Kumamoto Earthquake Research Articles

Experimental investigations on the influence of embedment depth and frequency on the dynamic behaviour of tunnels under repeated shaking events

ABSTRACT Recently, occurrence of repeated shaking events such as the Kobe earthquake (1995), the Wenchuan earthquake (2008), the Chi-Chi earthquake (1999) and the Kumamoto earthquake (2016), Kahramanmaras earthquake (2023), etc., posed a severe threat to the safety of infrastructures. Studies on the influence of repeated shaking events on underground structures are minimal. Considering the above, tunnel-soil interaction under repeated shaking events is attempted in the study. One-gram shaking table tests were conducted in this study by varying loading frequency (5 Hz, 10 Hz) and tunnel embedment depth (H/W − 0.85 and 1.2 where H is the tunnel embedment depth and W is the width of the tunnel) and subjected to incremental shaking conditions, i.e. 0.2 g, 0.3 g and 0.4 g. A tunnel-embedded ground with 60% relative density was prepared and instrumented with conventional sensor schemes and a non-contact-based 2D digital image correlation technique. It was observed that the loading frequency and tunnel embedment influences tunnel’s performance during repeated shaking events. About 37% to 62.4% increment in tunnel displacement was observed in the case of H/W-0.85, and 20% to 29% increment in tunnel displacement was observed for H/W-1.2 when subjected to incremental acceleration shaking, i.e. 0.2 g to 0.4 g for varying embedment depth conditions.

Comparison of empirically-based and physically-based analyses of coseismic landslides: A case study of the 2016 Kumamoto earthquake

This study compares the performance of empirically- and physically-based methods for predicting coseismic landslides around Aso caldera during the 2016 Mw 7.0 Kumamoto earthquake. The physically-based method couples a regional-scale wave propagation simulation with a site-scale Newmark-type sliding analysis, while the empirically-based method predicts sliding displacements based on seismic recordings and/or ground motion prediction equations. By using the well-documented landslide inventory, the predictive capacity of each method is quantitatively assessed.The case study demonstrates that the physically-based method has the advantage of simulating complicated near-fault and topographic effects. It captures around 44% of observed landslides at the caldera rim, which is significantly better than the 20% captured from the empirically-based prediction. Both methods have similar prediction performance, capturing around 56% actual landslides at the central cone region. The empirically-based method is simple to use and provides fast landslide prediction. It can be further improved by incorporating a simple prediction model for the topographic amplification effect, which increases the percentage of captured landslides by around 8% across the caldera rim.

Quantitative strong motion simulations at three locations in downtown Mashiki during the 2016 Kumamoto Earthquake (Mw 7.0) based on the nonlinear ground response analyses with soil liquefaction

The mainshock of the 2016 Kumamoto Earthquake (Mw 7.0) caused extensive damage to buildings in downtown Mashiki, Kumamoto Prefecture, Japan. The heavy building damage in the area was associated with both strong ground motion and building response characteristics. Fortunately, there were two strong motion stations in the area and the observed records during the mainshock were distributed, showing peak ground velocities exceeding 100 cm/s on the surface. The level of shaking would be sufficient to make soft surface sediments nonlinear. To reproduce observed ground motions quantitatively, one-dimensional nonlinear effective-stress time-history analyses were conducted at three locations in downtown Mashiki. The input wave was employed as either the observed underground wave or simulated outcrop input motion based on the diffuse field theory. The main purpose of the study was twofold: to investigate the proper soil constitutive relationship and its nonlinear parameters based on the limited amount of in situ information, and to validate the method of input motion evaluation at the seismological bedrock level based on diffuse field theory. The nonlinear time history analyses using the on-site boring survey and the outcrop wave based on diffuse field theory showed that the waveform of the mainshock observed on the ground surface was explained with sufficient accuracy. In addition, the results of the effective stress analysis indicated that soil liquefaction might have occurred in the area with thick surface layers along the Akitsu River where the water table was considered to be quite shallow.Graphical

