Spatio-Temporal distribution characteristic of covid-19 vaccine using time series forecasting

Abstract

Over 170 nations have been affected from Coronavirus disease 2019(COVID-19). In nearly all the afflicted countries, the number of afflicted people and dying people has been rising at a frightening rate. Our biggest option for halting the pandemic’s spread is a COVID-19 vaccination. But vaccines are an exhaustible resource. Accurate prediction of vaccine distribution by already implemented policies is critical to assisting policymakers in making sufficient decisions in containing COVID-19 pandemic. Forecasting approaches can be utilized, aiding in the development of better plans and the making of sound judgments. These approaches analyze past events to make more accurate predictions about what will happen in the future according to the current implemented strategy. The effectiveness of various LSTM (Long Short-Term Memory) models as well as the ARIMA (Auto-Regressive Integrated Moving Average) model in projecting vaccine distribution for COVID-19 patients.