Modeling Housing Community Recovery Using a Stochastic Queueing Model

Post-earthquake housing community recovery monitoring is very important, especially since the housing sector usually represents 50 percent of the total monetary disaster loss. However, the very scarce recovery data, in addition to the complexities of the recovery process make modeling housing community recovery very difficult. Furthermore, most recovery models are only applicable to developed countries such as the US. In this project, I develop a novel stochastic queuing model that accounts for the total number of damaged buildings, the damage distribution, resource constraints and reconstruction prioritization strategies. The model was applied to seven regions that were affected by the 2018 Lombok earthquakes. which destroyed over 226,000 houses.

The journal paper for this project is published in the journal Earthquake Spectra, and can be found here.

This article also received the honorable mention for the EERI 2021 Graduate Student Paper Award. See the announcement here.

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About Me

Stanford PhD graduate. Data Scientist @ Lacuna Technologies. Lecturer @ Stanford