Using the Experience of Natural Disasters to Prevent Health Hazards in Shelters

Introduction:The number of deaths from natural disasters that have occurred in Japan since 1989 is in the order of (1) the Great East Japan Earthquake, (2) the Great Hanshin-Awaji Earthquake, and (3) the Kumamoto Earthquake, but the ratio of related deaths to the total number of deaths was highest for the Kumamoto earthquake.Method:In the case of the Kumamoto earthquake, an inland earthquake of the same scale as the Great Hanshin-Awaji Earthquake, direct deaths due to the earthquake were suppressed, but related deaths are thought to have increased due to the effects of evacuation life and other factors. According to a report by Kumamoto Prefecture, the majority of direct deaths from the Kumamoto earthquake were caused by trauma such as excessive pressure or asphyxiation. As for related deaths, most of the victims were aged 60 years or older, more than 80% of them had pre-existing medical conditions, and respiratory and circulatory system diseases were the most common causes of death.Results:A survey of victims transported by ambulance from evacuation centers to medical institutions after the Kumamoto earthquake showed that a large number of victims were transported in the acute phase after the disaster. The reasons for transport are diverse injuries and illnesses, including trauma from falls, dyspnea, impaired consciousness, and fever, suggesting that stress from the earthquake and problems in the living environment of the evacuation centers had an impact on the deterioration of health conditions.Conclusion:It is important to identify issues and consider countermeasures based on past experiences in order to prevent health hazards in evacuation centers.

Considering the Use of Mobile Medical Containers in the Event of Natural Disasters

Introduction:In recent years, Japan has been hit by a number of natural disasters including the Great East Japan Earthquake, the Kumamoto Earthquake, the heavy rains in western Japan, and the heavy rains in Kumamoto to name a few. In each of these events, a number of hospitals located within the disaster areas were damaged and ceased to function, leading to difficulties in providing regional medical care. This presentation examines the effectiveness of mobile medical containers in handling such situations in the future.Method:This study organizes lessons learned from past disasters as well as the merits of and challenges facing current mobile medical containers while looking into the future.Results:When the Great East Japan Earthquake occurred, assembly-and-installation type temporary health clinics were constructed, but due to the numerous Japanese laws and regulations, it took almost three months for these to be delivered. On the other hand, current mobile medical containers are already in use in countries such as Tonga and Senegal and have the following advantages: (1) High mobility and easy installation, (2) Expandability as necessary, and (3) Durability for long-term use.Conclusion:Despite challenges such as clarification of legal handling, electricity, water supply and drainage, we consider mobile medical containers to be effective alternative medical facilities in the event of disasters.

Current Status of the Disaster Health, Medical, and Welfare Coordination in Japan

Introduction:Non-coordinated support during disasters has negative effects on affected communities and people. From the 2004 Indian Ocean Tsunami, the United Nations introduced a cluster approach to avoid gaps and duplication of aid. Japan's disaster coordination of support for health and medical care was organized after the 2017 Kumamoto earthquake. The Ministry of Health, Labour and Welfare (MHLW) announced and issued the notice that the prefectures need to establish a system related to health and medical activities in the event of a large-scale disaster. In July 2022, welfare content was added. This study investigated the current status of health sector organizational coordination among health, medical, and welfare responders during 2022 the Large-Scale Earthquake National Exercise (LSENE).Method:The 2022 LSENE was conducted on October 1, 2022 with participation from the Disaster Medical Assistant Team (DMAT) and responders from each prefecture's health and welfare divisions and organizations. Each responder's exercise log sheet and the exercise controller's evaluation were reviewed.Results:Even though there was a notice from the MHLW, organized coordination was conducted only by several medical and health teams. DMAT is the only team with a system to dispatch teams from non-affected prefectures and coordinate well to allocate teams. Some other health and welfare organizations did not have a dispatching system. They had difficulty sending teams to affected areas, especially due to a lack of a systematic response system, training, coordination headquarters, and information sharing. It was suggested that information sharing and coordination among responders is necessary, although information gathering and request judgments related to dispatch coordination are different for each organization.Conclusion:In order to smoothly coordinate support teams for health, medical, and welfare in the event of a disaster, it is necessary not only to improve the coordination headquarters for health, medical, and welfare but also to verify its operation through training.

