India Needs 49-Day Lockdown to Stop COVID-19 Resurgence: Study

The model is possibly the first to include “age and social contact structure of the Indian population”.

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Two Indian-origin researchers from the University of Cambridge in the UK have come up with a new mathematical model that predicts a flat 49-day nationwide lockdown – or sustained lockdown with periodic relaxation extending over two months – may be necessary to prevent COVID-19 resurgence in India.

The paper by Ronojoy Adhikari in collaboration with Rajesh Singh from the Department of Applied Mathematics and Theoretical Physics at the university shows that the 21-day lockdown that the India government has imposed is unlikely to be effective and 'there will be a resurgence of COVID-19 at the end of it'.

The model is possibly the first to include "age and social contact structure of the Indian population" when assessing the impact of social distancing on the COVID-19 pandemic in the country.

The paper titled ‘Age-structured impact of social distancing on the COVID-19 epidemic in India’ has been published on open-access preprint repository ArXiv and is yet to be peer-reviewed.

The impact of social distancing measures – workplace non-attendance, school closure, lockdown – and their efficacy with duration has been investigated in the study. The researchers used an age-structured SIR model with social contact matrices obtained from surveys and Bayesian imputation to study the progress of the COVID-19 pandemic in India.

"The structures of social contact critically determine the spread of the infection and, in the absence of vaccines, the control of these structures through large-scale social distancing measures appears to be the most effective means of mitigation," the authors wrote.

The country’s total corona-affected patient count, including those who have been cured, has crossed 1000 in India. The country went in to the 21-day lockdown from 24 March midnight.

The mathematical model contains both asymptomatic and symptomatic infectives.

"Due to the paucity of data on the number of asymptomatic cases we have chosen to set these to zero. This provides a lower bound on the number of morbidities and mortalities and the intensity and duration of the social distancing measures that are required for mitigation," the authors mentioned.

According to the authors, extensive testing of the population can provide data on the number of asymptomatic cases and this, when incorporated into the model, will provide more accurate estimates of the progress of the epidemic and the impact of mitigatory social distancing.

"More generally, there are uncertainties in all parameters of our model and these would translate into uncertainties in forecasts and estimates. These uncertainties can be reduced with better availability of case data and uncertainties can be quantified through Bayesian error propagation analysis," explained the duo.

However, a three-week lockdown is found insufficient to prevent a resurgence and, instead, protocols of sustained lockdown with periodic relaxation are suggested. The duo in their study wrote,

“Our principal conclusion is that the three-week lockdown will be insufficient. Our model suggests sustained periods of lockdown with periodic relaxation will reduce the number of cases to levels where individualised social contact tracing and quarantine may become feasible.”

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