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Plenary 3: Emerging Issues and New Technologies 1 - SARS-CoV 2
10:50am - 12:00pm
Session Chair: Manfred Kleidorfer
Location:Lecture Hall BMT
BMTEG138 (HS BMT), Biomedical Engineering Building at Stremayrgasse 16, 8010 Graz, ground floor
10:50am - 11:10am
Evaluation of sampling strategies for upstream sampling for SARS-CoV-2 RNA
Albert Wilhelm König1, Sarah Ariano2, Darko Joksimovic2
1Graz University of Technology, Austria; 2Ryerson University, Toronto, Canada
An engine for water quality simulations of pulse loads in sewer systems was developed
The engine was used to generate synthetic water quality data of SARS-CoV-2 RNA in order to evaluate sampling strategies regarding their suitability for upstream sewer sampling
The evaluation included consistency of the results, their correlation with the number of infected in the catchment and representation of the catchment
11:10am - 11:30am
SARS-CoV 2 adsorption and desorption capacity of passive samplers for wastewater surveillance
Christelle Schang1, Rachael Poon2, Monica Nolan2, Nick Crosbie3, Yussi M. Palacios1, Chi-Wen Tseng1, Rebekah Henry1, David T. McCarthy1
1Department of Civil Engineering, Monash University, Wellington Rd, Clayton, Victoria, 3800, Australia; 2Department of Health and Human Services, 50 Lonsdale St., Melbourne, Victoria, 3000, Australia.a; 3Melbourne Water, 990 La Trobe St, Docklands, Victoria, 3008, Australia.
SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has been found in infected symptomatic and asymptomatic patients’ secretions and showed that human wastewater monitoring has the potential to act as a sensitive surveillance system. Passive samplers have shown to be an effective technique for wastewater surveillance however more needs to be known about their adsorption and desorption kinetics. This study showed that electronegative cellulose nitrate membrane followed a linear adsorption relationship and had a slow desorption for up to 7 days since first exposed to the virus. More work is needed to understand the factors influencing these relationships.
11:30am - 11:50am
Developing an open-source, relational data model for recording SARS- CoV-2 signals across multiple sewersheds
Jean-David Therrien1, Mathew Thomson2, Thomas Maere1, Douglas Manuel2,3, Peter A. Vanrolleghem1
1modelEAU, Université Laval, Québec (QC), Canada; 2Ottawa Hospital Research Institute, uOttawa, Ottawa (ON), Canada; 3Public Health Agency of Canada, Ottawa (ON), Canada
The SARS-CoV-2 pandemic has created a demand for simple and cost-effective ways to monitor the health of populations. Wastewater-based epidemiology (WBE) is a monitoring approach that has gained wide acceptance in recent years. However, the complexity of the wastewater system makes the interpretation of the collected data particularly difficult. The PHES-ODM data model was designed to record and organize all variables of interest for a public health measurement campaign to support data exploration and interpretation. The case of Québec province SARS-CoV-2 surveillance is used to demonstrate how this model can be used to create a structured, reusable data pipeline.