South Florida RAD: Using Wastewater Measurements to Predict COVID-19 in the Community
The University of Miami (UM) and Weill Cornell Medicine (WCM) established a collaborative study for human and environmental surveillance of SARS-CoV-2, the virus that causes COVID-19 disease, including surface, air, and wastewater based surveillance efforts.
Five shared resources at UM helped establish and are currently providing coordinated support for ongoing surveillance and research, providing a case study of how a diverse array of shared resources can work together to facilitate human and environmental surveillance for SARS-CoV-2. The shared resources involved in this effort include a group of Sylvester Comprehensive Cancer Center (SCCC) Shared Resources, including the Behavioral and Community Based Research Shared Resource, Biospecimen Shared Resource, and Onco-Genomics Shared Resource, along with the Miami Center for AIDS Research (CFAR) Laboratory Sciences Core, and the Miami Clinical and Translational Science Institute (CTSI) Biostatistics Collaboration and Consulting Core.
UM has deployed an extensive human surveillance testing, tracking, and tracing system to monitor students, faculty, and staff, and widespread wastewater surveillance of SARS-CoV-2 from buildings on all campuses. This surveillance includes a major hospital that is part of UM and that treats COVID-19 patients.
WCM has established an international consortium for SARS-CoV-2 environmental surveillance. The goals of this UM/WCM study are to generate, optimize, standardize, and compare SARS-CoV-2 human and wastewater surveillance with various sampling, processing, detection, and analysis approaches, and to integrate wastewater data with community and hospital COVID-19 prevalence, with the aim of developing predictive models of local and community level spread of COVID-19 and also the spread of other existing and emerging pathogens.
A significant impact of this research will be that it compares SARS-CoV-2 human surveillance data to WBT measurements of SARS-CoV-2, non-COVID microbes, and physical chemical parameters, to improve sensitivity and specificity of wastewater measurements. Results will be used to standardize sample collection and concentration procedures. Innovative methods of sample concentration and detection will be explored to provide for more rapid processing and lower limits of detection, while at the same time providing for simplified detection procedures. Results of measurements will be used to develop a model that predicts local and community spread of COVID-19 based upon WBT. Thus, the results of the proposed research will broaden the scope of communities able to implement WBT to augment human-disease surveillance programs. Moreover, the results will inform and improve public health and safety strategies on the local community and municipal levels and may also impact public health strategies at the state, national, and international levels.
Laboratory Sciences Core
Biostatistics Collaboration and Consulting Core