Evidence map›Paper›PMID 33194950›Full record

ArticleFrontiers in public health2020

Are Lockdown Measures Effective Against COVID-19?

Samer Kharroubi, Fatima Saleh

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
3.0field-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

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 111 citations in OpenAlex.

  1. Anxiety Linked to COVID-19: A Systematic Review Comparing Anxiety Rates in Different Populations.International journal of environmental research and public health · 2022
    Pooled it
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  4. The impact of the COVID-19 lockdown on social and economic welfare in Uganda.Archives of public health = Archives belges de sante publique · 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

2 authors at 2 institutions in 1 country.

Samer KharroubiDepartment of Nutrition and Food Sciences, Faculty of Agricultural and Food Sciences, American University of Beirut, Beirut, Lebanon.
Fatima SalehDepartment of Medical Laboratory Sciences, Faculty of Health Sciences, Beirut Arab University, Beirut, Lebanon.
American University of Beirut · LBBeirut Arab University · LB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the Coronavirus Disease 2019 (COVID-19) pandemic progresses, countries around the world are increasingly implementing a range of responses that are intended to help prevent the transmission of this disease. In the absence of a COVID-19 vaccine, we assess the potential role of containment measures to suppress the virus transmission, thereby slowing down the growth rate of cases and rapidly reducing case incidence. The aim of this study is to show that country lockdown has a critical and significant impact on the pandemic. This is explored using real time incidence data in Lebanon. We analyze COVID-19 cases in Lebanon before and after lockdown measures have been implemented. The findings show that the nationwide lockdown was effective in reducing cases and has been successful in, so far, containing the virus. This study could be an evidence-based call to continue with the lockdown measures, based on real time incidence data. Further research is encouraged.

Indexed as

COVID-19Communicable Disease ControlCOVID-19 VaccinesHumansLebanonSARS-CoV-2COVID-19 VaccinesCOVID-19Lebanonlockdown measuresmodelingPoisson regression model

Identifiers

PMID33194950
PMCPMC7642264
OpenAlexW3093758471

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.