Lanzarotti, Esteban; Rojas, Andrea Pineda; Roslan, Francisco; Groisman, Leandro; Santi, Lucio; Castro, Rodrigo
A multi-scale agent-based model of aerosol-mediated indoor infections in heterogeneous scenarios Journal Article
In: Journal of Simulation, vol. 0, no. 0, pp. 1–19, 2025, ISSN: 1747-7778, (Publisher: Taylor & Francis _eprint: https://doi.org/10.1080/17477778.2025.2476456).
Abstract | Links | BibTeX | Tags: Agent-based model, Airborne transmission, DEVS, Multi-scale simulation, QSS, Viral infection
@article{lanzarotti_multi-scale_2025,
title = {A multi-scale agent-based model of aerosol-mediated indoor infections in heterogeneous scenarios},
author = {Esteban Lanzarotti and Andrea Pineda Rojas and Francisco Roslan and Leandro Groisman and Lucio Santi and Rodrigo Castro},
url = {https://doi.org/10.1080/17477778.2025.2476456},
doi = {10.1080/17477778.2025.2476456},
issn = {1747-7778},
year = {2025},
date = {2025-01-01},
urldate = {2025-07-01},
journal = {Journal of Simulation},
volume = {0},
number = {0},
pages = {1–19},
abstract = {We present a hybrid agent-based and equation-based simulation model to study airborne infection transmission events in heterogeneous indoor spaces. Agents move between different rooms, generating evolving networked social interactions. Suspended aerosols enable both direct and indirect transmission, shaping multi-scale contagion at local (room) and global (building layout) levels within a SEIR process. This approach provides a very flexible platform for dealing with environmental and population heterogeneities. Our model reproduces well-documented real-world contagion events and analytical models in the literature over a wide range of environments (hospitals, offices, restaurants, and classrooms). The model is applied to study transmission patterns in a typical school day, exploring three heterogeneity-driven scenarios: (i) varying break-time activity intensity, (ii) localized ventilation reductions, and (iii) flexible class/break durations, uncovering emerging nonlinear system-level dynamics. Our results show that neglecting heterogeneities can lead to considerable underestimation of attack rates. Such scenarios cannot be modeled with previous agent-based frameworks.},
note = {Publisher: Taylor & Francis
_eprint: https://doi.org/10.1080/17477778.2025.2476456},
keywords = {Agent-based model, Airborne transmission, DEVS, Multi-scale simulation, QSS, Viral infection},
pubstate = {published},
tppubtype = {article}
}