Evidence map›Paper›PMID 40450205›Full record

ArticleBMC public health2025

Developing a syndromic surveillance tool to support the epidemiological investigation into paediatric acute hepatitis of unknown aetiology in England.

Alex J Elliot, Helen E Hughes, Christopher Bennett, Thomas C Hughes, Kirsty Challen, Conall H Watson, Sema Mandal, Gillian E Smith, Daniel Todkill

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Alex J ElliotReal-time Syndromic Surveillance Team, Field Services Division, UK Health Security Agency, Birmingham, UK. alex.elliot@ukhsa.gov.uk.ORCID http://orcid.org/0000-0002-6414-3065
Helen E HughesReal-time Syndromic Surveillance Team, Field Services Division, UK Health Security Agency, Birmingham, UK.ORCID http://orcid.org/0000-0002-3664-2983
Christopher BennettReal-time Syndromic Surveillance Team, Field Services Division, UK Health Security Agency, Birmingham, UK.ORCID http://orcid.org/0000-0002-3977-0008
Thomas C HughesOxford University Hospitals NHS Foundation Trust, Oxford, UK.ORCID http://orcid.org/0000-0001-5490-1267
Kirsty ChallenLancashire Teaching Hospitals NHS Foundation Trust, Preston, UK.ORCID http://orcid.org/0000-0003-4032-5531
Conall H WatsonImmunisation and Vaccine Preventable Diseases Division, UK Health Security Agency, London, UK.ORCID http://orcid.org/0000-0002-2469-791X
Sema MandalBlood Safety, Hepatitis, STI and HIV Division, UK Health Security Agency, London, UK.ORCID http://orcid.org/0000-0003-3379-3118
Gillian E SmithReal-time Syndromic Surveillance Team, Field Services Division, UK Health Security Agency, Birmingham, UK.ORCID http://orcid.org/0000-0002-4257-0568
Daniel TodkillReal-time Syndromic Surveillance Team, Field Services Division, UK Health Security Agency, Birmingham, UK.ORCID http://orcid.org/0000-0002-4325-4786

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring 2022, a new public health threat emerged when cases of paediatric acute hepatitis of unknown aetiology (HUA) were identified in children aged under 16 years old in the United Kingdom (UK). At the time, the epidemiology and extent of cases was based upon limited and non-standardised reporting from hospitals and liver units. We aimed to adapt existing real-time syndromic surveillance systems to support the epidemiological investigation of cases of HUA presenting to emergency departments (EDs) in England.

methodsSyndromic surveillance is generally based on the collection of patient symptoms or chief complaints, which are collected using automated routines in near real-time. Here, we used an existing ED syndromic surveillance system monitoring daily patient attendances across a network of approximately 150 EDs in England. Clinical diagnosis codes related to the potential symptoms associated with the HUA incident were selected and attendance data monitored retrospectively and prospectively during the incident.

resultsFrom 2 April 2018 to 31 December 2021, there were small sporadic numbers of daily ED attendances for 'liver conditions' in children with no observed secular trends or seasonality across the 1 to 4 and 5 to 14 years age groups. The period 2 April to 29 July was compared across each year included in the analysis. Mean daily HUA attendances during 2018 to 2021 was 0.05 and 0.22 for 1 to 4 and 5 to 14 years respectively, however in 2022 there were 0.26 and 0.42 mean daily attendances. This represented an increase of 377% and 94% in the 1 to 4 and 5 to 14 years age groups, respectively. From June 2022, daily syndromic 'liver condition' attendances appeared to decrease and the rate of increase in cumulative attendances slowed.

conclusionsWe demonstrate how syndromic surveillance provided support to the HUA outbreak using an existing syndromic surveillance framework to develop new indicators based on the newly emerging clinical symptoms. The outputs from the syndromic tool matched clinical and epidemiological findings with respect to trends in other HUA-related data, including clinical and laboratory reports, over time. This work demonstrates the potential for syndromic surveillance supporting the epidemiological surveillance of hepatitis and providing a valuable tool for the real-time management of future unknown health threats.

Indexed as

Epidemiological MonitoringHepatitisPopulation SurveillanceAcute DiseaseAdolescentChildChild, PreschoolEmergency Service, HospitalEnglandFemaleHumansInfantMaleRetrospective StudiesAcute hepatitisEmergency departmentHepatitis of unknown originnon-HepA–E hepatitisPaediatric acute hepatitis of unknown aetiologyPaediatric hepatitisSyndromic surveillance

Identifiers

PMID40450205
PMCPMC12125797

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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.