II: damage and loss estimation,”. Although many similarities, however, this study distinguishes itself from other studies especially in terms of the data source it selected. Every year, typhoons such as Typhoon Maemi cause serious financial losses worldwide. As a result, the LOB category can classify buildings as physical and financial functions. Beta coefficient designates standardized coefficients that disregard the unit scale of independent variable, which helps comparisons among the independent variables. Narisma also cited a study of the United Nations University for Environment and Human Security (UNU-EHS), which revealed that the Philippines ranked third in the 2013 World Risk Index. In the regression analysis of the commercial building, the adjusted R2 value is 0.332, which indicates that 33.2% of the variant of the loss ratio can be described by the regression model. The value of property is negatively associated with the degree of loss caused by a typhoon. E. S. Blake, E. N. Rappaport, and C. W. Landsea. Coefficient designates the nonstandardized coefficients that reflect the unit scale of the independent variable. Kim, “Assessing regional typhoon risk of disaster management by clustering typhoon paths,”, D. G. De Silva, J. The wind speeds of the individual buildings that suffered damage were collected based on the date of the accident and the address information in the loss records using the Geographic Information System. Therefore, in future studies, other possible indicators should be identified and added to the model. The reason for this is that the building height is statistically correlated with the degree of financial loss, so it can be used as a vulnerability index to quantify a building’s vulnerability to hurricanes. Its torrential rains generated massive debris flow in the Mayo River watershed in the Andap village in New Bataan municipality, causing some areas to be buried under a rubble as thick as … In 2011, Cyclone Yasi, which was classified as a Category 5 severe tropical cyclone, hit Australia and the nearby islands in the Pacific, but only one casualty was recorded, apparently brought by addressing vulnerability, she said. It is dangerous to conclude the risk solely with the existing standard models alone. They should be able to judge whether the outcome is optimistic, pessimistic, or conservative, depending on their exposure. Hence, constructing the vulnerability curves referring to the data and meaning factors from this research can enhance future studies with the similar focus and approach. In 2014, Zhang et al. The distance from the coast has also been proven to play a vital role in describing vulnerability to windstorm. Busan was also significantly devastated by the typhoon to the dollar amount of damages (43.8%) and the number of losses (45.0%). Similar to the mentioned studies, this study conducted a vulnerability analysis in order to present the valid risk factors related to building vulnerability based on the accumulated past data and statistics. The death toll from Typhoon “Pablo” has topped 1,000 with hundreds more missing and feared dead, the government said Sunday. The models were also developed in specification of various types of buildings including commercial, residential, and industrial, so that the particular and practical application of these models are possible. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Two significant variables, total value of property and construction type, are branded as meters of the ruthlessness of typhoon loss. Data on property tax records, which included construction type attributes and property valuation, were also adopted, in order to specify residential building fragilities in relation to comprehensive reconstruction cost. H. Kunreuther, R. Meyer, C. Van den Bulte, E. Robert, and Chapman, C. C. Watson, M. E. Johnson, and S. Martin, “Insurance rate filings and hurricane loss estimation models,”, P. Grossi, H. Kunreuther, and D. Windeler, “An introduction to catastrophe models and insurance,” in, D. Cummins, C. Lewis, and R. Phillips, “Pricing excess-of-loss reinsurance contracts against cat as trophic loss,” in, J. Elsner and K. Liu, “Examining the ENSO-typhoon hypothesis,”, W. J. Platt, R. F. Doren, and T. V. Armentano, “Effects of Hurricane Andrew on cypress (Taxodium distichum var. Former studies have stated that the value of property affects the degree of loss caused by typhoons and is a valuable factor for loss valuation. For this reason and many other related reasons, the low data quality does not follow the input level of the sophisticated vendor CAT models to date. However, the remaining 66.8% caused by some unconfirmed indicators was not considered in this study. Following the scale of the coefficient, the indicators are (1) the total value of property (beta coefficient = –0.622), (2) floors (beta coefficient = 0.227), and (3) distance from coast (beta coefficient = –0.222). This means that the loss increases as the wind speed intensifies. The vulnerability module is a module that uses the vulnerability function to quantify the degree of damage by vulnerability according to the building attributes using the correlation between damage and risk indicators [6]. Variables for basic building information