From a cross-disciplinary approach
Department of Social Work , Tunghai University, Taiwan. Email: email@example.com
Li-Ju Jang, Department of Medical Sociology & Social Work , Chung Shan Medical University, Taiwan.
Fang-Yie Leu, Computer Science Department , Tunghai University, Taiwan.
Jieh-Jiuh Wang, Department of Architecture / Graduate School of Architecture and Urban Disaster Management , Ming-Chuan University, Taiwan.
Shu-Twu Wang, Department of Social Work , National Ping Tung University of Science and Technology, Taiwan.
Department of Social Work
Department of Medical Sociology & Social Work
Computer Science Department
Department of Architecture / Graduate School of Architecture
and Urban Disaster Management
Department of Social Work
On September 21, 1999, Taiwan encountered the worst ever earthquake in the past hundred years which caused tremendous loss of lives and property. In the past ten years, government, NGOs, and NPOs have been working together to reconstruct the affected areas. The authors propose a cross-disciplinary model of community disaster management support system. The construction of a comprehensive community disaster management support system means the enhancement and promotion of capacity and skills in different aspects, including 1.) implementation of community hazard-risk-vulnerability (HRV) analysis, 2.) promotion in disaster managing capacity of the individuals, community, as well as the government at all levels, 3.) a sound operation and interaction mechanism between community organizations and the governments, as well as among levels of government, and 4.) construction of systems and skills that monitoring disaster occurrence and managing available resources.
Centered with mountains and surrounded by sea, the island of Taiwan has suffered from all kinds of natural hazards. According to the report of World Bank (2005), Taiwan experiences more natural hazard events than any other places in the world. The Department of Statistics of the Ministry of the Interior, Taiwan (2008) reports that 270 natural hazards, including destructive earthquakes, typhoons, floods, as well as landslides, occurred and caused more than 32,944 deaths or injuries from 1958 to 2007. There has been a tendency for natural disasters to become more severe and occur more frequently. Eight destructive earthquakes have occurred in the past ten years. The Chi-Chi Earthquake (also known as the 921 Earthquake) which occurred on September 21, 1999 caused the most destruction in hundred years. Since then, the Taiwanese government and non-profit organizations (NPOs) have worked hand-in-hand on disaster mitigation and emergency management plans. In the year of 2002, the Taiwanese government even developed an integrated Community-Based Disaster Management (CBDM) program to facilitate community recovery plans (Wu & Kang, 2007). Various departments in the Central Government continue carrying on disaster mitigation and emergency management plans. Through the joint efforts of governmental agencies and NPOs, most of the affected areas have completed possible reconstruction projects. Disaster coping skills have been sharpened and local emergency management plans have been improved. However, it is found that those plans tend to focus on the reconstruction of buildings and infrastructures.
Additionally, the nation’s disaster response capacity and its emergency management plans have become an important issue in public policy making. Building on studies analyzing the post-quake reconstruction efforts among all levels of government (e.g. Chiang, 2001; Chiou, 2004), Chiang proposes to strengthen the communications between central and local governments, revise the reconstruction policy, assess local resources, respect local culture and understand its unique strengths and weakness, and enhance the local government’s capacity on disaster response. Chiou focuses on the government’s responsibility in helping schools at the affected areas. He encourages the government to assist schools to develop an integrated emergency management plan on campus. Other studies indicate that NPOs have become the partners of government in carrying out the rescue and relief works, and even continue their efforts to the reconstruction phase (Chang, 2007; Liu, Chiou & Lu, 2003). Liu & Chang (2004) emphasize that NPOs provide indispensable spontaneous help when natural disasters occur. They found that GIS would be a valuable tool in managing available resources and coordinating departments of emergency management plans, and subsequently promote the efficiency of community response to disaster.
Even though a majority of survivors have moved on with their lives, they experience emotional distress from time to time, especially during the anniversaries of the 921 Earthquake and/or news on worldwide natural disaster occurrences. Thus, programs in promoting survivors’ psychological well-being should be included in the emergency management plans. Being aware of such a need, the Taiwanese government funded a series of studies on the survivors’ post-quake psychological well-being. For example, Tsai and colleagues (2001) work on disaster-related depression of the living alone elderly; Hsu and Tzeng (2003) study the impacts of property loss on psychological well-being; Hsu (2000) focuses on high school students’ disaster coping styles and posttraumatic symptoms; and Chen and Wang (2001) study culturally sensitive treatments for traumatized children and adolescents. Implications and suggestions are expected to be used as references for establishing future disaster mitigation and emergency management plans. Furthermore, the government has tried to reinforce the cohesiveness of community members through the Neighborhood Watch Program of the National Police Agency (NPA) or The Utilization of the Civil-capital of the National Fire Agency (NFA), yet, their efforts seem to focus on strengthening the security system. It sounds like people from all walks of life have sensed the importance of and have been trying to build disaster resistant communities around the island.
However, examining the current disaster mitigation and emergency management plans, it is found that those plans tend to focus on security of buildings and infrastructures. Most of the researchers and emergency managers are trained in the field of building and planning, engineering, and/or architecture. People from the field of social science often found themselves in an awkward place in the plans. Voices of community members, traits of local culture and its socioeconomic conditions, as well as social capital issues often like missing pieces in the puzzle of disaster mitigation and emergency management plans.
The authors believe that building a community disaster management support system requires professional trainings from various fields. Thus, they propose a cross-disciplinary community disaster management support system which consists of four dimensions: 1.) hazard-risk-vulnerability (HRV) analysis, 2.) community resilience and social capital evaluation, 3.) the interaction mechanisms between community organizations and the governments, 4.) spatial analysis and disaster monitoring system (Figure 1).
Figure 1. A cross-disciplinary model of community disaster management support system
Hazard-Risk-Vulnerability (HRV) analysis is crucial to a community’s safety. It is an important means to examine community safety by understanding both human behaviors and hazards from extreme natural events and then responding accordingly through adaptive measures. Wang (2006, 2009) asserts that Hazards include any potentials that may threaten human life and property before turning into disasters and include triggers as well as direct and indirect disasters. It is obvious that without a full HRV analysis, a community may overlook possible and potential hazards.
UN (2004) defines risk as “the probability of harmful consequences, or expected losses (deaths, injuries, property, livelihoods, economic activity disrupted or environment damaged) resulting from interactions between natural or human-induced hazards and vulnerable conditions.” Therefore, risk assessment focuses on measuring, within a specific social system, the probability and severity that the distribution and frequency of interaction between natural, physical and man-made environmental factors may cause hazards turn to disasters.
Vulnerability has become a focal point (Mitchell, 1989). In this model, vulnerability is defined as the active tendency of things to cause disasters or their passive tendency to incur damage. A measurement of the tendency and degree of severity for infrastructure, population, economy and social and political systems in the environment to become impacted by hazards, it also includes the distribution of people and goods and the quantity and type of relevant activities.
HRV analysis can provide decision-makers with a factual basis in terms of spatial and environmental threats (Cohrssen & Covello, 1989). When assessing hazard-prone areas, the decision-makers should familiarize themselves with the potential extent of damage, the probability of damage to public and private buildings and the susceptibility to the impact, as well as how changes in land use will alter the disasters’ impact. Further, they need to not just understand the anticipated damage to people, economy and the physical environment, but also take into account the effect on society, organizations and systems. Finally, they must consider the physical context’s degree of exposure and risk-bearers emotions, and work with the social vulnerability and community resilience specific to the areas exposed to disasters.According to Wang (2009), there are some important steps. Firstly , the hazard identification of all-hazard approach for the community based on gathered historic data should be executed. Then, the community should be split into different areas depending on the locations of possible disaster occurrences, and potential hazard occurrence rates should be analyzed. After collecting all the necessary data, a comprehensive hazard analysis for the entire community should be performed including the hazard types, locations and characteristics, conditions that may aggravate risk factors, and possible trends. Investigation into possible damage depending on the physical vulnerability must also be covered in the overall evaluation. Vulnerability can be classified as the physical vulnerability and non-physical vulnerability. Both types should be analyzed in terms of consequence, trend and resilience. The main focus of exploration should encompass possible affected subjects, impact severity, risk causes and vulnerability factors and affected locations and durations. The consideration of non-physical vulnerability must also include a full evaluation of economic, social, cultural, institutional, political and psychological factors. Both risk and vulnerability analyses should factor in extensive economic, commercial, social and environmental costs (both short- and long-term) as well as opportunities.
Community resilience and social capital evaluations cover community history of natural disasters, uniqueness of local culture, available resources, potential threats, socioeconomic conditions, composition of community members, social capital, and so forth. Studies indicate that certain communities adapt to post-disaster conditions better than others. They tend to bounce back to pre-disaster functions quickly, some even experience posttraumatic growth (Jang, 2008; Linley & Joseph, 2004). Community members strive to use inner strengths as well as outer available resources to face post-disaster life and solve challenges caused by the disaster. This is a demonstration of community resilience. Paton (2006) classifies factors promoting community disaster resilience into three levels: 1) personal-level: factors promoting positive outcome expectancy, such as characteristics of personality. For example, people who are optimist and with high self-efficacy are more likely to have positive outcome expectancy. They tend to be more willing to have an active role in emergency management plans. 2.) community-level: factors facilitating community participation and articulating problems, such as community awareness, local culture, resource availability, social support networks, required knowledge and skills and so forth; 3) institutional-level: support to economical and community needs, national policy of disaster prevention and response, and trust the community members have for their governments.
