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疫苗接种前时代儿童疾病报告不完整的保守模式。

Conserved patterns of incomplete reporting in pre-vaccine era childhood diseases.

作者信息

Gunning Christian E, Erhardt Erik, Wearing Helen J

机构信息

Department of Biology, University of New Mexico, Albuquerque, NM, USA

Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, USA.

出版信息

Proc Biol Sci. 2014 Nov 7;281(1794):20140886. doi: 10.1098/rspb.2014.0886.

Abstract

Incomplete observation is an important yet often neglected feature of observational ecological timeseries. In particular, observational case report timeseries of childhood diseases have played an important role in the formulation of mechanistic dynamical models of populations and metapopulations. Yet to our knowledge, no comprehensive study of childhood disease reporting probabilities (commonly referred to as reporting rates) has been conducted to date. Here, we provide a detailed analysis of measles and whooping cough reporting probabilities in pre-vaccine United States cities and states, as well as measles in cities of England and Wales. Overall, we find the variability between locations and diseases greatly exceeds that between methods or time periods. We demonstrate a strong relationship within location between diseases and within disease between geographical areas. In addition, we find that demographic covariates such as ethnic composition and school attendance explain a non-trivial proportion of reporting probability variation. Overall, our findings show that disease reporting is both variable and non-random and that completeness of reporting is influenced by disease identity, geography and socioeconomic factors. We suggest that variations in incomplete observation can be accounted for and that doing so can reveal ecologically important features that are otherwise obscured.

摘要

不完整观测是观测性生态时间序列的一个重要但常被忽视的特征。特别是,儿童疾病的观测病例报告时间序列在种群和集合种群的机械动力学模型的制定中发挥了重要作用。然而据我们所知,迄今为止尚未对儿童疾病报告概率(通常称为报告率)进行全面研究。在此,我们详细分析了疫苗接种前美国各城市和州的麻疹和百日咳报告概率,以及英格兰和威尔士各城市的麻疹报告概率。总体而言,我们发现地点和疾病之间的变异性大大超过了方法或时间段之间的变异性。我们证明了疾病在地点内部以及地理区域之间的疾病内部存在很强的关系。此外,我们发现诸如种族构成和入学率等人口统计学协变量解释了报告概率变化的相当一部分。总体而言,我们的研究结果表明疾病报告既具有变异性又非随机,并且报告的完整性受到疾病种类、地理位置和社会经济因素的影响。我们建议可以解释不完整观测中的变化,这样做可以揭示那些否则会被掩盖的具有生态重要性的特征。

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