4.3 Article

Region-Specific Associations between Environmental Factors and Escherichia coli in Freshwater Beaches in Toronto and Niagara Region, Canada

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MDPI
DOI: 10.3390/ijerph182312841

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Escherichia coli; water quality; recreational water; environmental factors; fecal indicator bacteria

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  1. Public Health Agency of Canada [2021-HQ-000017]

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The study found significant clustering of E. coli values at beaches in Toronto, while minimal clustering was observed in Niagara, indicating an important beach-specific effect in Toronto. Air temperature and turbidity showed a positive association with E. coli in all models in both regions. Rainfall had varying associations with E. coli levels in different regions.
Poor freshwater beach quality, measured by Escherichia coli (E. coli) levels, poses a risk of recreational water illness. This study linked environmental data to E. coli geometric means collected at 18 beaches in Toronto (2008-2019) and the Niagara Region (2011-2019) to examine the environmental predictors of E. coli. We developed region-specific models using mixed effects models to examine E. coli as a continuous variable and recommended thresholds of E. coli concentration (100 CFU/100 mL and 200 CFU/100 mL). Substantial clustering of E. coli values at the beach level was observed in Toronto, while minimal clustering was seen in Niagara, suggesting an important beach-specific effect in Toronto beaches. Air temperature and turbidity (measured directly or visually observed) were positively associated with E. coli in all models in both regions. In Toronto, waterfowl counts, rainfall, stream discharge and water temperature were positively associated with E. coli levels, while solar irradiance and water level were negatively associated. In Niagara, wave height and water level had a positive association with E. coli, while rainfall was negatively associated. The differences in regional models suggest the importance of a region-specific approach to addressing beach water quality. The results can guide beach monitoring and management practices, including predictive modelling.

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