Evolution of COVID-19 Pandemic in India

A mathematical analysis of patterns for the evolution of COVID-19 cases is key to the development of reliable and robust predictive models potentially leading to efficient and effective governance against COVID-19. Towards this objective, we study and analyze the temporal growth pattern of COVID-19 infection and death counts in various states of India. Our analysis up to August 4, 2020, shows that several states (namely Maharashtra, Tamil Nadu, West Bengal) have reached t2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$t^2$$\end{document} power-law growth, while Gujarat and Madhya Pradesh exhibit linear growth. Delhi has reached t\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sqrt{t}$$\end{document} phase and may flatten in the coming days. However, some states have deviated from the universal pattern of the epidemic curve. Uttar Pradesh and Rajasthan show a gradual rise in the power-law regime, which is not the usual trend. Also, Bihar, Karnataka, and Kerala are exhibiting a second wave. In addition, we report that initially, the death counts show similar behavior as the infection counts. Later, however, the death growth rate declines as compared to the infection growth due to better handling of critical cases and increased immunity of the population. These observations indicate that except Delhi, most of the Indian states are far from flattening their epidemic curves.