Predicting COVID-19 Cases in Near Future in India Using Logistic Function
By: Samrat Dutta
Tags: Covid 19, Journal Publication, Logistic Regression

This paper is published by ITEE Journal, Vol 9, No. 5, October 2020. Find it on http://www.iteejournal.org/v9no5oct20_pdf10.pdf

Abstract

On 27th August, the day of conducting this study, India reported the highest single-day increase of over 75,000 COVID-19 cases [8]. With the exponential increase in the number of COVID-19 cases in India, our lives are at risk. There is subsequent stress on our health professionals and administration as the number of cases is increasing every day and a large number of people are being unable to afford a bed in a hospital. It will be helpful for the administration if they have a predicted value of COVID-19 cases that we might see in future. Making important decisions by the government and other professionals will be easy if they have an overview of how much the disease is likely to spread in the near future. We used a dataset that has daily recorded COVID-19 data, from 30th January 2020, when the first COVID-19 case was reported in India, to 27th August 2020. I used Logistic function to predict the number of COVID-19 cases we might see in future, in India. The prediction is based on only the recorded increment in COVID-19 cases daily in India.

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