Multi-parametric disease dynamics study and analysis of the COVID-19 epidemic and implementation of population-wide intrusions: The Indian perspective

The outbreak of COVID-19 had spread at a deadly rate since its onset at Wuhan, China and is now spread across 216 countries and has affected more than 6 million people all over the world. The global response throughout the world has been primarily the implementation of lockdown measures, testing and contact tracing to minimise the spread of the disease. The aim of the present study was to predict the COVID-19 prevalence and disease progression rate in Indian scenario in order to provide an analysis that can shed light on comprehending the trends of the outbreak and outline an impression of the epidemiological stage for each state of a diverse country like India. In addition, the forecast of COVID-19 incidence trends of these states can help take safety measures and policy design for this epidemic in the days to come. In order to achieve the same, we have utilized an approach where we test modelling choices of the spatially unambiguous kind, proposed by the wave of infections spreading from the initial slow progression to a higher curve. We have estimated the parameters of an individual state using factors like population density and mobility. The findings can also be used to strategize the testing and quarantine processes to manipulate the spread of the disease in the future. This is especially important for a country like India that has several limitations about healthcare infrastructure, diversity in socioeconomic status, high population density, housing conditions, health care coverage that can be important determinants for the overall impact of the pandemic. The results of our 5-phase model depict a projection of the state wise infections/disease over time. The model can generate live graphs as per the change in the data values as the values are automatically being fetched from the crowd-sourced database.