Evaluating hospital infection control measures for antimicrobial-resistant pathogens using stochastic transmission models: application to Vancomycin-Resistant Enterococci in intensive care units

TL;DR

This study develops stochastic transmission models to evaluate infection control measures for VRE in ICU settings, providing insights into their effectiveness and colonization dynamics based on detailed patient data.

Contribution

It introduces patient-level stochastic models for analyzing infection control efficacy using detailed longitudinal data, applied specifically to VRE in ICU environments.

Findings

Estimated efficacy of control measures

Proportion of unobserved colonized patients

Colonization on admission rates

Abstract

Nosocomial pathogens such as Methicillin-Resistant {\em Staphylococcus aureus} (MRSA) and Vancomycin-resistant {\em 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 VRE 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 VRE and the proportion of patients colonized on admission.