Evidence map›Paper›PMID 34607714›Full record

ArticleHealth policy (Amsterdam, Netherlands)2021

Inferring a cause-effect relationship between lockdown restrictions and COVID-19 pandemic trend during the first wave.

Rosario Megna

Abstract read
In one paragraph

Article in Health policy (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. The political cost of sanctions: Evidence from COVID-19.Health policy (Amsterdam, Netherlands) · 2022
    Article
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

1 author.

Rosario MegnaNational Research Council, Institute of Biostructure and Bioimaging, Via Tommaso de Amicis, Naples 80145, Italy. Electronic address: rosario.megna@cnr.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The large number of infected persons due to the COVID-19 pandemic and the need of hospital care for many of them induced the majority of world governments to implement lockdown measures. We developed an analytical model to evaluate the trend of the SARS-CoV-2 pandemic. This model was applied to the first four months of the epidemiological data of the most affected countries in Europe and Russia, in order to evaluate the effect of the lockdown on the epidemic curves during the first wave. According to our model, the difference between the beginning of the lockdown and the slope change of the curve representing the daily distribution of counts was: Germany and Spain 6 days, France 7 days, the United Kingdom 9 days, Italy 21 days, and Russia 30 days. On the basis of these results, we infer a possible cause-effect relationship between the lockdown imposed in countries taken into account and the curve representing the daily distribution of new cases. Lockdown measures imposed by governments slowed the spread of the pandemic and reduced the number of infected persons. In economic terms, the damage was considerable, with entire production sectors in crisis. On the other hand, the efforts and innovations implemented to produce vaccines and effective treatments against the pandemic could be applied also in other fields of public health.

Indexed as

COVID-19PandemicsCommunicable Disease ControlHumansSARS-CoV-2SpainCOVID-19Health policyLockdownModellingPublic healthSARS-CoV-2

Identifiers

PMID34607714
PMCPMC8461269

What OpenQuestion holds

Textmetadata
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.