Evidence map›Paper›PMID 36806994›Full record

ArticleBulletin of mathematical biology2023

A Spatial Kinetic Model of Crowd Evacuation Dynamics with Infectious Disease Contagion.

Juan Pablo Agnelli, Bruno Buffa, Damián Knopoff, Germán Torres

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2023. 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

4 authors.

Juan Pablo Agnelli *Centro de Investigaciones y Estudios de Matemática (CIEM), CONICET, Medina Allende s/n, Córdoba, 5000, Córdoba, Argentina.
Bruno Buffa *FaMAF, Universidad Nacional de Córdoba, Medina Allende s/n, Córdoba, 5000, Córdoba, Argentina.
Damián Knopoff *Centro de Investigaciones y Estudios de Matemática (CIEM), CONICET, Medina Allende s/n, Córdoba, 5000, Córdoba, Argentina. damian.knopoff@unc.edu.ar.ORCID http://orcid.org/0000-0002-4477-5639
Germán Torres *Instituto de Modelado e Innovación Tecnológica (IMIT), CONICET, Av. Libertad 5460, Corrientes, 3404, Corrientes, Argentina.

Funding

CONICET PIP 2015-2017 11220150100500 COMinisterio de Ciencia e Innovación EV-2017-0718Universidad Nacional de Cordoba Secyt-UNC Project 33620180100326CBUniversidad Nacional del Nordeste Project 2020-2023 19F010
6 · The paper itself

Abstract

This paper proposes a kinetic theory approach coupling together the modeling of crowd evacuation from a bounded domain with exit doors and infectious disease contagion. The spatial movement of individuals in the crowd is modeled by a proper description of the interactions with people in the crowd and the environment, including walls and exits. At the same time, interactions among healthy and infectious individuals may generate disease spreading if exposure time is long enough. Immunization of the population and individual awareness to contagion is considered as well. Interactions are modeled by tools of game theory, that let us propose the so-called tables of games that are introduced in the general kinetic equations. The proposed model is qualitatively studied and, through a series of case studies, we explore different scenarios related to crowding and gathering formation within indoor venues under the spread of a respiratory infectious disease, obtaining insights on specific policies to reduce contagion that may be implemented.

Indexed as

Communicable DiseasesModels, BiologicalCrowdingGame TheoryHumansMathematical ConceptsActive particlesAwarenessCrowd dynamicsDisease contagionEvacuationImmunizationKinetic theory

Identifiers

PMID36806994
PMCPMC9937870

What OpenQuestion holds

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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.