Aiming for a Society Where No One is Left Behind in a Humanitarian Crisis: Examples of Cooperation Among Health, Medical Care, and Welfare

Introduction:Japan is geographically prone to natural disasters such as earthquakes, volcanoes, and tsunamis, economically advanced, and socially characterized as a super-aged society. The SDGs are a concrete strategy to achieve a society where no one is left behind. So what exactly can we do to protect the vulnerable populace? This presentation will introduce the system of cooperation and implementation of medical, health, and welfare disaster relief in Japan.Method:Government documents were received on developing national policies regarding the strategy for the unification of medical, health, and welfare. For implementation, the status of support teams specializing in disaster welfare and training status was reviewed.Results:National policy level achievements: The Ministry of Health, Labor and Welfare (MHLW) issued a "Notification on Enhancing and Strengthening the Medical System in Times of Disaster" in 2012 and conducted a critical review of the initial response to the Kumamoto earthquake in 2016 in the "Initial Response Verification Report." This process reaffirmed the need to support vulnerable populations such as the disabled, children, and the elderly. In 2021, the Disaster Welfare Assistance Team was added to the Basic Plan for Disaster Management and the MHLW Disaster Management Work Plan.Implementation level Achievement: As of 2022, 24 of the 47 prefectures have a DWAT in place. Gunma, Kyoto, and Miyazaki prefectures were the most advanced, with 1) ongoing meetings to strengthen cooperation with medical and health care teams, 2) participation in joint drills, and 3) DWAT awareness-raising activities through training for municipal administrative staff.Conclusion:While this review revealed that the national government had made progress in developing policies, the implementation revealed that some prefectures have not yet established DWATs.

Strong ground motion simulations of the 2016 Kumamoto earthquakes using corrected empirical Green’s functions: methods and results for ESG6 blind prediction Steps 2 and 3 with improved parameters

This paper describes the methods and results of the strong ground motion simulations for three earthquakes from the 2016 Kumamoto earthquake sequence using corrected empirical Green’s functions. The target earthquakes were an aftershock (Mw 5.5), the largest foreshock of the sequence (Mw 6.1), and the mainshock (Mw 7.1). The corrected empirical Green’s function method was used in the simulations. This simulation method combines simple source and path factors with empirical site amplification and phase factors to generate realistic site-specific strong motions. Simulations were originally conducted to participate in blind prediction exercises in ESG6. Although the simulations performed in this study were based on the models submitted to the blind prediction committee, several modifications were made after the blind prediction exercise. First, the observed records at the target site of the blind prediction called KUMA were used to compare observed and synthetic strong ground motions. In addition, a regional spectral inversion was conducted to obtain a more appropriate Q-value and site amplification factor. Synthetic strong motions were found to explain the observed strong ground motions at KUMA and other stations. Comparisons with predictions by other methods and the sensitivity to the rupture scenario were also discussed. These results provide useful information for applying the corrected Green’s function method to strong ground motion simulations.Graphical

Backscattering Characteristics of SAR Images in Damaged Buildings Due to the 2016 Kumamoto Earthquake

Most research on the extraction of earthquake-caused building damage using synthetic aperture radar (SAR) images used building damage certification assessments and the EMS-98-based evaluation as ground truth. However, these methods do not accurately assess the damage characteristics. The buildings identified as Major damage in the Japanese damage certification survey contain damage with various characteristics. If Major damage is treated as a single class, the parameters of SAR images will vary greatly, and the relationship between building damage and SAR images would not be properly evaluated. Therefore, it is necessary to divide Major damage buildings into more detailed classes. In this study, the Major damage buildings were newly classified into five damage classes, to correctly evaluate the relationship between building damage characteristics and SAR imagery. The proposed damage classification is based on Japanese damage assessment data and field photographs, and is classified according to the dominant damage characteristics of the building, such as collapse and damage to walls and roofs. We then analyzed the backscattering characteristics of SAR images for each classified damage class. We used ALOS-2 PALSAR-2 images observed before and after the 2016 Kumamoto earthquake in Mashiki Town, where many buildings were damaged by the earthquake. Then, we performed the analysis using two indices, the correlation coefficient R and the coherence differential value γdif, and the damage class. The results indicate that the backscattering characteristics of SAR images show different trends in each damage class. The R tended to decrease for large deformations such as collapsed buildings. The γdif was likely to be sensitive not only to collapsed buildings but also to damage with relatively small deformation, such as distortion and tilting. In addition, it was suggested that the ground displacement near the earthquake fault affected the coherence values.

