Coronavirus lockdown beneficial, shows European study

Coronavirus lockdown beneficial, shows European study; NITI Aayog member too claims the same

Representative image/PTI Photo

Days before the Centre takes a call on the extension of the coronavirus lockdown, new research has emerged on Friday demonstrating how containment measures have averted approximately 200,000 hospitalizations in Italy as of March 25.

Studying the growth of the COVID-19 pandemic in Italy, a team of European researchers have shown that a combination of behavioural changes and containment measures had reduced virus transmission by 45% in Italy, one of the worst-hit countries.

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The authors modelled disease spread in the absence of some or all of the containment measures. Based on these scenarios, they estimated containment measures averted approximately 200,000 hospitalisations as of March 25.

The results – published in the Proceedings of the National Academy of Sciences – underscored the positive impacts of the drastic governmental interventions imposed in Italy. It also highlighted the need for massive testing and improved contact tracing for disease containment.


One of India’s top health policy experts too argued in favour of the lockdown on Friday citing analyses made by several experts.  

Without the travel bans, lockdown and other containment measures, India would have 8,51,505 Covid-19 patients between March 21 and April 23; but the actual number of total cases was 23,077, Dr V K Paul, a retired professor at the All India Institute of Medical Sciences, Delhi and member (Health) at NITI Aayog said in a presentation, arguing in favour of containment.

A second presentation shared by Dr Paul showed that India would have 73,400 Covid-19 cases between March 25 and April 23 if the average daily growth of such patients was 16% as seen between March 25 and April 6. But a substantially lower number successfully illustrated the impacts of containment measures.

The PNAS study by Italian and Swiss researchers estimates the effect of containment measures on COVID-19 spread in Italy using computer models in which factors related to human behaviour and government action are fed as parameters.

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