title: Evaluating hospital infection control measures for antimicrobial-resistant pathogens using stochastic transmission models: Application to vancomycin-resistant enterococci in intensive care units.
abstract: Nosocomial pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) are the cause of significant morbidity and mortality among hospital patients. It is important to be able to assess the efficacy of control measures using data on patient outcomes. In this paper, we describe methods for analysing such data using patient-level stochastic models which seek to describe the underlying unobserved process of transmission. The methods are applied to detailed longitudinal patient-level data on vancomycin-resistant Enterococci from a study in a US hospital with eight intensive care units (ICUs). The data comprise admission and discharge dates, dates and results of screening tests, and dates during which precautionary measures were in place for each patient during the study period. Results include estimates of the efficacy of the control measures, the proportion of unobserved patients colonized with vancomycin-resistant Enterococci, and the proportion of patients colonized on admission.
authors.affiliation: 1 Centre for Mathematical Sciences, School of Computing, Electronics and Mathematics, University of Plymouth, UK.
authors.forename: Yinghui
authors.initials: Y
authors.lastname: Wei
authors.affiliation: 2 School of Mathematical Sciences, University of Nottingham, UK.
authors.forename: Theodore
authors.initials: T
authors.lastname: Kypraios
authors.affiliation: 2 School of Mathematical Sciences, University of Nottingham, UK.
authors.forename: Philip D
authors.initials: PD
authors.lastname: O'Neill
authors.affiliation: 3 Division of Infectious Disease and Health Policy Research Institute, University of California Irvine School of Medicine, Irvine, CA, USA.
authors.forename: Susan S
authors.initials: SS
authors.lastname: Huang
authors.affiliation: 4 Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
authors.forename: Sheryl L
authors.initials: SL
authors.lastname: Rifas-Shiman
authors.affiliation: 5 Mahidol Oxford Tropical Medicine Research Unit (MORU), Bangkok, Thailand.|6 Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
authors.forename: Ben S
authors.initials: BS
authors.lastname: Cooper
mesh_terms: D000890:Anti-Infective Agents; D001499:Bayes Theorem; D003140:Communicable Disease Control / Q000379:methods*; D003428:Cross Infection / Q000517:prevention & control*; D006761:Hospitals; D006801:Humans; D007362:Intensive Care Units; D055624:Methicillin-Resistant Staphylococcus aureus; D013203:Staphylococcal Infections / Q000517:prevention & control*; D013269:Stochastic Processes; D065507:Vancomycin-Resistant Enterococci
chemical_list: D000890:Anti-Infective Agents
keywords: Antimicrobial resistance; Bayesian methods; MRSA; healthcare-associated infections; vancomycin-resistant Enterococci