新冠肺炎病例数比较的同时置信带方法。

Pub Date : 2023-01-01 Epub Date: 2023-03-07 DOI:10.1007/s12561-023-09364-y
Q Shao
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引用次数: 1

摘要

2020年1月,新型冠状病毒(新冠肺炎)的爆发被宣布为全球紧急事件,世界各地的日常生活受到干扰。在许多关于新冠肺炎的问题中,社会有兴趣确定男性和女性的每日病例数是否存在显著差异。由于传染病的性质,每日病例数序列是相关的,并且由于一些意外事件,如疫苗接种和德尔塔变异株的出现,包含非线性趋势。这些意外事件可能改变了生成数据的动力系统。经典的t检验不适合分析这种具有非恒定趋势的相关数据。本研究采用同时置信带方法试图克服这些困难;即,使用B样条估计构建自回归移动平均时间序列趋势的同时置信带。将所提出的方法应用于2020年4月1日至2022年3月31日俄亥俄州男女老年人(至少60岁)的每日病例数数据,结果显示,根据人口规模调整后的男女病例数在95%置信水平上存在显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts.

Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts.

Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts.

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Simultaneous Confidence Band Approach for Comparison of COVID-19 Case Counts.

The outbreak of the novel coronavirus (COVID-19) was declared to be a global emergency in January of 2020, and everyday life throughout the world was disrupted. Among many questions about COVID-19 that remain unanswered, it is of interest for society to identify whether there is any significant difference in daily case counts between males and females. The daily case count sequences are correlated due to the nature of a contagious disease, and contain a nonlinear trend owing to several unexpected events, such as vaccinations and the appearance of the delta variant. It is possible that these unexpected events have changed the dynamical system that generates data. The classic t-test is not appropriate to analyze such correlated data with a nonconstant trend. This study applies a simultaneous confidence band approach in an attempt to overcome these difficulties; that is, a simultaneous confidence band for the trend of an autoregressive moving-average time series is constructed using B-spline estimation. The proposed method is applied to the daily case count data of seniors of both genders (at least 60 years old) in the State of Ohio from April 1, 2020 to March 31, 2022, and the result shows that there is a significant difference at the 95% confidence level between the two gender case counts adjusted for the population sizes.

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