Shareholder reaction to corporate philanthropy after a natural disaster: an empirical exploration of the “signaling financial prospects” explanation

Corporate response to natural disaster in the forms of cash and/or in-kind donations (corporate philanthropic disaster response, or CPDR) is a growing form of corporate philanthropy. Through an event study methodology based on 1,775 firms listed on the Tokyo Stock Exchange, we analyze shareholder reaction to CPDR announcements after the 2016 Kumamoto earthquakes in Japan. Controlling for the possibility that the most common explanations (buying goodwill and corporate governance) are at play, our results provide an empirical test of a little-explored explanation for the positive shareholder reaction to CPDR: namely, that corporate philanthropy is a market signal to outside investors of the firm’s future financial prospects. We find this explanation to be significant. Of note are also the facts that shareholder reaction is only significantly positive in the case of cash donation (as opposed to in-kind), and is more positive when announced early. Overall, our results align with the “strategic philanthropy” view grounded in resource-dependence theory. But instead of the typical focus on non-financial stakeholders, we argue that philanthropic donations can be used to directly influence investors.

THE ACTUAL CONDITIONS AND ISSUES CONCERNING THE RECONSTRUCTION COST AND PERIOD OF THE HOUSE RECONSTRUCTION PROCESS AFTER THE KUMAMOTO EARTHQUAKE

In this study, in order to contribute to the work of supporting the reconstruction of the lives of future disaster victims, we ascertained the actual level of building damage and public support for victims in Mashiki Town, which was damaged by the 2016 Kumamoto Earthquake. We then investigated and figured out the actual situation of the reconstruction process of households that have repaired or rebuilt their house through a questionnaire survey to focus on the time taken, cost of repair and rebuilding. We also clarified the level of understanding of the support system and ease of creating application forms.

Noncompliance with Hypertension Treatment and Related Factors among Kumamoto Earthquake Victims Who Experienced the COVID-19 Pandemic during Postearthquake Recovery Period.

Survivors of the Kumamoto earthquake of 2016 experienced the coronavirus disease (COVID-19) outbreak while carrying additional burdens that might bring inadequate coping. This cross-sectional survey aimed to identify untreated and interrupted consultations among those with hypertension and related factors and to identify the disaster's long-term effects. Of the 19,212 earthquake survivors who had moved to permanent housing, 7367 (4196 women and 3171 men, mean age 61.8 ± 17.3 years) completed a self-administered questionnaire. The prevalence of hypertension was 41.4%. The results of the logistic regression analysis with the significant independent variables in the bivariate analysis were: reduced income due to COVID-19 (AOR = 3.23, 95%CI = 2.27-4.58) and poor self-rated health (AOR = 2.49, 95%CI = 1.72-3.61) were associated with a risk of untreated or discontinued treatment. Moreover, living in rental, public or restoration public housing was also significantly associated with a higher risk of hypertension noncompliance (AOR = 1.92, 95%CI = 1.20-3.07; AOR = 2.47, 95%CI = 1.38-4.42; AOR = 4.12, 95%CI = 1.14-14.90). These results suggest that changes due to COVID-19, the extent of self-rated health and the type of permanent housing influence the hypertension consulting behaviour of earthquake survivors during recovery. It is crucial to implement long-term public support for the mental health, income and housing concerns of the survivors.

Factors Related to Physical Activity among Older Adults Who Relocated to a New Community after the Kumamoto Earthquake: A Study from the Viewpoint of Social Capital.

Previous studies have shown an association between social capital and physical activity in older adults. Older adults who relocated after the Kumamoto earthquake may become physically inactive, and the extent of this inactivity may be buffered by social capital. Accordingly, this study applied the social capital perspective to examine factors that affect the physical activity of older adults who relocated to a new community after the Kumamoto earthquake. We conducted a self-administered mail questionnaire survey with 1494 (613 male, 881 female, mean age 75.12 ± 7.41 years) evacuees from temporary housing in Kumamoto City, aged 65 years and above, who relocated to a new community after the earthquake. We performed a binomial logistic regression to examine the factors affecting participants' physical activity. The results showed that physical inactivity (decreased opportunities for physical activity, decreased walking speed, and no exercise habits) was significantly associated with non-participation in community activities, lack of information about community activities, and being aged 75 years and over. Lack of social support from friends was significantly associated with lack of exercise habits. These findings encourage participation in community activities, alongside giving and receiving social support in health activities that target older adults who relocated to new communities after the earthquake.

