Evidence map›Paper›PMID 41673549›Full record

ArticleZoonoses and public health2026

Bayesian Estimation of True Prevalence and Associated Risk Factors for Leptospira spp. Among Slaughterhouse Workers and Slaughtered Cattle in the Bahr El Ghazal Region of South Sudan.

David Onafruo, Jörn Klein, Polychronis Kostoulas, Joseph Erume, Ikwap Kokas, Ambrose Jubara, Javier Sánchez Romano, Terence Odoch, Estella Kitale, Peter Marin and 2 more

Abstract read
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Article in Zoonoses and public health, 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

David OnafruoDepartment of Biosecurity, Ecosystem and Veterinary Public Health, Makerere University, Kampala, Uganda.ORCID https://orcid.org/0009-0008-7568-9224
Jörn KleinDepartment of Nursing and Health Sciences, Faculty of Health and Social Sciences, University of South-Eastern Norway, Porsgrunn, Norway.
Polychronis KostoulasDepartment Laboratory of Epidemiology & Artificial Intelligence, Faculty of Public Health & One Health, University of Thessaly, Karditsa, Greece.ORCID https://orcid.org/0000-0001-7051-1541
Joseph ErumeDepartment of Biotechnical and Diagnostic Sciences, Makerere University, Kampala, Uganda.
Ikwap KokasDepartment of Biomolecular Resources and Biolab Sciences, Makerere University, Kampala, Uganda.
Ambrose JubaraDepartment of Clinical Studies, University of Bahr El Ghazal (UBG), Wau, South Sudan.ORCID https://orcid.org/0009-0002-3923-5969
Javier Sánchez RomanoInstitute of Zoology, Zoological Society of London, London, UK.ORCID https://orcid.org/0000-0002-8305-7947
Terence OdochDepartment of Biosecurity, Ecosystem and Veterinary Public Health, Makerere University, Kampala, Uganda.
Estella KitaleDepartment of Biosecurity, Ecosystem and Veterinary Public Health, Makerere University, Kampala, Uganda.
Peter MarinDepartment of Biosecurity, Ecosystem and Veterinary Public Health, Makerere University, Kampala, Uganda.
Esther SabbathDepartment of Biosecurity, Ecosystem and Veterinary Public Health, Makerere University, Kampala, Uganda.
Clovice KankyaDepartment of Biosecurity, Ecosystem and Veterinary Public Health, Makerere University, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLeptospirosis is a major but under-reported zoonotic disease, and epidemiological data from South Sudan remain limited. This study estimated the true prevalence of Leptospira spp. exposure and identified associated risk factors among slaughterhouse workers and slaughtered cattle in Western Bahr El Ghazal.

methodsA cross-sectional study was conducted in major slaughterhouses. Serum samples from workers and cattle were tested using the microscopic agglutination test (MAT). Bayesian hierarchical models were used to adjust for diagnostic test imperfections and to estimate true prevalence. Structured questionnaires captured occupational and animal-level risk factors for analysis within the Bayesian framework.

resultsThe estimated true prevalence was 10% in slaughterhouse workers and 85% in slaughtered cattle, indicating a high zoonotic exposure risk. Among workers, flaying, inconsistent use of protective equipment, and handling higher numbers of carcasses per day were significantly associated with seropositivity. In slaughtered cattle, exposure varied by breed, age, and sex. The model further indicated a 78% probability that a randomly selected slaughterhouse was affected and a 65% probability that infection levels among workers remained below 5%.

conclusionsThis study provides the first Bayesian-based estimates of leptospiral exposure in slaughterhouse settings in Western Bahr El Ghazal. The findings underscore the need to improve occupational safety, strengthen surveillance, and apply One Health approaches to reduce zoonotic transmission. Despite limitations, including lack of environmental data, the Bayesian framework proved effective for generating robust prevalence estimates in a resource-limited setting. Expanded geographic coverage and incorporation of environmental assessments are recommended to inform targeted leptospirosis control strategies.

Indexed as

AbattoirsCattle DiseasesLeptospiraLeptospirosisAnimalsBayes TheoremCattleCross-Sectional StudiesFemaleHumansMalePrevalenceRisk FactorsSouth SudanZoonosesBayesianLeptospira spp.South Sudantrue prevalence

Identifiers

PMID41673549
PMCPMC13053607

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.