Wang Lei, Time Series Analysis and Prediction of COVID-19 pandemic using Dynamic Harmonic Regression Models, Journal of Model Based Research, Volume 2, Issue 1, 2023, Pages 28-36, ISSN 2643-2811, https://doi.org/10.14302/issn.2643-2811.jmbr-23-4528.
(https://oap-researcharticles.org/jmbr/article/1958)
Abstract: Rapidly spreading Covid-19 virus and its variants, especially in metropoli- tan areas around the world, became a major health public concern. The tendency of Covid-19 pandemic and statistical modelling represent an urgent challenge in the United States for which there are few solutions. In this paper, we demonstrate com- bining Fourier terms for capturing seasonality with ARIMA errors and other dynamics in the data. Therefore, we have analyzed 156 weeks COVID-19 dataset on national level using Dynamic Harmonic Regression model, including simulation analysis and ac- curacy improvement from 2020 to 2023. Most importantly, we provide a new advanced pathways which may serve as targets for developing new solutions and approaches.
Keywords: Dynamic Harmonic Regression with ARIMA errors; COVID-19 pan- demic; Forecasting models; Time series Analysis; Weekly seasonality.