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Sanjak JS, McAuley EM, Raybern J, Pinkham R, Tarnowski J, Miko N, Rasmussen B, Manalo CJ, Goodson M, Stamps B, Necciai B, Sozhamannan S, Maier EJ. Wastewater Surveillance Pilot at US Military Installations: Cost Model Analysis. JMIR Public Health Surveill 2024; 10:e54750. [PMID: 39240545 PMCID: PMC11396592 DOI: 10.2196/54750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 05/23/2024] [Accepted: 05/30/2024] [Indexed: 09/07/2024] Open
Abstract
Background The COVID-19 pandemic highlighted the need for pathogen surveillance systems to augment both early warning and outbreak monitoring/control efforts. Community wastewater samples provide a rapid and accurate source of environmental surveillance data to complement direct patient sampling. Due to its global presence and critical missions, the US military is a leader in global pandemic preparedness efforts. Clinical testing for COVID-19 on US Air Force (USAF) bases (AFBs) was effective but costly with respect to direct monetary costs and indirect costs due to lost time. To remain operating at peak capacity, such bases sought a more passive surveillance option and piloted wastewater surveillance (WWS) at 17 AFBs to demonstrate feasibility, safety, utility, and cost-effectiveness from May 2021 to January 2022. Objective We model the costs of a wastewater program for pathogens of public health concern within the specific context of US military installations using assumptions based on the results of the USAF and Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense pilot program. The objective was to determine the cost of deploying WWS to all AFBs relative to clinical swab testing surveillance regimes. Methods A WWS cost projection model was built based on subject matter expert input and actual costs incurred during the WWS pilot program at USAF AFBs. Several SARS-CoV-2 circulation scenarios were considered, and the costs of both WWS and clinical swab testing were projected. Analysis was conducted to determine the break-even point and how a reduction in swab testing could unlock funds to enable WWS to occur in parallel. Results Our model confirmed that WWS is complementary and highly cost-effective when compared to existing alternative forms of biosurveillance. We found that the cost of WWS was between US $10.5-$18.5 million less expensive annually in direct costs as compared to clinical swab testing surveillance. When the indirect cost of lost work was incorporated, including lost work associated with required clinical swab testing, we estimated that over two-thirds of clinical swab testing could be maintained with no additional costs upon implementation of WWS. Conclusions Our results support the adoption of WWS across US military installations as part of a more comprehensive and early warning system that will enable adaptive monitoring during disease outbreaks in a more cost-effective manner than swab testing alone.
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Affiliation(s)
- Jaleal S Sanjak
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Erin M McAuley
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Justin Raybern
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Richard Pinkham
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Jacob Tarnowski
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Nicole Miko
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Bridgette Rasmussen
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Christian J Manalo
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
| | - Michael Goodson
- United State Air Force Research Laboratory, Wright Patterson Air Force Base, OH, United States
| | - Blake Stamps
- United State Air Force Research Laboratory, Wright Patterson Air Force Base, OH, United States
| | - Bryan Necciai
- Chemical, Biological, Radiological and Nuclear Defense Enabling Biotechnologies, Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense, Frederick, MD, United States
| | - Shanmuga Sozhamannan
- Chemical, Biological, Radiological and Nuclear Defense Enabling Biotechnologies, Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense, Frederick, MD, United States
- Joint Research and Development, Inc, Stafford, VA, United States
| | - Ezekiel J Maier
- Booz Allen Hamilton, 4747 Bethesda Ave, Bethesda, MD, United States, 1 5712413499
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Tandukar S, Thakali O, Baral R, Tiwari A, Haramoto E, Tuladhar R, Joshi DR, Sherchan SP. Application of wastewater-based epidemiology for monitoring COVID-19 in hospital and housing wastewaters. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 931:171877. [PMID: 38531458 DOI: 10.1016/j.scitotenv.2024.171877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 03/04/2024] [Accepted: 03/20/2024] [Indexed: 03/28/2024]
Abstract
An alternative and complementary diagnostic method of surveillance is provided by wastewater-based surveillance (WBS), particularly in low-income nations like Nepal with scant wastewater treatment facilities and clinical testing infrastructure. In this study, a total of 146 water samples collected from two hospitals (n = 63) and three housing wastewaters (n = 83) from the Kathmandu Valley over the period of March 2021-Febraury 2022 were investigated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using quantitative reverse transcription TaqMan PCR assays targeting the N and E genes. Of the total, 67 % (98/146) samples were positive for SARS-CoV-2 RNA either by using N- or E-gene assay, with concentrations ranging from 3.6 to 9.1 log10 copies/L. There was a significant difference found between positive ratio (Chi-square test, p < 0.05) and concentration (t-test, p = 0.009) of SARS-CoV-2 RNA detected from hospital wastewater and housing waters. Wastewater data are correlated with COVID-19 active cases, indicating significance in specific areas like the Hospital (APFH) (p < 0.05). According to the application of a bivariate linear regression model (p < 0.05), the concentrations of N gene may be used to predict the COVID-19 cases in the APFH. Remarkably, SARS-CoV-2 RNA was detected prior to, during, and following clinical case surges, implying that wastewater surveillance could serve as an early warning system for public health decisions. The significance of WBS in tracking and managing pandemics is emphasized by this study, especially in resource-constrained settings.
