Evidence map›Paper›PMID 35969766›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

The effectiveness of COVID-19 testing and contact tracing in a US city.

Xutong Wang, Zhanwei Du, Emily James, Spencer J Fox, Michael Lachmann, Lauren Ancel Meyers, Darlene Bhavnani

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

13 citing papers in PubMed, 28 citations in OpenAlex.

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  7. Time trends and modifiable factors of COVID-19 contact tracing coverage, Geneva, Switzerland, June 2020 to February 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2024
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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

7 authors at 3 institutions in 2 countries.

Xutong WangDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712.
Zhanwei DuDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712.ORCID 0000-0002-2020-767X
Emily JamesInformation Technology Project Management Office, Dell Medical School, The University of Texas at Austin, Austin, TX 78712.
Spencer J FoxDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712.ORCID 0000-0003-1969-3778
Michael LachmannSanta Fe Institute, Santa Fe, NM 87501.
Lauren Ancel MeyersDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712.ORCID 0000-0002-5828-8874
Darlene BhavnaniDepartment of Population Health, Dell Medical School, The University of Texas at Austin, Austin, TX 78712.
The University of Texas at Austin · USSanta Fe Institute · USHong Kong Science and Technology Parks Corporation · HK

Funding

Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial dataR01AI151176 · NIAID · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2020 to 2024
$3.9M
RFA-IP-22-004, Modeling toolkit to evaluate multifaceted control strategies for seasonal and pandemic influenzaU01IP001136 · IP · UNIVERSITY OF TEXAS AT AUSTIN · PI MEYERS, LAUREN ANCEL · 2020 to 2024
$3.4M
NCIRD CDC HHS U01 IP001136NIAID NIH HHS R01 AI151176
6 · The paper itself

Abstract

Although testing, contact tracing, and case isolation programs can mitigate COVID-19 transmission and allow the relaxation of social distancing measures, few countries worldwide have succeeded in scaling such efforts to levels that suppress spread. The efficacy of test-trace-isolate likely depends on the speed and extent of follow-up and the prevalence of SARS-CoV-2 in the community. Here, we use a granular model of COVID-19 transmission to estimate the public health impacts of test-trace-isolate programs across a range of programmatic and epidemiological scenarios, based on testing and contact tracing data collected on a university campus and surrounding community in Austin, TX, between October 1, 2020, and January 1, 2021. The median time between specimen collection from a symptomatic case and quarantine of a traced contact was 2 days (interquartile range [IQR]: 2 to 3) on campus and 5 days (IQR: 3 to 8) in the community. Assuming a reproduction number of 1.2, we found that detection of 40% of all symptomatic cases followed by isolation is expected to avert 39% (IQR: 30% to 45%) of COVID-19 cases. Contact tracing is expected to increase the cases averted to 53% (IQR: 42% to 58%) or 40% (32% to 47%), assuming the 2- and 5-day delays estimated on campus and in the community, respectively. In a tracing-accelerated scenario, in which 75% of contacts are notified the day after specimen collection, cases averted increase to 68% (IQR: 55% to 72%). An accelerated contact tracing program leveraging rapid testing and electronic reporting of test results can significantly curtail local COVID-19 transmission.

Indexed as

Contact TracingCOVID-19COVID-19 TestingHumansQuarantineSARS-CoV-2Texascontact tracingCOVID-19COVID-19 testingmathematical modelpandemic

Identifiers

PMID35969766
PMCPMC9407477
OpenAlexW4291910179

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.