Evidence map›Paper›PMID 35137317›Full record

ReviewEnvironmental science and pollution research international2022

Passive Samplers, an Important Tool for Continuous Monitoring of the COVID-19 Pandemic.

Albert Z Jiang, Fulin Nian, Han Chen, Edward A McBean

Abstract readReview
In one paragraph

Review in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Albert Z JiangSchool of Engineering, University of Guelph, 50 Stone Rd. E, Guelph, N1G 2W1, Canada. zjiang@uoguelph.ca.
Fulin NianDepartment of Digestive, Shanghai Pudong Hospital, Fudan University Affiliated Pudong Medical Center, 2800 Gongwei Road, Shanghai, 201399, China.
Han ChenCollege of Environmental Science and Engineering/Sino-Canada Joint R&D Centre for Water and Environmental Safety, Nankai University, Tianjin, 300071, China.
Edward A McBeanSchool of Engineering, University of Guelph, 50 Stone Rd. E, Guelph, N1G 2W1, Canada.

Funding

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada NSERC COVID grant (400655)
6 · The paper itself

Abstract

The global pandemic caused by COVID-19 has resulted in major costs around the world, costs with dimensions in every aspect, from peoples' daily living to the global economy. As the pandemic progresses, the virus evolves, and more vaccines become available, and the 'battle against the virus' continues. As part of the battle, Wastewater-Based Epidemiology (WBE) technologies are being widely deployed in essential roles for SARS-CoV-2 detection and monitoring. While focusing on demonstrating the advantages of passive samplers as a tool in WBE, this review provides a holistic view of the current WBE applications in monitoring SARS-CoV-2 with the integration of the most up-to-date data. A novel scenario example based on a recent Nanjing (China) outbreak in July 2021 is used to illustrate the potential benefits of using passive samplers to monitor COVID-19 and to facilitate effective control of future major outbreaks. The presented contents and how the application of passive samplers indicates that this technology can be beneficial at different levels, varying from building to community to regional. Countries and regions that have the pandemic well under control or have low positive case occurrences have the potential to significantly benefit from deploying passive samplers as a measure to identify and suppress outbreaks.

Indexed as

COVID-19HumansPandemicsSARS-CoV-2WastewaterWastewater-Based Epidemiological MonitoringWastewaterCOVID-19Example scenarioPassive samplerSARS-CoV-2Wastewater-based epidemiologyWastewater monitoring

Identifiers

PMID35137317
PMCPMC9072756

What OpenQuestion holds

Textmetadata
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.