'Journal’s death figures wrong': Health ministry rejects study estimating 3 million Covid deaths in India
Without naming the study or the journal, the ministry said that media reports based on it were “mischievious.”
NEW DELHI: The Union health ministry on Friday rejected a recent study published in the prestigious journal Science, which estimated that over three million Indians may have died during the two Covid-19 waves. The is more than six times the official Indian estimate. The ministry termed this “fallacious”.
Without naming the study or the journal, the ministry said that media reports based on it were “mischievious.” Officially, the government has registered less than five lakh Covid deaths so far.
The study published in the Science last week had estimated that the actual Covid toll in India during the first two waves was between 3.1 million and 3.4 million, with roughly 2.7 million of these happening in the April-July period, when the second wave was at its peak.
According to the government, the country has a reliable and robust system of birth and death reporting based on a statute which is carried out regularly from the gram panchayat level to the district and state level, under the observation of the Registrar General of India.
It also said that the Centre has a very comprehensive definition to classify Covid deaths, based on globally acceptable categorisation and all deaths are being independently reported by states and compiled centrally.
The backlog in Covid-19 mortality data submitted by the states at different times are being reconciled in the central data on a regular basis, said the ministry, adding that a large number of states have reconciled death numbers and reported arrear deaths in a transparent manner. “Therefore, to project that deaths have been under-reported is without basis and without justification.”
The ministry also stressed there is an extreme difference in Covid caseload and linked mortality between states and any assumptions putting all states in one envelope would mean mapping skewed data of outliers together with states reporting lowest mortality, which is bound to stretch the median towards higher and wrong results.