A hierarchical Bayesian latent class mixture model with censorship for detection of linear temporal changes in antibiotic resistance

Identifying and controlling the emergence of antimicrobial resistance (AMR) is a high priority for researchers and public health officials. One critical component of this control effort is timely detection of emerging or increasing resistance using surveillance programs. Currently, detection of temp...

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Detalles Bibliográficos
Autores principales: Zhang, Min, Wang, Chong, O’Connor, Annette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6993983/
https://www.ncbi.nlm.nih.gov/pubmed/32004341
http://dx.doi.org/10.1371/journal.pone.0220427

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6993983/
https://www.ncbi.nlm.nih.gov/pubmed/32004341
http://dx.doi.org/10.1371/journal.pone.0220427

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