Prediction of COVID-19 Disease Progression in India : Under the Effect of National Lockdown

Abstract

In this policy paper, we implement the epidemiological SIR to estimate the basic reproduction number \(\mathcal{R}_0\) at national and state level. We also developed the statistical machine learning model to predict the cases ahead of time. Our analysis indicates that the situation of Punjab (\(\mathcal{R}_0\approx 16\)) is not good. It requires immediate aggressive attention. We see the \(\mathcal{R}_0\) for Madhya Pradesh (3.37) , Maharastra (3.25) and Tamil Nadu (3.09) are more than 3. The \(\mathcal{R}_0\) of Andhra Pradesh (2.96), Delhi (2.82) and West Bengal (2.77) is more than the India's \(\mathcal{R}_0=2.75\), as of 04 March, 2020. India's \(\mathcal{R}_0=2.75\) (as of 04 March, 2020) is very much comparable to Hubei/China at the early disease progression stage. Our analysis indicates that the early disease progression of India is that of similar to China. Therefore, with lockdown in place, India should expect as many as cases if not more like China. If lockdown works, we should expect less than 66,224 cases by May 01,2020. All data and \texttt{R} code for this paper is available from \url{https://github.com/sourish-cmi/Covid19}