Estimating the under-reporting rate for infectious gastrointestinal illness in Ontario
Estimating the under-reporting rate for infectious gastrointestinal illness in Ontario
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DOI：
10.1007/bf03403685
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发表时间：
2005-05-01
影响因子：
4.3
通讯作者：
Wilson, JB
中科院分区：
文献类型：
--
作者：
Majowicz, SE;Edge, VL;Wilson, JB
背景资料：在安大略，传染性胃肠道疾病（IGI）报告可通过省级可报告疾病监测系统中捕获病例所需的几个连续步骤的线性模型表示。由于可报告的肠道数据是已知的，代表只有一小部分的总IGI在社区中，本研究的目的是估计IGI的漏报率在安大略。方法：一个分布的合理值的漏报率估计指定输入分布的比例报告在报告链中的每一步，并乘以这些分布一起使用模拟方法。输入分布使用加拿大公共卫生署急性胃肠道疾病国家研究（NSAGI）倡议的数据确定报告链每一步报告的病例比例（分布类型和参数）。对于安大略省报告的每一例肠道疾病，社区IGI病例的估计数为105至1389例，中位数为285，平均值和标准差分别为313和128.Conclusions：每例肠道疾病报告的安大略省代表估计几百例IGI的社区。因此，在估计此类疾病的负担时，应谨慎使用可报告的疾病数据。项目规划者和公共卫生人员在制定基于人群的干预措施时可能需要考虑这一事实。
Background: In Ontario, infectious gastrointestinal illness (IGI) reporting can be represented by a linear model of several sequential steps required for a case to be captured in the provincial reportable disease surveillance system. Since reportable enteric data are known to represent only a small fraction of the total IGI in the community, the objective of this study was to estimate the under-reporting rate for IGI in Ontario.Methods: A distribution of plausible values for the under-reporting rate was estimated by specifying input distributions for the proportions reported at each step in the reporting chain, and multiplying these distributions together using simulation methods. Input distributions (type of distribution and parameters) for the proportion of cases reported at each step of the reporting chain were determined using data from the Public Health Agency of Canada's National Studies on Acute Gastrointestinal Illness (NSAGI) initiative.Results: For each case of enteric illness reported to the province of Ontario, the estimated number of cases of IGI in the community ranged from 105 to 1,389, with a median of 285, and a mean and standard deviation of 313 and 128, respectively.Conclusions: Each case of enteric illness reported to the province of Ontario represents an estimated several hundred cases of IGI in the community. Thus, reportable disease data should be used with caution when estimating the burden of such illness. Program planners and public health personnel may want to consider this fact when developing population-based interventions.