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Without lockdown, COVID peak in India would have arrived by June: ICMR

An Indian Council of Medical Research (ICMR) study has revealed that the spread of COVID-19 in India was reduced due to the nationwide lockdown imposed in March. It said that without the lockdown, India would have hit a peak of 14.7 million infections by June 2020.

COVID representational
COVID representational

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Published : Oct 30, 2020, 7:15 PM IST

New Delhi: A study conducted by Indian Council of Medical Research (ICMR) has revealed that the number of active Covid-19 infections in India would have peaked at close to 14.7 million, resulted in more than 2.6 million deaths, and would have arrived by June 2020, "had there been no lockdown at the initial stage of the pandemic."

The number of deaths with the current trends may be less than 0.2 million, the ICMR said.

The study further said that the disease spread was reduced due to initial lockdown. In Delhi, the predictions from the model were corroborated with July and September surveys, which showed antibodies in 23.5 and 33 per cent population.

"The susceptible-asymptomatic-infected-recovered (SAIR) model has helped understand the disease better. If the model is correct, we may have reached herd immunity with about 380 million people already infected. However, personal protective measures remain crucial," the study said.

It said that to handle the current COVID-19 pandemic in India, multiple strategies have been applied and implemented to slow down the virus transmission. "These included clinical management of active cases, rapid development of treatment strategies, vaccines computational modelling and statistical tools," the study said.

However, several existing mathematical models were not able to account for asymptomatic patients, with limited testing capability at onset and no data on serosurveillance.

Read:COVID-19 Antibodies May Provide Immunity For At Least 5 Months

The ICMR study highlighted that a consultative committee was constituted by the Department of Science and Technology to develop a supermodel consisting of mathematical predictions as related to the COVID-19 pandemic in India.

During the deliberations of the committee, there were extensive discussions and literature review of the evolving pandemic and experience from other countries. Several mathematical models submitted to the committee, for the spread of a pandemic were analyzed in detail and the gaps identified, namely the inability of the standard susceptible-infected-recovered (SIR)/susceptible-exposed infected-recovered (SEIR) models to account for asymptomatic patients, which were a novel feature of COVID-19.

"There is a paucity of data on the behaviour of the virus among Indian population. Limited testing capability in India at the time of onset of the pandemic, non-availability of standardized tests for serosurveillance and non-availability of data on asymptomatic cases were other limitations of the current COVID-19 pandemic, a large fraction of population showed little or no symptoms. The standard mathematical models could not explain the role of asymptomatic cases in unfolding of the pandemics," the ICMR said in its study.

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"The pandemic progression's actual data showed a peak in September. Our model predicted a slightly higher peak (by 1.5%) four days later. Cumulative deaths are predicted to be slightly less than 0.2 million," it said.

The mathematical model used in this study was developed to analyze the spread of the disease under three different hypothetical scenarios, namely no lockdown, lockdown starting April 1, 2020 and lockdown starting May 1, 2020.

"To simulate the trajectories, the assumptions made are that no lockdown on March 26 allows migrants and others to travel back home. Due to this, a small number of infected people reach many parts of the country," the ICMR said in its study.

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