Project Abstract

This project will assess the earthquake risk of hospitals and their ability to sustain operations after future large earthquakes. The project will be led by the NYU Disaster Risk Analysis Lab, the World Bank’s Disaster Risk Management Division, and the Earthquake Engineering Research Institute (EERI)’s Public Health Working Group. The project’s main goal is to apply robust disaster risk analysis techniques on hospital datasets to better understand post-disaster hospital capacity. The project will investigate new risk metrics relevant to inform practical risk mitigation policy implementation and emergency planning, e.g., mobilizing patients from neighborhoods with little hospital capacity to high hospital capacity. The goal is to inform communities on how to mitigate not only potential economic losses, as currently done in practice, but also potential functional and societal impacts.

Project Description & Overview

This project will focus on conducting earthquake risk analysis in two cities’ hospital systems. One case study will be located in the Bay Area, California, and the other one will be in a developing country defined according to data availability. The project will have four parts:

• (A) Curating and completing datasets for assessing earthquake risk: The students will be provided with initial datasets that map hospital infrastructure and its seismic vulnerabilities. Students will extend these datasets, with guidance from their advisors, to be integrated into disaster risk analyses. 
• (B) Conducting earthquake risk analysis: Students will use the datasets to conduct earthquake risk analysis using open-source software like OpenQuake or SimCenter Tools. The analysis will incorporate seismic hazards and vulnerability models to quantify risk comprehensively, e.g., probability of hospital disruptions in a given year, return period of hospital collapse. 
• (C) Conceptualizing and assessing hospital system risk metrics: Students will review scientific reports and emergency response articles and define metrics to assess hospital system risk with the project mentors. The students will carefully examine what metrics can be estimated with risk analysis and use their results to quantify them. For example, students can assess the spatial distribution of post-earthquake hospital capacity to investigate potential disparities in hospital accessibility after earthquakes. 
• (D) Visualizing hospital system risk: Students will generate visualizations to communicate their findings to stakeholders. An integral part of risk analysis is using results to inform policy, e.g., retrofitting hospitals. Thus, the students will carefully prepare visualizations to showcase their findings. Also, the students will draft recommendations for preparedness and risk mitigation in hospital systems, with guidance from their advisors.

Datasets

Disaster Risk Analysis requires hazard, vulnerability, and exposure data. Data for hazard analysis will be provided. Vulnerability and exposure data will be provided partially. Students will work on completing and curating datasets for vulnerability and exposure. Specifically, the following will be provided:

• (A) Bay Area
  • (A.1) Dataset with hospitals and their locations
  • (A.2) Seismic hazard data
• (B) Another city in a developing country
  • (B.1) Dataset with hospitals, their locations, and their vulnerabilities. This dataset may contain proprietary information and be provided under an NDA.
  • (B.2) Seismic hazard data

Competencies

Students will require a background in statistics and risk analysis. Otherwise, they are highly encouraged to enroll in the Disaster Risk Analysis and Urban Systems Resilience Class (CUSP-CX 8006). Please get in touch with Professor Ceferino for further inquiries about competencies.

Learning Outcomes & Deliverables

• Learning Objectives
  • Understand the data requirements for conducting regional disaster risk analysis
  • Build skillsets for hands-on disaster risk quantification
  • Develop risk communication and visualization skills relevant for policymaking in disaster risk management
• Deliverables
  • Documented datasets with hospital information to conduct disaster risk analysis
  • Maps visualizing the risk study
  • Presentations, including one with a wider audience from the World Bank
  • Progress and final reports

Students

Sai Charan Kukunoor, Dan Mao, Xinlu Xu