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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.
Online Dashboards For Sars-Cov-2 Wastewater Data Need Standard Best Practices: An Environmental Health Communication Agenda, Colleen C. Naughton, Rochelle H. Holm, Nancy J. Lin, Brooklyn P. James, Ted Smith
Online Dashboards For Sars-Cov-2 Wastewater Data Need Standard Best Practices: An Environmental Health Communication Agenda, Colleen C. Naughton, Rochelle H. Holm, Nancy J. Lin, Brooklyn P. James, Ted Smith
Faculty Scholarship
The COVID-19 pandemic has highlighted the benefits of wastewater surveillance to supplement clinical data. Numerous online information dashboards have been rapidly, and typically independently, developed to communicate environmental surveillance data to public health officials and the public. In this study, we review dashboards presenting SARS-CoV-2 wastewater data and propose a path toward harmonization and improved risk communication. A list of 127 dashboards representing 27 countries was compiled. The variability was high and encompassed aspects including the graphics used for data presentation (e.g., line/bar graphs, maps, and tables), log versus linear scale, and 96 separate ways of labeling SARS-CoV-2 wastewater concentrations. …
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 …
Advancing The Use Of Fecal Sludge For Timelier And Better-Quality Epidemiological Data In Low- And Middle-Income Countries For Pandemic Prevention, Petros Chigwechokha, Renée Street, Rochelle H. Holm
Advancing The Use Of Fecal Sludge For Timelier And Better-Quality Epidemiological Data In Low- And Middle-Income Countries For Pandemic Prevention, Petros Chigwechokha, Renée Street, Rochelle H. Holm
Faculty Scholarship
No abstract provided.
Wastewater-Informed Public Health Intervention Playbook
Wastewater-Informed Public Health Intervention Playbook
Sustain Magazine
As the SARS-CoV-2 pandemic quickly spread from country to country and continent to continent in 2020, governments and scientists needed a way to track COVID-19 through populations in order to position public health interventions in the most impactful locations. Having a decision-based risk framework may help to guide policy creation that could minimize or prevent possible outbreaks and surges of infection within communities. The University of Louisville in partnership with Louisville’s Department of Public Health and Wellness tested this strategy in 2021 and 2022. This Wastewater-Informed Public Health Intervention Playbook describes the decisions and actions of that academic and public …
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 …
Predictive Modeling Of Clinical Outcomes For Hospitalized Covid-19 Patients Utilizing Cytof And Clinical Data., Onajia Stubblefield
Predictive Modeling Of Clinical Outcomes For Hospitalized Covid-19 Patients Utilizing Cytof And Clinical Data., Onajia Stubblefield
Electronic Theses and Dissertations
In December 2019, an outbreak of a novel coronavirus initiated a global pandemic. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that causes the disease coronavirus disease 2019 (COVID-19). Symptoms of infection with COVID-19 vary widely between individuals. While some infected individuals are asymptomatic, others need more extensive care and require hospitalization. Indeed, the COVID-19 pandemic was characterized by a shortage of hospital beds which presented additional complications in providing adequate care for patients. In this study, we used a combination of T cell population data collected from mass cytometry analysis and clinical markers to form a predictive …