Evidence map›Paper›PMID 38764074›Full record

ArticlePorcine health management2024

Influenza surveillance in pigs: balancing act between broad diagnostic coverage and specific virus characterization.

Julia Stadler, Sophia Zwickl, Sophie Gumbert, Mathias Ritzmann, Kathrin Lillie-Jaschniski, Timm Harder, Annika Graaf-Rau, Vassilis Skampardonis, Matthias Eddicks

Abstract read
In one paragraph

Article in Porcine health management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. 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

9 authors.

Julia StadlerClinic for Swine, Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Oberschleißheim, Germany. J.Stadler@med.vetmed.uni-muenchen.de.
Sophia ZwicklClinic for Swine, Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Oberschleißheim, Germany.
Sophie GumbertClinic for Swine, Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Oberschleißheim, Germany.
Mathias RitzmannClinic for Swine, Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Oberschleißheim, Germany.
Kathrin Lillie-JaschniskiCEVA Tiergesundheit, Duesseldorf,, Germany.
Timm HarderInstitute of Diagnostic Virology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
Annika Graaf-RauInstitute of Diagnostic Virology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
Vassilis SkampardonisDepartment of Epidemiology, Biostatistics and Economics of Animal Production, School of Veterinary Medicine, University of Thessaly, 43132, Karditsa, Greece.
Matthias EddicksClinic for Swine, Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-Universität München, Oberschleißheim, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMonitoring of infectious diseases on swine farms requires a high diagnostic sensitivity and specificity of the test system. Moreover, particularly in cases of swine influenza A virus (swIAV) it is desirable to include characterization of the virus as precisely as possible. This is indispensable for strategies concerning prophylaxis of swIAV and furthermore, to meet the requirements of a purposeful monitoring of newly emerging swIAV strains in terms of vaccine design and public health. Within the present cross-sectional study, we compared the diagnostic value of group samples (wipes of surfaces with direct contact to mouth/nose, dust wipes, udder skin wipes, oral fluids) to individual samples (nasal swabs, tracheobronchial swabs) for both swIAV identification and characterization. Sampling included different stages of pig production on 25 sow farms with attached nursery considered as enzootically infected with swIAV. Firstly, samples were analyzed for IAV genome and subsequently samples with Ct-values < 32 were subtyped by multiplex RT-qPCR.

resultsNasal swabs of suckling piglets and nursery pigs resulted in a higher odds to detect swIAV (p < 0.001) and to identify swIAV subtypes by RT-qPCR (p < 0.05) compared to nasal swabs of sows. In suckling piglets, significant higher rates of swIAV detection could be observed for nasal swabs (p = 0.007) and sow udder skin wipes (p = 0.036) compared to contact wipes. In the nursery, group sampling specimens were significantly more often swIAV positive compared to individual samples (p < 0.01), with exception of the comparison between contact wipes and nasal swabs (p = 0.181). However, in general nasal swabs were more likely to have Ct-value < 32 and thus, to be suitable for subtyping by RT-qPCR compared to dust wipes, contact wipes, udder skin wipes and tracheobronchial swabs (p < 0.05). Interestingly, different subtypes were found in different age groups as well as in different specimens in the same holding.

conclusionAlthough population-based specimens are highly effective for swIAV monitoring, nasal swabs are still the preferable sampling material for the surveillance of on-farm circulating strains due to significantly higher virus loads. Remarkably, sampling strategies should incorporate suckling piglets and different age groups within the nursery to cover as many as possible of the on-farm circulating strains.

Indexed as

Cross-sectionalEnzootic infectionMultiplex RT-qPCRSampling materialSubtypingSwine influenza a virus

Identifiers

PMID38764074
PMCPMC11104006

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.