Evidence map›Paper›PMID 33712693›Full record

ArticleNPJ digital medicine2021

Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state.

Matthew Abueg, Robert Hinch, Neo Wu, Luyang Liu, William Probert, Austin Wu, Paul Eastham, Yusef Shafi, Matt Rosencrantz, Michael Dikovsky and 7 more

Open access · goldAbstract read
In one paragraph

Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
23.0field-weighted citation impact, top 1% 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

56 citing papers in PubMed, 3 syntheses or guidelines pooled it, 93 citations in OpenAlex.

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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

17 authors at 2 institutions in 2 countries.

Matthew Abueg *Google Research, Mountain View, CA, USA.ORCID http://orcid.org/0000-0002-4848-1988
Robert Hinch *Nuffield Department of Medicine, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0003-3169-698X
Neo WuGoogle Research, Mountain View, CA, USA.
Luyang LiuGoogle Research, Mountain View, CA, USA.
William ProbertNuffield Department of Medicine, University of Oxford, Oxford, UK.
Austin WuGoogle Research, Mountain View, CA, USA.
Paul EasthamGoogle Research, Mountain View, CA, USA.
Yusef ShafiGoogle Research, Mountain View, CA, USA.
Matt RosencrantzGoogle Research, Mountain View, CA, USA.
Michael DikovskyGoogle Research, Mountain View, CA, USA.
Zhao ChengGoogle Research, Mountain View, CA, USA.
Anel NurtayNuffield Department of Medicine, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0001-7107-1656
Lucie Abeler-DörnerNuffield Department of Medicine, University of Oxford, Oxford, UK.
David BonsallNuffield Department of Medicine, University of Oxford, Oxford, UK.
Michael V McConnellGoogle Research, Mountain View, CA, USA.
Shawn O'BanionGoogle Research, Mountain View, CA, USA. obanion@google.com.ORCID http://orcid.org/0000-0003-3950-6474
Christophe FraserNuffield Department of Medicine, University of Oxford, Oxford, UK. christophe.fraser@bdi.ox.ac.uk.ORCID http://orcid.org/0000-0003-2399-9657
Google (United States) · USUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contact tracing is increasingly used to combat COVID-19, and digital implementations are now being deployed, many based on Apple and Google's Exposure Notification System. These systems utilize non-traditional smartphone-based technology, presenting challenges in understanding possible outcomes. In this work, we create individual-based models of three Washington state counties to explore how digital exposure notifications combined with other non-pharmaceutical interventions influence COVID-19 disease spread under various adoption, compliance, and mobility scenarios. In a model with 15% participation, we found that exposure notification could reduce infections and deaths by approximately 8% and 6% and could effectively complement traditional contact tracing. We believe this can provide health authorities in Washington state and beyond with guidance on how exposure notification can complement traditional interventions to suppress the spread of COVID-19.

Identifiers

PMID33712693
PMCPMC7955120
OpenAlexW3134152404

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.