Efficacy of monitoring and empirical predictive modeling at improving public health protection at Chicago beaches
ABSTRACT Efforts to improve public health protection in recreational swimming waters have focused on obtaining real-time estimates of water quality. Current monitoring techniques rely on the time-intensive culturing of fecal indicator bacteria (FIB) from water samples, but rapidly changing FIB concentrations result in management errors that lead to the public being exposed to high FIB concentrations (type II error) or beaches being closed despite acceptable water quality (type I error). Empirical predictive models may provide a rapid solution, but their effectiveness at improving health protection has not been adequately assessed. We sought to determine if emerging monitoring approaches could effectively reduce risk of illness exposure by minimizing management errors. We examined four monitoring approaches (inactive, current protocol, a single predictive model for all beaches, and individual models for each beach) with increasing refinement at 14 Chicago beaches using historical monitoring and hydrometeorological data and compared management outcomes using different standards for decision-making. Predictability (R(2)) of FIB concentration improved with model refinement at all beaches but one. Predictive models did not always reduce the number of management errors and therefore the overall illness burden. Use of a Chicago-specific single-sample standard-rather than the default 235 E. coli CFU/100 ml widely used-together with predictive modeling resulted in the greatest number of open beach days without any increase in public health risk. These results emphasize that emerging monitoring approaches such as empirical models are not equally applicable at all beaches, and combining monitoring approaches may expand beach access.
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- "Increasingly, efforts to develop a variety of water quality criteria have focused on the use of field data to develop relationships between biological responses and their stressors, and then to identify levels of the stressors that preserve the desired biological conditions. Examples of stressors other than nutrients that have been investigated in this way include river sediments, pathogens, metals, and specific conductance (Shine et al. 2003; Paul and McDonald 2005; Cormier et al. 2008, 2013; Hollister et al. 2008; Nevers and Whitman 2011; USEPA 2011). "
ABSTRACT: High levels of the nutrients nitrogen and phosphorus can cause unhealthy biological or ecological conditions in surface waters, and prevent the attainment of their designated uses. Regulatory agencies are developing numeric criteria for these nutrients in an effort to ensure that the surface waters in their jurisdictions remain healthy and productive, and that water quality standards are met. These criteria are often derived using field measurements that relate nutrient concentrations and other water quality conditions to expected biological responses such as undesirable growth or changes in aquatic plant and animal communities. Ideally, these numeric criteria can be used to accurately "diagnose" ecosystem health and guide management decisions. However, the degree to which numeric nutrient criteria are useful for decision-making depends on how accurately they reflect the status or risk of nutrient-related biological impairments. Numeric criteria that have little predictive value are not likely to be useful for managing nutrient concerns. This paper presents information on the role of numeric nutrient criteria as biological health indicators, and the potential benefits of sufficiently accurate criteria for nutrient management. In addition, it describes approaches being proposed or adopted in states such as Florida and Maine to improve the accuracy of numeric criteria and criteria-based decisions. This includes a preference for developing site-specific criteria where sufficient data are available, and the use of nutrient concentration and biological response criteria together in a framework to support designated use attainment decisions. Together with systematic planning during criteria development, the accuracy of field-derived numeric nutrient criteria can be assessed and maximized as a part of an overall effort to manage nutrient water quality concerns. Integr Environ Assess Manag © 2013 SETAC.Integrated Environmental Assessment and Management 01/2014; 10(1). DOI:10.1002/ieam.1485
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- "These steps can hinder the process of emergency preparedness and prevention, particularly for remote areas and regions having numerous water bodies such as Canada. Further, the concentration values of microbial indicators can change rapidly and result in management errors regarding the exposure of the public to higher concentrations of bacteria or beach closures despite an acceptable water quality (Nevers & Whitman, 2011). The assessment and monitoring of microbiological quality of surface water requires standardized measurements and systematic observations, in a systemic approach integrating microbiological indicators, environmental determinants (land cover and use, topography, climate, extreme weather events, etc.) and socioeconomic factors, at various scales of water governance such as the watershed (Fig. 1), "
ABSTRACT: Contaminated surface water poses a risk to human populations and is a challenge for public health authorities. Climatic change, intensification of agriculture, urban development of coastal areas, and declining freshwater sources may contribute significantly to the risk of surface water contamination and increase incidence of waterborne diseases. Monitoring of surface water quality requires early detection of problems in order to minimize any negative impact on public health. Tele-epidemiology uses remote sensing and geospatial technologies to characterize the spatial and temporal variability of environmental determinants involved in the epidemiology of some diseases. By offering a systematic and integrated approach to water and risk management in public health, tele-epidemiology can be an efficient tool to assess surface water quality and any associated health risks.
- "Predictive modeling of water quality based on environmental factors is being explored as an alternative to the current monitoring techniques which can take days to complete. Such models can predict the FIB levels using observed environmental conditions with varying degrees of success (Nevers & Whitman, 2011). This approach allows proactive beach closure for recreational use as soon as the conditions for contamination are met, rather than waiting for the water sample results. "