Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods.

ABSTRACT: The spread of pathogens in swine populations is in part determined by movements of animals between farms. However, understanding additional characteristics that predict disease outbreaks and uncovering landscape factors related to between-farm spread are crucial steps toward risk mitigation. This study integrates animal movements with environmental risk factors to identify the occurrence of porcine epidemic diarrhea virus (PEDV) outbreaks. Using weekly farm-level incidence data from 332 sow farms, we applied machine-learning algorithms to quantify associations between risk factors and PEDV outbreaks with the ultimate goal of training predictive models and to identify the most important factors associated with PEDV occurrence. Our best algorithm was able to correctly predict whether an outb

SUBMITTER: Machado G 

PROVIDER: S-EPMC6345879 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature