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性传播疾病核心理论:人与地点和时间的作用。

Sexually transmitted disease core theory: roles of person, place, and time.

机构信息

Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th Floor, Toronto, Ontario, Canada.

出版信息

Am J Epidemiol. 2011 Jul 1;174(1):81-9. doi: 10.1093/aje/kwr035. Epub 2011 May 3.

Abstract

The authors' purpose was to expand sexually transmitted disease core theory by examining the roles of person, place, and time in differentiating geographic core areas from outbreak areas. The authors mapped yearly census-tract-level syphilis rates for San Francisco, California, based on new primary and secondary syphilis cases reported to the San Francisco City sexually transmitted disease surveillance program between January 1, 1985, and December 31, 2007. SaTScan software (Information Management Services, Inc., Silver Spring, Maryland) was used to identify geographic clusters of significantly elevated syphilis rates over space and time. The authors graphed epidemic curves for 1) core areas, 2) outbreak areas, 3) neither core nor outbreak areas, and 4) noncore areas, where noncore areas included outbreaks, and stratified these curves according to demographic characteristics. Five clusters of significantly elevated primary and secondary syphilis rates were identified. A 5-year threshold was useful for differentiating core clusters from outbreak clusters. Epidemic curves for core areas, outbreak areas, neither core nor outbreak areas, and noncore areas were perfectly synchronized in phase trends and wavelength over time, even when broken down by demographic characteristics. Between epidemics, the occurrence of syphilis affected all demographic groups equally. During an epidemic, a temporary disparity in syphilis occurrence arose and a homogeneous core group of cases could be defined.

摘要

作者的目的是通过考察人、地、时在区分地理核心区和暴发区中的作用,扩展性传播疾病核心理论。作者基于 1985 年 1 月 1 日至 2007 年 12 月 31 日向旧金山市性传播疾病监测项目报告的新发原发性和继发性梅毒病例,绘制了加利福尼亚州旧金山市每年按人户区划分的梅毒发病率图。SaTScan 软件(马里兰州银泉市信息管理服务公司)用于确定空间和时间上梅毒发病率显著升高的地理聚集区。作者绘制了 1)核心区、2)暴发区、3)非核心和暴发区、4)非核心区(其中非核心区包括暴发区)的流行曲线,并根据人口统计学特征对这些曲线进行分层。确定了 5 个原发性和继发性梅毒发病率显著升高的聚集区。5 年的时间阈值有助于区分核心聚集区和暴发聚集区。核心区、暴发区、非核心和暴发区以及非核心区的流行曲线在时间上的相位趋势和波长完全同步,即使按人口统计学特征进行分层也是如此。在流行间歇期,梅毒的发生同样影响所有人群。在流行期间,梅毒的发生暂时出现差异,并可定义一个同质的核心病例组。

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