Wastewater-based epidemiology for tracking COVID-19 trend and variants of concern in Ohio, United States

Ai, Yuehan; Davis, Angela; Jones, Daniel M.; Lemeshow, Stanley; Tu, Huolin; He, Fan; Ru, Peng; Pan, Xiaokang; Bohrerova, Zazuna; Lee, Ji-Young

doi:10.1101/2021.06.08.21258421

Cited by 16 publications

(21 citation statements)

References 62 publications

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“…Better methods of normalisation using biochemical markers would be valuable. Although promising, crAssphage has not been a clear successsee Ai et al (2021) and Greenwald et al (2021). The USA data discussed here used pepper mild mottle virus for normalisation, but the results were not better than the unnormalised Scottish data.…”

Section: Discussionmentioning

confidence: 75%

“…Many recent papers (Ai et al 2021;Feng et al 2021;Greenwald et al 2021;Melvin et al 2021;Zulli et al 2021;Wurtzer et al 2022) show a correlation between the daily or weekly amount of COVID-19 RNA in WW and the numbers of COVID-19 infections reported to the PH authorities, but some do not go beyond showing a correlation. Certainly, the presence of a correlation indicates the potential for a prediction but substantial additional work is necessary before an operational model that provides numerical predictions can be produced.…”

Section: Introductionmentioning

confidence: 99%

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Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease

Faraway

Boxall-Clasby

Feil

et al. 2022

Journal of Water and Health

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Researchers around the world have demonstrated correlations between measurements of SARS-CoV-2 RNA in wastewater (WW) and case rates of COVID-19 derived from direct testing of individuals. This has raised concerns that wastewater-based epidemiology (WBE) methods might be used to quantify the spread of this and other diseases, perhaps faster than direct testing, and with less expense and intrusion. We illustrate, using data from Scotland and the USA, the issues regarding the construction of effective predictive models for disease case rates. We discuss the effects of variation in, and the problem of aligning, public health (PH) reporting and WW measurements. We investigate time-varying effects in PH-reported case rates and their relationship to WW measurements. We show the lack of proportionality of WW measurements to case rates with associated spatial heterogeneity. We illustrate how the precision of predictions is affected by the level of aggregation chosen. We determine whether PH or WW measurements are the leading indicators of disease and how they may be used in conjunction to produce predictive models. The prospects of using WW-based predictive models with or without ongoing PH data are discussed.

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Section: Discussionmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease

Faraway

Boxall-Clasby

Feil

et al. 2022

Journal of Water and Health

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“…Viable SARS-CoV-2 is shed in human stool. SARS-CoV-2 RNA and has also been detected in wastewater 31,32 and urban runoff 33 , although the infectivity of SARS-CoV-2 from these sources is undetermined. The recent detection of genetically distinct SARS-CoV-2 virus fragments in New York City wastewater introduces an intriguing hypothesis that SARS-CoV-2 could be transmitting cryptically in rodents 34 .…”