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Affiliation(s)
- Sarmila Tandukar
- Organization for Public Health and Environment Management, Lalitpur, Nepal
| | - Ocean Thakali
- Organization for Public Health and Environment Management, Lalitpur, Nepal
| | - Rakshya Baral
- Center of Research Excellence in Wastewater based Epidemiology, Morgan State University, Baltimore, MD 21251, United States of America
| | - Ananda Tiwari
- Expert Microbiology Research Unit, Finnish Institute for Health and Welfare, Kuopio 70701, Finland
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Reshma Tuladhar
- Central Department of Microbiology, Tribhuvan University, Kathmandu, Nepal
| | - Dev Raj Joshi
- Central Department of Microbiology, Tribhuvan University, Kathmandu, Nepal
| | - Samendra P Sherchan
- Organization for Public Health and Environment Management, Lalitpur, Nepal; Center of Research Excellence in Wastewater based Epidemiology, Morgan State University, Baltimore, MD 21251, United States of America; Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan; Central Department of Microbiology, Tribhuvan University, Kathmandu, Nepal; Department of Environmental Health Sciences, Tulane University, New Orleans, LA 70112, United States of America.
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Schmiege D, Haselhoff T, Thomas A, Kraiselburd I, Meyer F, Moebus S. Small-scale wastewater-based epidemiology (WBE) for infectious diseases and antibiotic resistance: A scoping review. Int J Hyg Environ Health 2024; 259:114379. [PMID: 38626689 DOI: 10.1016/j.ijheh.2024.114379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/25/2024] [Accepted: 04/08/2024] [Indexed: 04/18/2024]
Abstract
Wastewater analysis can serve as a source of public health information. In recent years, wastewater-based epidemiology (WBE) has emerged and proven useful for the detection of infectious diseases. However, insights from the wastewater treatment plant do not allow for the small-scale differentiation within the sewer system that is needed to analyze the target population under study in more detail. Small-scale WBE offers several advantages, but there has been no systematic overview of its application. The aim of this scoping review is to provide a comprehensive overview of the current state of knowledge on small-scale WBE for infectious diseases, including methodological considerations for its application. A systematic database search was conducted, considering only peer-reviewed articles. Data analyses included quantitative summary and qualitative narrative synthesis. Of 2130 articles, we included 278, most of which were published since 2020. The studies analyzed wastewater at the building level (n = 203), especially healthcare (n = 110) and educational facilities (n = 80), and at the neighborhood scale (n = 86). The main analytical parameters were viruses (n = 178), notably SARS-CoV-2 (n = 161), and antibiotic resistance (ABR) biomarkers (n = 99), often analyzed by polymerase chain reaction (PCR), with DNA sequencing techniques being less common. In terms of sampling techniques, active sampling dominated. The frequent lack of detailed information on the specification of selection criteria and the characterization of the small-scale sampling sites was identified as a concern. In conclusion, based on the large number of studies, we identified several methodological considerations and overarching strategic aspects for small-scale WBE. An enabling environment for small-scale WBE requires inter- and transdisciplinary knowledge sharing across countries. Promoting the adoption of small-scale WBE will benefit from a common international conceptualization of the approach, including standardized and internationally accepted terminology. In particular, the development of good WBE practices for different aspects of small-scale WBE is warranted. This includes the establishment of guidelines for a comprehensive characterization of the local sewer system and its sub-sewersheds, and transparent reporting to ensure comparability of small-scale WBE results.
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Affiliation(s)
- Dennis Schmiege
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany.
| | - Timo Haselhoff
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany
| | - Alexander Thomas
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131, Essen, Germany
| | - Ivana Kraiselburd
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131, Essen, Germany
| | - Folker Meyer
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131, Essen, Germany
| | - Susanne Moebus
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany
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