Effective emergency response policies for hospital systems in the wake of time-varying seismic hazard

Worldwide, earthquakes have caused tens or even hundreds of thousands of injuries in matter of minutes in countries such as China in 2008 and Turkey in 1999. Because of their suddenness and their long and uncertain recurrence times, large earthquakes pose more critical challenges for emergency response than other natural disasters, for instance, hurricanes or wildfires. This dissertation develops novel models that capture key processes that govern the emergency response of complex urban centers to large earthquakes, and it also demonstrates through case studies how these methods can aid emergency managers and policymakers to create better risk mitigation measures. The models and case studies in this dissertation are built using an interdisciplinary two-part approach. The first part combines engineering with seismology to improve existing methods for seismic hazard assessment. I develop a time-dependent model that characterizes complex space and time tectonic interactions of large earthquakes. By applying this model to the subduction fault offshore the coast of Peru, I show that these developments successfully capture seismic gap effects, leading to variations in seismic hazard predictions by a factor of four. Then, I construct a Bayesian parameter estimation technique that leverages synthetic earthquake catalogs to supplement the existing limited historical catalogs for large earthquakes. As part of the dissertation, I built the synthetic catalogs for the subduction fault in Peru using physics-based simulations based on the rate-and-state friction law and high-performance computing. My results show that these synthetic catalgs reduce the uncertainty in the parameter estimates by a factor of two and also improve parameter median estimates, triggering additional variations in the time-dependent hazard estimates by up to 40\%. The second part of this dissertation merges engineering with emergency medicine to model emergency response and design effective plans to treat and transfer patients more effectively after an earthquake. First, I extend the performance-based earthquake engineering formulation from focusing on single buildings to multiple buildings. Then, I exploit the variables' interdependence structure to model multiseverity earthquake casualties with computational efficiency. Applying the model to Lima demonstrates that this model can outperform widely used empirical fatality formulas for countries where earthquake fatality data is sparse and not recent. Next, I develop a network model that captures critical features of an earthquake emergency response by combining the multiseverity casualty model with predictions of post-earthquake hospital functionality based on an extensive hospital infrastructure dataset in Lima. The model identifies the neighborhoods that will most likely be underserved by healthcare services after an earthquake. Finally, I formulate an optimization procedure that designs strategies for patient transfers, ambulance usage and deployment of field hospitals to make treatment more effective after an earthquake. A case study demonstrates that high-coordination emergency plans in large urban centers can reduce patient waiting times by a factor of three. I envision that policymakers and emergency planners who leverage the methods and findings in this dissertation will be able to develop more robust risk reduction programs, protect their most vulnerable residents, and potentially save more lives after an earthquake.

Advisor: Kiremidjian Anne S. (Anne Setian) 
Baker Jack W. 
Deierlein Gregory G. (Gregory Gerard)