In December 2019, a novel coronavirus was found in a seafood wholesale market in Wuhan, China. On January 30, 2020 the first case of COVID-19 pandemic in India was reported. The spread escalated in the month of March and April in India. This paper deals with traditional infectious disease prediction models predicting the bed occupancy rate for few states in India. The correlation for recovered and deceased with confirmed cases were found and a relation is obtained by using linear and quadratic regression equation. Based on the results obtained probabilistic model is predicted for number of bed occupancy for a specific time period. The three distributions that are used with the probabilistic models are Poisson distribution, weighted Poisson distribution and Geometric Poisson distribution. The data has been taken from website for the month of March and April and were tested for fitting of proposed distributions using goodness of fit. Graph of deceased, recovered, and confirmed COVID cases for a particular time period is shown. The study is considered to be preliminary as there is only comparison of the distributions based on bed occupancy and the probability of occurrence. But this method can be extended for more months and for various distributions for better future predictions. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Application of Geometric Poisson Distribution for COVID-19 in Selected States of India