Evidence map›Paper›PMID 35789191›Full record

ArticleScientific reports2022

Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland.

Piotr Pałka, Robert Olszewski, Małgorzata Kęsik-Brodacka, Agnieszka Wendland, Karolina Nowak, Urszula Szczepankowska-Bednarek, David Th Liebers

Abstract read
In one paragraph

Article in Scientific reports, 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. Review
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

7 authors.

Piotr PałkaFaculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland.
Robert OlszewskiFaculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland. robert.olszewski@pw.edu.pl.ORCID 0000-0003-1697-9367
Małgorzata Kęsik-BrodackaNational Medicines Institute, Warsaw, Poland.
Agnieszka WendlandFaculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland.
Karolina NowakDepartment of Applied Pharmacy, Faculty of Pharmacy With Laboratory Medicine, Medical University of Warsaw, Warsaw, Poland.
Urszula Szczepankowska-BednarekCentre for Innovation and Technology Transfer Management, Warsaw University of Technology, Warsaw, Poland.
David Th LiebersNew York University Langone Health, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the article, the authors present a multi-agent model that simulates the development of the COVID-19 pandemic at the regional level. The developed what-if system is a multi-agent generalization of the SEIR epidemiological model, which enables predicting the pandemic's course in various regions of Poland, taking into account Poland's spatial and demographic diversity, the residents' level of mobility, and, primarily, the level of restrictions imposed and the associated compliance. The developed simulation system considers detailed topographic data and the residents' professional and private lifestyles specific to the community. A numerical agent represents each resident in the system, thus providing a highly detailed model of social interactions and the pandemic's development. The developed model, made publicly available as free software, was tested in three representative regions of Poland. As the obtained results indicate, implementing social distancing and limiting mobility is crucial for impeding a pandemic before the development of an effective vaccine. It is also essential to consider a given community's social, demographic, and topographic specificity and apply measures appropriate for a given region.

Indexed as

COVID-19Influenza, HumanComputer SimulationHumansPandemicsPoland

Identifiers

PMID35789191
PMCPMC9252566

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.