ArticleEpidemiology and infection2014
Estimating the time at which commercial broiler flocks in Great Britain become infected with Campylobacter: a Bayesian approach.
Article in Epidemiology and infection, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 13 citations in OpenAlex.
- Longitudinal Changes inApplied and environmental microbiology · 2022Article
- Association of Broiler Litter Microbiome Composition andFrontiers in veterinary science · 2021Article
- The transmission dynamics of Campylobacter jejuni among broilers in semi-commercial farms in Jordan.Epidemiology and infection · 2019Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Campylobacter is a common cause of intestinal disease in humans and is often linked to the consumption of contaminated poultry meat. Despite considerable research on the topic there is a large amount of uncertainty associated with Campylobacter epidemiology. A Bayesian model framework was applied to multiple longitudinal datasets on Campylobacter infection in UK broiler flocks to estimate the time at which each flock was first infected with Campylobacter. The model results suggest that the day of first infection ranges from 10 to 45 days; however, over half had a time of infection between 30 and 35 days. When considering only those flocks which were thinned, 48% had an estimated day of infection within 2 days of the day of thinning, thus suggesting an association between thinning and Campylobacter infection. These results demonstrate how knowledge of the time of infection can be correlated to known events to identify potential risk factors for infection.
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