Hybrid epidemic simulation framework coupling equation-based and individual-based models
Abstract
Mass gathering events (MGEs) can create intense, short-lived transmission hotspots whose effects propagate through urban populations. Quantifying these effects requires linking fine-scale interactions during gatherings with epidemic transmission across metropolitan mobility networks. We developed a hybrid multiscale simulation framework coupling empirically derived individual-based contact networks for MGEs with a stochastic metapopulation susceptible-exposed-infected-recovered (SEIR) model. Using population and commuting data from Madrid, Spain, we investigated how event-related transmission affects epidemic dynamics and district-level invasion. Across the scenarios examined, MGEs increased epidemic peak incidence and accelerated epidemic progression, although the magnitude of these effects depended on event-specific contact patterns and background transmissibility. Dense contact patterns produced greater epidemic amplification, whereas measures reducing close-contact interactions weakened these effects. MGEs also advanced epidemic invasion across districts and increased the temporal synchronization of arrival times, producing a more synchronized metropolitan epidemic wave. The association between MGEs and earlier district-level invasion was partly explained by the size of the event-generated epidemic seed. The main patterns persisted across the epidemiological parameter ranges examined. The framework provides a multiscale approach for investigating how mass gathering management may influence metropolitan epidemic dynamics.
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BibTeX
@misc{kwak2026hybrid,
title = {{Hybrid epidemic simulation framework coupling equation-based and individual-based models}},
author = {Jaeyoung Kwak and Michael H. Lees and Chin Chun Ooi and Wentong Cai},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.35162},
eprint = {2609.35162},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.35162},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Hybrid epidemic simulation framework coupling equation-based and individual-based models
AU - Jaeyoung Kwak
AU - Michael H. Lees
AU - Chin Chun Ooi
AU - Wentong Cai
PY - 2026
DA - 2026/09/28
PB - arXiv
DO - 10.48550/arxiv.2609.35162
UR - https://arxiv.org/abs/2609.35162
AB - Mass gathering events (MGEs) can create intense, short-lived transmission hotspots whose effects propagate through urban populations. Quantifying these effects requires linking fine-scale interactions during gatherings with epidemic transmission across metropolitan mobility networks. We developed a hybrid multiscale simulation framework coupling empirically derived individual-based contact networks for MGEs with a stochastic metapopulation susceptible-exposed-infected-recovered (SEIR) model. Using population and commuting data from Madrid, Spain, we investigated how event-related transmission affects epidemic dynamics and district-level invasion. Across the scenarios examined, MGEs increased epidemic peak incidence and accelerated epidemic progression, although the magnitude of these effects depended on event-specific contact patterns and background transmissibility. Dense contact patterns produced greater epidemic amplification, whereas measures reducing close-contact interactions weakened these effects. MGEs also advanced epidemic invasion across districts and increased the temporal synchronization of arrival times, producing a more synchronized metropolitan epidemic wave. The association between MGEs and earlier district-level invasion was partly explained by the size of the event-generated epidemic seed. The main patterns persisted across the epidemiological parameter ranges examined. The framework provides a multiscale approach for investigating how mass gathering management may influence metropolitan epidemic dynamics.
ER -