Vancomycin-resistant enterococci in intensive-care hospital settings: Transmission dynamics, persistence, and the impact of infection control programs

Abstract

Vancomycin-resistant enterococci (VRE) recently have emerged as a nosocomial pathogen especially in intensive-care units (ICUs) worldwide. Transmission via the hands of health-care workers is an important determinant of spread and persistence in a VRE-endemic ICU. We describe the transmission of nosocomial pathogens by using a microepidemiological framework based on the transmission dynamics of vector-borne diseases. By using the concept of a basic reproductive number, R 0 , defined as the average number of secondary cases generated by one primary case, we show quantitatively how infection control measures such as hand washing, cohorting, and antibiotic restriction affect nosocomial cross-transmission. By using detailed molecular epidemiological surveillance and compliance monitoring, we found that the estimated basic reproductive number for VRE during a study at the Cook County Hospital, Chicago, was approximately 3-4 without infection control and 0.7 when infection control measures were included. The impact of infection control was to reduce the prevalence from a predicted 79% to an observed 36%. Hand washing and staff cohorting are the most powerful control measures although their efficacy depends on the magnitude of R 0 . Under the circumstances tested, endemicity of VRE was stabilized despite infection control measures, by the constant introduction of colonized patients. Multiple stochastic simulations of the model revealed excellent agreement with observed pattern. In conjunction with detailed microbiological surveillance, a mathematical framework provides a precise template to describe the colonization dynamics of VRE in ICUs and impact of infection control measures. Our analyses suggest that compliance for hand washing significantly in excess of reported levels, or the cohorting of nursing staff, are needed to prevent nosocomial transmission of VRE in endemic settings.

Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA)

“…Whereas stochastic models define movements of individuals to be chance events occurring at random time-intervals determined by the model parameters, meaning the outcome may be different for different simulation runs. There have been a number of previous models looking specifically at nosocomial infection transmission dynamics [10][11][12][13][14][15][16][17][18][19]. This work builds on those studies, particularly those by Cooper et al [4,18,19] which use stochastic models to explore the spread of nosocomial pathogens.…”

Studies of antibiotic resistance within the patient, hospitals and the community using simple mathematical models

“…Another important factor is the frequent mixing of patients and health-care workers (HCWs)öfor whom asymptomatic carriage is a potential threat. Although some emphasis has been placed on the population dynamics of competition between resistant and susceptible bacteria (Massad et al 1993;Bonhoe¡er et al 1997), little work has been completed to date with regards to the transmission dynamics of resistant infections within frameworks that meld genetics and epidemiology (Austin et al 1998a;Sebille et al 1997). Many hospital pathogens are capable of colonizing patients without inducing overt symptomatic infection.…”

Modeling Nosocomial Transmission of Rotavirus in Pediatric Wards

“…Austin, Bonten, Lipsitch and collaborators, working in the same area, focused instead on the effects of preventive measures such as hand-washing, cohorting and other barrier precautions, drawing extensively upon stochastic models to simulate transmission within a single ward, more often than not as direct patient-to-patient contact [4,6,7,23]. Stochastic models (including agent-based models (ABMs) or individual-based models) are important tools for capturing variability in pathogen transmission due to individual differences and fluctuations in the environment, which is especially important to consider in small populations like a single hospital ward [12].…”