Evidence map›Paper›PMID 33214148›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Event-specific interventions to minimize COVID-19 transmission.

Paul Tupper, Himani Boury, Madi Yerlanov, Caroline Colijn

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.1field-weighted citation impact, top 9% 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

28 citing papers in PubMed, 71 citations in OpenAlex.

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  12. Event-Specific Transmission Forecasting of SARS-CoV-2 in a Mixed-Mode Ventilated Office Room Using an ANN.International journal of environmental research and public health · 2022
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  17. Effective bubble-based testing for SARS-CoV-2 using swab-pooling.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
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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

4 authors at 1 institution in 2 countries.

Paul TupperDepartment of Mathematics, Simon Fraser University, Burnaby, BC V5A1S6, Canada; pft3@sfu.ca.
Himani BouryFaculty of Health Science, Simon Fraser University, Burnaby, BC V5A1S6, Canada.ORCID 0000-0001-5250-6079
Madi YerlanovDepartment of Mathematics, Simon Fraser University, Burnaby, BC V5A1S6, Canada.ORCID 0000-0003-4882-2989
Caroline ColijnDepartment of Mathematics, Simon Fraser University, Burnaby, BC V5A1S6, Canada.ORCID 0000-0001-6097-6708
Simon Fraser University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is a global pandemic with over 25 million cases worldwide. Currently, treatments are limited, and there is no approved vaccine. Interventions such as handwashing, masks, social distancing, and "social bubbles" are used to limit community transmission, but it is challenging to choose the best interventions for a given activity. Here, we provide a quantitative framework to determine which interventions are likely to have the most impact in which settings. We introduce the concept of "event

Indexed as

PandemicsCOVID-19Disease OutbreaksHumansMasksSARS-CoV-2COVID-19disease transmissionepidemicsinterventions

Identifiers

PMID33214148
PMCPMC7749284
OpenAlexW3103543186

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.