Peer-reviewed veterinary case report
Statistical approaches for farm and parasitic risk profiling in geographical veterinary epidemiology.
- Journal:
- Statistical methods in medical research
- Year:
- 2012
- Authors:
- Catelan, Dolores et al.
- Affiliation:
- Department of Statistics G. Parenti · Italy
Plain-English summary
This study looked at the risk of parasites on sheep farms in the Campania Region. Researchers examined 121 farms to see how 16 different parasites were spread out across the area. They used a special statistical model to help estimate the likelihood of each farm being affected by these parasites. The findings showed that their method was effective for identifying which farms were at risk for parasitic infections, and the decision-making rules they developed were straightforward to use. Overall, the approach worked well for assessing parasitic risks in sheep farming.
Abstract
We address the problem of farm and parasitic risk profiling in the context of Veterinary Epidemiology. We take advantage of a cross-sectional study carried out in the Campania Region in order to study the spatial distribution of 16 parasites in 121 ovine farms. We propose a tri-level hierarchical Bayesian model, which account for multivariate spatially structured overdispersion, to obtain estimate of posterior classification probabilities, that is for each parasite and farm the probability to belong to the set of the null hypothesis. We explore four decision rules based on either posterior probabilities or posterior means and compare the results in terms of the number of false discoveries/non-discoveries or the rate of false discovery/non-discovery. Our approach proved useful for parasitological risk profiling and we show that decision rules can be easily handled.
Find similar cases for your pet
PetCaseFinder finds other peer-reviewed reports of pets with the same symptoms, plus a plain-English summary of what was tried across them.
Search related cases →Original publication: https://pubmed.ncbi.nlm.nih.gov/22517272/