Wastewater-Based Epidemiological Modeling for Continuous Surveillance of COVID-19 Outbreak

Fazli, Mehrdad; Sklar, Samuel; Porter, Michael D.; French, Brent A.; Shakeri, Heman

doi:10.1109/bigdata52589.2021.9671543

Cited by 6 publications

(6 citation statements)

References 25 publications

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“…SEIR epidemiological models offer a framework for epidemiologists to analyze the dynamics of outbreaks using wastewater data (7,8,(44)(45)(46)(47)(48). Specifically, in our study, we demonstrate that our SEIR model can provide reliable forecasts of when case numbers are trending upwards in rural communities.…”

Section: While Epidemiologists Can Examine Wastewater Data Side-by-si...mentioning

confidence: 62%

Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

Meadows,

Coats,

Narum

et al. 2024

Preprint

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Wastewater can play a vital role in infectious disease surveillance, especially in underserved communities where it can reduce the equity gap to larger municipalities. However, using wastewater surveillance in a predictive manner remains a challenge. We tested if detecting SARS-CoV-2 in wastewater can predict outbreaks in rural communities. Under the CDC National Wastewater Surveillance program, we monitored several rural communities in Idaho (USA). While high daily variations in wastewater viral load made real-time interpretation difficult, a SEIR model could factor out the data noise and forecast the start of the Omicron outbreak in five of the six cities that were sampled soon after SARS-CoV-2 quantities increased in wastewater. For one city, the model could predict an outbreak 11 days before reported clinical cases began to increase. An epidemiological modeling approach can transform how epidemiologists use wastewater data to provide public health guidance on infectious diseases in rural communities.

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Section: While Epidemiologists Can Examine Wastewater Data Side-by-si...mentioning

confidence: 62%

Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

Meadows,

Coats,

Narum

et al. 2024

Preprint

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“…e authors stated that their approach integrates noisy wastewater data and daily case numbers into a dynamic epidemiological model and enhances the surveillance of wastewater for early epidemic prediction. In [67], a stochastic wastewater-based SEIR model was used to show the importance of viral load in wastewater for the early detection and prediction of an outbreak in a community. e SEIR model based on viral load data could reliably predict the number of infections in the future.…”

Section: Seir Model Linked To Wastewatermentioning

confidence: 99%

The Mathematical Modeling Approach for the Wastewater Treatment Process in Saudi Arabia during COVID‐19 Pandemic

Ahmadini

Msmali

Meetei

et al. 2022

Discrete Dynamics in Nature and Society

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The novel coronavirus disease (COVID-19) pandemic has had devastating effects on healthcare systems and the global economy. Moreover, coronavirus has been found in human feces, sewage, and in wastewater treatment plants. In this paper, we highlight the transmission behavior, occurrence, and persistence of the virus in sewage and wastewater treatment plants. Our approach follows the process of identifying a coronavirus hotspot through existing wastewater plants in major cities of Saudi Arabia. The mathematical distributions, including the log-normal distribution, Gaussian model, and susceptible-exposed-infected-recovered (SEIR) model, are adopted to predict the coronavirus load in wastewater plants. We highlight not only the potential virus removal techniques from wastewater treatment plants but also methods of tracing SARS-CoV-2 in humans through wastewater treatment plants. The results indicate that our modeling approach may facilitate the analysis of SARS-CoV-2 loads in wastewater for early prediction of the epidemic outbreak and provide significant implications to the public health system.

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“…Wastewater based epidemiology provides certain advantages over case-based surveillance [2]. These include the ability to monitor large numbers of persons by testing single samples and the potential to estimate the burden of disease in that community from quantitative data [3], [4,5]. WBE eliminates inherent biases in disease burden estimation arising through differential health seeking by infected persons, variable access to clinical laboratory testing and variation in health care practitioner's propensity to test [1].…”

Section: Introductionmentioning

confidence: 99%

“…WBE eliminates inherent biases in disease burden estimation arising through differential health seeking by infected persons, variable access to clinical laboratory testing and variation in health care practitioner's propensity to test [1]. WBE may provide early warning of increases in case-incidence [6,7] enabling prompt public health action to be taken to prevent outbreaks and their consequences [5]. Furthermore, WBE is inherently cost-saving relative to patient-based surveillance systems.…”

Section: Introductionmentioning

confidence: 99%

The role of wastewater-based epidemiology for SARS-CoV-2 in developing countries: cumulative evidence from South Africa supports sentinel site surveillance to guide public health decision-making

Iwu

Ndlovu

Rachida

et al. 2023

Preprint

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Background: The World Health Organisation recommends wastewater based epidemiology (WBE) for SARS-CoV-2 as a complementary tool for monitoring population-level epidemiological features of the COVID-19 pandemic. Yet, uptake of WBE in low-to-middle income countries (LMIC) is low. We report on findings from SARS-CoV-2 WBE surveillance network in South Africa, and make recommendations regarding implementation of WBE in LMICs Methods: Seven laboratories using different test methodology, quantified influent wastewater collected from 87 wastewater treatment plants (WWTPs) located in all nine South African provinces for SARS-CoV-2 from 01 June 2021 to 31 May 2022 inclusive, during the 3rd and 4th waves of COVID-19. Regression analysis with district laboratory confirmed SARS-CoV-2 case loads, controlling for district, size of plant and testing frequency was determined. The sensitivity and specificity of rules based on WBE data to predict an epidemic wave based on SARS-CoV-2 wastewater levels were determined. Results: Among 2158 wastewater samples, 543/648 (85%) samples taken during a wave tested positive for SARS-CoV-2 compared with 842 positive tests from 1512 (55%) samples taken during the interwave period. Overall, the regression-co-efficient was 0,66 (95% confidence interval=0,6-0,72, R squared=0.59), but ranged from 0.14 to 0.87 by testing laboratory. Early warning of the 4th wave of SARS-CoV-2 in Gauteng Province in November-December 2021 was demonstrated. A 50% increase in log-copies SARS-CoV-2 compared with a rolling mean over the previous 5 weeks was the most sensitive predictive rule (58%) to predict a new wave. Conclusion: Variation in the strength of correlation across testing laboratories, and redundancy of findings across co-located testing plants, suggests that test methodology should be standardised and that surveillance networks may utilise a sentinel site model without compromising the value of WBE findings for public health decision-making. Further research is needed to identify optimal test frequency and the need for normalisation to population size, so as to identify predictive and interpretive rules to support early warning and public health action. Our findings support investment in WBE for SARS-CoV-2 surveillance in low and middle-income countries.

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Wastewater-Based Epidemiological Modeling for Continuous Surveillance of COVID-19 Outbreak

Cited by 6 publications

References 25 publications

Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities

The Mathematical Modeling Approach for the Wastewater Treatment Process in Saudi Arabia during COVID‐19 Pandemic

The role of wastewater-based epidemiology for SARS-CoV-2 in developing countries: cumulative evidence from South Africa supports sentinel site surveillance to guide public health decision-making

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