A DYNAMIC MODEL TO ASSESS MICROBIAL HEALTH RISKS ASSOCIATED WITH BENEFICIAL USES OF BIOSOLIDS

There is currently a substantial amount of interest and controversy regarding the beneficial reuse of biosolids in the United States and worldwide. U.S. Federal laws regulating allowable levels of chemical contaminants in biosolids (Part 503 Rule) were developed using a risk-based methodology. However, the maximum allowable levels of microbiological contaminants in biosolids were based on performance or technology-based standards, management, and record keeping practices, because microbiological risk assessment methodologies were not sufficiently developed at the time that the Part 503 rule was promulgated. The first step in addressing potential concerns related to microbial pathogens in biosolids is to critically evaluate the potential risk to public health that may be associated with exposure to biosolids.A three year Water Environment Research Foundation (WERF) investigation was recently completed in which a methodology was developed for characterizing the risks to human health from pathogens via exposure to biosolids (Colford et al. 2003; Eisenberg et al. 2004). For both infectious and noninfectious disease processes, infectivity as a function of dose (estimated using a dose-response function) is an important factor to account for when estimating risk. There are, however, other factors that also potentially play an important role in infectious disease processes. Such factors include but are not limited to person-to-person transmission, immunity, asymptomatic infection, and incubation period. The methodology developed during this WERF investigation employs a population-based model that explicitly accounts for those properties that are unique to an infectious disease process.To demonstrate the applicability of this risk-based method, numerical simulations were carried out for a case study example in which the route of pathogen exposure was direct consumption of biosolids-amended soil and the pathogen present in the soil was enterovirus. The output from the case study yielded a decision tree that differentiates between conditions in which the relative risk from biosolids exposure is high and those conditions in which the relative risk from biosolids is low. This decision tree illustrates the interaction among the important factors in quantifying risk for the exposure scenario investigated. For the case study example, those factors include biosolids treatment processes, the pathogen shedding rate of infectious individuals, secondary transmission and immunity.An overview of the risk assessment methodology will be provided. Case study results will be summarized, and the status of related ongoing research will be presented.