Table of Contents Verbal Presentations Verbal Presentations – Monday………………………………………………………...................... Page 2 Verbal Presentations – Tuesday……………………………………………………………………… Page 17 Verbal Presentations – Wednesday………………………………………………………..…….….. Page 32 Verbal Presentations – Thursday……………………….……………………………….………..…. Page 46 Poster Presentations Poster Presentations – Monday…………………………………………………………………..…. Page 52 Poster Presentations – Tuesday……………………………………………………………..……… Page 64 Poster Presentations – Wednesday……………………………………………………….……….. Page 77 Poster Presentations – Thursday……………………………………….………………….……….. Page 90 Page 1 of 99 Verbal Presentations Monday, May 15th 8:30 – 10 AM Grumman A Microsimulation Approach to Estimating Annual Risk in QMRA. Coping with Non-Random Variation in Risk Amongst Populations Paul Hunter, The Norwich Medical School, University of East Anglia Additional Author: James Maas Most QMRA studies have focused on refining the estimation of the daily risk comparatively little thought has been given to estimating the annual risk. As pointed out by Karavarsamis and Hamilton most studies have used a relatively simple method of estimating annual risk from the distribution of daily risks, namely 1-(1-Pd)^365 (1). This approach essentially assumes that the daily risk is constant through the year and Karavarsamis and Hamilton, with justification, refer to this approach as "Naϊve". Instead they propose a stochastic approach that essentially samples the distribution of daily risks and then calculates the annual risk as 1-the product of (1- 365 randomly sampled daily risk), calling this the "Gold Standard Approach". We argue that Karavarsamis and Hamilton's gold standard approach is also naϊve. Daily risks in any one individual are neither constant through a year nor are they entirely random. For example, across a population some people drink a lot of water each day and others drink very little. Other factors like the concentration of pathogen in a supply may vary much more randomly. We propose a microsimulation approach to QMRA that allows both random and non-random drivers of risk to be incorporated into the analysis. Microsimulation models as applied to QMRA essentially simulate risk at the individual level over the course of one year and then combine the results of the individual analysis into a population level risk assessment. To illustrate the microsimulation approach we conducted a QMRA analysis of cryptosporidium concentrations in six private water supplies (2). Cryptosporidium concentrations were taken from the original dataset. Water consumption data for the UK was obtained from the Drinking Water Inspectorate. Initial analyses were done in @Risk using the exponential dose response model with k = 5.72E-02. The mean annual risk using Karavarsamis and Hamilton's "Naϊve" approach was 44 infections/1000person years whilst their "Gold Standard" approach gave 64. When water consumption was assumed to be constant this fell to 53 infections/1000person years. The two original approaches represent extremes with full and no autocorrelation of daily risks over the year. A microsimulation approach gives a closer estimate of real population risk. Microsimulation would also enable easier estimates of risk when there are multiple sources of infection. QMRA is also being used to estimate disease burden across nations and in such circumstances current methods are likely to be biased unless a microsimulation process is used. 1. Karavarsamis N, Hamilton AJ. Estimators of annual probability of infection for quantitative microbial risk assessment. Journal of Water and Health. 2010 Jun 1;8(2):365-73. 2. Kay D, Watkins J, Francis CA, Wyn-Jones AP, Stapleton CM, Fewtrell L, Wyer MD, Drury D. The microbiological quality of seven large commercial private water supplies in the United Kingdom. Journal of Water and Health, 2007; 5:523-538. The QMRAcatch Modelling Approach: Using Best Available Pathogen, Indicator and Source Tracking Data to Support Catchment Protection & Water Safety Management Julia Derx, TU Wien, ICC Water & Health Additional Authors: Jack Schijven; Regina Sommer; Christa Zoufal-Hruza; Georg Reischer; Alexander Kirschner; Christina Frick; Alfred Paul Blaschke; Andreas Farnleitner Motivated by recent progresses in water and sanitation safety planning (e.g. WHO water- and sanitation safety plans) the model QMRAcatch was recently developed to support sustainable decision making (Schijven et al. 2015). QMRAcatch allows the simulation of pathogen concentrations in a river and a river/floodplain environment including infection risk assessment by QMRA. Best available data on fecal indicator bacteria, genetic microbial source tracking (MST) markers, and reference pathogens can be combined to support source-targeted calibration of the