Evidence map›Paper›PMID 40590566›Full record

ArticleApplied and environmental microbiology2025

Hospital wastewater surveillance for SARS-CoV-2 identifies intra-hospital dynamics of viral transmission and evolution.

Medini K Annavajhala, Anne L Kelley, Lingsheng Wen, Maya Tagliavia, Sofia Z Moscovitz, Heekuk Park, Simian Huang, Jason E Zucker, Anne-Catrin Uhlemann

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Medini K AnnavajhalaDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0002-9229-8849
Anne L KelleyDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.
Lingsheng WenDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0009-0003-0433-0218
Maya TagliaviaDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.
Sofia Z MoscovitzDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.
Heekuk ParkDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.
Simian HuangDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.
Jason E ZuckerDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0001-6987-6412
Anne-Catrin UhlemannDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0002-9798-4768

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Optimizing SARS-CoV-2 wastewater based surveillance in urban and university campus settings.U01DA053949 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHANDRAN, KARTIK, UHLEMANN, ANNE-CATRIN · 2021 to 2022
$4.8M
Mentoring program in patient-oriented research in microbial genomicsK24AI183182 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Anne-Catrin Uhlemann · 2024 to 2026
$606k
Operationalizing wastewater-based surveillance of multidrug-resistant bacteriaK99AI163348 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ANNAVAJHALA, MEDINI K · 2022 to 2023
$251k
National Institute of Allergy and Infectious Diseases K24AI183182National Institute of Allergy and Infectious Diseases K99AI163348NCATS NIH HHS UL1 TR001873NIAID NIH HHS K24 AI183182NIAID NIH HHS K99 AI163348NIDA NIH HHS U01 DA053949NIDA NIH HHS U01DA053949
6 · The paper itself

Abstract

Wastewater testing has emerged as an effective, widely used tool for population-level severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surveillance. Such efforts have been implemented primarily at wastewater treatment plants, providing data for large resident populations but hindering the ability to implement targeted interventions or follow-ups. Conversely, building-level wastewater data exhibit increased variability due to rapid daily population dynamics but allow for targeted follow-up or mitigation efforts. Here, we implemented a three-site wastewater sampling strategy on our university-affiliated medical campus from May 2021 to March 2024, comprised of two distinct hospital quadrants and a building primarily consisting of research laboratories and classrooms. We first addressed several limitations in implementing hospital-level wastewater surveillance by optimizing sampling frequency and laboratory techniques. We subsequently improved our ability to model SARS-CoV-2 case counts using wastewater data by performing sensitivity analyses on viral shedding assumptions and testing the utility of internal normalization factors for population size. Our unique infrastructure allowed us to detect intra-hospital dynamics of SARS-CoV-2 prevalence and diversity and confirmed that direct sequencing of wastewater was able to capture corresponding clinical viral diversity. In contrast, research building wastewater sampling showed that for most non-residential settings, despite low overall viral loads, a threshold approach can still be used to identify peaks in cases or transmission among the general population. Our study expands on current wastewater surveillance practices by examining the utility of, and best practices for, upstream and particularly hospital settings, enabling the use of non-municipal, medium-scale wastewater testing to inform efforts for reducing the burden of coronavirus disease 2019 (COVID-19).IMPORTANCESince the onset of the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has been increasingly implemented to track the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most wastewater testing across the United States occurs at municipal wastewater treatment plants. Yet, this testing method could also be beneficial at non-municipal and non-residential sites, including hospitals, where wastewater data for SARS-CoV-2 signals and viral diversity could directly impact hospital practices to control its spread. We analyzed both hospital and non-residential research building wastewater over a 3-year period to establish optimized methods for collecting and interpreting wastewater data at sites upstream of treatment plants. We found that even within a single hospital building, wastewater testing in different locations showed distinct signatures over time, which corresponded with data from patients hospitalized in those locations. This study provides a framework for the use of wastewater viral surveillance upstream of municipal treatment plants to enable targeted interventions to limit the spread of SARS-CoV-2.

Indexed as

COVID-19SARS-CoV-2WastewaterWastewater-Based Epidemiological MonitoringHospitalsHumansWastewaterCOVID-19hospital wastewaterSARS-CoV-2wastewater-based epidemiologywastewater surveillance

Identifiers

PMID40590566
PMCPMC12285251

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.