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Structures present a risk during seismic events from partial or full collapse that can cause death and injury to the occupants. The United States Geological Survey (USGS) has collated data on deaths from and magnitudes of earthquakes. These data have not previously been analyzed to establish any relationships between fatality tolls or fatality rate...
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... conclusion reached from the data presented in these studies is the physical separation between the Memphis population center and the known active faults should prevent the extreme death tolls such as occurred in Tangshan, but even moderate earthquakes in this region have the potential to cause fatalities in Memphis. Shannon and Pyle, (1993, 111, figure 11.1) provide d etails of motor vehicle deaths. ...
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... the 1915 Avezzano earthquake the Italian authorities collected statistical data on the locations and the rates of death in the various villages scattered in the fatality area (ING-SGA 2000). This well-documented data provided point type data that were extremely useful in calibration (Figure 1). ...
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... summary, two critical lines have been defined from the data shown in Figure 1. Plot 1 line represents the function that defines the upper bound of Region 2 for twentieth century data. ...
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... were on average five fatal earthquakes per year at the start of the twentieth century and eighteen fatal earthquakes per year at the start of the twenty-first century. Of the estimated minimum two million people who died in the twentieth century, almost half died in ten events and one quarter died in two events (Jones et al, 1993). ...
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... intraplate area typically has more circular isoseismals and the interplate area typically has more elliptical. The elliptical fatality curves for Avezzano shown on Figure 1 suggest a 2 to 1 ratio. The Californian data suggests a ratio between 5 to 1 and 8 to 1 (Algermissen 1972Part 1 Isoseismal Studies, Hanks and Johnston 1992, Peek-Asa et al 2002. ...
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Citations
... The earliest empirical loss curve was introduced by Kawasumi in 1954, establishing a linear relationship between potential fatalities and the number of destroyed buildings in Japan 18 . Subsequent scholars have refined and expanded upon this foundational work, increasing the complexity of the expressions and establishing relationships between various earthquake parameters and exposure, including functions related to magnitude [19][20][21] , ground motion 22,23 , and earthquake intensity [24][25][26] . Earthquake intensity is a macro indicator that reflects the severity of surface damage caused by an earthquake. ...
... Earthquake death assessment models can be divided into two categories: empirical models based on seismic parameters and analytical models based on building vulnerability. The first type of model generally performs regression analysis based on historical earthquake damage data, and then obtaining empirical equations for magnitude or intensity, without considering the distribution of disaster-bearing bodies and their vulnerability [3][4][5][6]. The second type of model considers detailed building vulnerability data and estimates the number of earthquake deaths based on the vulnerability of different components and building structures in earthquakes [7][8][9][10][11]. ...
... 4) Define the spatial function of beetle whiskers: (3) where lt x is the position of the left antennae when searching for the best solution t times, rt ...
In recent years, China has experienced frequent catastrophic earthquakes, causing huge casualties. If the death toll can be quickly predicted after a disaster, then relief supplies can be delivered in a timely and reasonable manner, and the death toll and property losses can be minimized. Therefore, rapid and effective prediction of earthquake deaths plays a key role in guiding post-earthquake emergency rescue. However, there are many factors affecting the number of deaths in an earthquake. Aimed at this issue, a prediction model for earthquake deaths based on extreme learning machine (ELM) optimized by principal component analysis (PCA) and beetle antennae search (BAS) algorithm has been proposed in this study. Firstly, this study selected sample data of destructive earthquakes in mainland China in the past 50 years, then PCA was used to reduce the dimensionality of the factors affecting earthquake deaths, the principal components with lower contribution rates were removed, and the principal components with higher contribution rates were used as the input variables of ELM. Meanwhile, the earthquake deaths were used as the output variable, and the connection weights and thresholds of ELM was optimized using BAS. Finally, the prediction model for earthquake deaths based on PCA-BAS-ELM was established. The established model was used to predict the test samples. The results showed that the prediction results of PCA-BAS-ELM model had a higher fit with the actual values, and its mean square error, mean absolute percentage error and root mean square error were 2.433, 2.756% and 5.443, respectively, which suggested higher prediction accuracy.
... Large-magnitude earthquakes cause extensive damage, loss of life, and economic losses in developing and developed countries [1][2][3][4][5]. Examples include the earthquakes in Colombia (1999, 6.2 Mw, 2000 victims) [6], [9], China (Wenchuan, 2008, 87,476 victims, USD 85 billion) [7], Chile (2010, 8.8 Mw, 521 victims, USD 30 billion) [10], Tohoku (2012, 9 Mw, 15,000 victims, USD 411 billion), and Nepal (2015, 7.8 Mw, 8000 victims) [11]. ...
