Evidence map›Paper›PMID 33493409›Full record

ReviewPopulation health management2021

Model for Mitigation of Workplace Transmission of COVID-19 Through Population-Based Testing and Surveillance.

Peter J Plantes, Maren S Fragala, Charles Clarke, Zachary N Goldberg, Jeff Radcliff, Steven E Goldberg

Open access · hybridAbstract readReview
In one paragraph

Review in Population health management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

6 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Impact of Mass Workplace COVID-19 Rapid Testing on Health and Healthcare Resource Savings.International journal of environmental research and public health · 2021
    Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Peter J Planteshc1, Indianapolis, Indiana, USA.
Maren S FragalaQuest Diagnostics, Secaucus, New Jersey, USA.
Charles Clarkehc1, Indianapolis, Indiana, USA.
Zachary N GoldbergQuest Diagnostics, Secaucus, New Jersey, USA.
Jeff RadcliffQuest Diagnostics, Secaucus, New Jersey, USA.
Steven E GoldbergQuest Diagnostics, Secaucus, New Jersey, USA.
Quest Diagnostics (United States) · USIndianapolis Zoo · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease-2019 (COVID-19) pandemic is having a widespread impact on societies across the globe. As part of the effort to control transmission in the United States, many businesses either closed or instituted nonpharmaceutical control measures and allowed only essential workers on-site. During summer and fall of 2020, employers began formulating "return to work" strategies designed to mitigate the risk of transmission among employees. On a population level, several countries implemented national testing and surveillance strategies that proved effective in mitigating citizen-to-citizen transmission and contributed to suppressing COVID-19. A crucial component of many such strategies is population-based testing to identify and engage individuals with asymptomatic or presymptomatic infection, which also is relevant to return-to-work strategies. The authors describe an approach that multisite employers might use to help mitigate transmission of COVID-19 in the workplace. This approach leverages a bioinformatics platform informed by real-time PCR test data at the county and subcounty (eg, Public Use Microdata Area) level, allowing for population-based testing to be selectively targeted for employees in geographies with elevated SARS-CoV-2 positivity. A "Command Center" application integrates data from multiple sources (eg, local infection trends, employee symptom diaries, Bluetooth thermometers) in real time, which can be used to inform decisions regarding surveillance and employee self-isolation or quarantine; a mobile phone-based application provides for rapid, secure communication with employees. This overview is based on peer-reviewed literature and the early experience of a large employer with implementing bioinformatics tools to mitigate the impact of the pandemic on the workplace.

Indexed as

COVID-19Models, StatisticalOccupational HealthComputational BiologyCOVID-19 TestingHumansPandemicsPublic Health SurveillanceSARS-CoV-2United StatesWorkplaceCOVID-19population-based testingSARS-CoV-2surveillanceworkplace mitigation

Identifiers

PMID33493409
PMCPMC7875134
OpenAlexW3125178974

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.