Seyed Mohammad Reza Hosseini Mousavi - M.A. Student, North Tehran Branch of Azad University, Tehran, Iran
Salar Arian-Moghaddam - Ph.D., North Tehran Branch of Azad University, Tehran, Iran

Hospitals constitute an important part of the health care system. During a disaster, their role is even more critical;therefore, it is vital to provide high quality and on-time treatment to injured patients in order to minimise fatalities. Hospital performance estimates (before and during an extreme event) can assist disaster mitigation efforts to provide such level of function in post-disaster recovery process, so it is essential to provide a quantitative measure that will eventually be used by policy makers.Providing a model for evaluating the resilience in a multidisciplinary manner considering variety of subsets has always been a challenging concept in Iran. In case of health care facilities, the complex nature of such systems, as well as, intricate interaction among structural, non-structural and organizational features causes more complications in the phaseof resilience quantification. To achieve this goal, in the current study, a model for quantitative assessment of the probabilistic probability index of seismic resilience of hospitals was presented. Following the mentioned proposed methodology; all structural and nonstructural components of the hospital were evaluated in accordance with the list of items proposed by WHO in the HSI checklist. Then, a questionnaire-based approach has been applied to utilize Iranian expert s opinion related to the time and cost of repairs or replacement of different sources of vulnerability with the new system. Finally, by using collected and processed data as the input of resilience measurement, probabilistic resilience index has been calculated using the existing selected fragility curves and the proposed model. The index of the resilience was calculated for different parts of a sample hospital considering different damage states and several hazard levels in terms of earthquake return periods. The outputs are ranked and the components corresponding to the lowest probability resilience index are identified in their subset. The results show that the recovery time, cost of repair and cost of replacement in case of complex systems such as hospitals is strongly dependant to the localized indigenous features related to the maintenance and procurement. This paper can be considered as the primary efforts towards the provision of critical data for quantification of seismic resilience

Resilience, Recovery, Structural components, Nonstructural components, Vulnerability