Earthquake catastrophe bond pricing models (ECBPMs) employ extreme value theory (EVT) to predict severe losses, although studies on EVT’s use in ECBPMs are still rare. Therefore, this study aimed to use a mini-review approach (MRA) to examine the use of EVT and identify the gaps and weaknesses in the methods or models developed. The MRA stages include planning, search and selection, analysis, and interpretation of the results. The selection results showed five articles regarding the application of EVT in ECBPMs. Furthermore, the analysis found the following: First, the generalized extreme value (GEV) could eliminate extreme data in a period. Second, the trigger model using two parameters is better than one, but the study did not discuss the joint distribution of the two parameters. Third, the autoregressive integrated moving average (ARIMA) allows negative values. Fourth, Cox–Ingersoll–Ross (CIR) in-coupon modeling is less effective in depicting the real picture. This is because it has a constant volatility assumption and cannot describe jumps due to monetary policy. Based on these limitations, it is hoped that future studies can develop an ECBPM that reduces the moral hazard.
... Empirical fatality models provide an estimation of death toll based on correlation of earthquake magnitude or shaking related parameters with the affected population. There are several empirical fatality models in literature which differ in functional forms and variables [7,11,12,14,[36][37][38][39][40][41]. There are two important challenges regarding the aforementioned models. ...
This paper presents the results of a study carried out to develop an empirical fatality model based on data of fatal and non-fatal earthquakes occurred in Iran since 1962. Two reliable databases (RAISE-DAT and REXPO-DAT) which incorporate the number of deaths and the affected population in the past earthquakes of Iran were compiled to make correlation between fatality rate and shaking related parameters. The uncertainties of these parameters (i.e., the number of fatalities in the past earthquakes and the ground motion values provided by the ShakeMap) were considered in the analysis, using the fuzzy regression and Monte Carlo simulation tools. In addition, the appropriateness of three distinct parameters including PGA, PGV and MMI were examined to be employed in the fatality model. The results show that PGA represents the best estimation of fatality (especially for strong earthquakes), while the other parameters (PGV and MMI) underestimate the fatality rate. As a case study, the model was applied in the Ahar-Varzaghan (6.5 Mw) 2012, Iran earthquake. The result shows a good agreement between the actual number of deaths and the estimated fatality. The proposed model can provide an initial assessment of death toll after destructive earthquakes. This is important for organizing rescue and relief activities during golden hours' after an earthquake. Accordingly, the model is used for rapid loss assessment system of Iran's earthquakes, called RAISE. The model can also be used for simulation potential impacts of earthquakes; therefore, it can be employed for seismic risk mitigation planning in Iran.
... Based on the data of strong global earthquakes in the 20th century, Samardjieva and Badal [9] and Badal et al. [27,28] used the method of Christoskov et al. [26] to establish the fatality estimation model. Similar methods with the relationship between fatality and seismic magnitude were also used by Oike [29] and Nichols and Beavers [30]. Bastami and Soghrat [31] then replaced the magnitude in Christoskov et al. [26] with peak ground acceleration to estimate fatalities for Iran. ...
... which is held to be the range of intensity likely to cause fatalities. To develop the earthquake fatality ratio r(I) model for Mainland China, we tested three most commonly used models: (1) the logarithmiclinear model, log(r) = β + θ⋅I [9,27,32]; (2) the logarithmic-exponential model, log(r) = β⋅exp(θ ⋅I) [24,30]; and (3) the lognormal cumulative ...
To rapidly estimate fatalities following an earthquake and provide adequate emergency response and medical rescue, a suitable model should be developed according to local data and physical conditions. Mainland China is divided into five regions based on the regionalization of tectonic background, seismic activity, and development level. This study develops several earthquake fatality ratio estimation models for different regions using 377 earthquake fatalities and population exposure data from 1951 to 2018 provided by the Mainland China Composite Damaging Earthquake Catalog. The earthquake fatality records are normalized by the Human Development Index to the year 2018 level. Because the fatality records of a few catastrophic events have a negative impact on the regression results of all events, we also develop fatality ratio estimation models, especially for catastrophic earthquakes. Furthermore, we use the recorded fatalities of two example periods to verify the applicability of the fatality ratio estimation models. The results show that more than 85% of estimations are within one order of magnitude compared to the records. Finally, based on the verified model and the normal cumulative distribution method, we also try to determine the earthquake emergency response level. We then perform a rapid estimation of fatalities for the 2019 Changning Ms 5.8 earthquake, obtaining an expected result. The applicability of the proposed model to post-earthquake rapid fatality estimation and disaster assessment of earthquake scenarios is expected to play an important role in future earthquake relief planning and post-earthquake rapid emergency response of the Chinese government.
