Evidence map›Paper›PMID 34749838›Full record

ArticleEpidemiology and infection2021

Developing a sentinel syndromic surveillance system using school-absenteeism data, example monitoring absences over the 2020 COVID-19 pandemic.

Jennifer Lai, Helen E Hughes, Roger Morbey, Paul Loveridge, Jamie Lopez Bernal, Vanessa Saliba, Esther Kissling, Alex Lovelock-Wren, Jeremy Mabbitt, Alex J Elliot

Abstract read
In one paragraph

Article in Epidemiology and infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jennifer LaiPublic Health England, Real-time Syndromic Surveillance Team, Field Service, National Infection Service, Birmingham, UK.ORCID 0000-0002-0593-1424
Helen E HughesPublic Health England, Real-time Syndromic Surveillance Team, Field Service, National Infection Service, Birmingham, UK.ORCID 0000-0002-3664-2983
Roger MorbeyPublic Health England, Real-time Syndromic Surveillance Team, Field Service, National Infection Service, Birmingham, UK.ORCID 0000-0001-8543-477X
Paul LoveridgePublic Health England, Real-time Syndromic Surveillance Team, Field Service, National Infection Service, Birmingham, UK.
Jamie Lopez BernalPublic Health England, Immunisation and Countermeasures Division, National Infection Service, London, UK.
Vanessa SalibaPublic Health England, Immunisation and Countermeasures Division, National Infection Service, London, UK.
Esther KisslingEpiconcept, Paris, France.
Alex Lovelock-WrenStudybugs, Brighton and Hove, UK.
Jeremy MabbittStudybugs, Brighton and Hove, UK.
Alex J ElliotPublic Health England, Real-time Syndromic Surveillance Team, Field Service, National Infection Service, Birmingham, UK.ORCID 0000-0002-6414-3065

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study describes the development of a pilot sentinel school absence syndromic surveillance system. Using data from a sample of schools in England the capability of this system to monitor the impact of disease on school absences in school-aged children is shown, using the coronavirus disease 2019 (COVID-19) pandemic period as an example. Data were obtained from an online app service used by schools and parents to report their children absent, including reasons/symptoms relating to absence. For 2019 and 2020, data were aggregated into daily counts of 'total' and 'cough' absence reports. There was a large increase in the number of absence reports in March 2020 compared to March 2019, corresponding to the first wave of the COVID-19 pandemic in England. Absence numbers then fell rapidly and remained low from late March 2020 until August 2020, while lockdown was in place in England. Compared to 2019, there was a large increase in the number of absence reports in September 2020 when schools re-opened in England, although the peak number of absences was smaller than in March 2020. This information can help provide context around the absence levels in schools associated with COVID-19. Also, the system has the potential for further development to monitor the impact of other conditions on school absence, e.g. gastrointestinal infections.

Indexed as

AbsenteeismEpidemiological MonitoringSentinel SurveillanceChildCommunicable Disease ControlCOVID-19Disease OutbreaksEnglandHumansMalePandemicsSARS-CoV-2SchoolsStudentsAbsence dataCOVID-19real-time surveillanceschool-aged childrensyndromic surveillance

Identifiers

PMID34749838
PMCPMC8668399

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.