Analyzing Pathogen Transmission in the Dialysis Unit

Abstract

Infectious diseases and antimicrobial-resistant microorganisms are a growing problem for the dialysis population. The frequency of patient visits and intimate, prolonged physical contact with the inanimate environment during dialysis treatments make these facilities potentially efficient venues for nosocomial pathogen transmission. Isolation measures and infection control practices can be inconvenient and consume limited resources. Quantitative tools for analyzing the effects of different containment strategies can help to identify optimal strategies for further study. However, spatial and temporal considerations germane to the dialysis unit greatly complicate analyses relying on conventional mathematical approaches. A stochastic, individual-based, Monte Carlo simulation tool that predicts the effects of various infection control strategies on pathogen dissemination through the dialysis unit in the face of diagnostic uncertainty was developed. The model was configured to emulate a medium-sized dialysis unit. The predicted consequences of various policies for scheduling patients who were suspected of being infectious were then explored, using literature-based estimates of pathogen transmissibility, prevalence, and diagnostic uncertainty. Environmental decontamination was predicted to be of paramount importance in limiting pathogen dissemination. Temporal segregation (scheduling patients who were suspected of being infectious to dialysis shifts that are later in the day) was predicted to have the greatest effectiveness in reducing transmission, given adequate environmental decontamination between successive days. Decontamination of the patient's environment (chair) can markedly attenuate pathogen dissemination. Temporal segregation could be a simple, low-cost, system-level intervention with significant potential to reduce nosocomial transmission in the dialysis unit.