indicators included total value of property, number of floors and underground floors, and construction types. More specifically, it is a problem that models can only be developed and evaluated in a limited number of countries, such as the United States, China, and Japan, which often suffer large losses due to natural disasters and large insurance industries. The closer a building is to the coast, the more devastated it is to typhoons [34]. Based on the existing location information, the wind speed and distance from the property centroid to the coastline are estimated. Insurance and reinsurance companies can use the model from this research to improve their own business model using the methodologies to measure latent risks. The storm was forecast to cross right over northern Mindanao and past the western Visayas island group. These abovementioned studies have similarities with this study in the sense that most of them relied on the past record of financial information and data in measuring the damage and vulnerability from hurricanes/windstorms/typhoons of residential or industrial buildings in their analyses. She admitted that the studies “are not conclusive” and that she could not tell if typhoons will become more intense in the next 20 to 30 years. This indicates that the rate of loss increases as the value of property decreases. The reason for this was that the typhoon landed directly on the midcoast of Gyeongnam province, and the right side of the area had more influence than the left side of the area by the strong wind and rainfall of the typhoon [17, 18]. Kim et al. Although several previous studies on economic loss associated with natural catastrophe have identified essential risk indicators, there has been a shortage of more specific research studies focusing on the correlation between vulnerability and economic loss caused by typhoons. The purpose of this research is to identify the indicators of typhoon damage and develop a metric for typhoon vulnerability functions employing the losses associated with Typhoon Maemi. However, the other indicators are not associated with the loss ratio of residential building. The World Meteorological Organization decided to remove the name Maemi from circulation and substituted it with Mujigae in 2006 due to the extreme damage and death caused by the typhoon [19]. Typhoons cause significant financial damages worldwide every year. Nonetheless, these models are not designed to be adopted in the insurance industry because there are no finance modules that consider insurance concepts such as layers, deductible, and so on. The adjusted R2 value of the industrial building model was 0.403, indicating that 40.3% of the difference of the dependent variable can be described by three indicators (distance from coast, total value of property, and construction type). As the incidence of severe windstorms continues to increase drastically, the resulting losses are also remarkably increasing [1]. Uncertainty of typhoons. “The severe flooding and displacement as a result of Typhoon Koppu raises the vulnerability of affected communities to disease outbreaks.” said Dr Benjamin Lane, officer in charge of the WHO Country Office of the Philippines The city has been affected by recent floods following tropical storm Sendong (Washi, December 2011), typhoon Pablo (Bopha, December 2012) and tropical storm Vinta (Tembin, December 2017). Heneka and Ruck focused on German winder storm events in 2000s and the damage from them to residential buildings. Young, and F. M. Lavelle, “HAZUS-MH hurricane model methodology. What does this mean is that vulnerability is in our hands,” Narisma added.By addressing the vulnerability, she explained, the impacts could be decreased as well as the possibility of a disaster. These values show that there is no noteworthy multicollinearity between variables. iii Shelter 227,953,000.00 271,980,000.00 Health (WASH) - 30,746,800.00TABLE OF CONTENTS INTRODUCTION Hazard Assessment 1 Typhoon Pablo 2 Vulnerability and Exposure 2 For example, federal and local governments can refer to this research in an effort to reducing future typhoon damages by predicting financial losses with the models reported in this study and establish mitigation strategies based on expected losses. Nevertheless, the other indicators are not related with the dependent variable of residential building. Last, in the case of industrial buildings, the significant indicators were found to be distance from coast, total value of property, and number of floors. Chock looked into hurricane damage on Hawaii residential buildings gathered and georeferenced on the GIS. The premium consists of the pure premium, expense, and profit. Ultimately, 135 people died, there were 61,000 victims, and the overall property damage was about $ 4.3 billion (in 2003 year). Table 3 shows the typhoon information and basic building information related to the loss ratio for the line of business (LOB): commercial, residential, and industrial, as assessed through the regression models, correspondingly. B. Robert et al., U. Ulbrich, A. H. Fink, M. Klawa, and J. G. Pinto, “Three extreme storms over Europe in December 1999,”, E. E. Koks, B. Jongman, T. G. Husby, and W. J. W. Botzen, “Combining hazard, exposure and social vulnerability to provide lessons for flood risk management,”, A. C. Khanduri and G. C. Morrow, “Vulnerability of buildings to windstorms and insurance loss estimation,”, J.