Estimating fatality rate of house collapse based on human activity pattern
Efficient estimation of casualties in earthquake scenarios involves the identification of mortality rate variations among individuals in different spatial states,which may be achieved through the simulation and replication of population spatial distributions during earthquakes.Based on the human activity pattern model set which was generated from the China Human Activity Pattern of Rural Residents Survey(HAPRRES),we simulated individuals'activities during 13 earthquakes in China from 2005 to 2018 to estimate the spatial state snapshot distributions of the earthquake affected areas at their onset moment.These estimates allowed the optimization of mortality rate models by distinguishing between sleeping and awake people in earthquake-damaged houses.The optimized mortality models reveal that the mortality rate for individuals asleep(5.16‰)is six times higher than that for individuals awake(0.85‰)in seismically collapsed houses.Notably,when the adobe houses are destroyed,the mortality rate of sleeping people(1.60％)is 11.9 times higher than that for the awake people(1.34‰).Conversely,during the destruction of non-adobe houses,the mortality rate for the sleeping people(2.35‰)is 4.3 times higher than that of the awake people(0.54‰).An uncertainty analysis proves the robustness of the mortality rate model.As this explorative research demonstrates,incorporating human activity pattern model will help to improve the rapid estimation of casualties of sudden disasters.
human activity patternearthquakebuilding damagemortality rateadobe house
万方数据
维普
