Abstract
We utilized the average weekly estimated reproduction number data of COVID-19 from March (2020–2021). By applying ARIMA and L-moments methodology, short-and-long-term forecasting of R0 is made for Govt. officials and public health experts to take before-time policy measures to control the spread of novel coronavirus. This study helps medical staff to measure the expected demand of COVID-19 vaccine doses. We applied various ARIMA models on each country’s data and the best selected based on RMSE, AIC, and BIC for point and interval forecasting. Application L-Moments techniques selected GLO, GEV, and GNO distributions and quantile estimation with return period calculations. The forecasting shows that maximum countries mean R0 > 1, which is still a serious threat and can lead to heath disaster. The forecasting provided an alarming situation in the coming months for India, France, Turkey, and Spain; health experts should take strict measures because the cases rise due to the high R0 forecast. The USA, Russia, and the UK mean R0 will not suddenly increase; these countries consistent in COVID-19 R0 control. We find that even the significant population differences prevail among selected countries, the R0 is still high in maximum countries, so its a dire need to take strict control actions to minimize the R0 for public safety.
Forecasting of COVID-19 Reproduction Number by ARIMA Methodology and Quantile Estimation based on Best Fit Distribution by L- moments for Top-10 Affected Countries