Study Information

dbGaP Study Accession: phs002542

NIH Institute/Center: NIDA

RADx Data Program: RADx-rad

Release Date: 11/07/2022

DOI: 10.60773/6y92-jm05

Updated Date: 10/23/2023

Study Description: Developing next generation technology to simplify wastewater RNA extraction and quantification makes wastewater surveillance feasible and scalable in facilities and rural communities. Wastewater testing for SARS-CoV-2 in rural communities using field-friendly technology provides important information to local authorities and citizens about the spread and trend of SARS-CoV-2 infection in their communities. This project accomplished two aims: 1) Develop next generation wastewater assessment technology, and 2) Implement and evaluate the next generation wastewater assay. Aim 1 adapted technology termed exclusion-based sample preparation (ESP) to simplify and improve RNA extraction from wastewater. ESP was paired with loop-mediated isothermal amplification (LAMP) technology for RNA detection to create a sensitive, robust, and field-friendly platform for testing wastewater for SARS-CoV-2 RNA. The next generation assay was compared with established techniques on metrics of sensitivity, specificity, and usability (e.g., assay time, number of assay steps). Aim 2 first validated the next generation assay in the field at congregate living facilities in a side-by-side comparison with conventional wastewater surveillance. Next, building on existing relationships in Eastern Kentucky, a purposive group of wastewater treatment plant operators, watershed watch citizen scientists, and school science teachers were recruited and trained to test wastewater in their communities and schools using the field-friendly next generation wastewater assay. Field results were validated in the lab. A robust mixed methods evaluation using the RE-AIM framework assessed community perceptions of feasibility, acceptability, and utility of wastewater surveillance for SARS-CoV-2 and identified community measures taken in response to test results.

Principal Investigator: Keck, James

Has Data Files: Yes

Study Domain: Next Generation Sequencing (NGS); Wastewater Surveillance

Data Collection Method: Interview or Focus Group; Molecular (Nucleic Acid/PCR) Testing Device; Wastewater Sampling

Keywords: Sample Data; Isothermal Technology; Nucleic Acid/Isothermal Test; Nucleic Acid Amplification Test (NAAT); Assays

Study Design: Device Validation Study

Multi-Center Study: FALSE

Data Types: Other; Environmental (Physical); Questionnaires/Surveys

Data Types, Other: Interview, Qualitative Data, Wastewater Analysis for Presence of SARS-CoV-2 Biomarkers (RNA)

Study Start Date: 01/01/2021

Study End Date: 05/31/2023

Species: Non-Human Data; Human Data

Estimated Cohort Size: 24

Study Population Focus:

Acknowledgement Statement: This study was supported through funding, 4U01DA053903-02, for the National Institute on Drug Abuse (NIDA) as part of the RADx-rad program. Data used in this study were collected by the Wastewater Assessment for Coronavirus in Kentucky - Implementing Enhanced Surveillance Technology (WACKIEST) Team. Approved users should acknowledge the provision of data access by dbGaP for accession phs002542.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.

Funding Opportunity Announcement (FOA) Number: RFA-OD-20-015

NIH Grant or Contract Number(s): 4U01DA053903-02

Consent/Data Use Limitations: General Research Use

Data Files
Total Files: 7
Data Files: 5
Metadata Files: 0
Dictionary Files: 2
Study Datasets Table
File Name
File Type
File Format(s)
# of Records
# of Variables
Metadata
Dictionary
rad_015_903-01_DATA_20230407_DATA_origcopy.csvTabular Data - Non-harmonizedcsv1013

rad_015_903-01_DATA_20230407_DATA_transformcopy.csvTabular Data - Harmonizedcsv1013

rad_015_903-01_20220531_DATA_transformcopy.csvTabular Data - Harmonizedcsv566

rad_015_903-01_20220930_DATA_transformcopy.csvTabular Data - Harmonizedcsv754

rad_015_903-01_20220531_DATA_origcopy.csvTabular Data - Non-harmonizedcsv566