ARIMA Model Analysis of COVID-19 Mortality Rate Changes: Evaluation of Pfizer Vaccine Effectiveness

Weiqun Xu ()
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Weiqun Xu: Nanjing Medical University, School Of Health Policy & Management

A chapter in Proceedings of the 2024 3rd International Conference on Public Service, Economic Management and Sustainable Development (PESD 2024), 2024, pp 215-223 from Springer

Abstract: Abstract COVID-19, caused by a novel coronavirus called SARS-CoV-2, is an infectious disease. The virus was initially identified in late 2019 in Wuhan, Hubei Province, China, and rapidly disseminated worldwide, resulting in a widespread global pandemic and substantial loss of life. To examine whether the Pfizer vaccine had a significant effect on the reduction of mortality from CDC by analysing the difference in mortality rates before and after Pfizer vaccination of confirmed cases of COVID-19 An autoregressive summated moving average (ARIMA) was constructed based on data released by the CDC. The implicit assumption of this model is that the predictions of the model are treated as a “control group” containing only the time trend that is not affected by the vaccine, and that the experimental group is the true value affected by the vaccine. Two models, ARIMA (2,1,1) and ARIMA (10,2,3), showed an increasing difference between predicted and actual values. The mortality rate of COVID-19 had a substantial decrease following widespread administration of the Pfizer COVID-19 vaccine. This study aims to examine if the widespread distribution of the Pfizer vaccine has resulted in a decrease in the fatality rate of COVID-19 infections.

Keywords: Covid-19; Death rate; ARIMA (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-598-0_22

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