Evidence map›Paper›PMID 24083852›Full record

ArticleBMC public health2013

Validity and timeliness of syndromic influenza surveillance during the autumn/winter wave of A (H1N1) influenza 2009: results of emergency medical dispatch, ambulance and emergency department data from three European regions.

Nicole Rosenkötter, Alexandra Ziemann, Luis Garcia-Castrillo Riesgo, Jean Bernard Gillet, Gernot Vergeiner, Thomas Krafft, Helmut Brand

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC public health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
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

14 citing papers in PubMed, 25 citations in OpenAlex.

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  8. Daily volume of cases in emergency call centers: construction and validation of a predictive model.Scandinavian journal of trauma, resuscitation and emergency medicine · 2017
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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

7 authors at 4 institutions in 4 countries.

Nicole RosenkötterDepartment of International Health, CAPHRI School for Public Health and Primary Care, Faculty for Health, Medicine and Life Sciences, Maastricht University, Duboisdomein 30, Maastricht 6229 GT, The Netherlands. nicole.rosenkoetter@maastrichtuniversity.nl.
Alexandra Ziemann
Luis Garcia-Castrillo Riesgo
Jean Bernard Gillet
Gernot Vergeiner
Thomas Krafft
Helmut Brand
Maastricht University · NLKU Leuven · BEPedagocial University Tyrol · ATUniversidad de Cantabria · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEmergency medical service (EMS) data, particularly from the emergency department (ED), is a common source of information for syndromic surveillance. However, the entire EMS chain, consists of both out-of-hospital and in-hospital services. Differences in validity and timeliness across these data sources so far have not been studied. Neither have the differences in validity and timeliness of this data from different European countries. In this paper we examine the validity and timeliness of the entire chain of EMS data sources from three European regions for common syndromic influenza surveillance during the A(H1N1) influenza pandemic in 2009.

methodsWe gathered local, regional, or national information on influenza-like illness (ILI) or respiratory syndrome from an Austrian Emergency Medical Dispatch Service (EMD-AT), an Austrian and Belgian ambulance services (EP-AT, EP-BE) and from a Belgian and Spanish emergency department (ED-BE, ED-ES). We examined the timeliness of the EMS data in identifying the beginning of the autumn/winter wave of pandemic A(H1N1) influenza as compared to the reference data. Additionally, we determined the sensitivity and specificity of an aberration detection algorithm (Poisson CUSUM) in EMS data sources for detecting the autumn/winter wave of the A(H1N1) influenza pandemic.

resultsThe ED-ES data demonstrated the most favourable validity, followed by the ED-BE data. The beginning of the autumn/winter wave of pandemic A(H1N1) influenza was identified eight days in advance in ED-BE data. The EP data performed stronger in data sets for large catchment areas (EP-BE) and identified the beginning of the autumn/winter wave almost at the same time as the reference data (time lag +2 days). EMD data exhibited timely identification of the autumn/winter wave of A(H1N1) but demonstrated weak validity measures.

conclusionsIn this study ED data exhibited the most favourable performance in terms of validity and timeliness for syndromic influenza surveillance, along with EP data for large catchment areas. For the other data sources performance assessment delivered no clear results. The study shows that routinely collected data from EMS providers can augment and enhance public health surveillance of influenza by providing information during health crises in which such information must be both timely and readily obtainable.

Indexed as

AmbulancesEmergency Service, HospitalEuropeHumansInfluenza A Virus, H1N1 SubtypeInfluenza, HumanPublic Health SurveillanceReproducibility of ResultsSeasons

Identifiers

PMID24083852
PMCPMC3852468
OpenAlexW2084309487

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.