Predicting COVID-19 cases in diverse population groups using SARS-CoV-2 wastewater monitoring across Oklahoma City

Kuhn, Katrin Gaardbo; Jarshaw, Jane; Jeffries, Erin; Adesigbin, Kunle; Maytubby, Phil; Dundas, Nicole; Miller, Anastasia; Rhodes, Emily R.; Stevenson, Bradley S.; Vogel, Jason R.; Reeves, Halley

doi:10.1016/j.scitotenv.2021.151431

Cited by 24 publications

(24 citation statements)

References 24 publications

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“…Testing revealed distinct patterns across different racial or ethnic groups 29 , provided an early warning of Oklahoma's transition from Delta to Omicron, and signaled to local physicians and hospitals that a surge in COVID-19 cases was imminent. As Omicron infections can be resistant to the antibody treatments used for Delta infections, the variant information from wastewater monitoring also enabled local physicians to target antibody treatments to patients on the basis of the relative abundance of Omicron in their community's wastewater.…”

Section: Methods Approach Benefitsmentioning

confidence: 99%

Wastewater surveillance of pathogens can inform public health responses

Diamond

Keshaviah

Bento

et al. 2022

Nat Med

120

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Section: Methods Approach Benefitsmentioning

confidence: 99%

Wastewater surveillance of pathogens can inform public health responses

Diamond

Keshaviah

Bento

et al. 2022

Nat Med

120

View full text Add to dashboard Cite

show abstract

“…The COVID-19 pandemic revealed the need for improved community surveillance efforts to better understand disease dynamics to guide public health policy. WBE was adopted early in the pandemic across the globe to fill this need by monitoring viral trends, predicting spikes in hospitalizations, and tracking viral variants circulating within a community 21,38,42,46,47,49,[62][63][64][65] . In this study we assessed the mass balance equation using WBE and determined that it is a useful and effective tool for generating accurate COVID-19 prevalence estimates within a community.…”

Section: Discussionmentioning

confidence: 99%

Assessment of a mass balance equation for estimating community-level prevalence of COVID-19 using wastewater-based epidemiology in a mid-sized city

Rainey

Loeb

Robinson

et al. 2022

Sci Rep

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Wastewater-based epidemiology (WBE) has emerged as a valuable epidemiologic tool to detect the presence of pathogens and track disease trends within a community. WBE overcomes some limitations of traditional clinical disease surveillance as it uses pooled samples from the entire community, irrespective of health-seeking behaviors and symptomatic status of infected individuals. WBE has the potential to estimate the number of infections within a community by using a mass balance equation, however, it has yet to be assessed for accuracy. We hypothesized that the mass balance equation-based approach using measured SARS-CoV-2 wastewater concentrations can generate accurate prevalence estimates of COVID-19 within a community. This study encompassed wastewater sampling over a 53-week period during the COVID-19 pandemic in Gainesville, Florida, to assess the ability of the mass balance equation to generate accurate COVID-19 prevalence estimates. The SARS-CoV-2 wastewater concentration showed a significant linear association (Parameter estimate = 39.43, P value < 0.0001) with clinically reported COVID-19 cases. Overall, the mass balance equation produced accurate COVID-19 prevalence estimates with a median absolute error of 1.28%, as compared to the clinical reference group. Therefore, the mass balance equation applied to WBE is an effective tool for generating accurate community-level prevalence estimates of COVID-19 to improve community surveillance.

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“…There are also assumptions to consider regarding the sampling system, the infrastructure, and the flow composition. Many recent efforts utilized grab sampling for long term WBE studies [ 9 , 18 , 22 , 38 ]. From real-world analysis, it takes approximately two minutes for a common autosampler to take a 100 mL sample.…”

Section: Methodsmentioning

confidence: 99%

Optimization of sewage sampling for wastewater-based epidemiology through stochastic modeling

et al. 2023

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The proliferation of the SARS-CoV-2 global pandemic has brought to attention the need for epidemiological tools that can detect diseases in specific geographical areas through non-contact means. Such methods may protect those potentially infected by facilitating early quarantine policies to prevent the spread of the disease. Sampling of municipal wastewater has been studied as a plausible solution to detect pathogen spread, even from asymptomatic patients. However, many challenges exist in wastewater-based epidemiology such as identifying a representative sample for a population, determining the appropriate sample size, and establishing the right time and place for samples. In this work, a new approach to address these questions is assessed using stochastic modeling to represent wastewater sampling given a particular community of interest. Using estimates for various process parameters, inferences on the population infected are generated with Monte Carlo simulation output. A case study at the University of Oklahoma is examined to calibrate and evaluate the model output. Finally, extensions are provided for more efficient wastewater sampling campaigns in the future. This research provides greater insight into the effects of viral load, the percentage of the population infected, and sampling time on mean SARS-CoV-2 concentration through simulation. In doing so, an earlier warning of infection for a given population may be obtained and aid in reducing the spread of viruses.

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Predicting COVID-19 cases in diverse population groups using SARS-CoV-2 wastewater monitoring across Oklahoma City

Cited by 24 publications

References 24 publications

Wastewater surveillance of pathogens can inform public health responses

Wastewater surveillance of pathogens can inform public health responses

Assessment of a mass balance equation for estimating community-level prevalence of COVID-19 using wastewater-based epidemiology in a mid-sized city

Optimization of sewage sampling for wastewater-based epidemiology through stochastic modeling

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