Global seasonal and pandemic patterns in influenza: An application of longitudinal study designs

IF 1.7 3区数学 Q1 STATISTICS & PROBABILITY

International Statistical Review Pub Date : 2022-10-23 DOI:10.1111/insr.12529

Elena N. Naumova, Ryan B. Simpson, Bingjie Zhou, Meghan A. Hartwick

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引用次数: 0

Abstract

The confluence of growing analytic capacities and global surveillance systems for seasonal infections has created new opportunities to further develop statistical methodology and advance the understanding of the global disease dynamics. We developed a framework to characterise the seasonality of infectious diseases for publicly available global health surveillance data. Specifically, we aimed to estimate the seasonal characteristics and their uncertainty using mixed effects models with harmonic components and the δ-method and develop multi-panel visualisations to present complex interplay of seasonal peaks across geographic locations. We compiled a set of 2 422 weekly time series of 14 reported outcomes for 173 Member States from the World Health Organization's (WHO) international influenza virological surveillance system, FluNet, from 02 January 1995 through 20 June 2021. We produced an analecta of data visualisations to describe global travelling waves of influenza while addressing issues of data completeness and credibility. Our results offer directions for further improvements in data collection, reporting, analysis and development of statistical methodology and predictive approaches.

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流感的全球季节性和大流行模式:纵向研究设计的应用

日益增长的分析能力和全球季节性感染监测系统的汇合为进一步发展统计方法和促进对全球疾病动态的了解创造了新的机会。我们开发了一个框架，为公开的全球卫生监测数据描述传染病的季节性特征。具体来说，我们的目标是使用谐波分量和δ方法的混合效应模型来估计季节特征及其不确定性，并开发多面板可视化来呈现不同地理位置的季节峰值的复杂相互作用。从1995年1月2日至2021年6月20日，我们编制了一套2422个每周时间序列，其中包括世界卫生组织(世卫组织)国际流感病毒学监测系统fluet的173个会员国的14项报告结果。我们制作了一份数据可视化的analecata，以描述全球流感传播波，同时解决数据完整性和可信度问题。我们的研究结果为进一步改进数据收集、报告、分析以及统计方法和预测方法的发展提供了方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Statistical Review 数学-统计学与概率论

CiteScore

4.30

自引率

5.00%

发文量

审稿时长

>12 weeks

期刊介绍： International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.