Bayesian Network Modeling Applied to Feline Calicivirus Infection Among Cats in Switzerland.

ABSTRACT: Bayesian network (BN) modeling is a rich and flexible analytical framework capable of elucidating complex veterinary epidemiological data. It is a graphical modeling technique that enables the visual presentation of multi-dimensional results while retaining statistical rigor in population-level inference. Using previously published case study data about feline calicivirus (FCV) and other respiratory pathogens in cats in Switzerland, a full BN modeling analysis is presented. The analysis shows that reducing the group size and vaccinating animals are the two actionable factors directly associated with FCV status and are primary targets to control FCV infection. The presence of gingivostomatitis and Mycoplasma felis is also associated with FCV status, but signs of upper respiratory tract dise

SUBMITTER: Kratzer G 

PROVIDER: S-EPMC7055399 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature