| NSF Org: |
CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems |
| Recipient: |
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| Initial Amendment Date: | April 27, 2020 |
| Latest Amendment Date: | April 27, 2020 |
| Award Number: | 2026599 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Mamadou Diallo
CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems ENG Directorate for Engineering |
| Start Date: | May 1, 2020 |
| End Date: | December 31, 2022 (Estimated) |
| Total Intended Award Amount: | $198,388.00 |
| Total Awarded Amount to Date: | $198,388.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
615 W 131ST ST NEW YORK NY US 10027-7922 (212)854-6851 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
500 West 120th Street New York NY US 10027-6902 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | COVID-19 Research |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The current global COVID-19 pandemic is caused by SARS-CoV2, a coronavirus. While human coronaviruses are highly infective and responsible for the majority of respiratory tract infections, the novel SARS-CoV2 is particularly virulent. These viruses can survive under a variety of conditions and environments including within human waste streams. Wastewater treatment systems are widely used as a final barrier to protect water bodies from the impacts of human pollution. However, the fate of coronaviruses during the wastewater treatment process is poorly understood. The goal of this RAPID project is to develop a science-based understanding of the fate of SARS-CoV2 and other viruses during the treatment of human waste in wastewater treatment plants. Results of this research will inform the scientific community and relevant stakeholders of the impact of waste treatment on SARS-CoV2, as well as other potential threats and agents. If successful, this approach will provide urgently needed information to help respond to the current global pandemic and form the basis of a global database for future pandemic events.
This proposal addresses a current pressing need to understand the abundance, activity and transmission of SARS-CoV2 and other viral determinants in engineered wastewater treatment systems. The emergence of increasingly frequent and especially potent microbial pathogens like SARS-CoV2 presents an urgent challenge to public health. The extremely rapid global spread of SARS-CoV-2 infections as well as an asymptomatic latency period in subjects suggests significant gaps in our understanding of potential reservoirs and transmission pathways of SARS-CoV2. One such reservoir and potential transmission pathway is the engineered wastewater cycle. Wastewater treatment serves to reduce pollution and minimize exposure of human populations to microbiological threats. The goal of this project is to determine if wastewater treatment systems serve as a reservoir in the current COVID-19 pandemic. This will be achieved by conducting a worldwide environmental surveillance study using massively parallel high-throughput systems biology approaches to characterize viral structure-function-activity measures in the engineered wastewater cycle. The results of this study will provide a database of SARS-CoV2 and other viruses in a broad spectrum of waste streams, treatment systems, and disinfection processes. A second aim of this research is to develop -omics based biomarkers and quantitative assays for SARS-CoV2 to track fate in engineered wastewater treatment systems. Successful completion of this research will provide urgently needed information on SARS-CoV2 behavior in the environment that will inform efforts to manage and mitigate the impacts of the global pandemic.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This NSF RAPID project was awarded in response to and during the early stages of the COVID-19 pandemic. As a brief preface, the PI of this NSF RAPID project was coincidentally actively leading a different waste-based surveillance project focused more on fecal pathogens and other human-health markers, including antimicrobial resistance traits. Through extremely timely support from this NSF RAPID project, and in response to the initial reports of the pandemic, we were able to initiate wastewater monitoring at several sites (first in the Northeastern United States and then expanding to some other locations).
Through this project, rapid progress was made toward establishing and refining protocols for measuring the concentrations and diverstiy of SARS-CoV-2 in different wastewater-associated streams.
This project supported monitoring at several diverse locations including centralized wastewater treatment plants, university campus buildings, healthcare facilities and incarceration facilities. Importantly, the results obtained from this project led to other projects from state and federal agencies as well.
This NSF RAPID project supported the doctoral studies of one researcher at Columbia University.
The notable highlights of the results obtained from this project include the following:
- Through wastewater-based SARS-CoV-2 tracking, we were able to protect and safeguard community health. In multiple telling instances, we were able to inform the concerned health officials of impending upticks in SARS-CoV-2 infection rates and cases approximately two weeks in advance.
- The most notable among these were prior to the surge just before Thanksgiving 2020 and the even higher surge associated with Omicron during December 2021. The first instance was notable due to the lack of vaccines or testing during that stage of the pandemic. The second instance was even more notable, given the nationwide shortage in testing facilities that occurred during that time.
- Furthermore, for much of the duration of the pandemic, wastewater testing was used as the basis for actions such as quarantining or isolation or further testing on our University campus. The prominence of wastewater-testing as supported by this project was also exemplified by its use as a driver on the University testing program and dashboard.
- Over the course of the pandemic, multiple 'waves' of different SARS-CoV-2 variants were also detected and tracked through whole genome sequencing. Attempts were also made to link public health outcomes to the identity and functionality of the different variants based on their genome sequences.
The results from this project were also quite prominently featured in public media. Some select links included the following:
- https://news.columbia.edu/news/columbia-tests-wastewater-residence-halls-coronavirus
- https://abcnews.go.com/Health/watching-covid-variant/story?id=83468177
- https://www.muckrock.com/news/archives/2022/aug/04/new-york-city-wastewater-shows-link-between-crypti/
- https://gothamist.com/news/wastewater-can-predict-covid-19-surges-but-nycs-data-remains-hard-to-find
The subject matter of this project were also used as part of a University-wide townhall to share the results and other details with the community.
The results from this project informed policy in Bergen County NJ and served as a substantial motivation for Bergen County, NJ to establish a monitoring program.
- https://www.northjersey.com/story/news/coronavirus/2022/02/28/covid-sewage-bergen-county-warning-surges-pandemic-wastewater/6916105001/
Last Modified: 08/17/2023
Modified by: Kartik Chandran
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