Evidence map›Paper›PMID 32730356›Full record

ArticlePloS one2020

Enacting national social distancing policies corresponds with dramatic reduction in COVID19 infection rates.

Daniel J McGrail, Jianli Dai, Kathleen M McAndrews, Raghu Kalluri

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 3 pooled it
4.3field-weighted citation impact, top 4% 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

66 citing papers in PubMed, 3 syntheses or guidelines pooled it, 145 citations in OpenAlex.

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  16. Mask Adherence and Social Distancing in Houston, TX from January to April 2021.International journal of environmental research and public health · 2023
    Observational
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  18. Review
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6 more citing papers are in PubMed but not listed here.

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 1 country.

Daniel J McGrailDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, United States of America.ORCID 0000-0002-6669-6069
Jianli DaiDepartment of Cancer Biology, Metastasis Research Center, University of Texas MD Anderson Cancer Center, Houston, TX, United States of America.
Kathleen M McAndrewsDepartment of Cancer Biology, Metastasis Research Center, University of Texas MD Anderson Cancer Center, Houston, TX, United States of America.
Raghu KalluriDepartment of Cancer Biology, Metastasis Research Center, University of Texas MD Anderson Cancer Center, Houston, TX, United States of America.
The University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak the SARS-CoV-2 (CoV-2) virus has resulted in over 6.5 million cases of COVID19, greatly stressing global healthcare infrastructure. Lacking medical prophylactic measures to combat disease spread, many nations have adopted social distancing policies in order to mitigate transmission of CoV-2. While mathematical models have suggested the efficacy of social distancing to curb the spread of CoV-2, there is a lack of systematic studies to quantify the real-world efficacy of these approaches. Here, we first demonstrate that implementation of social distancing policies in US states corresponded with a reduction in COVID19 spread rates, and that the reduction in spread rate is proportional to the average change in mobility. We validate this observation on a worldwide scale by analyzing COVID19 spread rate in 134 nations with varying social distancing policies. Globally, we find that social distancing policies significantly reduced the COVID19 spread rate, with resulting in an estimated 65% reduction (95% CI = 39-80%) in new COVID19 cases over a two week time period. These data suggest that social distancing policies may be a powerful tool to prevent spread of COVID19 in real-world scenarios.

Indexed as

BetacoronavirusModels, TheoreticalCoronavirus InfectionsCOVID-19HumansInternational Health RegulationsPandemicsPneumonia, ViralQuarantineSARS-CoV-2United States

Identifiers

PMID32730356
PMCPMC7392246
OpenAlexW3046865003

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.