A Prospective Approach on Covid-19 Forecasting Using LSTM

Abstract

The novel Corona virus has been proclaimed as a worldwide pandemic through World Health Organization in the March 2020 has immensely affected the world with its ferocity. By observation, the scientists got to know that it transmits from one human to other by droplets which range from larger respiratory droplets to smaller aerosols or direct contact with an infected person. Its impurity has been assessed to have an incubation time of 6.4 days than a simple reproduction amount of 2.24-3.58.[19] The transmission rate and spread of infection is quite rapid as compared to other fatal viral infections encountered till date. A massive loss of human life was faced even by the developed countries which had the best health-care facilities. According to WHO, COVID-19 has been confirmed in 238,521,855 people over the world, with 4,863,818 deaths as of October 9th, 2021. After experiencing the second covid wave, the number of cases had got dropped drastically but the increase in their number in the recent days is a major cause of concern. This stresses us to build some prediction models which could help in providing relief to the virus-prone areas. In this study, we are using time series for predicting forthcoming cases of corona virus.