Chair and Professor
University of Michigan
We developed and analyzed a deterministic compartmental model of Acinetobacter baumannii describing the contact-mediated process among HCWs, patients, and the environment. We compared a system using measured asymmetrical transfer efficiency to 2 symmetrical transfer efficiency systems.
Healthcare-associated infections (HAIs) affect millions of patients every year. Pathogen transmission via fomites and healthcare workers (HCWs) contribute to the persistence of HAIs in hospitals. A critical parameter needed to assess risk of environmental transmission is the pathogen transfer efficiency between fomites and fingers. Recent studies have shown that pathogen transfer is not symmetric. In this study,we evaluated how the commonly used assumption of symmetry in transfer efficiency changes the dynamics of pathogen movement between patients and rooms and the exposures to uncolonized patients.
Symmetric models consistently overestimated contamination levels on fomites and underestimated contamination on patients and HCWs compared to the asymmetrical model. The magnitudes of these miscalculations can exceed 100%. Regardless of the model, relative percent reductions in contamination declined after hand hygiene compliance reached approximately 60% in the large fomite scenario and 70% in the small fomite scenario.
This study demonstrates how healthcare facility-specific data can be used for decision-making processes. We show that the incorrect use of transfer efficiency data leads to biased effectiveness estimates for intervention strategies. More accurate exposure models are needed for more informed infection prevention strategies.