Evidence map›Paper›PMID 28278292›Full record

ArticlePloS one2017

Salmonella serovars and their distribution in Nigerian commercial chicken layer farms.

Idowu Oluwabunmi Fagbamila, Lisa Barco, Marzia Mancin, Jacob Kwaga, Sati Samuel Ngulukun, Paola Zavagnin, Antonia Anna Lettini, Monica Lorenzetto, Paul Ayuba Abdu, Junaidu Kabir and 3 more

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

  1. Article
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  5. Phylogenetic Analysis and Public Health Implications ofAnimals : an open access journal from MDPI · 2025
    Article
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  14. Non-typhoidalInternational journal of veterinary science and medicine · 2024
    Article
  15. Prevalence ofVeterinary world · 2023
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

13 authors.

Idowu Oluwabunmi FagbamilaBacterial Research Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria.
Lisa BarcoReference Laboratory for Salmonella, Instituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Padova, Italy.
Marzia MancinReference Laboratory for Salmonella, Instituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Padova, Italy.
Jacob KwagaDepartment of Veterinary Public Health and Preventive Medicine, Ahmadu Bello University, Zaria, Nigeria.
Sati Samuel NgulukunBacterial Research Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria.
Paola ZavagninReference Laboratory for Salmonella, Instituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Padova, Italy.
Antonia Anna LettiniReference Laboratory for Salmonella, Instituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Padova, Italy.
Monica LorenzettoReference Laboratory for Salmonella, Instituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Padova, Italy.
Paul Ayuba AbduDepartment of Medicine, Faculty of Veterinary Medicine, Ahmadu Bello University, Zaria, Nigeria.
Junaidu KabirDepartment of Veterinary Public Health and Preventive Medicine, Ahmadu Bello University, Zaria, Nigeria.
Jarlath UmohDepartment of Veterinary Public Health and Preventive Medicine, Ahmadu Bello University, Zaria, Nigeria.
Antonia RicciReference Laboratory for Salmonella, Instituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Padova, Italy.
Maryam MuhammadBacterial Research Division, National Veterinary Research Institute, Vom, Plateau State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Commercial poultry farms (n° 523), located in all the six regions of Nigeria were sampled with a view to generate baseline information about the distribution of Salmonella serovars in this country. Five different matrices (litter, dust, faeces, feed and water) were collected from each visited farm. Salmonella was isolated from at least one of the five matrices in 228 farms, with a farm prevalence of 43.6% (CI95[39.7-48.3%]). Altogether, 370 of 2615 samples collected (14.1%, CI95[12.8; 15.5%]) contained Salmonella. Considering the number of positive farms and the number of positive samples, it was evident that for the majority of the sampled farms, few samples were positive for Salmonella. With regard to the matrices, there was no difference in Salmonella prevalence among the five matrices considered. Of the 370 isolates serotyped, eighty-two different serotypes were identified and Salmonella Kentucky was identified as having the highest isolation rate in all the matrices sampled (16.2%), followed by S. Poona and S. Elisabethville. S. Kentucky was distributed across the country, whereas the other less frequent serovars had a more circumscribed diffusion. This is one of few comprehensive studies on the occurrence and distribution of Salmonella in commercial chicken layer farms from all the six regions of Nigeria. The relatively high prevalence rate documented in this study may be attributed to the generally poor infrastructure and low biosecurity measures in controlling stray animals, rodents and humans. Data collected could be valuable for instituting effective intervention strategies for Salmonella control in Nigeria and also in other developing countries with a similar poultry industry structure, with the final aim of reducing Salmonella spread in animals and ultimately in humans.

Indexed as

AnimalsChickensDustFarmsFecesNigeriaPoultry DiseasesPrevalenceSalmonellaSalmonella Infections, AnimalSerogroupWater MicrobiologyDust

Identifiers

PMID28278292
PMCPMC5344354

What OpenQuestion holds

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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.