Evidence map›Paper›PMID 40488402›Full record

ArticleEpidemiology and infection2025

Application of joinpoint regression to SARS-CoV-2 wastewater-based epidemiology in Las Vegas, Nevada, USA.

Casey A Barber, Lung-Chang Chien, Brian Labus, Katherine Crank, Katerina Papp, Daniel Gerrity, Cheryl Collins, Edwin C Oh, Lei Zhang, Anil T Mangla and 2 more

Abstract read
In one paragraph

Article in Epidemiology and infection, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

12 authors.

Casey A BarberSchool of Public Health, https://ror.org/0406gha72University of Nevada, Las Vegas, Las Vegas, NV, USA.ORCID 0000-0002-9139-1873
Lung-Chang ChienSchool of Public Health, https://ror.org/0406gha72University of Nevada, Las Vegas, Las Vegas, NV, USA.
Brian LabusSchool of Public Health, https://ror.org/0406gha72University of Nevada, Las Vegas, Las Vegas, NV, USA.
Katherine CrankApplied Research and Development Center, https://ror.org/01h772984Southern Nevada Water Authority, Las Vegas, NV, USA.
Katerina PappApplied Research and Development Center, https://ror.org/01h772984Southern Nevada Water Authority, Las Vegas, NV, USA.
Daniel GerrityApplied Research and Development Center, https://ror.org/01h772984Southern Nevada Water Authority, Las Vegas, NV, USA.
Cheryl Collinshttps://ror.org/02vg22c33Desert Research Institute, Las Vegas, NV, USA.
Edwin C OhCollege of Sciences; School of Integrated Health Sciences; https://ror.org/0406gha72Kirk Kerkorian School of Medicine at UNLV, University of Nevada, Las Vegas, Las Vegas, NV, USA.
Lei Zhanghttps://ror.org/036svm011Southern Nevada Health District, Las Vegas, NV, USA.
Anil T ManglaSchool of Public Health, https://ror.org/0406gha72University of Nevada, Las Vegas, Las Vegas, NV, USA.
Cassius Locketthttps://ror.org/036svm011Southern Nevada Health District, Las Vegas, NV, USA.
L-W Antony ChenSchool of Public Health, https://ror.org/0406gha72University of Nevada, Las Vegas, Las Vegas, NV, USA.ORCID 0000-0002-2311-7506

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Temporal variability and methodological differences in data normalization, among other factors, complicate effective trend analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater surveillance data and its alignment with coronavirus disease 2019 (COVID-19) clinical outcomes. As there is no consensus approach for these analyses yet, this study explored the use of piecewise linear trend analysis (joinpoint regression) to identify significant trends and trend turning points in SARS-CoV-2 RNA wastewater concentrations (normalized and non-normalized) and corresponding COVID-19 case rates in the greater Las Vegas metropolitan area (Nevada, USA) from mid-2020 to April 2023. The analysis period was stratified into three distinct phases based on temporal changes in testing protocols, vaccination availability, SARS-CoV-2 variant prevalence, and public health interventions. While other statistical methodologies may require fewer parameter specifications, joinpoint regression provided an interpretable framework for characterization and comparison of trends and trend turning points, revealing sewershed-specific variations in trend magnitude and timing that also aligned with known variant-driven waves. Week-level trend agreement corroborated previous findings demonstrating a close relationship between SARS-CoV-2 wastewater surveillance data and COVID-19 outcomes. These findings guide future applications of advanced statistical methodologies and support the continued integration of wastewater-based epidemiology as a complementary approach to traditional COVID-19 surveillance systems.

Indexed as

COVID-19SARS-CoV-2WastewaterWastewater-Based Epidemiological MonitoringHumansNevadaRegression AnalysisWastewaterCOVID-19infectious disease epidemiologypublic healthSARS-CoV-2 wastewater surveillancewastewater-based epidemiology

Identifiers

PMID40488402
PMCPMC12171900

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.