model. Additional reference pathogens can be selected based on assumed source concentrations to support cross-comparison of infection risks. The hydrological situation and the importance of animal and human pollution sources can be considered by scenario analysis. Results inform about sustainable catchment protection measures and required log-reductions of pathogens during treatment and disinfection to meet a maximum tolerable infection risk. Both, drinking water safety management and infection risks associated during bathing activities can be considered. The scientific model software was recently launched at the World Water Congress in Brisbane and can be downloaded at www.waterandhealth.at. The aim of the presentation is to demonstrate the model application at the River Danube and associated river/floodplain area in Austria used for drinking water production and recreation focusing on the impact of human sources. The model was calibrated by the use of human-associated MST markers (qPCR data). In this regard it was proven that the required quantitative sensitivity and specificity of the selected human-associated genetic fecal qPCR markers were successfully supported by the assay characteristics (i.e. simulations showed that MST marker concentrations due to false positive signals from animal sources had negligible effects on the calibration Page 2 of 99 efforts for the human-specific emission patterns). Based on the calibrated model, low and high fecal contamination scenarios (e.g. wastewater treatment with and without disinfection, variable percentage of visitors that practice open defecation, low to high viral prevalence of pathogens) could be compared to evaluate sustainable water safety management scenarios for the considered catchment. Using human enteric viruses (i.e. entero- and noroviruses) required log-reduction during river bank filtration and final disinfection could also be calculated to support safe drinking water production in respect to the different scenarios. Further strategies and challenges to include also animal MST markers for multiple-source calibration will be discussed. This is a joint publication within the Interuniversity Cooperation Centre for Water and Health. Schijven, J, Derx, J., De Roda Husman, A.M., Blaschke, A.P. & Farnleitner AH (2015) QMRAcatch - Microbial quality simulation of water resources including infection risk assessment. J. Environ. Qual. 44(5): 1491-1502 QMRA (Quantitative Microbial Risk Assessment) of a Wastewater System Undergoing a Novel Treatment Process for Rural Environments in a Developing Country Bettina Genthe, CSIR Impartially treated wastewater may pose a public health risk due to the presence of pathogenic bacteria, enteric viruses, and protozoa into receiving waters causing potential health risks to surrounding communities through unintentional exposure. Conventional treatment processes such as activated sludge and biofilms are seldom used in rural South Africa due to lack of electricity and financial resources. Therefore, it is important to search for possible alternative options to improve the effluent of WWTPs in Southern Africa since classic ponds (waste stabilization ponds) have been used as wastewater treatment option in most of the rural areas of Southern Africa. Phyco-remediation is an environmentally friendly and cost effective alternative treatment option for rural areas. There are several ways in which an individual can acquire disease from wastewater: direct ingestion of the wastewater or aerosols created during spray irrigation may result in infection. In addition, infection may occur from ingestion There are several ways in which an individual can acquire disease from wastewater: direct ingestion of the wastewater or aerosols created during spray irrigation may result in infection. In addition, infection may occur from ingestion of pathogens on contaminated vegetation, oysters or other surfaces. Both fecal indicator organisms and specific pathogens were tested for in the ponds of the wastewater treatment works. To calculate microbial risk, the density of pathogens (number of micro-organisms per liter) in the source water were quantified and entered into the risk model. The sources of information for quantifying pathogen density in source waters were water samples collected from the site and analyzed for the presence of pathogens as well as modelling scenarios based on presence of indicator organisms. In this study surrogate pathogenic viruses and parasites were initially analyzed followed by indicator organisms to model changes. Doses were calculated based on a few hypothetical volumes of ingestion (accidental or deliberate) and frequency of exposure to provide a range of probabilities of infection. The probability of

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