Evidence map›Paper›PMID 36600331›Full record

ArticleBMJ open2022

Evaluation of vaccination strategies for the metropolitan area of Madrid via agent-based simulation.

David E Singh, Carmen Olmedo Luceron, Aurora Limia Sanchez, Miguel Guzman Merino, Christian Duran Gonzalez, Concepcion Delgado-Sanz, Diana Gomez-Barroso, Jesus Carretero, Maria-Cristina Marinescu

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Article in BMJ open, 2022. 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. 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

9 authors.

David E SinghUniversidad Carlos III de Madrid, Computer Science Department, Leganes, Spain.
Carmen Olmedo LuceronMinisterio de Sanidad, Madrid, Spain.
Aurora Limia SanchezMinisterio de Sanidad, Madrid, Spain.
Miguel Guzman MerinoUniversidad Carlos III de Madrid, Computer Science Department, Leganes, Spain.
Christian Duran GonzalezUniversidad Carlos III de Madrid, Computer Science Department, Leganes, Spain.
Concepcion Delgado-SanzMinisterio de Sanidad, Madrid, Spain.
Diana Gomez-BarrosoMinisterio de Sanidad, Madrid, Spain.
Jesus CarreteroUniversidad Carlos III de Madrid, Computer Science Department, Leganes, Spain.
Maria-Cristina MarinescuBarcelona Supercomputing Center, CASE Department, Barcelona, Spain mariacristina.marinescu@gmail.com.ORCID 0000-0002-6978-2974

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021. MATERIALS AND

methodsThe predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator-including the vaccination model-is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million.

resultsThe main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation.

conclusionThe existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities.

Indexed as

COVID-19VaccinesAgedComputer SimulationCOVID-19 VaccinesHumansVaccinationCOVID-19 VaccinesVaccinesCOVID-19EpidemiologyHealth policyHEALTH SERVICES ADMINISTRATION & MANAGEMENTPublic health

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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.