ArticleTropical animal health and production2017
Risk factors for rotavirus infection in pigs in Busia and Teso subcounties, Western Kenya.
Article in Tropical animal health and production, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- 4D-DIA Proteomic Analysis of IPEC-J2 Cells Infected with Porcine Group A Rotavirus G9P[23] Strain.Veterinary sciences · 2025Article
- Isolation, Genomic Characterization and Evolution of Six Porcine Rotavirus A Strains in a Pig Farming Group.Veterinary sciences · 2024Article
- Article
- Cross-sectional study on rotavirus A (RVA) infection and assessment of risk factors in pre- and post-weaning piglets in India.Tropical animal health and production · 2020Article
- Spatiotemporal dynamics and risk factors of rotavirus A circulation in backyard pig farms in a Philippine setting.Tropical animal health and production · 2019Article
- A G3P[13] porcine group A rotavirus emerging in China is a reassortant and a natural recombinant in the VP4 gene.Transboundary and emerging diseases · 2018Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We analysed data that were previously collected for molecular characterisation of rotavirus (RV) groups A and C in pigs from Teso and Busia subcounties in Kenya to determine risk factors for its infection. The data included records from 239 randomly selected piglets aged between 1 and 6 months raised in free range and backyard production systems. RV infection was confirmed by screening of fresh faecal samples by using reverse transcription polymerase chain reaction (RT-PCR); selected positive samples were subsequently sequenced and used for phylogenetic analysis. In this analysis, RV infection status was used as outcome variable, while the metadata collected at the time of sampling were used as predictors. A Bayesian hierarchical model which used integrated nested Laplace approximation (INLA) method was then fitted to the data. The model accounted for the spatial effect by using stochastic partial differential equations (SPDEs). Of the 239 samples screened, 206 were available for the analysis. Descriptive analyses showed that 27.7 % (57/206) of the samples were positive for rotaviruses groups A and C, 18.5 % were positive for group A rotaviruses, 5.3 % were positive for group C rotaviruses, while 3.9 % had co-infections from both groups of rotaviruses. The spatial effect was insignificant, and a simple (non-spatial) model showed that piglets (≤4 months) and those pigs kept in free range systems had higher risk of exposure to rotavirus infection as compared to older pigs (>4 months) and those tethered or housed, respectively. Intervention measures that will target these high-risk groups of pigs will be beneficial to farmers.
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