Evidence map›Paper›PMID 42344342›Full record

ArticleVeterinary world2026

Bacterial contamination and prevalence of antibiotic-resistant

Metrine Namalwa Nyanja, Christine Minoo Mbindyo, Daniel Wambua Wanja, Jackson Ombui, Getrude Shepelo Peter, Felix M Kibegwa, George C Gitao, Charles Drago Kato

Abstract read
In one paragraph

Article in Veterinary world, 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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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

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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

8 authors.

Metrine Namalwa NyanjaDepartment of Public Health Pharmacology and Toxicology Pathology, Faculty of Veterinary Medicine, University of Nairobi, Nairobi, Kenya.
Christine Minoo MbindyoDepartment of Veterinary Pathology, Microbiology and Parasitology, Faculty of Veterinary Medicine, University of Nairobi, Nairobi, Kenya.
Daniel Wambua WanjaDepartment of Veterinary Pathology, Microbiology and Parasitology, Faculty of Veterinary Medicine and Surgery, Egerton University, Njoro-Egerton, Kenya.
Jackson OmbuiDepartment of Public Health Pharmacology and Toxicology Pathology, Faculty of Veterinary Medicine, University of Nairobi, Nairobi, Kenya.
Getrude Shepelo PeterDepartment of Clinical Studies, Faculty of Veterinary Medicine, University of Nairobi, Nairobi, Kenya.
Felix M KibegwaDepartment of Animal Production, Faculty of Veterinary Medicine, University of Nairobi, Nairobi, Kenya.
George C GitaoDepartment of Veterinary Pathology, Microbiology and Parasitology, Faculty of Veterinary Medicine, University of Nairobi, Nairobi, Kenya.
Charles Drago KatoSchool of Biosecurity, Biotechnical and Laboratory Sciences, College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: Foodborne diseases caused by bacterial contamination of meat remain a major global public health concern, particularly in low- and middle-income countries. Materials and Methods: A cross-sectional study was conducted between November 2024 and June 2025. A total of 320 meat samples (105 chicken and 215 pork) were collected from slaughterhouses, butcher shops, supermarkets, and public wet markets. Total viable counts (TVC) were determined using standard plate count methods. Isolation and identification of Results: High levels of bacterial contamination were observed, with mean TVC exceeding recommended limits (6.45 log Conclusion: The study demonstrates substantial bacterial contamination and high prevalence of antimicrobial-resistant pathogens in raw meat along the Kenyan meat value chain. These findings highlight the urgent need for strengthened hygiene practices, improved food safety regulation, and enhanced AMR surveillance within a One Health framework to mitigate public health risks.

Indexed as

antimicrobial resistanceEscherichia colifood safetyKenyameat contaminationmultidrug resistancepork and chickenSalmonella

Identifiers

PMID42344342
PMCPMC13290336

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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.