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时间序列分析在中国一大型城市中甲型、乙型、丙型和戊型肝炎感染:预测分析的应用。

Time-series analysis of hepatitis A, B, C and E infections in a large Chinese city: application to prediction analysis.

机构信息

Department of Hygiene, Sapporo Medical University School of Medicine, Sapporo, Hokkaido, Japan.

出版信息

Epidemiol Infect. 2013 May;141(5):905-15. doi: 10.1017/S095026881200146X. Epub 2012 Jul 20.

Abstract

Viral hepatitis is recognized as one of the most frequently reported diseases, and especially in China, acute and chronic liver disease due to viral hepatitis has been a major public health problem. The present study aimed to analyse and predict surveillance data of infections of hepatitis A, B, C and E in Wuhan, China, by the method of time-series analysis (MemCalc, Suwa-Trast, Japan). On the basis of spectral analysis, fundamental modes explaining the underlying variation of the data for the years 2004-2008 were assigned. The model was calculated using the fundamental modes and the underlying variation of the data reproduced well. An extension of the model to the year 2009 could predict the data quantitatively. Our study suggests that the present method will allow us to model the temporal pattern of epidemics of viral hepatitis much more effectively than using the artificial neural network, which has been used previously.

摘要

病毒性肝炎是最常报告的疾病之一,特别是在中国,由病毒性肝炎引起的急性和慢性肝病一直是一个主要的公共卫生问题。本研究旨在通过时间序列分析(日本 MemCalc、Suwa-Trast)方法分析和预测中国武汉的甲型、乙型、丙型和戊型肝炎感染监测数据。在谱分析的基础上,为 2004-2008 年的数据分配了解释数据基本变化的基本模式。该模型是使用基本模式和数据的基本变化计算的,并且很好地再现了数据。该模型的扩展到 2009 年可以定量预测数据。我们的研究表明,与之前使用的人工神经网络相比,本方法将使我们能够更有效地对病毒性肝炎的流行模式进行建模。

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