Microbial water quality indicators are found in high concentrations in sewage, and are thus used to determine whether or not a water body is safe for recreational purposes. Recently, concerns have been raised about the appropriate use of microbial indicators to regulate recreational uses of water bodies. This is particularly true for water bodies located in sub/tropical environments, due to the potential for microbial regrowth in sub/tropics, and the fact that studies used to set national guidelines were not conducted in sub/tropical environments. The primary goal of this proposed study is to evaluate the relationship between human health, and the physical and microbial characteristics of a coastal water and its shoreline. This goal will be addressed by measuring human health effects and microbial water quality at a recreational beach site within a sub/tropical climate, and by developing a predictive, coupled hydrodynamic and microbial fate model that can be used to distinguish impacts from sewage sources versus regrowth of microbes, each of these sources possibly resulting in different health effects as observed at the beach site. Substantial pilot data have been collected for the sub/tropical study site chosen for this research. These pilot data, as well as the literature, indicate that exposure to contaminated recreational marine waters may result in human health effects, and that the shoreline sediments is one likely source of indicator microbes. Human health will be evaluated in the proposed project through an epidemiologic study which will randomly assign exposure to water or beach with coordinated individual environmental sampling and repeated follow up of reported human health effects. Water quality will be evaluated through two sets of environmental measurements. The first phase of the environmental assessment will focus on identifying the distribution and sources of enterococci (the current federally recommended indicator microbe) within the study site. Enterococci will be monitored through an intensive effort aimed at identifying sources, in particular shoreline sources, and correlations with suspended sediment concentrations. The data gathered from this intensive sampling effort will be used to develop source functions for an enterococci fate model to be coupled with a hydrodynamic oceanographic model developed for the area. The coupled enterococci model will be used in a predictive fashion to determine when and where within the study beach the epidemiologic study should take place. The second phase of environmental measurements will focus on the analysis of multiple microbes coincident with times that participants participate in the epidemiologic study. Microbe measurements will include traditional (enterococci, E. coli, fecal coliform) and non-traditional (C. perfringens, coliphage) microbial indicators, as well as direct measurement of microbial pathogens (S. aureus, enterovirus, Norwalk virus, hepatitis A, C. parvum, and G. lamblia). Analysis of the viral and protozoan pathogens will include traditional PCR and results will be cross-checked against new Luminex technology. A primary goal of this research is to develop a rapid (same day), accurate high throughput and sensitive molecular test for the identification of pathogenic microorganisms in marine and freshwater environments. The Remote Sensing Core and the Genomics Core will participate in this proposed interdisciplinary collaborative research study. The results from the coupled hydrodynamic and microbial fate model will be compared with the pathogen and human health data for the purposes of predicting beach closures due to health hazards. Ultimately, the human, environmental and oceanographic data will be used to develop a predictive model with broad applicability to beaches in the sub/tropics with appropriate modifications for local conditions. The final result will be the improvement of recreational water quality monitoring in the sub/tropical marine environment, and an increase in public confidence in the results from microbial water quality monitoring and modeling.
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