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六种肠道传染病的季节性与环境温度

Seasonality in six enterically transmitted diseases and ambient temperature.

作者信息

Naumova E N, Jagai J S, Matyas B, DeMaria A, MacNeill I B, Griffiths J K

机构信息

Department of Public Health and Family Medicine, Tufts University School of Medicine, Boston, MA 02111, USA.

出版信息

Epidemiol Infect. 2007 Feb;135(2):281-92. doi: 10.1017/S0950268806006698.

Abstract

We propose an analytical and conceptual framework for a systematic and comprehensive assessment of disease seasonality to detect changes and to quantify and compare temporal patterns. To demonstrate the proposed technique, we examined seasonal patterns of six enterically transmitted reportable diseases (EDs) in Massachusetts collected over a 10-year period (1992-2001). We quantified the timing and intensity of seasonal peaks of ED incidence and examined the synchronization in timing of these peaks with respect to ambient temperature. All EDs, except hepatitis A, exhibited well-defined seasonal patterns which clustered into two groups. The peak in daily incidence of Campylobacter and Salmonella closely followed the peak in ambient temperature with the lag of 2-14 days. Cryptosporidium, Shigella, and Giardia exhibited significant delays relative to the peak in temperature (approximately 40 days, P<0.02). The proposed approach provides a detailed quantification of seasonality that enabled us to detect significant differences in the seasonal peaks of enteric infections which would have been lost in an analysis using monthly or weekly cumulative information. This highly relevant to disease surveillance approach can be used to generate and test hypotheses related to disease seasonality and potential routes of transmission with respect to environmental factors.

摘要

我们提出了一个分析性和概念性框架,用于对疾病季节性进行系统和全面的评估,以检测变化,并对时间模式进行量化和比较。为了演示所提出的技术,我们研究了马萨诸塞州在10年期间(1992 - 2001年)收集的六种经肠道传播的应报告疾病(EDs)的季节性模式。我们量化了ED发病率季节性高峰的时间和强度,并研究了这些高峰时间相对于环境温度的同步性。除甲型肝炎外,所有EDs均呈现出明确的季节性模式,可分为两组。弯曲杆菌和沙门氏菌的每日发病率高峰紧随环境温度高峰之后,滞后2 - 14天。隐孢子虫、志贺氏菌和贾第虫相对于温度高峰出现了显著延迟(约40天,P<0.02)。所提出的方法提供了对季节性的详细量化,使我们能够检测到肠道感染季节性高峰的显著差异,而这些差异在使用月度或每周累积信息的分析中可能会被忽略。这种高度相关的疾病监测方法可用于生成和检验与疾病季节性以及与环境因素相关的潜在传播途径有关的假设。

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