises when a certain number is thrown as mortality. “As per our estimates, infection fatality is 0.05% and case fatality rate is 1.15%. When somebody attaches a number without thinking of understanding… they (NYT) are taking 0.3% IFR (infection fatality rate) which is six times of 0.05% and 0.6% is 12 times. On what basis? No basis at all,” Dr Paul said, adding that India’s death reporting is “systematic and robust”.

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