Wang Lei, Seasonal ARIMA model for Covid-19 pandemic Prediction in the United States, Journal of Model Based Research, Volume 2, Issue 1, 2023, Pages 20-27, ISSN 2643-2811, https://doi.org/10.14302/issn.2643-2811.jmbr-23-4529.
(https://oap-researcharticles.org/jmbr/article/1956)
Abstract: The COVID-19 pandemic has had a profound impact on global health and economies. The pandemic continues to spread and accurate forecasting of its spread is essential for the effective management of healthcare systems and the development of effective policies. The development of forecasting models for COVID-19 has become increasingly important as the pandemic continues to evolve. In this paper, we will summarize the Covid-19 pandemic in the United States state by state. And then, we utilize the temporal data of coronavirus spread from January 18, 2020 to January 29, 2023. Finally, we model the evolution of the COVID-19 outbreak and perform prediction using ARIMA and time series forecasting models on some selected states.
Keywords: Dynamic Harmonic Regression; COVID-19 pandemic; Forecasting models; Time series; Analysis