Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models.

ABSTRACT:

Background

Mathematical and statistical models are used to predict trends in epidemic spread and determine the effectiveness of control measures. Automatic regressive integrated moving average (ARIMA) models are used for time-series forecasting, but only few models of the 2019 coronavirus disease (COVID-19) pandemic have incorporated protective behaviors or vaccination, known to be effective for pandemic control.

Methods

To improve the accuracy of prediction, we applied newly developed ARIMA models with predictors (mask wearing, avoiding going out, and vaccination) to forecast weekly COVID-19 case growth rates in Canada, France, Italy, and Israel between January 2021 and March 2022. The open-source data was sourced from the YouGov survey and Our World in Data. Prediction per

SUBMITTER: Cheng C 

PROVIDER: S-EPMC10408098 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature