Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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SRA 2013 Annual Meeting Abstracts P.72 Chang, CH; Chuang, YC; Chen, CC; Wu, KY*; National Taiwan University; achchg@gmail.com Probabilistic Assessment of Cancer Risk for N-Nitrosodimethylamine in Drinking Water by Using Bayesian Statistics with MarKov Chain Monte Carlo Simulation N-Nitrosodimethylamine (NDMA) is an emerging nitrogenated Disinfection By-Product (N-DBP) in drinking water formed during chloramination and chlorination. NDMA is genotoxic and carcinogenic to rodents after cytochrome P-450 metabolism by the liver as its target organ. The potential health risk posed by NDMA exposures through water consumption has been of great concern. With the majority of NDMA data in drinking water below detection limit, the research community has yet to perform its cancer risk assessment. In order to deal with a majority of Non-detectable (ND) data of NDMA in drinking water, a Bayesian statistics with Markov chain Monte Carlo simulation was first used to assess probabilistic cancer risk for NDMA in drinking water in WinBUGS1.4 (Bayesian analysis software Using Gibbs Sampling for Windows Version 1.4). The dataset of NDMA concentration was cited from a published study in Taiwan; from which 50 drinking water samples were collected and only one sample was detected at 4.5ng/L. Posterior distributions revealed a mean concentration of NDMA in drinking water at 0.54ng/L. The estimated 95th percentile of lifetime cancer risk was 2.897E-6. These results suggest that the NDMA levels in drinking water in Taiwan do not pose significant cancer risk; regulation of NDMA may be needed in order to fully protect the general public. T1-H.2 Chatterjee, S*; Salazar, D; Hora, S; CREATE, University of Southern California; samrat.chatterjee@usc.edu Frequency-severity relationships for human-caused extreme events Rare but extremely severe events can occur due to intentional and accidental hazards. This study explores the relationship between the frequency and severity of such human-caused events. Tools of extreme value statistics and statistical learning are employed to analyze data from The Global Terrorism Database (GTD)-developed by the START Center at the University of Maryland and The Hazardous Materials Incident Database-developed by the U.S. Department of Transportation Pipeline and Hazardous Materials Safety Administration. Event severity is expressed in terms of fatalities, injuries, and direct property damage. We also investigate the scale invariance property in such human-caused events. M3-E.3 Che, WW*; Frey, HC; Lau, AKH; The Hong Kong University of Science & Technology North Carolina State University; wenweicherren@gmail.com Sensitivity of estimated children PM2.5 exposure to activity patterns, and geographic and seasonal variations Children’s exposure to ambient Particulate Matter (PM) depends on activity patterns and ventilation in micro-environments, which in turn can depend on climate zone and season. Distribution of inter-individual variability in daily PM2.5 exposure for school age children (5-18) were estimated using the U.S. Environmental Protection Agency’s Air Pollutants Exposure model (APEX). The key inputs to APEX include ambient concentration, air exchange rate, penetration factor, deposition rate, census data and activity diary data. Inter-individual variability in exposure of elementary school (6-11), middle school (12-14) and high school (15-18) children were estimated and compared for selected regions in North Carolina (NC), New York City (NYC) and Texas (TX) for four seasons (spring, summer, fall and winter). Home and school are the most important microenvironments for children’s exposure on school days; while home and outdoors are predominant on non-school days. The ratio of ambient exposure to ambient PM2.5 concentration (E/C) is significantly different (P
SRA 2013 Annual Meeting Abstracts P.71 Chen, YT*; Chang, CH; Chung, YC; Chen, CC; Wang, GS; Wu, KY; National Taiwan University; r01844001@ntu.edu.tw Probabilistic Risk Assessment of Cisplatin for Medical Staff of Medical Centers in Taiwan Cisplatin, a platinum-based chemotherapeutic medicine, widely used in chemotherapy, is mutagenic and has ability to cause chromosal aberrations, micronuclei and to induce nephrotoxicity, birth abnormality, and reproductive effect. Potential cisplatin exposures to medical staff including pharmacists and nurses who handle the chemotherapeutic medicine have been of great concerns. A preliminary study was conducted to analyze urinary platinum to assess exposures for 126 medical staff in three medical centers in Taiwan, showing that urinary platinum was detectable in only 5 of these study subjects in the range from 1.59 to 89.1 ppt. In this study, the urinary platinum levels were used to reconstruct cisplatin exposures for probabilistic risk assessment by using Bayesian statistics Markov chain Monte Carlo simulation with the WINBUGS software. The results showed that cisplatin exposures were 0.03 