Duane Graves, PhD. (Tennessee), coauthored a paper entitled “COVID-19 Wastewater Epidemiology: a Model to Estimate Infected Populations” published in The Lancet Planetary Health.

Christopher McMahan (Clemson University, Clemson, SC) was the lead author and the coauthors in addition to Duane included Stella Self (University of South Carolina, SC), Lior Rennert (Clemson University, Clemson, SC), Corey Kalbaugh (Clemson University, Clemson, SC), David Kriebel (University of Massachusetts, Lowell, MA), Cameron Colby (Renewable Water Resources, Greenville, SC), Jessica Deaver (Clemson University, Clemson, SC), Sudeep Popat (Clemson University, Clemson, SC), Tanju Karanfl (Clemson University, Clemson, SC) and David Freedman (Clemson University, Clemson, SC).

Duane is the US Operations Manager at SiREM with over 30 years of experience focused on environmental biotechnology; environmental forensics; in situ groundwater, soil and sediment remediation; evaluation of airborne biological contaminants; and remediation of groundwater. His practice at SiREM specializes in (i) the development, selection, feasibility evaluation, design and deployment of remedial solutions of hazardous and mixed-waste treatability for complex process engineering and wastewater; (ii) biogeochemical evaluations related to metals attenuation, and (iii) investigation and mitigation of biological agents. Duane also provides expert opinions and testimony to support litigation regarding environmental chemistry, remediation, and microbiology associated with the transport and fate of organic, organochlorine, and inorganic chemicals and metals in sediment, soil, and groundwater; environmental forensics; liability allocation; remediation; and environmental technology issues.

The Lancet Planetary Health, is a gold open access journal that seeks to be the pre-eminent journal for enquiry into sustainable human civilizations in the Anthropocene. As such, they publish peer reviewed research and reviews as well as comment, correspondence, and reportage broadly encompassing sustainable development (the SDG’s) and global environmental change. They particularly favor work that contributes to the understanding of, and transition into, a safe and just space for humanity, respecting planetary boundaries and the social and economic foundations of a healthy life. They are interested in all important aspects of societal development and its interaction with the environment including the drivers of change, the implications of those changes for people and society, and practical policies and interventions for a healthier planetary future.

The Lancet began as an independent, international weekly general medical journal founded in 1823 by Thomas Wakley. Since its first issue (Oct 5, 1823), the journal has strived to make science widely available so that medicine can serve and transform society, and positively impact the lives of people.

Over the past two centuries, The Lancet has sought to address urgent topics in society, initiate debate, put science into context, and influence decision makers around the world.

The Lancet has evolved as a family of journals but retains at its core the belief that medicine must serve society, that knowledge must transform society, that the best science must lead to better lives.

Published Abstract

Background Wastewater-based epidemiology provides an opportunity for near real-time, cost-effective monitoring of community-level transmission of SARS-CoV-2. Detection of SARS-CoV-2 RNA in wastewater can identify the presence of COVID-19 in the community, but methods for estimating the numbers of infected individuals on the basis of wastewater RNA concentrations are inadequate.

Methods This is a wastewater-based epidemiology study using wastewater samples that were collected weekly or twice a week from three sewersheds in South Carolina, USA, between either May 27 or June 16, 2020, and Aug 25, 2020, and tested for SARS-CoV-2 RNA. We developed a susceptible-exposed-infectious-recovered (SEIR) model based on the mass rate of SARS-CoV-2 RNA in the wastewater to predict the number of infected individuals, and have also provided a simplified equation to predict this. Model predictions were compared with the number of confirmed cases identified by the Department of Health and Environmental Control, South Carolina, USA, for the same time period and geographical area.

Findings We plotted the model predictions for the relationship between mass rate of virus release and numbers of infected individuals, and we validated this prediction on the basis of estimated prevalence from individual testing. A simplified equation to estimate the number of infected individuals fell within the 95% confidence limits of the model. The rate of unreported COVID-19 cases, as estimated by the model, was approximately 11 times that of confirmed cases (ie, ratio of estimated infections for every confirmed case of 10·9, 95% CI 4·2–17·5). This rate aligned well with an independent estimate of 15 infections for every confirmed case in the US state of South Carolina.

Interpretation The SEIR model provides a robust method to estimate the total number of infected individuals in a sewershed on the basis of the mass rate of RNA copies released per day. This approach overcomes some of the limitations associated with individual testing campaigns and thereby provides an additional tool that can be used to inform policy decisions.

More Information

Learn more about the article: https://www.thelancet.com/pdfs/journals/lanplh/PIIS2542-5196(21)00230-8.pdf
Learn more about Journal: https://www.thelancet.com/lanplh/about
For consultation regarding COVID-19 Wastewater Epidemiology and testing services: dgraves@siremlab.com
Learn more about Duane: https://www.linkedin.com/in/duane-graves-a7b79b16/