From the strength-based perspective, Greene (2002) affirms that people are the experts on their own problems. She believes that survivors are capable of growing and becoming independent. They can face or even solve any problems caused by disaster only if they possess enough resources and/or skills. Greene encourages disaster managers and helpers to be culturally sensitive. They need to respect local culture and counsel with community leaders especially when working with people from different cultures. Professional disaster helpers could assist residents of disaster-prone areas in cultivating their strengths, identifying available resources, re-building social support networks, encouraging self-reliance, and participating in emergency management plans.
In the establishment of community resilience and social support systems, the recognition and usage of community social capitals is a critical component of disaster risk evaluation and management. The implications of social capital-related concepts is not new. As early as in 1970s, from a micro point of view, the focus has been placed on relative topics like social resources in daily life or neighborhood relationship and so on, as well as the relationship between personal social resources and social status (Jacobs, 1961; Laumann, 1966). Since then, it has become a consensus that interacting and forming networks with other people is an important resource to help achieve personal goals (Borgatti, 1998; Lin, Cook & Burt, 2001). In contrast to the previous social capital studies based on micro perspectives of individual, family and neighborhood networks, Putnam (2000) explores the application of regional management and development from a macro perspective. He proposed that the organization, regulation, and trust of social networks reveal the presence of social capital. These features are advantageous to community participants in fostering cooperating and achieving goals of mutual benefit. Furthermore, studies also point out that the enhancement of community capacity includes strengthening community members’ social support networks, promoting community cohesiveness, increasing relationship of trust among community members as well as with NPOs and the governments (Burt, 1997; Keyes, et al., 1996). Although there is no common consent on the definition of social capitals, most of them value its role in promoting community well-being.Examining the disaster mitigation and emergency management plans in the past few years, the government usually takes a leading role. However, the planning and implementation of reconstruction projects rely highly on the cohesiveness of local residents, the trust and coordination among community groups, and the resources from public and private sectors. These are important elements of community social capitals and represent the keystone to building a community disaster management support system.
The interaction patterns between community organizations and the governments would reflect traits of disaster vulnerability and resilience unique to this particular community. According to the Disaster Prevention and Protection Act enacted in 2002, the disaster prevention and response system should include central-, county/city-, and township-level of governments. Even though the government has planed the system well, accusations of not offering immediate assistance to affected people and areas when major natural or man-made hazards strike are common. Part of the reason for this is that dealing with bureaucratic systems can sometimes requires a lot of time, patience, and skills. Therefore, one way to ensure the efficiency of emergency management, which may reduce loss of life and property, depends on developing the capacity of local communities to actively respond using assistance from the governments. Sundet and Mermelstein (1984) found that the community experience of interaction between a community and the government in the past affects the response of the community when hazard occurs and is a key to efficient operation of community emergency management plans. Thus, when establishing a emergency management plan, the community should develop its own warning system, recognize available resources, set up the connections with institutional disaster prevention and protection systems, and promote disaster education etc. (Lin, Shen & Deng, 2003; McEntire & Myers, 2004). Only by keeping perfect interactions and coordination with the government emergency systems, the community can strengthen its ability to respond and prevent from the calamity. When the community disaster management plan efficiently cooperates with that of the governments, it can reach its full efficacy.
There are many studies discussing the role of community disaster management in the entire emergency management system of the governments (Li, 2004; Lin et al., 2003). Yet, the local organizations of disaster mitigation and preparation are not often assigned to function in the disaster management, response, and prevention. It is suggested that the government should efficiently utilize the power of local members, provide the residents with required knowledge and skills in response to hazards, assist communities to develop their own disaster management and operation plans, as well as set up disaster warning system and identify available resources. Meanwhile, the government should actively elaborate the interacting mechanism with the local communities. Thus, the community disaster mitigation and emergency management plans may be strengthened, preparedness would be facilitated, and in turn the loss of life and property can be reduced (Paton, 2007). Along the same vein, Allen (2006) asserts that “community-based disaster preparedness (CBDP)” is the important strategy in decreasing vulnerability and planning for emergency.
Spatial analysis and disaster monitoring system comprises spatial analysis on disaster and disaster monitoring. The former presents statuses and details of community disasters with a Geographical Information System (GIS) . The purpose is giving users an overview and details of the disasters so that people and government officers can accordingly make disaster management policies or decisions for disaster recovery and/or rescue (Leu & Huang, 2008). The targets of spatial analyses are as follows.
