Wastewater-based Surveillance of SARS-CoV-2 for Monitoring COVID-19 in Bexar County, Texas

Date
2022
Authors
Al-Duroobi, Haya Mohanad Qutaiba
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Abstract

With the emergence of the new coronavirus disease 2019 (COVID-19), hospitals, healthcare professionals, and community leaders have been exploring monitoring techniques to support their response to this respiratory illness worldwide. The spread of COVID-19 from person-to-person is mainly caused by respiratory droplets traveling through close contact. However, individuals infected with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) shed the virus and its viral genetic material in their fecal samples. The genetic material of this enveloped RNA virus can travel in sewage pipelines and reach to wastewater treatment plants where wastewater can be sampled and tested for genetic signals. This practice is known as Wastewater-based Epidemiology (WBE).In this dissertation, we explored the potential of WBE in the monitoring of SARS-CoV-2 prevalence in Bexar County, Texas. We developed robust molecular techniques to extract and quantify viral RNA related to SARS-CoV-2 in local sewage samples. We determined SARS-CoV-2 genetic material presence in untreated sewage within selected wastewater treatment plants in Bexar County, Texas for large scale monitoring and in schools' sewage systems for small scale monitoring. In addition, we were able to correlate SARS-CoV-2 RNA concentration in wastewater with trends of clinically reported COVID-19 cases and estimating monitoring leading and lagging times. We also conducted a treatment efficiency study for the removal of SARS-CoV-2 RNA along Wastewater Treatment Plant (WWTP) process stages. Subsequently, we were able to communicate wastewater surveillance results with the public health community, City of San Antonio, wastewater utility workers, and the public. The initial pilot study generated a preliminary assessment of the levels of SARS-CoV-2 RNA in wastewater at the Salitrillo Wastewater Treatment Plant in Texas during the initial peak of COVID-19 outbreak in summer 2020. We compared the viral RNA concentrations in wastewater with reported testing and infectivity data of patients from clinical testing to better evaluate the efficacy of using the wastewater data for tracking community infection dynamics. Since the testing period included the initial peak, we were able to ascertain the increase in COVID-19 cases as suggested by public testing data through the results of wastewater-based testing. Our preliminary results showed that wastewater surveillance is an effective tool to determine trends in infectious disease prevalence and provide complimentary information to clinical testing. In order to optimize the methodology, we conducted a second study to systematically evaluate the effect of using different virus concentration methods and recovery and normalization approaches. We measured SARS-CoV-2 RNA concentrations at two different WWTPs in Bexar County and evaluated three sample concentration methods: acidification, addition of MgCl2 or without any pre-treatment. Eventually, direct adsorption-extraction (AE) method without any pre-treatment showed the highest virus recovery rate which allowed for utilization of this method in subsequent studies and maintaining the workflow for wastewater surveillance. The fourth and fifth chapters of this dissertation discuss wastewater-based surveillance of schools/campuses. Firstly, methodological considerations such as site selection, sample collection and processing, SARS-CoV-2 quantification, and data interpretation for monitoring school/campus wastewater were reviewed. Subsequently, a case study was presented in which we implemented a selected methodology to conduct a surveillance program of SARS-CoV-2 presence in sewage within selected Northside Independent School District (NISD) schools in San Antonio. The final study involved a long-term monitoring of the largest wastewater treatment plant (WWTP) in San Antonio to investigate the persistence of SARS-CoV-2 RNA in untreated wastewater influent and throughout the stages of the activated sludge treatment process. The results showed significant removal of viral loads by primary and secondary treatment. Additionally, tertiary treatment was necessary to ensure complete removal. Enhanced wastewater surveillance strategy was achieved by sampling twice weekly from the plant's inlet. This allowed for better correlations with weekly COVID-19 infectivity rates and emphasized the potential of WBS as an early-warning tool for city-wide disease monitoring.

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Civil and Environmental Engineering