Integrating Consumer Risk Perception and Awareness with Simulation-Based Quantitative Microbial Risk Assessment Using a Coupled Systems Framework: A Case Study of Private Groundwater Users in Ontario

Abstract

Private well users in Ontario are responsible for ensuring the potability of their own private drinking water source through protective actions (i.e., water treatment, well maintenance, and regular water quality testing).  In the absence of regulation and limited surveillance, quantitative microbial risk assessment (QMRA) represents the most practical and robust approach to estimating the human health burden attributable to private wells. For an increasingly accurate estimation, QMRA of private well water should be represented by a coupled model, which includes both the socio-cognitive and physical aspects of private well water contamination and microbial exposure. The objective of the current study was to determine levels of waterborne exposure via well water consumption among three sub-groups (i.e., clusters) of private well users in Ontario and quantify the risk of waterborne acute gastrointestinal illness (AGI) attributed to Giardia, shiga-toxin producing E. coli (STEC) and norovirus from private drinking water sources in Ontario. Utilize baseline simulations to explore the effect of varying socio-cognitive scenarios on model inputs (i.e., increased awareness, protective actions, aging population). The current study uses a large spatio-temporal groundwater quality dataset and cross-sectional province-wide survey to create socio-cognitive-specific QMRA simulations to estimate the risk of waterborne AGI attributed to three enteric pathogens in private drinking waters source in Ontario. Findings suggest significant differences in the level of exposure among sub-groups of private well users. Private well users within Cluster 3 are characterised by higher levels of exposure and annual illness attributable to STEC, Giardia and norovirus than Clusters 1 and 2. Provincial incidence rates of 514.8 (1,418 illness per year), 530.1 (2,203 illness per year) and 589.4 (5,204 illness per year) cases/100,000 private well users per year were predicted for private well users associated with Clusters 1 to 3. The established models will enable development of the necessary tools that are tailored to specific groups of at-risk well users, allowing for preventative public health management of private groundwater sources. 

Keywords: Private water wells, quantitative microbial risk assessment, waterborne illness, coupled systems framework, risk management, E. coli