mg/kg/day for pharmacists in the departments of chemotherapeutic medicine, the corresponding hazard indexes (HI) were 129.98 ± 12.95; for nurses in oncology wards were 0.02 mg/kg/day, the corresponding HI were 86.53 ± 8.67; and for nurses in the oncology clinics were 0.04 mg/kg/day, the corresponding HI were 173.14 ± 17.23. These results suggest that the intervention should be implemented thoroughly and further studies should be conducted to protect medical staff handling the chemotherapy medicine in Taiwan. P.145 Chen, NC*; Yates, JY; Texas A&M University; nnchen@tamu.edu Decision Aiding for Extreme Event Evacuation Evacuating a large population from an impending extreme event is fraught with complexity, uncertainty and risk. Evacuees have to make decisions on route planning and point-of-destination while emergency managers need to ensure the appropriate personnel and infrastructure are available and capable of facilitating the evacuation. In evacuation, individual evacuees are exhibiting an increasing desire to communicate with family, friends and the local/state/federal authorities in-situ. We develop an agent-based simulation model to examine the impact of communication within social connections and emergency management during regional evacuations. We show how improved communication among evacuees impacts the evacuation process and we demonstrate how this knowledge can lead to improved public evacuation management. Furthermore, to better enable evacuee communication during an event, we formulate a time-dependent discrete optimization model to determine the location of telecommunications equipment as well as the assignment of evacuees to equipment. W3-D.2 Chen, Y*; Dennis, S; McGarry, S; Food and Drug Administration ; yuhuan.chen@fda.hhs.gov FDA’s Risk Assessment Model for Designating High-Risk Foods Pertaining to Product Tracing Required by FSMA Section 204 of the Food Safety Modernization Act (FSMA) requires FDA to designate high-risk foods for which additional record keeping requirements are appropriate and necessary to protect the public health. FSMA outlines the parameters that FDA should use in developing a high risk foods (HRF) list. These parameters include: (1) the known safety risks of a particular food, (2) the likelihood that a particular food has a high potential risk for microbiological or chemical contamination or would support growth of pathogen microorganisms, (3) the point in the manufacturing process where contamination is most likely to occur, (4) the likelihood of contamination and steps taken during manufacturing process to reduce the possibility of contamination, (5) the likelihood that consuming a food will result in a foodborne illness, and (6) the likely or known severity of a food borne illness attributed to a particular food. A predictive, data-driven risk assessment model with seven criteria that encompass the many factors required by FSMA is being developed. Data from multiple sources are used in implementing the model and provide a list of candidate food-hazard pairs for consideration in designating high-risk foods. The presentation will focus on current Agency thinking and stakeholder input on the development of the HRF list. T2-C.2 Cheung, C; Friesen, S*; Government of Canada; shaye.friesen@drdc-rddc.gc.ca The federal all hazards risk assessment: integrating strategic risk into emergency management planning – a Canadian perspective The purpose of this presentation is to describe the All Hazards Risk Assessment (AHRA) framework that was developed collaboratively between Public Safety Canada (PS) and Defence Research and Development Canada’s Centre for Security Science (DRDC CSS). Launched as a pilot in 2010, the AHRA methodology considers public safety and security threats and hazards, both malicious and non-malicious, of national significance and addresses them using a holistic, cross-government approach involving 25 federal departments and agencies. The AHRA provides a frame that other government departments may populate. The AHRA is a Canadian innovation that uses a comprehensive analytical approach towards scenario selection and development, risk scoring and analysis, and risk evaluation. This presentation discusses how the results from this process are integrated broadly amongst federal institutions. It illustrates how the AHRA has become a key component for ensuring a long-term, viable strategy, whereby federal institutions participate in an annual cycle to evaluate priority threats and hazards to Canada and validate their emergency management plans in relation to the identified scenarios. This presentation concludes by discussing the results from the third cycle of development, the merging of risk assessments with a broader capability assessment methodology, and the exploratory work to build a National AHRA Framework with Provinces, Territories and Regions. December 8-11, 2013 - Baltimore, MD
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Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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