WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong).
Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, Hong Kong, China (Hong Kong).
JMIR Public Health Surveill. 2023 Jan 11;9:e41329. doi: 10.2196/41329.
Influenza causes considerable disease burden each year, particularly in children. Monitoring school absenteeism has long been proposed as a surveillance tool of influenza activity in the community, but the practice of school absenteeism could be varying, and the potential of such usage remains unclear.
The aim of this paper is to determine the potential of monitoring school absenteeism as a surveillance tool of influenza.
We conducted a systematic review of the published literature on the relationship between school absenteeism and influenza activity in the community. We categorized the types of school absenteeism and influenza activity in the community to determine the correlation between these data streams. We also extracted this correlation with different lags in community surveillance to determine the potential of using school absenteeism as a leading indicator of influenza activity.
Among the 35 identified studies, 22 (63%), 12 (34%), and 8 (23%) studies monitored all-cause, illness-specific, and influenza-like illness (ILI)-specific absents, respectively, and 16 (46%) used quantitative approaches and provided 33 estimates on the temporal correlation between school absenteeism and influenza activity in the community. The pooled estimate of correlation between school absenteeism and community surveillance without lag, with 1-week lag, and with 2-week lag were 0.44 (95% CI 0.34, 0.53), 0.29 (95% CI 0.15, 0.42), and 0.21 (95% CI 0.11, 0.31), respectively. The correlation between influenza activity in the community and ILI-specific absenteeism was higher than that between influenza activity in community all-cause absenteeism. Among the 19 studies that used qualitative approaches, 15 (79%) concluded that school absenteeism was in concordance with, coincided with, or was associated with community surveillance. Of the 35 identified studies, only 6 (17%) attempted to predict influenza activity in the community from school absenteeism surveillance.
There was a moderate correlation between school absenteeism and influenza activity in the community. The smaller correlation between school absenteeism and community surveillance with lag, compared to without lag, suggested that careful application was required to use school absenteeism as a leading indicator of influenza epidemics. ILI-specific absenteeism could monitor influenza activity more closely, but the required resource or school participation willingness may require careful consideration to weight against the associated costs. Further development is required to use and optimize the use of school absenteeism to predict influenza activity. In particular, the potential of using more advanced statistical models and validation of the predictions should be explored.
流感每年都会给人类带来巨大的疾病负担，尤其是儿童。监测学校缺课率长期以来一直被提议作为社区流感活动的监测工具，但实际的监测情况可能因地区而异，其潜在用途仍不明确。
本文旨在确定监测学校缺课率作为流感监测工具的潜力。
我们对已发表的关于社区流感活动与学校缺课率之间关系的文献进行了系统回顾。我们对社区流感活动和学校缺课率进行了分类，以确定这些数据流之间的相关性。我们还提取了社区监测中不同时间滞后的相关性，以确定使用学校缺课率作为流感活动的领先指标的潜力。
在 35 项已确定的研究中，分别有 22 项（63%）、12 项（34%）和 8 项（23%）研究监测了全因缺勤、特定疾病缺勤和流感样疾病（ILI）缺勤，16 项（46%）使用了定量方法，并提供了 33 项关于社区流感活动与学校缺课率之间时间相关性的估计值。没有时间滞后、有 1 周滞后和有 2 周滞后的学校缺课率与社区监测之间的相关性的汇总估计值分别为 0.44（95%CI 0.34, 0.53）、0.29（95%CI 0.15, 0.42）和 0.21（95%CI 0.11, 0.31）。社区流感活动与 ILI 特异性缺勤之间的相关性高于社区全因缺勤与流感活动之间的相关性。在使用定性方法的 19 项研究中，有 15 项（79%）的研究结论认为，学校缺课率与社区监测结果一致、相符或相关。在已确定的 35 项研究中，只有 6 项（17%）试图从学校缺课率监测中预测社区流感活动。
学校缺课率与社区流感活动之间存在中度相关性。与无滞后相比，滞后时学校缺课率与社区监测之间的相关性较小，这表明需要谨慎应用学校缺课率作为流感流行的领先指标。ILI 特异性缺勤可更密切地监测流感活动，但所需资源或学校参与意愿可能需要仔细考虑，以权衡相关成本。需要进一步开发和优化使用学校缺课率来预测流感活动。特别是，应该探索使用更先进的统计模型和验证预测的潜力。
