ArticleApplied and environmental microbiology2013
Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection.
Article in Applied and environmental microbiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of predictive models of microbial water quality at freshwater recreational beaches.PloS one · 2021Pooled it
- Canadian beach cohort study: protocol of a prospective study to assess the burden of recreational water illness.BMC public health · 2024Article
- Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety.Applied and environmental microbiology · 2024Article
- Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data.Journal of applied microbiology · 2023Article
- Recreational water exposures and illness outcomes at a freshwater beach in Toronto, Canada: A prospective cohort pilot study.PloS one · 2023Article
- Region-Specific Associations between Environmental Factors andInternational journal of environmental research and public health · 2021Article
- Integrative Survey of 68 Non-overlapping Upstate New York Watersheds Reveals Stream Features Associated With Aquatic Fecal Contamination.Frontiers in microbiology · 2021Article
- Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to PredictFrontiers in artificial intelligence · 2021Article
- Prediction ofFrontiers in artificial intelligence · 2021Article
- Comparison of Resampling Algorithms to Address Class Imbalance when Developing Machine Learning Models to Predict Foodborne Pathogen Presence in Agricultural Water.Frontiers in environmental science · 2021Article
- Impact of Escherichia coli from stormwater drainage on recreational water quality: an integrated monitoring and modelling of urban catchment, pipes and lake.Environmental science and pollution research international · 2021Article
- Predictive Models May Complement or Provide an Alternative to Existing Strategies for Assessing the Enteric Pathogen Contamination Status of Northeastern Streams Used to Provide Water for Produce Production.Frontiers in sustainable food systems · 2020Article
- Landscape, Water Quality, and Weather Factors Associated With an Increased Likelihood of Foodborne Pathogen Contamination of New York Streams Used to Source Water for Produce Production.Frontiers in sustainable food systems · 2020Article
- Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water.Frontiers in microbiology · 2020Article
- Within-day variability in microbial concentrations at a UK designated bathing water: Implications for regulatory monitoring and the application of predictive modelling based on historical compliance data.Water research X · 2018Article
- The Interplay Between Predation, Competition, and Nutrient Levels Influences the Survival of Escherichia coli in Aquatic Environments.Microbial ecology · 2016Article
- Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters.Applied and environmental microbiology · 2013Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the E. coli standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day's E. coli concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. Cryptosporidium, adenovirus, eaeA (E. coli), ipaH (Shigella), and spvC (Salmonella) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to E. coli concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.
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