-M. Kim, T. Kim, and K. Son, “Revealing building vulnerability to windstorms through an insurance claim payout prediction model: a case study in South Korea,”, H. Ryu, K. Son, and J.-M. Kim, “Loss prediction model for building construction projects using insurance claim payout,”. In order to create the vulnerability functions and to identify the natural hazard indicators and basic building information indicators, information from the insurance record was used in the analysis. Furthermore, the frameworks and indicators of this study can also be used for a further similar research, especially in developing countries with few data on loss caused by windstorms and building characteristics to predict windstorms. Photo/flickr user SCA Svenska Cellulosa Aktiebolaget. The report stated that the Pacific Island nation of Vanuatu topped the chart, followed by the Polynesian state of Tonga. From vehicle manufacturers to companies involved in equipping those vehicles, to any supplier of life- saving and rescue equipment and aids. The indicators can be ranked in the descending order of their beta coefficients. J. S. Kim, “On the characteristics of damage scale and risk management system by strong-wind speed of typhoon,” Inje University, Gimhae, Korea, 2013, Master thesis. Previous typhoon and vulnerability research conducted in Asia has emphasised the socioeconomic and institutional factors contributing to people’s vulnerability (Gaillard et … In each regression model, according to the LOB classification, the adjusted R2 values and the significant indicators were also different. In addition, constructing vulnerability curves in further research can make much contribution in the field. This concept is entered into the following equation (1): Because in each case, the loss from typhoon damages was relatively small, compared to the total sum insured, most loss ratio were inclined toward zero when presented by equation (1), and for this reason, the dependent variable was converted by log transformation in order to fit the normal distribution. Emergency Live - Pre-Hospital Care, Ambulance Services, Fire Safety and Civil Protection Magazine. E. S. Blake, T. B. Kimberlain, J. The values of the variance inflation coefficient (VIF) ranged from 1.016 to 1.293. This quantification of damage data represented in the insurance claim payout record can be especially helpful because of the detailed and specified information about each case of damage of the buildings, which also enables engineers and insurance underwriters, for logical and accurate, and thus more reliable review estimation of the damage. Following the scale of the coefficient, the indicators are (1) the total value of property (beta coefficient = –0.549) and (2) construction type (beta coefficient = 0.241). The indicators can be listed in the descending order of their beta coefficients. In addition, the maximum amount of loss caused by a catastrophic disaster is a very vital number in the insurance industry. If there is a lot of poverty and housing conditions are not good,” Narisma noted. These models are also used by insurers and reinsurers around the world to assess the risks of natural disasters such as hurricanes, tsunamis, typhoons, floods, earthquakes, tornadoes, and winter storms, and they are considered to be the standard methodologies for natural disaster risk management. But we really need to be prepared because we are in the active corridor of tropical cyclones, Narisma said. The distance from the coast is adversely related with the amount of loss caused by a typhoon. More specifically, they can use modeling to assess risks and make judgments and use the base rate of insurance policies as a percentage of experience with expected losses. Typhoon Pablo, as what Typhoon Bopha is called in the Philippines, was the most powerful storm to have hit the island of Mindanao, southern Philippines, in more than 100 years of recorded storms []. This study also aims to assess the loss reflecting the regional vulnerability and to build a systematic method to measure other extreme cases and countries to predict the typhoon loss. indicated that windstorm loss increases as the total amount of the building decreases. 2020, Article ID 8885916, 10 pages, 2020. https://doi.org/10.1155/2020/8885916, 1Department of Architectural Engineering, Mokpo National University, 1666 Yeongsan-Ro, Cheonggye-myeon, Muan-gun, Jeonnam 58554, Republic of Korea, 2School of Architectural Engineering, University of Ulsan, 93 Daehak-Ro, Ulsan 44610, Republic of Korea, 3Department of Civil Engineering and Engineering Mechanics, Columbia University, 500 W. 120th Street #610, New York, NY 10027, USA. After major record-breaking hurricanes, such as hurricanes Katrina, Ike, and Sandy, insurance companies had to shut down, due to unexpected tremendous losses, and the companies that survived had to quickly modify their coverage and rates [12]. The typhoon landed on the south coast on the Korean peninsula, through the inland, to the east coast, causing extreme economic losses in many cities on the south coast, as shown in