Framework for Recovery Assessment of Hospital Cluster Following a Scenario Earthquake Event

Modeling the recovery process of a communitys infrastructure after the occurrence of extreme events is now at the forefront of research. Estimating post-disaster recovery of either single or multiple infrastructure in a community requires proper flow and interaction of information of the physical, economic and social components of the involved sectors. Understanding this recovery process is essential, particularly for critical infrastructure, such as a hospital, which is vital for a communitys well-being. In this study, a full seismic functionality and recovery process of a hospital cluster, located in Shelby County, Memphis, TN, is quantified and assessed using a comprehensive framework. The hospital functionality assessment encompasses both quantity and quality of the hospitalization service. The quantity of the hospitalization service is presented as a function of the number of staffed beds, which is expressed as a combination of the staff, space and supplies availability while the quality measured by the patient waiting time. The demand on the hospitals, estimated based on a newly developed patient-driven model, which considers patient constraints, patient-to-hospital connection, hospital availability in addition to hospital cluster interaction. The hospitals dependency on other infrastructure during the recovery process and the interaction between different hospitals is modeled. Socioeconomic data related to hospital operation and recovery after the earthquake are used for the assessment. The presented framework accounts for limitation in resources such as the repair crews within the community, expected economic return for each hospital, and interdependencies between the different lifelines including the investigated hospitals. The results are consequently used within a testbed to support assessment of community resilience in The Interdependent Networked Community Resilience Modeling Environment (NIST-CORE), which is a computational platform currently being developed to compute various resilience goals.Funding for this study was provided as part of Cooperative Agreement 70NANB15H044 between the National Institute of Standards and Technology (NIST) and Colorado State University. The content expressed in this paper are the views of the authors and do not necessarily represent the opinions or views of NIST or the U.S Department of Commerce. Researchers who helped with gathering data for Shelby County are acknowledged