Aldridge Robert W, Hayward Andrew C, Field Nigel, Warren-Gash Charlotte, Smith Colette, Pebody Richard, Fleming Declan, McCracken Shane
Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, United Kingdom.
The Farr Institute of Health Informatics Research, University College London, 222 Euston Road, London, NW1 2DA, United Kingdom.
PLoS One. 2016 Mar 2;11(3):e0146964. doi: 10.1371/journal.pone.0146964. eCollection 2016.
School aged children are a key link in the transmission of influenza. Most cases have little or no interaction with health services and are therefore missed by the majority of existing surveillance systems. As part of a public engagement with science project, this study aimed to establish a web-based system for the collection of routine school absence data and determine if school absence prevalence was correlated with established surveillance measures for circulating influenza.
We collected data for two influenza seasons (2011/12 and 2012/13). The primary outcome was daily school absence prevalence (weighted to make it nationally representative) for children aged 11 to 16. School absence prevalence was triangulated graphically and through univariable linear regression to Royal College of General Practitioners (RCGP) influenza like illness (ILI) episode incidence rate, national microbiological surveillance data on the proportion of samples positive for influenza (A+B) and with Rhinovirus, RSV and laboratory confirmed cases of Norovirus.
27 schools submitted data over two respiratory seasons. During the first season, levels of influenza measured by school absence prevalence and established surveillance were low. In the 2012/13 season, a peak of school absence prevalence occurred in week 51, and week 1 in RCGP ILI surveillance data. Linear regression showed a strong association between the school absence prevalence and RCGP ILI (All ages, and 5-14 year olds), laboratory confirmed cases of influenza A & B, and weak evidence for a linear association with Rhinovirus and Norovirus.
This study provides initial evidence for using routine school illness absence prevalence as a novel tool for influenza surveillance. The network of web-based data collection platforms we established through active engagement provides an innovative model of conducting scientific research and could be used for a wide range of infectious disease studies in the future.
学龄儿童是流感传播的关键环节。大多数病例与卫生服务机构很少或没有接触，因此大多数现有的监测系统都未能发现这些病例。作为公众参与科学项目的一部分，本研究旨在建立一个基于网络的系统，用于收集常规的学校缺勤数据，并确定学校缺勤率与已确立的流感流行监测指标之间是否存在关联。
我们收集了两个流感季节（2011/12和2012/13）的数据。主要结果是11至16岁儿童的每日学校缺勤率（加权处理以使其具有全国代表性）。通过图形分析和单变量线性回归，将学校缺勤率与皇家全科医师学院（RCGP）的流感样疾病（ILI）发病率、国家微生物监测数据（流感（A+B）阳性样本比例以及鼻病毒、呼吸道合胞病毒和实验室确诊的诺如病毒病例）进行对比分析。
27所学校在两个呼吸道疾病季节提交了数据。在第一个季节，通过学校缺勤率和既定监测方法测得的流感水平较低。在2012/13季节，学校缺勤率在第51周出现峰值，而RCGP的ILI监测数据显示在第1周出现峰值。线性回归显示，学校缺勤率与RCGP的ILI（所有年龄段以及5至14岁儿童）、实验室确诊的甲型和乙型流感病例之间存在很强的关联，而与鼻病毒和诺如病毒存在线性关联的证据较弱。
本研究为将常规学校疾病缺勤率用作流感监测的新工具提供了初步证据。我们通过积极参与建立的基于网络的数据收集平台网络提供了一种创新的科研模式，未来可用于广泛的传染病研究。
