Evidence map›Paper›PMID 39220928›Full record

ArticleHeliyon2024

Public health use and lessons learned from a statewide SARS-CoV-2 wastewater monitoring program (MiNET).

Nishita D'Souza, Alexis M Porter, Joan B Rose, Erin Dreelin, Susan E Peters, Penny J Nowlin, Samantha Carbonell, Kyle Cissell, Yili Wang, Matthew T Flood and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. 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

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

15 authors.

Nishita D'SouzaDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
Alexis M PorterAnnis Water Resources Insititute, Grand Valley State University, Muskegon, MI, USA.
Joan B RoseDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
Erin DreelinDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
Susan E PetersMichigan Department of Health and Human Services, Lansing, MI, USA.
Penny J NowlinNorthern Michigan Regional Laboratory, Gaylord, MI, USA.
Samantha CarbonellDepartment of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA.
Kyle CissellSaginaw Valley State University, Michigan, USA.
Yili WangUniversity of Michigan, Ann Arbor, Michigan, USA.
Matthew T FloodDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
Andri T RachmadiInstitute of Environmental Science and Research (ESR), New Zealand.
Chuanwu XiUniversity of Michigan, Ann Arbor, Michigan, USA.
Peter SongUniversity of Michigan, Ann Arbor, Michigan, USA.
Shannon BriggsMichigan Department of Environment, Great Lakes, and Energy, Lansing, MI, USA.
Michigan Network for Environmental Health and Technology (MiNET) consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global SARS-CoV-2 monitoring effort has been extensive, resulting in many states and countries establishing wastewater-based epidemiology programs to address the spread of the virus during the pandemic. Challenges for programs include concurrently optimizing methods, training new laboratories, and implementing successful surveillance programs that can rapidly translate results for public health, and policy making. Surveillance in Michigan early in the pandemic in 2020 highlights the importance of quality-controlled data and explores correlations with wastewater and clinical case data aggregated at the state level. The lessons learned and potential measures to improve public utilization of results are discussed. The Michigan Network for Environmental Health and Technology (MiNET) established a network of laboratories that partnered with local health departments, universities, wastewater treatment plants (WWTPs) and other stakeholders to monitor SARS-CoV-2 in wastewater at 214 sites in Michigan. MiNET consisted of nineteen laboratories, twenty-nine local health departments, 6 Native American tribes, and 60 WWTPs monitoring sites representing 45 % of Michigan's population from April 6 and December 29, 2020. Three result datasets were created based on quality control criteria. Wastewater results that met all quality assurance criteria (Dataset Mp) produced strongest correlations with reported clinical cases at 16 days lag (rho = 0.866,

Indexed as

MiNETPublic healthSARS-CoV-2Wastewater monitoring

Identifiers

PMID39220928
PMCPMC11363850

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.