There are many other applications of a GIS system which can not be completely listed in this paper.
The disaster monitoring can be divided into three cases: 1 ) pre-monitoring and pre-warning; 2) immediate warning; and 3) post-monitoring. Pre-monitoring and pre-warning is to observe phenomena or symptoms of a disaster. It often requires the help of domain experts or data mining techniques (Roiger & Geatz, 2003) . In other words, expert systems and data mining techniques are helpful in forecasting occurrence of disasters so that the monitoring system can warn the managers in advance. But, the forecast should be real time, otherwise pre-warning is helpless. Warning can be performed in different ways depending on currently available communication approaches. For example, if mobile phones or the Internet is available, pre-warning can be delivered to disaster managers through short messages or emails. However, when disaster occurs, regardless of whether we can communicate with the outside world or not, we have to isolate dangerous zones from people, and warn people (e.g., activating warning lights or sounds). The post-monitoring is to observe whether or not the disasters have continuously occurred, and to prevent the subsequent events. Often, the monitoring is performed manually. If we want the events to be monitored automatically, image processing and pattern recognition systems should be developed and implemented ( Theodoridis & Koutroumbas, 2003 ). In addition to warning people on the scene of the disaster, it would be better if we can mark the area on an electronic map, and show it on web sites to warn people who browse the web page.Further, collecting data for a disaster so that researchers can accordingly study the disaster later is also an important task of an information system. Although, currently many disaster information systems have provided something pertaining to recent disasters occurred in Taiwan, containing the positions of disasters, online monitoring potential mudslide/debris-flow risk area, etc, our opinion is that an disaster information should provide information concerning government orders, hyperlinks to other related websites (including government’s and non-government’s), online potential disasters monitoring and pre-warning, user remote login through different sizes of end devices (mobile phones, PDAs, PC and so on) and disaster document retrieval (for an easy access to documents).
The proposed cross-disciplinary model provides a preliminary exploration on the community disaster management support system. The construction of a comprehensive community disaster management support system means the enhancement and promotion of capacity and skills in different aspects, including 1.) implementation of community hazard-risk-vulnerability (HRV) analysis, 2.) promotion in disaster managing capacity of the individuals, community, as well as the governments, 3.) a sound operation and interaction mechanism between community organizations and the governments, as well as among levels of government, and 4.) construction of systems and skills that monitoring disaster occurrence and managing available resources. In other words, establishing a thorough community disaster management system needs to based on cross-disciplinary theory and application. The system starts with the participation of local community citizens, and then incorporates knowledge and practical operation of multi-dimensional disciplines, such as culture, society, politics, environment, spatial planning, disaster management, and information technology etc. Finally, it shall be efficiently linked with the institutional emergency management system.
However, it is admitted that the practice of such a cross-disciplinary integration reveals a humongous challenge in the communication and coordination as well as collaboration among the participants across academic backgrounds. With diversities in regulation, value system, knowledge base and learning culture, it is not easy for the experts and scholars trained in different fields to avoid the discrepancy in constructing and executing the integrated model. Thus, it has become a critical issue how to create a cooperative mechanism of efficient communication and mutual respect while planning and generating the community disaster management and operation model.
System integration is one of the most important components to success in cross-disciplinary research. Generally, there are two integration methods, distributed and centralized. With the former, researchers of each discipline should store and analyze their own data and develop their own information systems (Özsu & Valduriez, 1999). When cross-analyses are required, a researcher has to access data stored in other disciplinary systems. The main advantage is that data are stored dispersedly. There is no single-point-of-failure problem. The key disadvantage is consuming many more human resources to manage the data. The centralized approach is collecting all cross-disciplinary data in a centralized data base. Each discipline has a specific sub-database to keep the data. All sharable data are stored in a public area. When data are required, researchers have to log into the database to access the sharable or discipline-owned data. The advantage is requiring less human resources to manage and maintain the data. The disadvantage is single-point-of-failure problem.
In addition, the research team sets up a communication platform via internet to store and exchange information, attends professional workshops, call for coordination meetings from time to time. The exercise of these strategies is to advance team work, cross-professional knowledge, learning, and problem-solving. In the future, a study focusing on achieving efficient collaboration and implementation of cross-specialty team would be beneficial.
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Note: Support for this work was provided by Grants NSC 96-2625-Z-040 -001 – , NSC 97-2625-M-029-001 from National Science Council, Taiwan.
Massey University, New Zealand
17 December, 2010