... Loss of life is an unavoidable aspect of the consequences of a catastrophe. In terms of an earthquake, normally, the greater the seismic intensity, the more severe the damage to construction and the larger the number of deaths and injuries [41,42]. In addition to local population density and building structure types, other factors closely associated with earthquake casualties include ground motion intensity, local geological and geomorphic conditions, the distance to the seismic faulting location and the timing of earthquake occurrence, etc. [7,36,[43][44][45][46][47][48]. ...
The growing densities of human and economic activities in cities lead to more severe consequences when a catastrophe such as an earthquake occurs. This study on urban seismic risk evaluation is carried out from the perspective of the direct loss caused by disasters in urban areas, including the measurement of both the expected direct economic loss and loss of life in the face of characteristic earthquakes. Aiming to estimate, quantify and visualize the earthquake risk in each unit of urban space, this research proposes to assess urban seismic risk by integrating the direct economic loss and the loss of statistical life in a disaster, with consideration of diverse earthquake frequencies. Empirical research of the proposed assessment framework and corresponding models is then conducted to measure urban seismic risk in Xiamen, China. Key findings of the case study include the expected direct economic losses and the expected number of deaths in three characteristic earthquakes, their estimated spatial distributions, the average loss of the value of a statistical life (VSL) of one average local resident and the overall seismic risk distributions in Xiamen.
... Here, the fatality ratio is defined as the number of deaths or missing to the total number of affected population in the each affected zone. The second model is exponential which is similar to what was proposed by Nichols and Beavers (2003) for defining bounding function. The third model has lognormal cumulative distribution. ...
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/s2) 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.
... We chose all 43 structure types in China mainland to assess, which are far more than the number of the types in the previous studies [35]. Although the structure types of the WHE project are suitable for the most region of the world, it also lacks some structures that Chinese characteristic structure, such as the national civil structure, the old Tibetan house and the national brick-wood structure. ...
This study aims to analyze and compare the importance of feature affecting earthquake fatalities in China mainland and establish a deep learning model to assess the potential fatalities based on the selected factors. The random forest (RF) model, classification and regression tree (CART) model, and AdaBoost model were used to assess the importance of nine features and the analysis showed that the RF model was better than the other models. Furthermore, we compared the contributions of 43 different structure types to casualties based on the RF model. Finally, we proposed a model for estimating earthquake fatalities based on the seismic data from 1992 to 2017 in China mainland. These results indicate that the deep learning model produced in this study has good performance for predicting seismic fatalities. The method could be helpful to reduce casualties during emergencies and future building construction.
... Scholars have discussed the factors that affect earthquake fatalities, which include 85 magnitude, intensity, initial time, population exposure, housing fragility, and individual factors 86 (Oike, 1991;Nichols, 2003). Moreover, scholars have considered as many factors as they can 87 when modelling. ...
The rapid estimation of earthquake fatalities using earthquake parameters is the core basis for emergency response. However, there are numerous factors affecting earthquake fatalities, and it is impossible to obtain an accurate estimation result. The key to solve this problem is quantifying the uncertainty. In this paper, we proposed a new method to estimate earthquake fatalities and quantify the uncertainty based on basic earthquake emergency scenarios. The accuracy of the model is verified by earthquake that occurred during recent year. The preliminary analysis and comparison results show that the model is more effective and reasonable and can also provide a theoretical basis for post-earthquake emergency response.
... Based on the casualty rate (injuries/deaths) and the logarithmic-linear relationship of magnitude, Christoskov and Samardjieva (1984) assumed that the prediction of death toll was close to the expected accuracy, then they calculated the number of 5 injuries by the number of deaths. Similarly, Nichols and Beavers (2003) used magnitude as an indicator of ground motion intensity. By analysing the earthquakes that took place in the 20th century such as Messina earthquake in 1908, Avezzano earthquake in 1915 and Tangshan earthquake in 1976 etc., they created a threshold curve of death toll about the magnitude in the earthquake. ...
In order to make a scientific emergency strategic decision after an earthquake, casualties need to be estimated rapidly. Asia is the most earthquake-prone continent in the world. In this paper, by spatial statistic and regressive analysis of historical Asian earthquake data from 1990 to 2012, vulnerability curves portraying the empirical relationship between the magnitude of an earthquake event and the casualty rate caused by it were created for countries of six-groups and the Quick Assessment Model of Earthquake Casualties for Asia (QAMECA) was developed. The casualty rate was defined as the ratio of the sum of injuries and deaths in an earthquake to the number of people living in the earthquake-affected region. Thirty-one earthquake events from 2013 to 2016 were used to validate this model, and the validation results were good with actual casualties of twenty-one were within the range estimated by the model and the biases of eight out of ten were less than one hundred percent. The two input parameters of QAMECA were magnitude and location of epicenter of an earthquake and earthquake casualties can be estimated immediately after earthquake has occurred. As a consequence, QAMECA can be used to estimate earthquake casualties for Asian countries and aid decision making in international emergency relief in the future.
