Forecasting the dynamics of COVID-19 Pandemic in Top 15 countries in April 2020 through ARIMA Model with Machine Learning Approach

Pavan Kumar; Himangshu Kalita; Shashikanta Patairiya; Yagya Datt Sharma; Chintan Nanda; Meenu Rani; Jamal Rahmai; Akshaya Srikanth Bhagavathula

Another type of COVID-19, like SARS disease (Severe Acute Respiratory Syndrome), is analyzed without breaking the current situation and predicting the future perspective [8] . VAR model (Vector Auto Average) model is used to predict the spatial extinct while using remote sensing data and for the purpose of creation of GIS map of worldwide on three different variables [9] . These three variables in the GIS environment create a map of cumulative confirmed cases country-wise as well as recovered and death map [10] . The use of another statistical analysis is a generalized logistic growth model (GLM), which generally depicted as a scaling parameter of integrating an additional result-oriented value put method [11] . Some epidemic models used in disease epidemic conditions measure oscillates some multiple peak parameters inferred in sub-epidemic and pandemic conditions to determine the projected