Abstract
The entire world has been struggling with the threat of Covid-19 since last two years and grappling with the
lockdown. This has abruptly harmed the global economy, especially those of developing nations such as India.
Amidst this Indian government is trying to relax its lockdown policies to uplift the economy, the impact of this
virus is believed to diffuse faster. Keeping this theory in mind, the present study extends the diffusion-based
studies to model the number of deaths due to Covid-19 in India. The model assumes that deaths occur due to the
people who caught the virus during travel from abroad (imported carriers) as well as from the ones who
encountered such travellers within the country (local carriers). An important concept considered here is that of a
change point, which signifies any changes in the normal operationalization of the system due to strategic
modifications. The change point considered here is the time point at which the relaxations began during the
lockdown. The novel contribution of the proposed models is the introduction of the population control
parameter which denotes the part of the population that is saved from catching the infection as they have strong
immunity via BacilleCalmette Guerin vaccine or due to lockdown/airport screening type of measures imposed
by the government. The power function of time has been used to account for the variability induced by the
government due to timely changes in their policies. The parameter estimation results using non-linear regression
were found to be significant. Moreover, the performance of the change point model dominated the counterpart
model.
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