Lead time of early warning by wastewater surveillance for COVID-19: Geographical variations and impacting factors

Kumar, Manish; Jiang, Guangming; Thakur, Alok; Chatterjee, Shreya; Bhattacharya, Tanushree; Mohapatra, Sanjeeb; Chaminda, Tushara; Tyagi, Vinay Kumar; Vithanage, Meththika; Bhattacharya, Prosun; Nghiem, Long D.; Sarkar, Dibyendu; Sonne, Christian; Mahlknecht, Jürgen

doi:10.1016/j.cej.2022.135936

Cited by 63 publications

(41 citation statements)

References 63 publications

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“…Wastewater SARS-CoV-2 load was then normalized to population (copies/week/10,000 people) by dividing the SARS-CoV-2 load per week by each of the three estimated population metrics: (5) in which [N1.N2]SARS (copies/L), the SARS-CoV-2 concentration in the wastewater sewershed, was determined by RT-qPCR using equation ( 1). The COVID-19 incidence rate was defined as:…”

Section: Population Normalization Of Wastewater Sars-cov-2 Load and C...mentioning

confidence: 99%

“…3,4 The WBE can also provide a useful early warning of the emergence or reemergence of COVID-19 in a community, and afford timely insights for public health interventions, with previous studies showing that SARS-CoV-2 could be detected in wastewater up to two weeks before the cases were reported. 5 Furthermore, wastewater surveillance can be implemented in most communities since municipal wastewater collection systems serve nearly 80 percent of U.S. households. 6 The utility of WBE for cost-effective surveillance of SARS-CoV-2 levels in communities was recognized early in the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

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Population Normalization in SARS-CoV-2 Wastewater-Based Epidemiology: Implications from Statewide Wastewater Monitoring in Missouri

Bayati

Hsu

et al. 2022

Preprint

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The primary objective of this study was to identify a universal wastewater biomarker for population normalization for SARS-CoV-2 wastewater-based epidemiology (WBE). A total of 2,624 wastewater samples (41 weeks) were collected weekly during May 2021- April 2022 from 64 wastewater facilities across Missouri, U.S. Three wastewater biomarkers, caffeine and its metabolite, paraxanthine, and pepper mild mottle virus (PMMoV), were compared for the population normalization effectiveness for wastewater SARS-CoV-2 surveillance. Paraxanthine had the lowest temporal variation and strongest relationship between population compared to caffeine and PMMoV. This result was confirmed by data from ten different Wisconsin WWTPs with gradients in population sizes, indicating paraxanthine is a promising biomarker of the real-time population across a large geographical region. The estimated real-time population was directly compared against the population patterns with human movement mobility data. Of the three biomarkers, population normalization by paraxanthine significantly strengthened the relationship between wastewater SARS-CoV-2 viral load and COVID-19 incidence rate the most (40 out of 61 sewersheds). Caffeine could be a promising population biomarker for regions where no significant exogenous caffeine sources (e.g., discharges from food industries) exist. In contrast, PMMoV showed the highest variability over time, and therefore reduced the strength of the relationship between sewage SARS-CoV-2 viral load and the COVID-19 incidence rate, as compared to wastewater data without population normalization and the population normalized by either recent Census population or the population estimated based on the number of residential connections and average household size for that municipality from the Census. Overall, the findings of this long-term surveillance study concluded that the paraxanthine has the best performance as a biomarker for population normalization for SARS-CoV-2 wastewater-based epidemiology.

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Section: Population Normalization Of Wastewater Sars-cov-2 Load and C...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Population Normalization in SARS-CoV-2 Wastewater-Based Epidemiology: Implications from Statewide Wastewater Monitoring in Missouri

Bayati

Hsu

et al. 2022

Preprint

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“…More recent research has shown that using the specimen collection date rather than reporting date for case data shortens the wastewater lead time (16), and that when clinical tests are widely available and widely used, wastewater and clinical data are well-aligned, with no lead-time advantage of one over the other (6). The variability in reported lead times stems from a combination of biological early detection in wastewater (“latent” factors) and reporting lags in the clinical tests (“pragmatic” factors) (17, 18). Further, site to site differences in lead times can arise from differences in laboratory analytical methods, sewer infrastructure (including sewage travel time), and testing behaviors in the population.…”

Section: Introductionmentioning

confidence: 99%

Separating Signal from Noise in Wastewater Data: An Algorithm to Identify Community-Level COVID-19 Surges

Keshaviah

Huff

et al. 2022

Preprint

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Wastewater monitoring has shown promise in providing an early warning for new COVID-19 outbreaks, but to date, no approach has been validated to reliably distinguish signal from noise in wastewater data and thereby alert officials to when the data show a need for heightened public health response. We analyzed 62 weeks of data from 19 sites participating in the North Carolina Wastewater Monitoring Network to characterize wastewater metrics before and around the Delta and Omicron surges. We found that, on average, wastewater data identified new outbreaks four to five days before case data (reported based on the earlier of the symptom start date or test collection date). At most sites, correlations between wastewater and case data were similar regardless of how wastewater concentrations were normalized, and correlations were slightly stronger with county-level cases than sewershed-level cases, suggesting that officials may not need to geospatially align case data with sewershed boundaries to gain insights into disease transmission. Wastewater trend lines showed clear differences in the Delta versus Omicron surge trajectories, but no single wastewater metric (detectability, percent change, or flow-population normalized viral concentrations) adequately indicated when these surges started. After iteratively examining different combinations of these three metrics, we developed a simple algorithm that identifies unprecedented signals in the wastewater to help clarify changes in communities' burden. Our novel algorithm accurately identified the start of both the Delta and Omicron surges in 84% of sites, potentially providing public health officials with an automated way to flag community-level COVID-19 surges.

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“…Thus, when the source of SARS coronavirus-2 (SASR-CoV-2) is unclear, the rapid transmission of this virus could be explained with the help of several environmental factors which govern transmission and establishment of the infection. Moreover, the severity of an outbreak depends not only on the lethality of the virus but also upon its mode of transmission and the availability of cure/vaccine [ 8 ]. Vaccination and disease management has been able to control diseases like polio and HIV-acquired immunodeficiency syndrome (AIDS), respectively, but the novel SARS-CoV-2 is continued to be a global pandemic even when mass vaccination is at its peak in several parts of the world.…”

Section: Introductionmentioning

confidence: 99%

The COVID-19 pandemic: Virus transmission and risk assessment

Menon

Mohapatra²

2022

Current Opinion in Environmental Science & Health

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Lead time of early warning by wastewater surveillance for COVID-19: Geographical variations and impacting factors

Cited by 63 publications

References 63 publications

Population Normalization in SARS-CoV-2 Wastewater-Based Epidemiology: Implications from Statewide Wastewater Monitoring in Missouri

Population Normalization in SARS-CoV-2 Wastewater-Based Epidemiology: Implications from Statewide Wastewater Monitoring in Missouri

Separating Signal from Noise in Wastewater Data: An Algorithm to Identify Community-Level COVID-19 Surges

The COVID-19 pandemic: Virus transmission and risk assessment

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