COVID-19 epidemic: Power law spread and flattening of the curve

Mahendra K. Verma; Ali Asad; Soumyadeep Chatterjee

The I(t) plots of Fig. 1 exhibit different values for the growth rate β and the power law exponent n. These constants depend on various factors, such as immunity levels of the population, climate conditions, extent of lockdowns and social distancing, etc. South Korea and China exhibit power law growths of t 3 and t 2 respectively, from which we may infer that a stricter lockdown may result in a relatively lower power-law exponent. The second exponential regime for USA, France, Germany, and Spain, as well as stretched power law regimes for Italy may be due to delay in the lockdowns. For India, for around a week, the exponent appears to be unity, but it may be too early to deduce anything from it. We also believe that a careful study of the I(t) curves may help in forecasting when the epidemic curve will flatten. Now we summarize our findings. The COVID-19 real-time data of infected individuals, I(t), contains useful information that may help forecast the development of the epidemic. We conjecture that the power law growth of I(t) may be due to the epidemic transmission by asymptomatic carriers traveling long distances, and/or due to community spread.