A Bayesian Belief Network Model Assessing the Risk to Wastewater Workers of Contracting Ebola Virus Disease During an Outbreak.

During an outbreak of Ebola virus disease (EVD), hospitals' connections to municipal wastewater systems may provide a path for patient waste bearing infectious viral particles to pass from the hospital into the wastewater treatment system, potentially posing risks to sewer and wastewater workers. To quantify these risks, we developed a Bayesian belief network model incorporating data on virus behavior and survival along with structural characteristics of hospitals and wastewater treatment systems. We applied the model to assess risks under several different scenarios of workers' exposure to wastewater for a wastewater system typical of a mid-sized U.S. city. The model calculates a median daily risk of developing EVD of approximately 6.1x10(-12) (90% confidence interval: 1.0x10-1 to 5.4x10(-9); mean 1.8x10(-6)) when no prior exposure conditions are specified. Under a worst-case scenario in which a worker stationed in the sewer adjacent to the hospital accidentally ingests several drops (0.35 mL) of wastewater, median risk is 5.8x10(-4) (90% CI: 8.8x10(-7) to 9.5x10(-2); mean 3.2x10(-2)). Disinfection of patient waste with peracetic acid for 15 minutes prior to flushing decreases the estimated median risk to 3.8x10(-7) (90% CI: 4.1x10(-9) to 8.6x10(-5); mean 2.9x10(-5)). The results suggest that requiring hospitals to disinfect EVD patient waste prior to flushing may be advisable. The modeling framework can provide insight into managing patient waste during future outbreaks of highly virulent infectious pathogens.