Epidemic-Aware Evacuation Allocation: An Integer Program with Endemic-Epidemic Model-Derived Risk Constraints

Mass evacuation during a natural hazard can concentrate displaced populations in a limited number of destinations, altering mobility and contact patterns in ways that may increase infectious disease transmission. Existing evacuation models largely emphasize logistical considerations, while epidemic models typically treat population distribution as fixed, leaving limited integration between evacuation decisions and the epidemic risk those decisions create. This study proposes an epidemic-aware evacuation allocation framework to assign evacuees to shelters during co-occurring hurricanes and pandemics. A mixed-integer linear program is proposed that utilizes system-level reproduction numbers estimated using a spatio-temporal endemic-epidemic (EE) model under candidate evacuation scenarios. Regional transmission dynamics are estimated using the EE model with mobility-derived time-varying geographic coupling weights. For each candidate evacuation plan, post-evacuation population and mobility are updated, regional reproduction numbers are recalculated, and an effective, population-weighted system-level reproduction number, proposed as a heuristic epidemic risk index, is enforced via constraints. The framework is evaluated using a five-region synthetic study and a 30-region Hurricane Sally case study based on GPS mobility and COVID-19 data. Results show that alternative routing decisions can produce different post-evacuation epidemic risks even when the same populations are evacuated to the same total destination capacity. The proposed framework consistently maintained system-level epidemic risk index below a user specified threshold while achieving lower post-evacuation risk than the logistics-only allocation benchmark.

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Publication Details

Journal
Safety
Published
2026-11-11
DOI
https://doi.org/10.3390/safety12060147
Primary Topic
Facility Location and Emergency Management
Type
article
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article

Epidemic-Aware Evacuation Allocation: An Integer Program with Endemic-Epidemic Model-Derived Risk Constraints

Seyed Reza Abazari, Omer Arda Vanli, Davison Elijah Tsekeni
Safety
Facility Location and Emergency Management
article

Epidemic-Aware Evacuation Allocation: An Integer Program with Endemic-Epidemic Model-Derived Risk Constraints

Seyed Reza Abazari, Omer Arda Vanli, Davison Elijah Tsekeni
article en

Abstract

Mass evacuation during a natural hazard can concentrate displaced populations in a limited number of destinations, altering mobility and contact patterns in ways that may increase infectious disease transmission. Existing evacuation models largely emphasize logistical considerations, while epidemic models typically treat population distribution as fixed, leaving limited integration between evacuation decisions and the epidemic risk those decisions create. This study proposes an epidemic-aware evacuation allocation framework to assign evacuees to shelters during co-occurring hurricanes and pandemics. A mixed-integer linear program is proposed that utilizes system-level reproduction numbers estimated using a spatio-temporal endemic-epidemic (EE) model under candidate evacuation scenarios. Regional transmission dynamics are estimated using the EE model with mobility-derived time-varying geographic coupling weights. For each candidate evacuation plan, post-evacuation population and mobility are updated, regional reproduction numbers are recalculated, and an effective, population-weighted system-level reproduction number, proposed as a heuristic epidemic risk index, is enforced via constraints. The framework is evaluated using a five-region synthetic study and a 30-region Hurricane Sally case study based on GPS mobility and COVID-19 data. Results show that alternative routing decisions can produce different post-evacuation epidemic risks even when the same populations are evacuated to the same total destination capacity. The proposed framework consistently maintained system-level epidemic risk index below a user specified threshold while achieving lower post-evacuation risk than the logistics-only allocation benchmark.

SafetyVol. 12(6)
Florida A&M University - Florida State University College of Engineering (US)
Facility Location and Emergency Management
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