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Empirical fatality model for Indonesia based on a Bayesian approach
Sengara I.W.a, Suarjana M.a, Yulman M.A.a, Gashemi H.b, Ryu H.b
a Civil and Environmental Engineering Faculty, Institut Teknologi Bandung, Lebak Siliwangi, Coblong, Bandung City, West Java, 40132, Indonesia
b Geoscience Australia, Canberra, 2601, Australia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2017 The Author(s).An empirical fatality model for Indonesia has been developed by relating the macroseismic intensity to the fatality rate using compiled sub-district level fatality rate data and the numerically simulated ground-shaking intensity for four recent damaging events. The fatality rate data were compiled by collecting population and fatality statistics of the regions affected by the selected events. The ground-shaking intensity was numerically estimated by incorporating a finite-fault model of each event and local site conditions approximated by topographically based site amplifications. The macroseismic intensity distribution of each event was generated using ShakeMap software, combining a selected pair of ground motion prediction equations and ground motion to intensity conversion equations. The developed fatality model is a Bayesian generalized linear model in which the fatality rate is assumed to follow a mixture of Bernoulli and gamma distributions. The model was validated by calculating the fatalities in past events from the EXPO-CAT catalogue and comparing the estimates with the EXPO-CAT fatality records. Although the model can provide an estimate of the range of fatalities for future events, it needs ongoing refinement by the incorporation of additional fatality rate data from past and future events.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1144/SP441.9[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]