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

Mahendra K. Verma; Ali Asad; Soumyadeep Chatterjee

For COVID-19 epidemic, some of the new models have managed to provide good forecasts that appears to match with the data. Peng et al. [7] constructed a seven-variable model (including quarantined and death variables) for epidemic spread in China and predicted that the daily count of exposed and infectious individuals will be negligible by 30 March 2020. Their predictions are in good agreement with the present data. Chinazzi et al. [8] studied the effects of travel restrictions on the spread of COVID-19 in China and in the world, and Hollewell et al. [9] performed feasibility studies of controlling COVID-19 epidemic by isolation. Mandal et al. [10] constructed a India-specific model for devising intervention strategies; they focussed on four metros-Delhi, Mumbai, Kolkata, and Bengaluru-along with intercity connectivity. To account for spatio-temporal behavour, Min et al. [11] simulated how a disease could spread within a network with different mixing styles, and showed that the average epidemic size and speed depend critically on network parameters. In addition, there are many epidemic models that are inspired by population growth models [5, 12] . There are several other models designed to understand the spread of COVID-19 [13] [14] [15] .