Evidence map›Paper›PMID 39090157›Full record

ArticleScientific reports2024

The public health impact of COVID-19 variants of concern on the effectiveness of contact tracing in Vermont, United States.

François M Castonguay, Brian F Borah, Seonghye Jeon, Gabriel Rainisch, Patsy Kelso, Bishwa B Adhikari, Daniel J Daltry, Leah S Fischer, Bradford Greening, Emily B Kahn and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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. Article
  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

12 authors.

François M CastonguayNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA. francois.castonguay@umontreal.ca.
Brian F BorahVermont Department of Health, Burlington, USA.
Seonghye JeonNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Gabriel RainischNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Patsy KelsoVermont Department of Health, Burlington, USA.
Bishwa B AdhikariNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Daniel J DaltryVermont Department of Health, Burlington, USA.
Leah S FischerNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Bradford GreeningNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Emily B KahnNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Gloria J KangNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.
Martin I MeltzerNational Center for Emerging and Zoonotic Infectious Diseases, Division of Preparedness and Emerging Infections, Health Economics and Modeling Unit, Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, Atlanta, GA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Case investigation and contact tracing (CICT) are public health measures that aim to break the chain of pathogen transmission. Changes in viral characteristics of COVID-19 variants have likely affected the effectiveness of CICT programs. We estimated and compared the cases averted in Vermont when the original COVID-19 strain circulated (Nov. 25, 2020-Jan. 19, 2021) with two periods when the Delta strain dominated (Aug. 1-Sept. 25, 2021, and Sept. 26-Nov. 20, 2021). When the original strain circulated, we estimated that CICT prevented 7180 cases (55% reduction in disease burden), compared to 1437 (15% reduction) and 9970 cases (40% reduction) when the Delta strain circulated. Despite the Delta variant being more infectious and having a shorter latency period, CICT remained an effective tool to slow spread of COVID-19; while these viral characteristics did diminish CICT effectiveness, non-viral characteristics had a much greater impact on CICT effectiveness.

Indexed as

Contact TracingCOVID-19Public HealthSARS-CoV-2HumansVermontCase investigationCases avertedContact tracingCOVID-19Modeling

Identifiers

PMID39090157
PMCPMC11294356

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.