National Lockdown and COVID-19 Containment in India

What impact the 2020 COVID-19 lockdown has had on the spread of the virus in Class 1 cities of India is discussed using an interrupted time series model. Four variants of the susceptible–infected–recovered models are used to develop a counterfactual, which are compared with actual data. The analysis reveals that the lockdown has reduced the number of COVID-19 cases by 23.65 million–33.77 million and averted approximately 0.001 million–0.010 million deaths. At the regional level, it has prevented a major health crisis as existing intensive care unit and ventilator facilities for critically ill patients would have been inadequate.

The authors thank Santosh Kumar for his assistance in data analysis and Kakoli Das for arranging references.

The impact of the COVID-19 lockdown in containing the spread of the virus in Class 1 cities in India is examined. Specifically, the effect of the lockdown in terms of reducing the number of COVID-19 cases, deaths, and pressure on health infrastructure in India has been estimated. COVID-19 is a group of viruses affecting human beings through zoonotic transmission. It manifested in the Hubei Province, China in December 2019. By 13 March 2020, the outbreak had spread to 114 countries with more than 1,18,000 cases and 4,291 deaths, leading the World Health Organization (WHO 2020a) to declare it a pandemic. The major reason for concern with COVID-19 is its global scale of transmission, significant number of deaths, infection and mortality of care providers and healthcare workers (HCWs), and higher risk of death in vulnerable or susceptible groups (Chatterjee et al 2020). Under those circumstances, particularly in the absence of a licensed vaccine or effective therapeutics for COVID-19, slowing or breaking the transmission dynamics through quarantining and social distancing was adopted as a strategy (MOHFW 2020). Quite a few countries, including India—vide the Ministry of Home Affairs Order No 40-3/2020-D dated 24 March 2020—also adopted a lockdown of the economy.

A lockdown imposes a substantial economic and humanitarian burden on societies, particularly in developing countries, which persists even after the epidemic dies out. Such a cost is justified on the grounds that it decreases the number of cases, delays peak, and consequently reduces the pressure on health infrastructure. In a press statement on 23 May 2020, the NITI Aayog claimed that without the lockdown there would have been 3.6 million–7 million cases and 37 thousand–71 thousand deaths (Ghosh 2020). There have been several studies attempting to estimate the impact of travel bans, social distancing, containment, and lockdown on flattening the transmission curve using exponential growth models as well as the susceptible–infected–recovered (SIR) model and its variants (Kermack and McKendrick 1991). Such attempts compare actual cases with projected cases estimated using the SIR models and its variants. The limitation of such exercises is that parametric assumptions are either data-driven (such that noises in the data, particularly due to low testing rates, distort parametric assumptions) or are based on parameters from studies in other countries (which may not reflect the socio-economic realities of India).