Analysis of Time-Series Trends and ARIMA models to Forecast COVID – 19 cases

Abstract

COVID-19 a novel corona virus originated from Wuhan China. It turned into a pandemic resulting in a large number of deaths and loss of livelihood. It is vital to determine the manner in which the number of cases propagates so that future pandemics can be tackled scientifically. However the pandemic can be controlled systematically using efficient health care systems. It is difficult to predict the pandemic propagation over a large period of time due to various factors. In this paper an analysis is made for short periods using statistical tools like predicting the probability curve, probability density function. Forecasting of Covid-19 cases is done using time series trend analysis and ARIMA models. The test of hypothesis for difference of means and standard deviations of the actual and forecasted values with 99% CI showed no significant difference between them.