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The genus Arcobacter has been associated with human illness and fecal contamination by humans and animals. To better characterize the health risk posed by this emerging waterborne pathogen, we investigated the occurrence of Arcobacter spp. in Lake Erie beach waters. During the summer of 2010, water samples were collected 35 times from the Euclid, Villa Angela, and Headlands (East and West) beaches, located along Ohio's Lake Erie coast. After sample concentration, Arcobacter was quantified by realtime PCR targeting the Arcobacter 23S rRNA gene. Other fecal genetic markers (Bacteroides 16S rRNA gene [HuBac], Escherichia coli uidA gene, Enterococcus 23S rRNA gene, and tetracycline resistance genes) were also assessed. Arcobacter was detected frequently at all beaches, and both the occurrence and densities of Arcobacter spp. were higher at the Euclid and Villa Angela beaches (with higher levels of fecal contamination) than at the East and West Headlands beaches. The Arcobacter density in Lake Erie beach water was significantly correlated with the human-specific fecal marker HuBac according to Spearman's correlation analysis (r ‫؍‬ 0.592; P < 0.001). Phylogenetic analysis demonstrated that most of the identified Arcobacter sequences were closely related to Arcobacter cryaerophilus, which is known to cause gastrointestinal diseases in humans. Since human-pathogenic Arcobacter spp. are linked to human-associated fecal sources, it is important to identify and manage the human-associated contamination sources for the prevention of Arcobacter-associated public health risks at Lake Erie beaches.

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Current approaches for assessing human health risks associated with cyanotoxins often rely on the quantification of microcystin. Significant limitations of current approaches are cost and time to obtain a result. To address these challenges, a numerical index for screening microcystin risks above the World Health Organization’s (WHO) low-risk threshold for microcystin was developed for eutrophic Midwestern U.S. lakes based on water quality results from 182 beach water samples collected from seven Ohio lakes. In 48 (26.4%) samples we observed microcystin concentrations as measured by ELISA that exceeded the 4 μg/L microcystin threshold. A multivariable logistic regression model using practical real-time measures of in vivo phycocyanin (by fluorometry) and secchi depth was constructed to estimate the probability of a beach sample exceeding 4 μg/L microcystin. The final model achieved statistical significance (p = 0.030) as well as good calibration (as measured by the goodness-of-fit test comparing observed to expected counts within deciles of risk based on the model, p = 0.329) and discrimination (as indicated by the area under the receiver-operator-curve (0.795)). These results demonstrate two rapid and practical measures of recreational water quality are effective in identifying “at risk” lake conditions warranting additional management (e.g., advisory and/or advanced testing).

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