3次元レーザースキャナによる地震被害建物の変形量評価

In order to obtain knowledge regarding damage mechanisms of building located above surface of the 2016 Kumamoto earthquake fault, the residual deformations of the building were investigated with 3D point cloud data obtained by a laser scanner. The 3D point cloud data contain noise due to measurement error and diffuse reflection. Residual deformations were grasped accurately with method reducing the influence of measurement error by using RANSAC algorism which is one of robust estimations. The validity of the obtained results is also confirmed by comparing other research and evaluating the error.

A regional scale coseismic landslide analysis framework: Integrating physics-based simulation with flexible sliding analysis

This paper describes a framework for regional scale coseismic landslide evaluation that combines physics-based wave propagation simulation at a regional scale, with flexible sliding analysis at a site scale. The physics-based simulation incorporates fault rupture process, complex topography and dynamic site response. The sliding displacements of flexible masses are calculated by integrating seismic parameter k obtained from the physics-based simulation over seismic resistance.The framework is applied to the case study of coseismic landslides during the 2016 Mw 7.0 Kumamoto earthquake in Japan, which has well documented fault mechanism, geologic information and landslide inventory. The performance of the model prediction is evaluated by receiver operating characteristic (ROC) analysis. This study highlights the near-fault effect and soil nonlinear effect on landslide distribution, and it is demonstrated that the landslide prediction can be notably improved with the consideration of topographic amplification of ground motions. Empirical correlations between topographic amplification of key intensity measures and parameterized topographic features are developed. Overall, the simulation captures 58% of observed landslides in the inventory (using a displacement threshold of 15 cm), showing the proposed framework is a promising tool for regional coseismic landslide analysis.

Message from the Winner

It is my honor to receive the JDR Award for the Most Cited Paper 2022. I would sincerely like to thank the JDR editorial office, reviewers, and my co-author, Professor Yamazaki, for their support. The paper that received this honor was “Extraction of Collapsed Buildings in the 2016 Kumamoto Earthquake Using Multi-Temporal PALSAR-2 Data.” In this work, we proposed three change indices for evaluating the damage to buildings in Mashiki Town, Kumamoto Prefecture that were severely affected by the 2016 Kumamoto Earthquake. The indices were calculated from two pre- and one co-event ALOS-2 PALSAR-2 images. The most valid factor was adopted by comparing the extracted results with the reference data from field surveys. The factor was then applied to larger affected areas of Kumamoto City and its surroundings. In this work, the ALOS-2 proved to very effective in recognizing damages caused by nature disasters. This work has been cited by 21 journal papers as of December 2022. I am grateful to the editorial board of the JDR for affording us the opportunity to have this work published. We hope our results in this paper will help even more scientific works. Encouraged by this award, we will continue to conduct future investigations to further disaster prevention and management.

Characterized source model of the M7.3 2016 Kumamoto earthquake by the 3D reciprocity GFs inversion with special reference to the velocity pulse at KMMH16

The 2016 Kumamoto earthquakes caused severe damage centering on the Mashiki residential area. The velocity waveforms at station KMMH16 in Mashiki, during the M7.3 mainshock, show large pulses. We found that severe damage in Mashiki may be the result of the strong westward velocity pulse. The question raised is how the near-fault ground motions with strong velocity pulse at KMMH16 were generated during the mainshock. We focus on the characterized source model with Strong Motion Generation Areas (SMGA). Empirical Green’s function (EGF) method is widely used for source modeling in this case. However, in case that the target site is located just near the fault in nodal plane of source mechanism (like KMMH16), mechanism of the EGF event should perfectly fit mechanism of the mainshock, which is a rare case. Therefore, instead of using EGFs, we used theoretical 3D Green’s functions. Our approach is a nonlinear source inversion. This method requires calculation of waveforms and comparison with observations for many source models. To accelerate these calculations, we use pre-calculated GFs by the reciprocity method in the JIVSM velocity structure model. By comparison with aftershock records, we validated this structure for periods as short as 1.5 s. Target sites are limited to sites close to the fault: KMM005, KMM006, KMMH14, and KMMH16. First, we look for an initial SMGA source model by the grid search method applied to relatively long-period (> 3 s) waveforms and coarse grid of source parameters. Then, we tune that source model to fit observed short-period waveforms with the simplex search method. Necessary physical constraints for the range of the source parameters are applied here. The important point in our inversion scheme is to describe the Kostrov-like slip velocity functions inside each SMGAs by using two triangles. The resulting source model agrees well with other inversion results. We found that the observed westward pulse at KMMH16 is the result of the constructive interference of two pulses from SMGA1 and SMGA2, located in Hinagu fault and southwestern segment of Futagawa fault.Graphical

