Speaker
Description
We develop a next-generation matrix (NGM) framework for evaluating venue access policies that restrict or test attendees based on vaccination status. As both vaccination coverage and contact structures are age-dependent, contact structures at venues will change due to access policies \cite{bootsma2024heterogeneity}. To isolate the effect of selectively excluding unvaccinated individuals from that of reduced attendance, we introduce an attendance reduction benchmark and show that the relative benefit of selective exclusion depends on vaccination coverage, venue structure, and behavioral responses.
Static NGM analysis based on reproduction numbers cannot address peak magnitude or cumulative burden. We therefore embed the NGM transmission structure in a dynamic age-structured SIR model with vaccination rollout and compare infections across policies and enforcement levels. Finally, we extend both frameworks to distinguish vaccine-hesitant and vaccine-accepting unvaccinated individuals with assortative mixing. At the static level, segregation can change the
relative ranking of policies. At the dynamic level, the standard collapsed model systematically underestimates post-release risk, predicting lockdown release weeks too early and leading to ICU occupancy substantially exceeding capacity thresholds. Although illustrated with COVID-19-inspired parameters, the methodology applies broadly to intervention timing under vaccination heterogeneity.
Bibliography
@article{bootsma2024heterogeneity,
author = {Bootsma, Martin and Chan, K. M. D. and Diekmann, Odo and Inaba, Hisashi},
title = {The effect of host population heterogeneity on epidemic outbreaks},
journal = {Mathematics in Applied Sciences and Engineering},
volume = {5},
number = {1},
pages = {1--84},
year = {2024},
doi = {10.5206/mase/16718}
}
