Biases in routine influenza surveillance indicators used to monitor infection incidence and recommendations for improvement

O. Eales, J. McCaw, F. Shearer
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Abstract

Background: Monitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence. Method: Here we demonstrate, through mathematical reasoning, the relationship between the incidence of influenza infections and three commonly reported surveillance indicators: 1) the rate per unit time of influenza-like illness reported through sentinel healthcare sites, 2) the rate per unit time of laboratory-confirmed influenza infections, and 3) the proportion of laboratory tests positive for influenza (`test-positive proportion'). Results: Our analysis suggests that none of these ubiquitously reported surveillance indicators are a reliable tool for monitoring influenza incidence. In particular, we highlight how these surveillance indicators can be heavily biased by: the dynamics of circulating pathogens (other than influenza) with similar symptom profiles; changes in testing rates; and differences in infection rates, symptom rates, and healthcare-seeking behaviour between age-groups and through time. We make six practical recommendations to improve the monitoring of influenza infection incidence. The implementation of our recommendations would enable the construction of more interpretable surveillance indicator(s) for influenza from which underlying patterns of infection incidence could be readily monitored. Conclusion: The implementation of all (or a subset) of our recommendations would greatly improve understanding of the transmission dynamics, infection burden, and clinical severity of influenza, improving our ability to respond effectively to seasonal epidemics and future pandemics.
用于监测感染发生率的常规流感监测指标的偏差及改进建议
背景:监测流感感染率随时间的变化对量化流感的传播动态和临床严重程度非常重要。感染率难以直接测量,因此,我们使用其他更易于监测的数量来监测感染水平的趋势,并假定这些数量与感染率相关。方法:在此,我们通过数学推理证明了流感感染率与三种常见监测指标之间的关系:1)单位时间内通过定点医疗机构报告的流感样病例的比率;2)单位时间内经实验室确诊的流感感染病例的比率;3)流感实验室检测呈阳性的比例("检测呈阳性比例")。结果:我们的分析表明,这些普遍报告的监测指标都不是监测流感发病率的可靠工具。我们特别强调了这些监测指标是如何受到以下因素的严重影响:症状特征相似的流行病原体(流感除外)的动态变化;检测率的变化;不同年龄组和不同时期的感染率、症状率和就医行为的差异。我们提出了六项切实可行的建议,以改进对流感感染率的监测。实施我们的建议将有助于建立更易于解释的流感监测指标,从而可随时监测感染发生率的基本模式。结论:实施我们提出的所有(或部分)建议将极大地提高人们对流感传播动态、感染负担和临床严重程度的了解,从而提高我们有效应对季节性流行病和未来大流行病的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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