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Updated: Nov 3, 2025

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Quantifying Socioeconomic Impact of a Tornado by Estimating Population Outmigration as a Resilience Metric at the
Hassan Masoomi1, John W van de Lindt2, Lori Peek3
1PhD Candidate, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523-1372, USA.
Abstract:
Policymakers, community leaders, engineers, and researchers have gained interest in understanding tornado-resilient buildings, in part because of the number of deadly and destructive tornadoes over the last decade. In addition to direct losses, such as deaths and damages, tornadoes may also cause many indirect losses as a result of the highly coupled networks within communities. When networks are disrupted, this can cause population outmigration which, if significant and long-lasting enough, may exacerbate a community's indirect socioeconomic losses over time. In this study, a community was coarsely modeled with its physical-socio-economic attributes to study population outmigration as a community resilience metric. In this regard, recovery of affected physical networks (i.e., electric power network, water network, and buildings) in the wake of a tornado was investigated and linked to students, household residents, and employees as socioeconomic agents within the community. The probability of outmigration for each household was assessed based on the probability that these three agents in the household are affected over a prescribed time period from the occurrence of the hazard to the full restoration of the community. Finally, the potential population outmigration for the community was assessed by aggregating all the households in the community. The results of such an analysis can be used as a decision-making tool to prioritize hardening of existing infrastructure in a community or optimize master planning of new communities and demonstrates the importance of physical-socio-economic interactions in resilience studies.
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