After a storm, the bacteria from human and animal waste that washes into the sea can make swimmers sick—but no one knows exactly when the water is safe again. Current models for predicting this risk are too static. They fail to account for the episodic nature of contamination, which spikes after heavy rain and is shaped by tides, seasons, and a changing climate. This leaves coastal managers guessing whether to close beaches, upgrade sewage treatment, or restrict farming—decisions that pit public health against economic and social costs. This project will build a new integrated model that tracks faecal indicator organisms from their source—sewage outflows, farm manure, or urban runoff—through rivers and estuaries to the coast. It will combine this with dynamic health impact assessments and public risk perception data. If successful, the model will let regulators test policy options under future climate scenarios, trading off health risks against financial and carbon costs with far greater precision. The result could be smarter, faster decisions on when to close and reopen beaches, and more targeted investment in treatment infrastructure.
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Health impacts from pathogens indexed by faecal indicator organisms (FIOs) arise from water contact and food consumption derived from catchments, rivers, estuaries and coastal waters. However, the risks associated with these exposures are often highly episodic and determined by rates of pathogen shedding, tides, weather and seasons, all of which are impacted by changing climate, and particularly when storminess is included. Point sources include sewage effluents, intermittent discharges from combined sewer overflows, agricultural point sources such as manure stores, and diffuse sources. Faecal loads are attenuated during the soil - fresh water (including groundwater and/or river water) - estuarine - coastal pathway. Better predictions of the fate and transport of these pollutants along their pathways from sources to receptors would inform several health, policy and operational issues, including: - Whether to manage health risks by restricting access to receiving waters or by management of potential sources of pollutants; - When to declare coastal waters closed, and when to reopen them, trading off the health risks against the economic and social impacts; - What further sewage/intermittent discharge treatment to deploy, which involves trading off the financial and carbon costs against the infrequent health improvements; - What agricultural management options to impose, trading off the financial and food security impacts against the potential health improvements? - How better to optimise health and risk-management processes based on scientific evidence vis-a-vis public perception. The proposed research seeks to develop a new integrated model to predict the exposure to and the health impact assessment of pathogen risks, as indexed by FIOs, in near-shore coastal waters. The approach will be to build and validate a FIO fate and transport model which incorporates rainfall and catchment sources to coastal receiving waters, to use this model together with enhanced disease burden modelling and quantitative microbial risk assessment procedures to produce a dynamic quantitative health impact assessment. The overall model will then be used to analyse policy options for range of future scenarios, including climate change (in terms of changes in rainfall), and to relate the outcomes to actual and perceived health risks. The outputs of the research will inform identified policy gaps and afford improved decision making to minimise health risk from FIO.
Adrian John Saul (Principal Investigator)Binliang Lin (Co-Investigator)David Kay (Co-Investigator)David Lerner (Principal Investigator)Philip Catney (Co-Investigator)Roger Falconer (Co-Investigator)
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