Evaluating a microbial water quality prediction model for beach management under the revised EU Bathing Water Directive.

The revised Bathing Water Directive (2006/7/EC) requires EU member states to minimise the risk to public health from faecal pollution at bathing waters through improved monitoring and management approaches. While increasingly sophisticated measurement methods (such as microbial source tracking) assist in the management of bathing water resources, the use of deterministic predictive models for this purpose, while having the potential to provide decision making support, remains less common. This study explores an integrated, deterministic catchment-coastal hydro-environmental model as a decision-making tool for beach management which, based on advance predictions of bathing water quality, can inform beach managers on appropriate management actions (to prohibit bathing or advise the public not to bathe) in the event of a poor water quality forecast. The model provides a 'moving window' five-day forecast of Escherichia coli levels at a bathing water compliance point off the Irish coast and the accuracy of bathing water management decisions were investigated for model predictions under two scenarios over the period from the 11th August to the 5th September, 2012. Decisions for Scenario 1 were based on model predictions where rainfall forecasts from a meteorological source (www.yr.no) were used to drive the rainfall-runoff processes in the catchment component of the model, and for Scenario 2, were based on predictions that were improved by incorporating real-time rainfall data from a sensor network within the catchment into the forecasted meteorological input data. The accuracy of the model in the decision-making process was assessed using the contingency table and its metrics. The predictive model gave reasonable outputs to support appropriate decision making for public health protection. Scenario 1 provided real-time predictions that, on 77% of instances during the study period where both predicted and E. coli concentrations were available, would correctly inform a beach manager to either take action to mitigate for poor bathing water quality or take no action. However, Scenario 1 also provided data to support a decision to take action (when none was necessary - a type I error) in 4% of instances and to take no action (when action was required - a type II error) in 19% of the instances analysed. Type II errors are critical in terms of public health protection given that for this error, bathers can be exposed to risks from poor bathing water quality. Scenario 2, on the other hand, provided predictions that would support correct management actions for 79% of the instances but would result in type I and type II errors for 4% and 17% of the instances respectively. Comparison of Scenarios 1 and 2 for this study indicate that Scenario 2 gave a marginally better overall performance in terms of supporting correct management decisions, as it provided data that could result in a lower occurrence of the more critical type II errors. Given that the 28 member states of the European Union are required to engage with the public health provisions of the revised Bathing Water Directive, issues of compliance, pertaining particularly to the management of bathing water resources, remain topical. Decision supports for managing bathing waters in the context of the Directive are likely to become the focus of much attention and although, the current study has been validated in bathing waters off the east coast of Ireland, the approach of using a deterministic and integrated catchment-coastal model for such purposes is easily transferable to other bathing water jurisdictions.

Experimental and modelling evidence of splash effects on manure borne Escherichia coli washoff.

In tropical montane South-East Asia, recent changes in land use have induced increased runoff, soil erosion and in-stream suspended sediment loads. Land use change is also contributing to increased microbial pathogen dissemination and contamination of stream waters. Escherichia coli (E. coli) is frequently used as an indicator of faecal contamination. Field rain simulations were conducted to examine how E. coli is exported from the surface of upland, agricultural soils during runoff events. The objectives were to characterize the loss dynamics of this indicator from agricultural soils contaminated with livestock waste, and to identify the effect of splash on washoff. Experiments were performed on nine 1 m2 plots, amended or not with pig or poultry manure. Each plot was divided into two 0.5 m2 sub-plots. One of the two sub-plots was protected with a mosquito net for limiting the raindrop impact effects. Runoff, soil detachment by raindrop impact and its entrainment by runoff, and E. coli loads and discharge were measured for each sub-plot. The results show that raindrop impact strongly enhances runoff generation, soil detachment and entrainment and E. coli export. When the impact of raindrops was reduced with a mosquito net, total runoff was reduced by more than 50%, soil erosion was on average reduced by 90% and E. coli export from the amended soil surface was on average 3 to 8 times lower. A coupled physics-based approach was performed using the Cast3M platform for modelling the time evolutions of runoff, solid particles detachment and transfer and bacteria transport that were measured for one of the nine plots. After estimation of the saturated hydraulic conductivity, soil erodibility and attachment rate of bacteria, model outputs were consistent with measured runoff coefficients, suspended sediment and E. coli loads. This work therefore underlines the need to maintain adequate vegetation at the soil surface to avoid the erosion and export of soil borne potential pathogens towards downstream aquatic systems.

Multiplex PCR for the simultaneous detection of the Enterobacterial gene wecA, the Shiga Toxin genes (stx1 and stx2) and the Intimin gene (eae).

OBJECTIVES: The aetiology of several human diarrhoeas has been increasingly associated with the presence of virulence factors rather than with the bacterial species hosting the virulence genes, exemplified by the sporadic emergence of new bacterial hosts. Two important virulence factors are the Shiga toxin (Stx) and the E. coli outer membrane protein (Eae) or intimin, encoded by the stx and eae genes, respectively. Although several polymerase chain reaction (PCR) protocols target these virulence genes, few aim at detecting all variants or have an internal amplification control (IAC) included in a multiplex assay. The objective of this work was to develop a simple multiplex PCR assay in order to detect all stx and eae variants, as well as to detect bacteria belonging to the Enterobacteriaceae, also used as an IAC. RESULTS: The wecA gene coding for the production of the Enterobacterial Common Antigen was used to develop an Enterobacteriaceae specific qPCR. Universal primers for the detection of stx and eae were developed and linked to a wecA primer pair in a robust triplex PCR. In addition, subtyping of the stx genes was achieved by subjecting the PCR products to restriction digestion and semi-nested duplex PCR, providing a simple screening assay for human diarrhoea diagnostic.