Collaborative Research: Enhancing Earthquake Casualty Predictions: A Novel Modeling Framework Informed by Epidemiology and Local Human-Building Dynamics

This goal of this project is to investigate little-understood mechanisms that lead to many severe injuries during earthquakes to support the development of new, effective interventions to reduce seismic risks. Through this investigation, this project aims to utilize new engineering models to capture the critical injury mechanisms and interactions between humans and infrastructure during earthquakes at fine scales in space and time, focusing on predicting earthquake impacts on health and life. This research has the potential to inform policymaking to design effective hard and soft interventions to protect many communities living in vulnerable buildings close to active seismic areas, like in Los Angeles or the Bay Area, California. In addition, the project offers opportunities for PhD training in interdisciplinary methods in engineering and disaster medicine and a broad dissemination of results to scientists and policymakers. The project embraces equity, diversity, belonging, and inclusion in the research design, recruitment of students, training, and teaching plan. This project integrates civil engineering and disaster medicine concepts, measures, and methods to develop next-generation earthquake casualty models that are more fine-grained and accurate. The novel measures and models will support the design and assessment of novel interventions to reduce risks to health and life. First, the project augments the spatiotemporal granularity of traditionally coarse damage assessments of infrastructure failures to reflect more types of physical mechanisms that lead to earthquake injuries. This part of the project employs both numerical experiments and empirical damage observations of structural and non-structural components. Second, the research elevates the granularity of earthquake injury modeling to predict medical diagnoses and needs rather than just severities, building on a new, more refined taxonomy of earthquake injuries. This part of the project will employ two validated methods to collect granular injury data from experts and field investigations in communities affected by the 2023 Turkey Earthquake. Third, the project will include creation of a hyper-resolution agent-based model coupled with a building dynamics model to explore the effectiveness of hard (e.g., building retrofits) and soft (e.g., earthquake early warning) interventions to reduce injury risks for diverse buildings and populations. Overall, this project distills technical insights for seismic risk reduction, focusing on health and life. The findings will yield insights relevant to communities residing and working in non-ductile concrete frame buildings in the Bay Area, California. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.