Section: Discussionmentioning

confidence: 99%

SARS-CoV-2 infection in free-ranging white-tailed deer

Hale

Dennis

McBride

et al. 2021

Nature

328

358

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Humans have infected a wide range of animals with SARS-CoV-2 1-5 , but the establishment of a new natural animal reservoir has not been observed. Here we document that free-ranging white-tailed deer (Odocoileus virginianus) are highly susceptible to infection with SARS-CoV-2, are exposed to multiple SARS-CoV-2 variants from humans and are capable of sustaining transmission in nature. Using real-time PCR with reverse transcription, we detected SARS-CoV-2 in more than one-third (129 out of 360, 35.8%) of nasal swabs obtained from O. virginianus in northeast Ohio in the USA during January to March 2021. Deer in six locations were infected with three SARS-CoV-2 lineages (B. 1.2, B.1.582 and B.1.596). The B.1.2 viruses, dominant in humans in Ohio at the time, infected deer in four locations. We detected probable deer-to-deer transmission of B.1.2, B.1.582 and B.1.596 viruses, enabling the virus to acquire amino acid substitutions in the spike protein (including the receptor-binding domain) and ORF1 that are observed infrequently in humans. No spillback to humans was observed, but these findings demonstrate that SARS-CoV-2 viruses have been transmitted in wildlife in the USA, potentially opening new pathways for evolution. There is an urgent need to establish comprehensive 'One Health' programmes to monitor the environment, deer and other wildlife hosts globally.As of 9 November 2021, SARS-CoV-2, the virus responsible for coronavirus disease 2019 (COVID-19), has caused more than 5 million deaths globally 6 . The zoonotic origins of SARS-CoV-2 are not fully resolved 7 , exposing large gaps in our knowledge of susceptible host species and potential new reservoirs. Natural infections of SARS-CoV-2 linked to human exposure have been reported in domestic animals such as cats, dogs and ferrets, and in wildlife under human care, including several species of big cats, Asian small-clawed otters, western lowland gorillas and mink 1 . Detection of SARS-CoV-2 by PCR in free-ranging wildlife has been limited to small numbers of mink in Spain and in Utah in the USA, which were thought to have escaped from nearby farms 8,9 . An in silico study modelling SARS-CoV-2 binding sites on the angiotensin-converting enzyme 2 (ACE2) receptor across host species predicted that cetaceans, rodents, primates and several species of deer are at high risk of infection 10 . Experimental infections have identified additional animal species susceptible to SARS-CoV-2, including hamsters, North American raccoons, striped skunks, white-tailed deer, raccoon dogs, fruit bats, deer mice, domestic European rabbits, bushy-tailed woodrats, tree shrews and multiple non-human primate species [11][12][13][14][15][16][17][18][19][20] . Moreover, several species are capable of intraspecies SARS-CoV-2 transmission [13][14][15]17,[21][22][23] , including cats, ferrets, fruit bats, hamsters, raccoon dogs, deer mice and white-tailed deer. Vertical transmission has also been documented in experimentally infected white-tailed deer 23 . In July 2021, antibodies for SARS-CoV...

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“…Ai et al, 2021 [7] from the state of Ohio in the USA investigated nine WWTPs in central Ohio and considered normalization methods with PMMoV and Cross-Assembly phage (crAssphage) and also considered if wastewater surveillance can serve as a sentinel piece for detecting SARS-CoV-2 variants of concern within a community. SARS-CoV-2 RNA concentrations in wastewater and COVID-19 cases were found to correlate well when they were imputed using a 5-day moving day average.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Trend Analysis of SARS-CoV-2 RNA in Municipal Wastewater Exemplified with Sewershed-Specific COVID-19 Clinical Case Counts

Pileggi

Shurgold

Sun

et al. 2022

Preprint

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We present and demonstrate a quantitative statistical linear trend analysis (QTA) approach to analyze and interpret SARS-CoV-2 RNA wastewater surveillance results concurrently with clinical case data. This demonstration is based on the work completed under the Ontario (Canada) Wastewater Surveillance Initiative (WSI) by two laboratories in four large sewersheds within the Toronto Public Health (TPH) jurisdiction. The sewersheds were sampled over a 9-month period and data were uploaded to the Ontario Wastewater Surveillance Data and Visualization Hub (Ontario Dashboard) along with clinical case counts, both on a sewershed-specific basis. The data from the last 5-months, representing a range of high and low cases, was used for this demonstration. The QTA was conducted on a sewershed specific approach using the recommendations for public health interpretation and use of wastewater surveillance data by the United States Centers for Disease Control and Prevention (US CDC). The interpretation of the QTA results was based on the integration of both clinical and wastewater virus signals using an integration matrix in an interim draft guide by the Public Health Agency of Canada (PHAC). The key steps in the QTA consisted of (i) the calculation of Pepper Mild Mottle Virus (PMMoV), flow and flow-PMMoV-normalized virus loads; (ii) computation of the linear trends including interval estimation to identify the key inflection points using a segmented linear regression method and (iii) integrated interpretations based on consideration of both the cases and wastewater signals, as well as end user actionability. This approach is considered a complementary tool to commonly used qualitative analyses of SARS-CoV-2 RNA in wastewater and is intended to directly support public health decisions using a systematic quantitative approach.

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Wastewater-based epidemiology for tracking COVID-19 trend and variants of concern in Ohio, United States

Cited by 16 publications

References 62 publications

Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease

Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease

SARS-CoV-2 infection in free-ranging white-tailed deer

Quantitative Trend Analysis of SARS-CoV-2 RNA in Municipal Wastewater Exemplified with Sewershed-Specific COVID-19 Clinical Case Counts

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