Increase in traffic injury crashes following the 2016 Kumamoto earthquake in Japan: A model comparison

Objective Following natural disasters, the number of motor vehicle crashes may increase as drivers are often forced to drive under stressful conditions. This study aims to analyze the changes in motor vehicle crashes that resulted in injury or death (injury crash) following the 2016 Kumamoto earthquake in Japan. An existing study reported that the increased crashes resulted in property damage following the earthquake; however, the effects on injury crashes remain unreported. Methods Interrupted time series analysis is employed to investigate the changes in injury crashes following the earthquake. The results are compared based on several time series models, including negative binomial and autoregressive integrated moving average models. Monthly injury-crash data from 2011 to 2020 in Kumamoto and Fukuoka city is used. Results The results reveal a 1,642-count or 20% increase (1.20-times increase, 95% confidence interval: 1.12, 1.27) in injury crashes due to the earthquake in Kumamoto city, where the earthquake damage was heavy. In contrast, statistically significant change is not detected in Fukuoka city, where the earthquake damage is negligible. Conclusion The results indicate that the earthquake has increased the motor-vehicle-crash risk and that traffic crash alerts are important following disasters.

Detection of Damaged Buildings Using Temporal SAR Data with Different Observation Modes

Synthetic Aperture Radar (SAR) remote sensing has been widely used as one of the most effective tools for responding to earthquake disasters. In general, damaged-building detection with SAR data has been conducted based on change detection using temporal SAR data acquired in the same observation mode. However, it is not always possible to use SAR data obtained with the appropriate observation mode in unexpected events such as natural disasters. This study aims to detect earthquake-induced damaged buildings using temporal SAR data having different observation modes. We presented a contextual change analysis method to map damaged buildings based on novel textural features. This study was conducted using the bi-temporal Komapsat-5 data obtained in different polarization modes. Experimental results for the area severely damaged by the 2016 Kumamoto earthquake showed that the proposed textural analysis can improve detectability in building-damaged areas while maintaining low false alarm rates in agricultural areas. According to the grid-based accuracy analysis, the proposed method can successfully detect the damaged areas with a detection rate of about 72.5% and false alarms of about 6.8% even on challenging data sets.

Three-year follow-up of the impact of Kumamoto Earthquake on acute myocardial infarctions: An interrupted time series analysis

Study objectiveThis study aimed to investigate whether the incidence of acute myocardial infarction (AMI) and subsequent outcomes over the three years after the Kumamoto earthquake differed from the underlying trend before the earthquake. DesignQuasi-experimental design. SettingTwenty-one institutions participating from the Kumamoto Prefecture and capable of receiving AMI patients and performing coronary angiography and interventions. ParticipantsIn total 6553 consecutive patients with AMI between 2013 and 2019 were included in this study. InterventionsInterrupted time series analysis. Main outcome measure(s)AMI incidence and following cardiac events after the earthquake. ResultsThe rate ratio (RR) for AMI incidence after the earthquake was 1.12 (95 % confidence interval [CI]: 1.00–1.25) with reference to that before the earthquake. AMI rates increased among people with diabetes mellitus (RR: 1.20, 95 % CI: 1.01–1.44), those with current smoking (RR: 1.27, 95 % CI: 1.03–1.56), and those with a body mass index >25 kg/m2 (RR: 1.27, 95 % CI: 1.06–1.52). Increased number of AMI patients with onset-to-door time >12 h (RR: 1.46, 95 % CI: 1.02–2.08), a high Killip class on hospital admission (RR: 1.37, 95 % CI: 1.13–1.67), and unperformed emergent coronary angiography (RR: 1.40, 95 % CI: 1.02–1.91) were frequently observed after the earthquake, which may affect following in-hospital cardiac events (RR: 1.49, 95 % CI: 1.03–2.15). ConclusionsThe Kumamoto earthquake had an impact on the increase in the incidence of AMI and the following in-hospital cardiac outcomes. Emergency medical care should be ensured in such a way that high-risk patients are managed as usual, especially immediately after earthquake.