ABSTRACT
In recent times, the rapid rise of the COVID-19 has imparted a devastating effect on human society. India has been perceiving the significant impacts of the COVID-19 in many ways. Estimation of basic reproduction number and herd immunity has become an important question which might support policy makers to take decisions for the improvement of the current scenario. In this chapter, the autoregressive integrated moving average (ARIMA) tool has been used to estimate confirm cases, discharge, deaths, and case fatality rate due to COVID-19 in India during March 1st–May 6th, 2020. The sequential bayesian (SB) method, Wallinga and Teunis approach (TD), exponential growth (EG), and maximum likelihood (ML) techniques are used to estimate the basic reproduction number and herd immunity due to COVID-19 in India. The findings are: basic reproduction number in earlier method as follows, 1.6998 (95% CI, 1.4595–1.9210), 1.8043 (95% CI, 1.6287–1.9894), 1.4685 (95% CI, 1.4672–1.4698) and 1.8931 (95% CI, 1.8655–1.9210) in SB, TD, EG, and ML, respectively. The estimations of herd immunity as follows for SB, TD, EG, and ML such as, 0.4116 (95% CI, 0.3148–0.4794), 0.4457 (95% CI, 0.3860–0.4973), 0.3190 (95% CI, 0.3184–0.3196), and 0.4717 (95% CI, 0.4639–0.4794), respectively. Results demonstrate the significant impact of epidemic dynamics of COVID-19 in India. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.