The analysis of vaccination and the prediction model based on the seasonal-ARIMA model

YuHong Zhao

doi:10.1117/12.2649152

27 September 2022 The analysis of vaccination and the prediction model based on the seasonal-ARIMA model

YuHong Zhao

Proceedings Volume 12345, International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022); 1234518 (2022) https://doi.org/10.1117/12.2649152
Event: 2022 International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022), 2022, Qingdao, China

Abstract

Since the outbreak of the novel Coronavirus in 2019, every country around the world has invested many resources in vaccine research and development. The goal of this paper is to investigate the current vaccination status around the world. And using the time series model to have a general grasp of the future vaccination trend. We used the Seasonal-ARIMA Model to predict the vaccination status in the next two years based on the collected data. Seasonal-ARIMA model, as a very commonly used model in time series forecasting, has a relatively good performance in forecasting. The data in this article comes from the OWID organization (our world in data), which is a non-profit organization based in the United Kingdom focusing on large global issues. And the data from this organization has high credibility. We have a prediction of future vaccination by writing this article, which can serve as a reference for the relevant departments to formulate vaccine production plans.

Citation Download Citation

YuHong Zhao "The analysis of vaccination and the prediction model based on the seasonal-ARIMA model", Proc. SPIE 12345, International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022), 1234518 (27 September 2022); https://doi.org/10.1117/12.2649152

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