Potential for early warning of viral influenza activity in the community by monitoring clinical diagnoses of influenza in hospital emergency departments
Potential for early warning of viral influenza activity in the community by monitoring clinical diagnoses of influenza in hospital emergency departments
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DOI：
10.1186/1471-2458-7-250
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发表时间：
2007-09-19
影响因子：
4.5
通讯作者：
Churches, Tim
中科院分区：
文献类型：
--
作者：
Zheng, Wei;Aitken, Robert;Churches, Tim
背景：尽管综合症监测系统作为公共卫生的有用工具得到认可，但对预期的早期预警益处是否存在仍有疑虑。在比较监测时间序列时，对这一问题的许多评估没有充分考虑到自相关性和趋势的混淆影响，很少有人将综合症数据流与连续的基于实验室的标准进行比较。我们使用时间序列方法来评估监测被指定为流感临床诊断的急诊科(ED)就诊人数是否可以比监测实验室流感检测阳性结果的每日计数更早地提供人群中病毒性流感发病率上升的警告。方法：在2001年至2005年的五年期间，收集了澳大利亚新南威尔士州(NSW)被指派为临时流感诊断的急诊科就诊和实验室确认的流感病例的时间序列。泊松回归模型适用于这两个时间序列，以最大限度地减少趋势和自相关的混杂影响，并控制其他日历影响。为了评估两个序列的相对及时性，对模型残差进行了互相关分析。结果：使用完整的五年时间序列，估计ED时间序列的短期变化先于实验室序列的变化三天。就个别年份而言，估计为3至18天。2003年至2005年的时间优势估计在3至4天之间。结论：与实验室确诊的流感监测相比，临床诊断为流感的急诊科就诊监测时间序列可能提供3天的早期预警。如果考虑到目前的实验室处理和报告延误，这一时间优势甚至更大。
Background: Although syndromic surveillance systems are gaining acceptance as useful tools in public health, doubts remain about whether the anticipated early warning benefits exist. Many assessments of this question do not adequately account for the confounding effects of autocorrelation and trend when comparing surveillance time series and few compare the syndromic data stream against a continuous laboratory-based standard. We used time series methods to assess whether monitoring of daily counts of Emergency Department (ED) visits assigned a clinical diagnosis of influenza could offer earlier warning of increased incidence of viral influenza in the population compared with surveillance of daily counts of positive influenza test results from laboratories.Methods: For the five-year period 2001 to 2005, time series were assembled of ED visits assigned a provisional ED diagnosis of influenza and of laboratory-confirmed influenza cases in New South Wales (NSW), Australia. Poisson regression models were fitted to both time series to minimise the confounding effects of trend and autocorrelation and to control for other calendar influences. To assess the relative timeliness of the two series, cross-correlation analysis was performed on the model residuals. Modelling and cross-correlation analysis were repeated for each individual year.Results: Using the full five-year time series, short-term changes in the ED time series were estimated to precede changes in the laboratory series by three days. For individual years, the estimate was between three and 18 days. The time advantage estimated for the individual years 2003-2005 was consistently between three and four days.Conclusion: Monitoring time series of ED visits clinically diagnosed with influenza could potentially provide three days early warning compared with surveillance of laboratory-confirmed influenza. When current laboratory processing and reporting delays are taken into account this time advantage is even greater.