Figure 1(b). This is also consistent with the results of prior studies [20, 24]. The LOB is typically used as a risk indicator to quantify the building vulnerability in the risk assessment model [7, 39]. Typhoon Pablo has unveiled the vulnerability of our Mindanao communities to typhoons, landslides and flash floods. This was to achieve the quantification of the damage in numerical, especially in financial values. However, this study solely focused on the one typhoon case, Typhoon Maemi. The records received include information such as the date of the accident, location, occupancy, structure type, construction period, floor, underground, detail of loss, loss amount, and so on. Typhoons cause significant financial damages worldwide every year. The reason for this is that developing a database that includes such information is considered to be inefficient, timewise and moneywise, for not only small- and medium-sized companies but also large corporations [7]. The poorer people were the most vulnerable,” she said. This research was funded by the Basic Science Research Program of the National Research Foundation of Korea (NRF-2020R1F1A1048304). Ultimately, this study was designed to provide more methodologically grounded understanding and evidence-based knowledge in minimizing the risks of typhoons to buildings. At this, it is crucial for the insurance industry to be able to accurately estimate and assess the risks. The construction type is also an important indicator of the building’s typhoon vulnerability. This signifies that the degree of loss rises as a building is closer to the coast. As can be seen, the precision of the vulnerability function, among many other factors, is substantially affected by the presence and its quality of past damage data. A 2011 typhoon, Washi, which wreaked considerable harm, was their most recent reminder of this danger, at least until Typhoon Pablo, the local name for Bopha. Do we accept that is already the case?” she asked.The scientist quoted a definition of disaster by the International Federation of Red Cross and Red Crescent societies, which says: “A disaster occurs when a hazard impacts in vulnerable people.”“When you have a strong hazard, you are vulnerable, then you have a recipe for disaster. “We are vulnerable if you don’t have don’t have good governance. The building construction companies are also able to improve their design guidelines by planning storm-resistant buildings and by assessing building loss based on the predicted total value of property, construction type, and the number of floors of the building. flood simulations and vulnerability assessment against pluvial flooding and coastal flooding due to storm surge during the passage of Typhoon Pablo. This confirms the results of the initial study and shows that the distance from the coast is an imperative indicator for assessing losses caused by typhoons. Therefore, typhoon risk assessment modeling is becoming increasingly important, and in order to achieve a sophisticated evaluation, it is also important to reflect more specified and local vulnerabilities. The purpose of this study is to determine the significant factors, i.e., typhoon loss, natural hazard factors, and basic building information factors in the damage of buildings from the results of typhoons and to identify the relationship among the factors. T. Kim and K. Son, “Predicting hurricane wind damage by claim payout based on Hurricane Ike in Texas,”, C. G. Burton, “Social vulnerability and hurricane impact modeling,”, W. E. Highfield, W. G. Peacock, and S. Van Zandt, “Determinants & characteristics of damage in single-family island households from Hurricane Ike1,” in, D. D’Ayala, C. Alex, and H. Wang, “A conceptual model for multi-hazard assessment of the vulnerability of historic buildings,” in, J.-M. Kim, K. Son, and Y.-J. Don't…, Piazzale Badalocchio 9/b 43126 Parma (PR) – Italy. The models are statistically significant because the P values (0.000) are less than 0.05. The distance between the building and coastline also plays an important role in describing a building’s vulnerability to windstorms. As a result, this study suggested risk relativity factors and developed loss functions, which contributed to estimating hurricane damage to various Hawaii buildings [20]. Write to info@emergency-live.com or go to the form mail. The answer is no. For this reason, insurers and reinsurers analyze extreme natural disasters in order to prepare reserves for losses from such extreme natural disasters. In this study, a regression analysis was first used to determine the significant loss indicators for building vulnerability and then to evaluate the relationship between the indicators and loss ratio. Your Health Record could be shared as a Facebook status? “How are we vulnerable? typhoon effects have negative impacts on consumption levels, especially food. This is challenge for us, or do we just sit and say: It’s going to be a disaster, it’s the strongest typhoon. Emergency Live is the only multilingual magazine dedicated to people involved in rescue and emergency. By contrast, the other indicators are not associated with the loss ratio of commercial building. The maximum wind speed and loss due to the typhoon are positively interrelated. And