Evidence map›Paper›PMID 33796497›Full record

ArticleFrontiers in public health2021

Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area.

David E Singh, Maria-Cristina Marinescu, Miguel Guzmán-Merino, Christian Durán, Concepción Delgado-Sanz, Diana Gomez-Barroso, Jesus Carretero

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. PITS: An Intelligent Transportation System in pandemic times.Engineering applications of artificial intelligence · 2022
    Article
  5. Article
  6. Predictive Model of Preventive Behaviors against COVID-19 in the Older Adult: The PREASOC-COVID-19 Study.International journal of environmental research and public health · 2021
    Observational
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

David E SinghDepartment Computer Science, Universidad Carlos III de Madrid, Leganés, Spain.
Maria-Cristina MarinescuBarcelona Supercomputing Center, Barcelona, Spain.
Miguel Guzmán-MerinoDepartment Computer Science, Universidad Carlos III de Madrid, Leganés, Spain.
Christian DuránDepartment Computer Science, Universidad Carlos III de Madrid, Leganés, Spain.
Concepción Delgado-SanzCIBER en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Diana Gomez-BarrosoCIBER en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Jesus CarreteroDepartment Computer Science, Universidad Carlos III de Madrid, Leganés, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work presents simulation results for different mitigation and confinement scenarios for the propagation of COVID-19 in the metropolitan area of Madrid. These scenarios were implemented and tested using EpiGraph, an epidemic simulator which has been extended to simulate COVID-19 propagation. EpiGraph implements a social interaction model, which realistically captures a large number of characteristics of individuals and groups, as well as their individual interconnections, which are extracted from connection patterns in social networks. Besides the epidemiological and social interaction components, it also models people's short and long-distance movements as part of a transportation model. These features, together with the capacity to simulate scenarios with millions of individuals and apply different contention and mitigation measures, gives EpiGraph the potential to reproduce the COVID-19 evolution and study medium-term effects of the virus when applying mitigation methods. EpiGraph, obtains closely aligned infected and death curves related to the first wave in the Madrid metropolitan area, achieving similar seroprevalence values. We also show that selective lockdown for people over 60 would reduce the number of deaths. In addition, evaluate the effect of the use of face masks after the first wave, which shows that the percentage of people that comply with mask use is a crucial factor for mitigating the infection's spread.

Indexed as

Computer SimulationSocial NetworkingAlgorithmsCitiesCommunicable Disease ControlCOVID-19EpidemicsHumansMasksQuarantineSeroepidemiologic StudiesSpainTravelCOVID-19face maskmitigation policiessimulationsocial distancing

Identifiers

PMID33796497
PMCPMC8007867

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.