Wavelet-based Statistical and Mathematical Analysis of Spread of COVID-19

ABSTRACT

T he and spreadoutbreak mortality. of COVIDof Therefore, coronavirus-19−19 which the will researchers (NCoV-19)help in planninghas are developed using to control various a universalthe available diseasecrisis methods andduetotomanage to high study ratethe the ofhealth pattern infectioncare of resources. This study compares Autoregressive Integrated Moving Average (ARIMA) (statistical), Logistic, Gompertz (mathematical) and their hybrid using Wavelet−based Forecast (WBF) models to model and predict the number of confirmed cases of COVID−19. The study area includes the countries Iran, Italy, Pakistan, Saudi Arabia, USA, UK and Canada. Moreover, root mean squares error (RMSE) is used to compare the performance of studied models. Empirical analysis shows that confirmed cases could be adequately modelled using ARIMA and ARIMA-WBF for all the countries under consideration. However, for future prediction significance of the models varies region to region. © 2021. Advancements in Life Sciences. All rights reserved.