Evidence map›Paper›PMID 33243199›Full record

ArticleBMC public health2020

The effects of containment measures in the Italian outbreak of COVID-19.

M Supino, A d'Onofrio, F Luongo, G Occhipinti, A Dal Co

Abstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Observational
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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

5 authors.

M SupinoUniversité de Paris, Institut de physique du globe de Paris, CNRS, F-75005, Paris, France. supino@ipgp.fr.ORCID http://orcid.org/0000-0002-7222-9344
A d'OnofrioInternational Prevention Research Institute, Dardilly, France.
F LuongoDipartimento di Fisica 'Ettore Pancini', Università di Napoli Federico II, Naples, Italy.
G OcchipintiUniversité de Paris, Institut de physique du globe de Paris, CNRS, F-75005, Paris, France.
A Dal CoSchool of Engineering and Applied Sciences, Harvard University, Cambridge, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic is spreading worldwide. Italy emerged early on as the country with the largest outbreak outside Asia. The outbreak in Northern Italy demonstrates that it is fundamental to contain the virus' spread at a very early stage of diffusion. At later stages, no containment measure, even if strict, can prevent the saturation of the hospitals and of the intensive care units in any country. Here we show that it is possible to predict when the intensive care units will saturate, within a few days from the beginning of the exponential growth of COVID-19 intensive care patients. Using early counts of intensive care patients, we predict the saturation for Lombardy, Italy. We also assess short-term and long-term lockdown effects on intensive care units and number of deaths. Governments should use the Italian outbreak as a precedent and implement appropriate containment measures to prevent the saturation of their intensive care units and protect their population, also, and above all, in anticipation of a possible second exponential spread of infections.

Indexed as

QuarantineCoronavirus InfectionsCOVID-19Disease OutbreaksHumansIntensive Care UnitsItalyPandemicsPneumonia, Viral

Identifiers

PMID33243199
PMCPMC7689644

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.