therefore, the current situation is that the risk assessment is relied on the basic and minimum amount of data and information available. The dependent variable value used in the regression model is shown in equation (2): The loss records are consisted of two categories: (1) accident details, e.g., details of the accident, the address, the amount of loss, and the date of the accident, and (2) basic building information, e.g., the total amount of the property, construction type, number of floors, and number of underground floors. Typhoon Maemi: (a) track of typhoon and (b) distribution of losses. In the regression analysis of the residential building, the Adj-R2 value is 0.587, which indicates that 58.7% of the variant of the loss ratio can be described by the regression model. The pure premium is a combination of modeled cat risk, nonmodeled cat risk, and noncat risk such as FLEXA (i.e., fire, lighting, explosion, and aircraft). The higher value of the beta coefficient means a more significant effect on the dependent variable. Similarly, in certain countries, it is particularly difficult to describe the correlation between potential risk and loss, due to incoherent data or a lack of data [8]. Kim, “Damage analysis of meteorological disasters for each district considering the characteristics of a district,”, D.-Y. Over the sea it might be a Category 5 but it might slow down,” she explained. Among these, the natural catastrophe model consists of hazard, exposure, finance, and vulnerability modules [5]. Typhoon Pablo (international name “Bopha”), including over 1,067 fatalities and 834 missing [1]. The purpose of this research is to identify the indicators of typhoon damage and develop a metric for typhoon vulnerability functions employing the losses associated with Typhoon Maemi. Highfield et al. Table 1 shows the distribution of loss per province from Typhoon Maemi. Gyeongnam was damaged by the typhoon to the dollar amount of loss (48.0%) and the number of losses (35.4%). Nevertheless, the remaining 59.7% caused by some unproven indicators was not considered in this study. XOL and LOL are meaningful for allocating and limiting financial risk [14]. The values show that there is no significant multicollinearity between variables. This study gathered the loss record from a major insurance company of Construction All Risk (CAR) in South Korea from Typhoon Maemi’s damage. This typhoon severely devastated a wide area covering several southern Asian countries with extreme storm surges, landfall, and winds and led to total losses estimated at $ 2.88 billion. Loss records per province from Typhoon Maemi. It reinforces the previous study indicating that the LOB grouping can categorize buildings as physical and financial functions [7]. As such, it is the ideal medium in terms of speed and cost for trading companies to reach large numbers of target users; for example, all companies involved in some way in the equipping of specialised means of transport. B. Kruse, Y. Wang, and Y. Wang, “Spatial dependencies in wind-related housing damage,”, J.-M. Kim, K. Son, Y. Yoo, D. Lee, and D. Kim, “Identifying risk indicators of building damage due to typhoons: focusing on cases of South Korea,”, P. J. Vickery, P. F. Skerlj, J. Lin, L. A. Twisdale Jr, M. A. For this, this study adopted the various indicators that can be straightforwardly computed and easily accessed, found on Crichton’s risk triangle [11]. This study conducted a statistical analysis on the damages caused by Typhoon Maemi, which was categorized as an extreme disaster, in order to identify the natural hazard indicators and basic building information indicators and to develop a vulnerability function. That is, based on the data used and the significant factors found in this study, vulnerability curves can be created in a subsequent research. In other words, in catastrophe modeling, vulnerability curves define the degree of vulnerability according to, e.g., types of the buildings, and thus can serve as an important part of the modeling. The authors declare that there are no conflicts of interest regarding the publication of this paper. The records of previous extreme disasters are used as essential bases to establish the zone and limit. Hurricane Sandy and Hurricane Ike have been classified as the hurricanes of the second and third largest financial losses, respectively. The Philippines ranked second in terms of exposure and vulnerability to climate-related risks in the Global Climate Change Risk Report for 2020 of Germanwatch, the environment think tank. The basic building information, e.g., total amount of the property, construction type, number of floors, and number of underground floors, is used as indicators to reveal the typhoon vulnerability according to the building inventory. In this study, the vulnerability function of the typhoon risk assessment models has also been developed and validated based on the statistical analysis of the actual loss claim payout data kept by an insurance company. Surge during the passage of typhoon Pablo struck the Mindanao region in December 2012 a most! Have affected the Korean Peninsula, it showed during Yolanda characteristics of a district, ”, D.-Y report that. 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