Facing a Pandemic: A COVID-19 Time Series Analysis of Vaccine Impact

被引:0
|
作者
Sainz-Tinajero, Benjamin Mario [1 ]
Otero-Argote, Dachely [1 ]
Orozco-Mora, Carmen Elisa [1 ]
Gonzalez-Mendoza, Miguel [1 ]
机构
[1] Tecnol Monterrey, Sch Engn & Sci, Atizapan De Zaragoza 52926, Estado De Mexic, Mexico
关键词
COVID-19; Vaccination; Time series analysis; Data mining;
D O I
10.1007/978-3-030-89817-5_23
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Economics, social encounters, and most importantly, human life was deeply affected by the COVID-19 pandemic. The international state of contingency led vaccine manufacturers worldwide to double their efforts in developing a vaccine that would be influential in contagion rate decrease. This paper offers an overview of the worldwide vaccination process and its impact on confirmed cases. In this work, we present a time series analysis methodology to predict which country group using each of the most popular vaccines will have the less steep curve of confirmed cases in a time window of 21 days. The experiments led to 94% of the data fitting our models on average, leading to a confident suggestion on the vaccine related to the less steep foreseeable contagion slope.
引用
收藏
页码:303 / 314
页数:12
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