Evidence map›Paper›PMID 40302752›Full record

ArticleTransboundary and emerging diseases2025

Assessing the Use of Different Surveillance Components to Detect Highly Pathogenic Avian Influenza Outbreaks in Poultry in the Netherlands in Low- and High-Risk Years.

Imke Vredenberg, Gerdien van Schaik, Francisca C Velkers, Teun Fabri, Marcel A H Spierenburg, Evelien A Germeraad, Wim H M van der Poel, Arjan Stegeman

Abstract read
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Article in Transboundary and emerging diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

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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

8 authors.

Imke VredenbergDepartment of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CL, Utrecht, Netherlands.ORCID https://orcid.org/0009-0002-8562-1449
Gerdien van SchaikDepartment of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CL, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-0460-2629
Francisca C VelkersDepartment of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CL, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-2923-3233
Teun FabriResearch and Development Epidemiology, Royal GD, 7400 AA, Deventer, Netherlands.
Marcel A H SpierenburgIncident and Crisis Centre, Netherlands Food and Consumer Product Safety Authority, 3511 GG, Utrecht, Netherlands.ORCID https://orcid.org/0000-0001-6787-371X
Evelien A GermeraadDepartment Virology and Molecular Biology, Wageningen Bioveterinary Research, 8221 RA, Lelystad, Netherlands.
Wim H M van der PoelDepartment Virology and Molecular Biology, Wageningen Bioveterinary Research, 8221 RA, Lelystad, Netherlands.ORCID https://orcid.org/0000-0002-7498-8002
Arjan StegemanDepartment of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CL, Utrecht, Netherlands.ORCID https://orcid.org/0000-0003-4361-3846

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Avian influenza (AI) is a highly contagious zoonotic disease primarily affecting birds with clinical manifestation depending on bird species and virus subtype. Globally, outbreaks have had a large socioeconomic impact. Moreover, highly pathogenic AI virus (HPAIv) outbreaks can pose a public health risk. Detection of AIv, particularly HPAIv, mainly relies on passive surveillance, risking underreporting and delayed detection. This study describes and compares the contribution of passive and active surveillance components on HPAI detection in poultry flocks in years with different HPAIv introduction risk (free, seasonal outbreaks, and year round) in the Netherlands. We drafted a flowchart representing the flow of information and samples between farmers and veterinarians, the competent authority (CA), the national reference lab (NRL), and the private organization Royal GD and identified four different surveillance components and derived the use of each of these components during 2016 (reference), 2019 (low risk), and 2022 (high risk). The first component, "notification of suspicion," where farmers and veterinarians directly report suspicions to the CA, accounted for 88.4% of farm visits and detected 98.1% of all HPAIv outbreaks. The second component, "testing to exclude" (TTE), consisting postmortem/sample submission and contact with the veterinary helpdesk of GD detected 2% of the cases in 2022. The third and active surveillance component, "protection zone screening," screens farms closely to a positively detected farm. No outbreaks were detected, suggesting limited between-farm transmission. The last and active surveillance component, mandatory national serological surveillance detected two low pathogenic AI outbreaks. Analysis between years for the passive surveillance components "notification of suspicion" and "TTE," using chi-square test of independency and odd ratios, showed increased use and farm visits in the high-risk year. However, postmortem-related submissions for TTE were increased in the disease-free year. All components combined detected HPAI or provided valuable information across different risk periods.

Indexed as

Disease OutbreaksEpidemiological MonitoringInfluenza A virusInfluenza in BirdsPoultry DiseasesAnimalsNetherlandsPoultryactive surveillanceearly warningH5N1HPAIpassive surveillancezoonotic

Identifiers

PMID40302752
PMCPMC12016776

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Registered trials

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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.