Early Warnings of COVID-19 Second Wave in Detroit

Miyani, Brijen; Zhao, Liang; Spooner, Maddie; Buch, Sejal; Gentry, Zachary; Mehrotra, Anna S.; Norton, John; Xagoraraki, Irene

doi:10.1061/(asce)ee.1943-7870.0001907

Cited by 16 publications

(13 citation statements)

References 19 publications

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“…As SARS-CoV-2 RNA is shed in the feces of symptomatic and asymptomatic individuals, it has been possible to measure it in order to understand the wastewater-based epidemiology (WBE) of COVID-19 ( Amirian, 2020 ; Cheung et al, 2020 ; Jiehao et al, 2020 ; Tang et al, 2020 ; Wu et al, 2020b ; Xagoraraki and O'Brien, 2020 ; Zhang et al, 2020 ). Teams from across the world have reported the presence of SARS-CoV-2 RNA in municipal wastewaters ( Ahmed et al, 2020 ; Fitzgerald et al, 2021 ; Giraud-Billoud et al, 2021 ; Haramoto et al, 2020 ; Kumar et al, 2020 ; La Rosa et al, 2020 ; Medema et al, 2020 ; Miyani et al, 2021 ; Nemudryi et al, 2020 ; Peccia et al, 2020 ; Randazzo et al, 2020 ; Rusiñol et al, 2021 ; Sherchan et al, 2021 ; Westhaus et al, 2021 ; Wu et al, 2021 ; Wu et al, 2020a ; Wurtzer et al, 2020 ). These studies have shown that WBE is suitable for spatial and temporal monitoring of SARS-CoV-2 across diverse communities ( Kitajima et al, 2020 ), serves as a leading indicator correlating strongly with future diagnosed cases, hospitalizations and deaths ( Miyani et al, 2021 ; Zhu et al, 2021 ), predicts the burden of undiagnosed infections at the population level ( Bivins et al, 2020 ; Daughton, 2020 ; Nemudryi et al, 2020 ; Wannigama et al, 2021 ) and can play a key role in optimizing public health decision-making ( Daughton, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population

et al. 2022

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Section: Introductionmentioning

confidence: 99%

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population

et al. 2022

View full text Add to dashboard Cite

“…In the light of this, wastewater-based surveillance (WBS) has been described as a potential tool that could be adapted for this purpose. Indeed, WBS has proven transformative in understanding the COVID-19 pandemic (Acosta et al 2021; Acosta et al 2022; Acosta et al 2023; Peccia et al 2020; Randazzo et al 2020; Miyani et al 2021; Zhu et al 2021; Xiao et al 2021; Zhan et al 2022; Galani et al 2022; Hegazy et al 2022; Hubert et al 2022). WBS’s major advantage is its ability to objectively monitor entire populations passively and comprehensively, making it accurate, inclusive and cost-effective (Choi 2020; Sims and Kasprzyk-Hordern 2020).…”

Section: Introductionmentioning

confidence: 99%

Metagenomic analysis after selective culture enrichment of wastewater demonstrates increased burden of antibiotic resistant genes in hospitals relative to the community

Acosta

Lee

Bautista

et al. 2023

Preprint

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Antimicrobial resistance (AMR) is an ever-increasing threat to global health. Wastewater-based surveillance is an emerging methodology that objectively enables an inclusive and comprehensive assessment of population AMR in an observed sewershed. Here we compared the resistome of two tertiary-care hospitals with two separate neighborhoods, using complimentary targeted qPCR and metagenomics of wastewater before and after selective culture enrichment for clinically important Gram negatives. In total 26 ARG-type (1225 ARG-subtypes) were found across all samples, in which beta-lactam ARG was the richest (the number of different ARG-subtypes found) followed by multidrug, fluoroquinolone, macrolide-lincosamide-streptogramin (MLS) and aminoglycoside. The composition of ARGs in wastewater differed between raw wastewater pellets and culture-enriched wastewater samples and the resistomes clustered based on the type of location (Hospitals vs neighborhoods). Hospital wastewater was found to have higher diversity and greater abundance of ARGs compared to neighborhood wastewater when the composition profiles of ARGs in both raw and culture-enriched wastewater pellets. Clinically relevant ARG (i.e., VIM, NDM metallo-beta-lactamases) were detected in culture enrichment samples that were not identified in raw samples, despite a lower targeted sequencing depth. Wastewater-based surveillance is an effective, and potentially extremely important and powerful tool that could be developed to augment hospital-based infection control and antimicrobial stewardship programs, creating a safer space for those receiving care.

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“…Researchers around the world have demonstrated WBS can provide a leading indicator of many clinically relevant parameters, including; community diagnosed COVID-19 cases, COVID-19-related hospitalizations and ICU admissions, and even deaths (Acosta et al 2021; Acosta et al 2022; Peccia et al 2020; Randazzo et al 2020; Miyani et al 2021; Zhu et al 2021; Xiao et al 2021; Zhan et al 2022; Galani et al 2022; Hegazy et al 2022). Recognizing the tremendous potential of WBS to help shape and inform public health policy and actions including healthcare resource allocation, WBS programs have developed all over the world (Naughton et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism

Acosta¹,

Dai

Bautista

et al. 2023

Preprint

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Wastewater-based surveillance (WBS) is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19 impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with local workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.3 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5% (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4,524 unrelated absences COVID-19 cases were recorded. Employee absences significantly increased as wastewater signal increased through pandemic waves. Strong correlations between COVID-19-confirmed absences and wastewater SARS-CoV-2 signals (N1 gene: r=0.824, p<0.0001 and N2 gene: r=0.826, p<0.0001) were observed. Linear regression with adjusted R2-value demonstrated a robust association (adjusted R2=0.783), when adjusted by 7 days, indicating wastewater provides a one-week leading signal. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P<0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

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Early Warnings of COVID-19 Second Wave in Detroit

Cited by 16 publications

References 19 publications

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population

Metagenomic analysis after selective culture enrichment of wastewater demonstrates increased burden of antibiotic resistant genes in hospitals relative to the community

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism

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