Time Series Analysis for Understanding the Vaccination Rate using ARIMA
Amulya Maitre, Dr. K. Rajeswari, Sushma Rahul Vispute · Zenodo (CERN European Organization for Nuclear Research) · 2021
The pandemic of the novel Coronavirus has led to a devastating situation all around the globe. With the introduction of vaccines by various pharmaceutical companies, there is a hope of recovery from this dreadful condition. In this work, we are using a Machine Learning (ML) approach, based on time series analysis called ARIMA to forecast vaccination rates in various countries. With experimentation, we are able to conclude the forecast of probable increase or decrease in vaccination rates for developed, developing, and underdeveloped countries. This approach will be helpful to apprehend which country needs more attention in terms of vaccine supply or creating awareness amongst its citizens.