Evidence map›Paper›PMID 32574303›Full record

ArticleFrontiers in public health2020

A Simulation of a COVID-19 Epidemic Based on a Deterministic SEIR Model.

José M Carcione, Juan E Santos, Claudio Bagaini, Jing Ba

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 105 papers.

0numbers the graph read from it
0cells of the map it votes in
105citing papers in PubMed
9.1field-weighted citation impact, top 2% 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

105 citing papers in PubMed, 336 citations in OpenAlex.

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  11. The impact of non-pharmaceutical interventions on the spread of COVID-19 in Saudi Arabia: Simulation approach.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024
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45 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 3 institutions in 5 countries.

José M CarcioneNational Institute of Oceanography and Applied Geophysics - OGS, Trieste, Italy.
Juan E SantosSchool of Earth Sciences and Engineering, Hohai University, Nanjing, China.
Claudio BagainiIndependent Researcher, Haywards Heath, United Kingdom.
Jing BaSchool of Earth Sciences and Engineering, Hohai University, Nanjing, China.
Hohai University · CNHaywards Heath Hospital · GBNational Institute of Oceanography and Applied Geophysics · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An epidemic disease caused by a new coronavirus has spread in Northern Italy with a strong contagion rate. We implement an SEIR model to compute the infected population and the number of casualties of this epidemic. The example may ideally regard the situation in the Italian Region of Lombardy, where the epidemic started on February 24, but by no means attempts to perform a rigorous case study in view of the lack of suitable data and the uncertainty of the different parameters, namely, the variation of the degree of home isolation and social distancing as a function of time, the initial number of exposed individuals and infected people, the incubation and infectious periods, and the fatality rate. First, we perform an analysis of the results of the model by varying the parameters and initial conditions (in order for the epidemic to start, there should be at least one exposed or one infectious human). Then, we consider the Lombardy case and calibrate the model with the number of dead individuals to date (May 5, 2020) and constrain the parameters on the basis of values reported in the literature. The peak occurs at day 37 (March 31) approximately, with a reproduction ratio

Indexed as

Communicable Disease ControlComputer SimulationCOVID-19Models, StatisticalHumansItalySARS-CoV-2COVID-19epidemicinfection fatality rate (IFR)lockdownLombardy (Italy)reproduction ratio (R0)SEIR model

Identifiers

PMID32574303
PMCPMC7270399
OpenAlexW3029408214

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.