TY - JOUR
T1 - Toward unraveling airborne pathogen transmission in crowds
T2 - Parameter study for an agent-based exposure model
AU - Rahn, Simon
AU - Köster, Gerta
AU - Bungartz, Hans Joachim
N1 - Publisher Copyright:
© 2024
PY - 2024/7
Y1 - 2024/7
N2 - The coronavirus disease 2019 (COVID-19) pandemic has put forth the integration of pathogen transmission into microscopic crowd models to simulate the exposure risk for individuals. However, it is crucial to account for uncertainties in the model input as long as we lack data, particularly regarding airborne transmission of the coronavirus. In this study, we quantify uncertainties in such simulations to increase their reliability and informative value. We consider this an integral aspect of model validation. This study relies on a model originally introduced in a previous contribution. We adapt it to simulate airborne virus transmission in several everyday situations. The locomotion layer of the model captures crowd management strategies, while its pathogen transmission layer returns the virtual persons’ exposures to pathogens. We conduct a global sensitivity analysis to rank uncertain parameters according to their impact on the exposure risk and employ forward propagation techniques to quantify the output uncertainty. The sensitivity analysis reveals that two model parameters related to the extent and spread of aerosols are essential, whereas a parameter describing the decay of pathogens is barely influential. The forward propagation demonstrates how crowd management alleviates the exposure risk in the analyzed situations. Moreover, we identify aerosol spread as a dominant aspect on which research should focus.
AB - The coronavirus disease 2019 (COVID-19) pandemic has put forth the integration of pathogen transmission into microscopic crowd models to simulate the exposure risk for individuals. However, it is crucial to account for uncertainties in the model input as long as we lack data, particularly regarding airborne transmission of the coronavirus. In this study, we quantify uncertainties in such simulations to increase their reliability and informative value. We consider this an integral aspect of model validation. This study relies on a model originally introduced in a previous contribution. We adapt it to simulate airborne virus transmission in several everyday situations. The locomotion layer of the model captures crowd management strategies, while its pathogen transmission layer returns the virtual persons’ exposures to pathogens. We conduct a global sensitivity analysis to rank uncertain parameters according to their impact on the exposure risk and employ forward propagation techniques to quantify the output uncertainty. The sensitivity analysis reveals that two model parameters related to the extent and spread of aerosols are essential, whereas a parameter describing the decay of pathogens is barely influential. The forward propagation demonstrates how crowd management alleviates the exposure risk in the analyzed situations. Moreover, we identify aerosol spread as a dominant aspect on which research should focus.
KW - Agent-based modeling
KW - Exposure
KW - Microscopic crowd simulation
KW - Pathogen transmission
KW - Sensitivity analysis
KW - Uncertainty quantification
UR - http://www.scopus.com/inward/record.url?scp=85189683702&partnerID=8YFLogxK
U2 - 10.1016/j.ssci.2024.106524
DO - 10.1016/j.ssci.2024.106524
M3 - Article
AN - SCOPUS:85189683702
SN - 0925-7535
VL - 175
JO - Safety Science
JF - Safety Science
M1 - 106524
ER -