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[下萨克森州传染病通报数据的空间统计分析]

[Spatial-statistical analysis of infectious disease notification data in lower saxony].

作者信息

Dreesman J, Scharlach H

机构信息

Niedersächsisches Landesgesundheitsamt Hannover.

出版信息

Gesundheitswesen. 2004 Dec;66(12):783-9. doi: 10.1055/s-2004-813825.

Abstract

BACKGROUND

In Lower Saxony the analysis of notification data according to the infection protection law is based on two pillars: one pillar is the weekly analysis to identify clusters and locally non-detectable outbreaks by an early warning system. The second pillar is an annual reporting system for obtaining an overall picture and for identifying long-term trends. In both fields methods of spatial statistics are applied.

METHODS

For the 16 most frequent notifiable diseases, the notification data of the districts of Lower Saxony are analysed and presented on the Internet. The presentation starts with an overview page, on which differences between observed and expected case counts for these diseases are presented tabulated and graphically. On a separate page for each disease the temporal and spatial distribution is shown by means of the following graphs: Time series presentation (weekly case counts and moving averages), chloropleth map of regional incidence rates and dot map of regional case counts. For identification of outbreaks, Kulldorff's "scan statistic" is used to search the data for clusters and to assess the significance of these clusters. The methods are executed mainly automatically using predominantly public domain software.

RESULTS AND DISCUSSION

The approach attempts to meet the surveillance principle of providing the participants with immediate feedback. The scan statistics is a universal objective instrument for detecting and assessing spatial clusters. A special advantage is the identification of clusters which include several districts. The properties of the identified clusters (spatial extension, number of cases) offer some insight into the characteristic epidemiology of the diseases.

摘要

背景

在下萨克森州,依据《感染保护法》对通报数据进行分析基于两大支柱:一个支柱是每周分析,通过预警系统识别聚集性病例和局部未被发现的疫情。第二个支柱是年度报告系统,用于获取总体情况并识别长期趋势。在这两个领域都应用了空间统计方法。

方法

针对16种最常见的应通报疾病,对下萨克森州各地区的通报数据进行分析并在互联网上展示。展示从一个概述页面开始,在该页面上以表格和图形形式呈现这些疾病观察到的病例数与预期病例数之间的差异。在每种疾病的单独页面上,通过以下图表展示时间和空间分布:时间序列展示(每周病例数和移动平均值)、区域发病率的分级统计图以及区域病例数的点图。为了识别疫情,使用库尔道夫的“扫描统计量”在数据中搜索聚集性病例并评估这些聚集性病例的显著性。这些方法主要使用主要为公共领域的软件自动执行。

结果与讨论

该方法试图满足向参与者提供即时反馈的监测原则。扫描统计量是检测和评估空间聚集性病例的通用客观工具。一个特别的优势是能够识别包含多个地区的聚集性病例。所识别聚集性病例的特征(空间范围、病例数)为了解这些疾病的特征性流行病学提供了一些见解。

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