In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 8 ( 2022-8-30), p. e0273820-
Abstract:
The coronavirus disease (COVID-19) pandemic has changed our lives and still poses a challenge to science. Numerous studies have contributed to a better understanding of the pandemic. In particular, inhalation of aerosolised pathogens has been identified as essential for transmission. This information is crucial to slow the spread, but the individual likelihood of becoming infected in everyday situations remains uncertain. Mathematical models help estimate such risks. In this study, we propose how to model airborne transmission of SARS-CoV-2 at a local scale. In this regard, we combine microscopic crowd simulation with a new model for disease transmission. Inspired by compartmental models, we describe virtual persons as infectious or susceptible. Infectious persons exhale pathogens bound to persistent aerosols, whereas susceptible ones absorb pathogens when moving through an aerosol cloud left by the infectious person. The transmission depends on the pathogen load of the aerosol cloud, which changes over time. We propose a ‘high risk’ benchmark scenario to distinguish critical from non-critical situations. A parameter study of a queue shows that the new model is suitable to evaluate the risk of exposure qualitatively and, thus, enables scientists or decision-makers to better assess the spread of COVID-19 and similar diseases.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0273820
DOI:
10.1371/journal.pone.0273820.g001
DOI:
10.1371/journal.pone.0273820.g002
DOI:
10.1371/journal.pone.0273820.g003
DOI:
10.1371/journal.pone.0273820.g004
DOI:
10.1371/journal.pone.0273820.g005
DOI:
10.1371/journal.pone.0273820.g006
DOI:
10.1371/journal.pone.0273820.g007
DOI:
10.1371/journal.pone.0273820.g008
DOI:
10.1371/journal.pone.0273820.g009
DOI:
10.1371/journal.pone.0273820.g010
DOI:
10.1371/journal.pone.0273820.g011
DOI:
10.1371/journal.pone.0273820.g012
DOI:
10.1371/journal.pone.0273820.t001
DOI:
10.1371/journal.pone.0273820.s001
DOI:
10.1371/journal.pone.0273820.s002
DOI:
10.1371/journal.pone.0273820.s003
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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