Did the lockdown curb the spread of COVID-19 infection rate in India: A data-driven analysis

Abstract

In order to analyze the effectiveness of three successive nationwide lockdown enforced in India, we present a data-driven analysis of four key parameters, reducing the transmission rate, restraining the growth rate, flattening the epidemic curve and improving the health care system. These were quantified by the consideration of four different metrics, namely, reproduction rate, growth rate, doubling time and death to recovery ratio. The incidence data of the COVID-19 (during the period of 2nd March 2020 to 31st May 2020) outbreak in India was analyzed for the best fit to the epidemic curve, making use of the exponential growth, the maximum likelihood estimation, sequential Bayesian method and estimation of time-dependent reproduction. The best fit (based on the data considered) was for the time-dependent approach. Accordingly, this approach was used to assess the impact on the effective reproduction rate. The period of pre-lockdown to the end of lockdown 3, saw a \(45\%\) reduction in the rate of effective reproduction rate. During the same period the growth rate reduced from \(393\%\) during the pre-lockdown to \(33\%\) after lockdown 3, accompanied by the average doubling time increasing form \(4\)-\(6\) days to \(12\)-\(14\) days. Finally, the death-to-recovery ratio dropped from \(0.28\) (pre-lockdown) to \(0.08\) after lockdown 3. In conclusion, all the four metrics considered to assess the effectiveness of the lockdown, exhibited significant favourable changes, from the pre-lockdown period to the end of lockdown 3. Analysis of the data in the post-lockdown period with these metrics will provide greater clarity with regards to the extent of the success of the lockdown.