Abstract

BackgroundSyndromic surveillance systems are an essential component of public health surveillance and can provide timely detection of infectious disease cases and outbreaks. Whilst surveillance systems are generally embedded within healthcare, there is increasing interest in novel data sources for monitoring trends in illness, such as over-the-counter purchases, internet-based health searches and worker absenteeism. This systematic review considers the utility of school attendance registers in the surveillance of infectious disease outbreaks and occurrences amongst children.MethodsWe searched eight databases using key words related to school absence, infectious disease and syndromic surveillance. Studies were limited to those published after 1st January 1995. Studies based in nursery schools or higher education settings were excluded. Article screening was undertaken by two independent reviewers using agreed eligibility criteria. Data extraction was performed using a standardised data extraction form. Outcomes included estimates of absenteeism, correlation with existing surveillance systems and associated lead or lag times.ResultsFifteen studies met the inclusion criteria, all of which were concerned with the surveillance of influenza. The specificity of absence data varied between all-cause absence, illness absence and syndrome-specific absence. Systems differed in terms of the frequency of data submissions from schools and the level of aggregation of the data. Baseline rates of illness absence varied between 2.3–3.7%, with peak absences ranging between 4.1–9.8%. Syndrome-specific absenteeism had the strongest correlation with other surveillance systems (r = 0.92), with illness absenteeism generating mixed results and all-cause absenteeism performing the least well. A similar pattern of results emerged in terms of lead and lag times, with influenza-like illness (ILI)-specific absence providing a 1–2 week lead time, compared to lag times reported for all-cause absence data and inconsistent results for illness absence data.ConclusionSyndrome-specific school absences have potential utility in the syndromic surveillance of influenza, demonstrating good correlation with healthcare surveillance data and a lead time of 1–2 weeks ahead of existing surveillance measures. Further research should consider the utility of school attendance registers for conditions other than influenza, to broaden our understanding of the potential application of this data for infectious disease surveillance in children.Systematic review registrationPROSPERO 2019 CRD42019119737.

Highlights

  • Syndromic surveillance systems are an essential component of public health surveillance and can provide timely detection of infectious disease cases and outbreaks

  • Syndrome-specific absenteeism had the strongest correlation with other surveillance systems, with illness absenteeism generating mixed results and all-cause absenteeism performing the least well

  • A similar pattern of results emerged in terms of lead and lag times, with influenza-like illness (ILI)-specific absence providing a 1–2 week lead time, compared to lag times reported for all-cause absence data and inconsistent results for illness absence data

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Summary

Introduction

Syndromic surveillance systems are an essential component of public health surveillance and can provide timely detection of infectious disease cases and outbreaks. Whilst surveillance systems are generally embedded within healthcare, there is increasing interest in novel data sources for monitoring trends in illness, such as over-the-counter purchases, internet-based health searches and worker absenteeism. Public health surveillance was disease-specific, relying on clinical diagnoses and laboratory reports [3]. Such surveillance systems can be subject to significant delays and over recent years there has been increasing recognition of the value of syndromic surveillance in providing more timely detection of infectious illness [4,5,6,7]. There is increasing interest in the use of novel sources of data, such as over-the-counter purchases, internet-based health searches and worker absenteeism, which have been found to correlate well with traditional surveillance measures [11, 15,16,17,18,19,20,21]

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