Evidence map›Paper›PMID 42184064›Full record

ArticleVeterinary research communications2026

Blood swabs represent an alternative sample matrix for detection of antibodies against classical swine fever virus during surveillance in wild boar.

Denise Meyer, Sandra Blome, Lia Ebner, Paul Becher

Abstract read
In one paragraph

Article in Veterinary research communications, 2026. 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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0cells of the map it votes in
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

4 authors.

Denise MeyerEU and WOAH Reference Laboratory for Classical Swine Fever, Institute of Virology, University of Veterinary Medicine Hannover, Buenteweg 17, Hannover, 30559, Germany. denise.meyer@tiho-hannover.de.
Sandra BlomeInstitute of Diagnostic Virology, Federal Research Institute for Animal Health, Suedufer 10, Greifswald, 17493, Germany.
Lia EbnerInstitute of Diagnostic Virology, Federal Research Institute for Animal Health, Suedufer 10, Greifswald, 17493, Germany.
Paul BecherEU and WOAH Reference Laboratory for Classical Swine Fever, Institute of Virology, University of Veterinary Medicine Hannover, Buenteweg 17, Hannover, 30559, Germany. paul.becher@tiho-hannover.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Passive surveillance of fallen wild boar represents an important tool for detecting notifiable diseases such as Classical swine fever (CSF) and African swine fever (ASF) which are showing comparable pathological findings. For differential diagnosis, it is advantageous to use one sample matrix for testing of both diseases. Especially, if no serum sample can be collected from wild suids, blood swabs represent an alternative matrix in ASF diagnosis. On this basis, the present study aimed to analyze blood swabs serologically using CSF antibody ELISAs and virus neutralization tests. In total, twenty-nine CSF antibody positive samples and one-hundred CSF antibody negative samples were examined. The results show that this sample matrix is also suitable for detecting antibodies against CSF virus (CSFV). In general, the sensitivity of blood swabs is slightly reduced compared to the analysis of serum, which can affect the classification of samples taken during early seroconversion. However, samples collected at  ≥ 21 days post CSFV infection are tested safely antibody positive.

Indexed as

Antibodies, ViralClassical Swine FeverClassical Swine Fever VirusSus scrofaAfrican Swine FeverAnimalsEnzyme-Linked Immunosorbent AssayNeutralization TestsSensitivity and SpecificitySwineAntibodies, ViralAfrican swine feverAntibody detectionBlood swabsClassical swine feverSerologyWild boar

Identifiers

PMID42184064
PMCPMC13201338

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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.