Project Highlights

CAMRA Co-Director Wins Award for a Woman Leader in Water

On Sunday, September 7th the International Water Association will present CAMRA co-director Dr. Joan B. Rose with the first Hei-jin Woo Award for a woman leader in water.  The award will be presented during the opening ceremony of the IWA World Water Congress & Exhibition in Vienna, Austria where Dr. Rose will also present the first Hei-jin Woo Lecture on Wednesday, September 10th.

See the IWA award program flyer.

Dr. Rose is the Homer Nowlin Chair of Water Research at Michigan State University.

 

New Publication

Sushil B Tamrakar, Charles N Haas. (2008). Dose-Response Model for Lassa Virus. Human and Ecological Risk Assessment, 14(4), 742.

Abstract
This article develops dose-response models for Lassa fever virus using data sets found in the open literature. Dose-response data were drawn from two studies in which guinea pigs were given subcutaneous and aerosol exposure to Lassa virus. In one study, six groups of inbred guinea pigs were inoculated subcutaneously with doses of Lassa virus and five groups of out-bred guinea pigs were similarly treated. We found that the out-bred subcutaneously exposed guinea pig did not exhibit a dose-dependent trend in response. The inbred guinea pigs data were best fit by an exponential dose-response model. In a second study, four groups of out-bred guinea pigs were exposed to doses of Lassa virus via the aerosol route. In that study, aerosol diameter was less than 4.5 μ m and both mortality and morbidity were used as endpoints. The log-probit dose-response model provided a somewhat better fit than the Beta-Poisson model for data with mortality as the endpoint, but the Beta-Poisson is considered the best fit model because it can be derived using biological considerations. Morbidity data were best fit with an exponential dose-response model.
Keywords: Lassa fever virus; dose-response; microbial risk assessment; exponential model; beta-Poisson model; log-probit model

 

Christopher Y. Choi
Department of Agricultural and Biosystems Engineering
The University of Arizona

Water quality models are widely used in analyses of water distribution systems. These network models have been used quite successfully for operational purposes, but in the context of providing real-time response for contamination events, the general mixing assumptions are most likely inadequate. Water security has been a concern of the water distribution community for several years, and it has become apparent that additional accuracy is critical to properly develop real-time response tools, especially if in-situ sensor equipment will be used to help detect intrusions. Current models assume instantaneous and complete mixing at pipe junctions and several studies have contributed to growing evidence that this assumption may be inadequate. The 'complete' mixing assumption becomes especially questionable at pipe cross junctions, where there may be limited contact and retention time between the water flows in two incoming pipe legs. The impact of solute mixing at these intersections, geometric components of a network system, is the focus of this work. Our computational and experimental results clearly indicate that mixing at pipe cross junctions is far from 'perfect'. Incomplete mixing results from bifurcating inlet flows that reflect off one another with minimal contact time. Improving the existing water quality model based on accurate mixing data and simulations is important not only to predict concentrations of chemical species such as chlorine in water distribution systems, but also to prepare for potential intentional and accidental contamination events.

Water Distribution Network Laboratory at the Water Village of the University of Arizona

Computational Fluid Dynamics Simulations - Mixing Pattern of Contaminants at a Cross-Junction