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Environmental Health and Protection Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Environmental Health and Protection
Beyond Covid-19: Designing Inclusive Public Health Surveillance By Including Wastewater Monitoring, Rochelle H. Holm, Na'taki Osborne Jelks, Rebecca Schneider, Ted Smith
Beyond Covid-19: Designing Inclusive Public Health Surveillance By Including Wastewater Monitoring, Rochelle H. Holm, Na'taki Osborne Jelks, Rebecca Schneider, Ted Smith
Faculty Scholarship
Wastewater-based epidemiology is a promising and expanding public health surveillance method. The current wastewater testing trajectory to monitor primarily at community wastewater treatment plants was necessitated by immediate needs of the pandemic. Going forward, specific consideration should be given to monitoring vulnerable and underserved communities to ensure inclusion and rapid response to public health threats. This is particularly important when clinical testing data are insufficient to characterize community virus levels and spread in specific locations. Now is a timely call to action for equitably protecting health in the United States, which can be guided with intentional and inclusive wastewater monitoring.
Estimating Sewage Flow Rate In Jefferson County, Kentucky, Using Machine Learning For Wastewater-Based Epidemiology Applications, Dhiraj Kanneganti, Lauren E. Reinersman, Rochelle H. Holm, Ted Smith
Estimating Sewage Flow Rate In Jefferson County, Kentucky, Using Machine Learning For Wastewater-Based Epidemiology Applications, Dhiraj Kanneganti, Lauren E. Reinersman, Rochelle H. Holm, Ted Smith
Faculty Scholarship
Direct measurement of the flow rate in sanitary sewer lines is not always feasible and is an important parameter for the normalization of data used in wastewater-based epidemiology applications. Machine learning to estimate past wastewater influent flow rates supporting public health applications has not been studied. The aim of this study was to assess wastewater treatment plant influent flow rates when compared with weather data and to retrospectively estimate flow rates in Louisville, Kentucky (USA), based on other data types using machine learning. A random forest model was trained using a range of variables, such as feces-related indicators, weather data …
Quantifying The Relationship Between Sub-Population Wastewater Samples And Community-Wide Sars-Cov-2 Seroprevalence, Ted Smith, Rochelle H. Holm, Rachel J. Keith, Alok R. Amraotkar, Chance R. Alvarado, Krzysztof Banecki, Boseung Choi, Ian Santisteban, Adrienne M. Bushau-Sprinkle, Kathleen T. Kitterman, Joshua Fuqua, Krystal T. Hamorsky, Kenneth E. Palmer, J. Michael Brick, Aruni Bhatnagar, Grzegorz A. Rempala
Quantifying The Relationship Between Sub-Population Wastewater Samples And Community-Wide Sars-Cov-2 Seroprevalence, Ted Smith, Rochelle H. Holm, Rachel J. Keith, Alok R. Amraotkar, Chance R. Alvarado, Krzysztof Banecki, Boseung Choi, Ian Santisteban, Adrienne M. Bushau-Sprinkle, Kathleen T. Kitterman, Joshua Fuqua, Krystal T. Hamorsky, Kenneth E. Palmer, J. Michael Brick, Aruni Bhatnagar, Grzegorz A. Rempala
Faculty Scholarship
Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis …