An empirical model for fatality estimation of earthquakes in Iran

In order to estimate the human loss after an earthquake to address risk mitigation and response measures, appropriate models should be developed based on local conditions. In this paper, an empirical model for estimating the mortality rate based on shaking related parameter (PGA) is presented for Iran. For this purpose, a reliable fatality database of past earthquakes occurred in the country (between 1962 and 2017) along with corresponding ground motion shaking maps were compiled. It includes information of 88 fatal earthquakes in different cities and villages, compiled from reliable resources. Three distinct functional forms including log-linear, exponential and lognormal cumulative distribution were applied to be fitted to data. To evaluate the appropriateness of different functional forms a residual analysis was performed. The results indicate that the log-linear model shows the best performance. Additionally, a sensitivity analysis was performed to evaluate the impact of events with highest contributions in database on fatality function. The results depicted that excluding data of Bam (2003), Iran Earthquake may reduce fatality ratio to about 5%. This can be related to the paucity of data in high acceleration ranges (near 800 cm/s(2)) in the database. Finally, two separate curves have been developed for day and night. As expected, the result depicted that fatality ratio in day time is much lower than the night hours. The proposed model can be used for rapid loss assessment in Iran and other countries with similar construction types to provide an initial estimation of deaths after earthquakes or determining the priorities for risk reduction.