Characterizing infectious disease progression through discrete states using hidden Markov models.

ABSTRACT: Infectious disease management relies on accurate characterization of disease progression so that transmission can be prevented. Slowly progressing infectious diseases can be difficult to characterize because of a latency period between the time an individual is infected and when they show clinical signs of disease. The introduction of Mycobacterium avium ssp. paratuberculosis (MAP), the cause of Johne's disease, onto a dairy farm could be undetected by farmers for years before any animal shows clinical signs of disease. In this time period infected animals may shed thousands of colony forming units. Parameterizing trajectories through disease states from infection to clinical disease can help farmers to develop control programs based on targeting individual disease state, potentially reduc

SUBMITTER: Ceres KM 

PROVIDER: S-EPMC7678993 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature