Post-disaster Management Research Articles

Social impacts and post-disaster management in disaster-prone areas of East Java, Indonesia.

In disaster-affected areas, to restore the community's economic condition, local governments provide multiple kinds of assistance, including business capital (grants), low interest rates, production equipment, community empowerment activities, job opportunities and business partnerships with the local market. Furthermore, such strategies for disaster management should be implemented in an integrated manner, and the inclusion of local community members for prevention, mitigation, preparedness, and emergency response to recovery phases are also highly recommended.

Stochastic Differential Game of Sustainable Allocation Strategy for Idle Emergency Supplies in Post-Disaster Management

This study aims to explore allocation strategies for idle emergency supplies in a “demander–platform–supplier” supply chain system along with government regulation during the post-disaster recovery period. Allocation of emergency supplies is a complex task that encompasses resource allocation before and after disasters. It is essential to reduce losses in disaster-stricken areas and support development during post-disaster recovery. However, there is often an excessive supply of emergency materials and a mismatch between supply and demand sides in downstream supply chains, which may lead to severe waste and difficulties in recovering surplus materials. This paper takes idle emergency resource sharing level and corporate social responsibility goodwill as endogenous variables. The allocation approaches are dynamically evaluated by incorporating random elements that influence the endogenous variables. Three stochastic differential games are introduced to examine the interactions between the players. The centralized decision-making satisfies the consistency of overall and individual rationalities at any time in the emergency material allocation process, promoting the optimal sharing levels of emergency materials and overall profits. The decentralized decision-making with cost-sharing contracts achieves local optima and increases the dual marginal effect of the emergency industry chain. This paper incorporates the sharing economy into emergency management, showing how technology-driven sharing platforms can optimize resource utilization. The results suggest introducing cost-sharing contracts between demanders and suppliers can enhance collaboration and effort, leading to better resource allocation and increased efficiency. It contributes to sustainability by promoting efficient resource utilization through idle emergency resource sharing. By optimizing allocation strategies and enhancing corporate social responsibility, the study fosters the long-term viability and resilience of the supply chain system in post-disaster management.

R-RDSP: Reliable and Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management over DDS.

After natural disasters such as earthquakes, floods, or wars occur, cellular communication networks often sustain significant damage or become impaired. In these critical situations, first responders must coordinate with other rescue teams to communicate essential information to central command and survivors. To address this challenge, we have developed a reliable and rapidly deployable wireless ad hoc system for post-disaster management using Data Distribution Service (DDS) middleware, specifically RTI-DDS, named R-RDSP. The R-RDSP further enhances these metrics, achieving a 14.5% improvement in end-to-end delay and a 20.24% improvement in round-trip delay over the RDSP scheme. The R-RDSP system consists of three main modules: client, relay, and server. Each module connects to others via an ad hoc network, ensuring direct device-to-device communication without relying on existing infrastructure. The client module collects and sends the victim's location and emergency messages. The relay modules forward these messages across the ad hoc networks, ensuring minimal delay and high reliability. Finally, the server module receives the messages, processes them, and coordinates the response. Leveraging RTI-DDS for reliable message distribution, the system demonstrates robust performance even under challenging network conditions.

Sustainable Livelihood in Post-Disaster Tourism: Lesson Learned from Merapi Tourism Site

This research aims to explore the practice of the Sustainable Livelihood Tourism Framework (SLTF) in post-disaster management in the Mount Merapi area, Sleman, Yogyakarta. The focus of SLTF achievement in this study encompasses ecological, economic, sociocultural, and institutional dimensions. Research on the SLTF has indeed become a significant focus in tourism studies. However, most of these studies are confined to a single research methodology, resulting in limited scope and a lack of comprehensive discussion. This study used a mixed-method approach with an explanatory sequential design. The study found that tourism positively impacts the increase of economic activities in the community. However, on the ecological side, tourism presence degrades environmental quality due to issues such as carbon emissions, industrial waste, climate change, the greenhouse effect, illegal logging, and illegal mining. Furthermore, other policies were identified, such as mineral water mining permits that degrade the environment and the establishment of landfill sites in the Kaliurang area, which spoils the natural beauty. Tourism practices also have a negative impact on institutional aspects, as the community perceives government policies as too complex and not meeting their expectations. Lastly, in the socio-cultural aspect, tourism preserves traditional values, as tourists tend to respect them. This mixed-method approach underscores the need for balanced strategies that address environmental concerns while maximizing economic benefits, improving institutional involvement, and supporting socio-cultural enhancement.

Post-Fire Stability Bearing Capacity of I-Shaped Aluminum Alloy Members Under Axial Compression

Compared to steel structures, aluminum alloy structures are more susceptible to fire damage. Accurately evaluating the residual bearing capacity of fire-damaged aluminum alloy members is crucial for effective post-disaster management. Therefore, this paper investigates the post-fire bearing capacity of I-shaped aluminum alloy members under axial compression. First, a post-fire test on 16 I-shaped aluminum alloy members under axial compression was carried out. The test results indicate that all specimens fail by the minor axis flexural buckling, and the bearing capacity of the specimens decreases with the increase of the slenderness ratio. Moreover, a trilinear relationship is found between bearing capacity and post-fire temperatures. Second, finite element (FE) models are established using ABAQUS and validated against the test results. Subsequently, numerical analysis is carried out, considering various aluminum alloy brands, post-fire temperatures, slenderness ratios, initial geometrical imperfections, and cross-section dimensions. Through the statistical regression technology and the introduction of strength and stability-bearing capacity reduction coefficients, the formulae for estimating the post-fire stability-bearing capacity of I-shaped aluminum alloy members under axial compression are derived. Finally, the proposed formulae are verified to be accurate through error analysis.

Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation

Forests play a crucial role in maintaining the integrity of natural ecosystems. Accurate mapping of windfall damages following storms is essential for effective post-disaster management. While remote sensing image classification offers substantial advantages over ground surveys for monitoring changes in forests, it encounters several challenges. Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. This approach struggles with accurately modeling complex patterns in high-resolution images and often results in redundant samples. Secondly, the limited availability of labeled samples compromises the classification accuracy when they are divided into training and test sets. To address these issues, two innovative approaches are proposed in this paper. The first is a new sample selection method which combines block-based sampling with spatial features extracted by single or multiple windows. Second, a new evaluation criterion is proposed by using the homomorphic hypothesis margin map with out-of-bag (OOB) accuracy. The former can not only assess the confidence level of each pixel category but also make regional boundaries clearer, and the latter can replace the test set so that all samples can be used for change detection. The experimental results show that the OOB accuracy obtained by spatial features with whole block sampling was 7.2% higher than that obtained by spectral features with pixel-based sampling and 2–3% higher than that for block center sampling, of which the highest value reached 98.8%. Additionally, the feasibility of identifying storm-damaged forests using only post-storm images has been demonstrated.

The TransIRIO model: Capturing the economic ripple effect of different economic behaviours in post-disaster emergency - Recovery - Reconstruction

Existing models for assessing the indirect economic impact of disasters typically focus on the economic impact of post-disaster reconstruction and ignore the repercussions of the periodic characteristics of disaster management; thus, these models rarely capture the full indirect economic impact of disasters. In response, this study develops the TransIRIO model, which captures the amplified impacts of emergency rescue, transportation interruption and reconstruction on demand during the emergency - recovery - reconstruction. The balancing of adaptive behaviours, such as creating an inventory buffer, price elasticity, import/export control strategies, and distribution optimization is explored, and the intelligent response behaviour of interregional industrial entities in post-disaster management is assessed. We apply the TransIRIO model to simulate the propagation of impacts across 31 provinces in mainland China following the 2008 Wenchuan Earthquake. Our results found that previous assessment models that did not consider specific social activities during emergency rescue underestimated the indirect economic impact of disasters to some extent, and that underscored the importance of incorporating the spatially distributed and networked characteristics of transportation systems into supply-demand chain-based economic models. This study not only presents a novel approach to economic modelling but also provides valuable insights for policymakers and researchers engaged in post-disaster recovery planning.

Strategies for Humanitarian Logistics and Supply Chain in Organizational Contexts: Pre- and Post-Disaster Management Perspectives

Every organization typically comprises various internal components, including regional branches, operations centers/field offices, major transportation hubs, and operational units, among others, housing a population susceptible to disaster impacts. Moreover, organizations often possess resources such as staff, various vehicles, and medical facilities, which can mitigate human casualties and address needs across affected areas. However, despite the importance of managing disasters within organizational networks, there remains a research gap in the development of mathematical models for such scenarios, specifically incorporating operations centers/field offices and external stakeholders as relief centers. Addressing this gap, this study examines an optimization model for both before and after disaster planning in a humanitarian supply chain and logistical framework within an organization. The affected areas are defined as regional branches, operational units, major transportation hubs, operations centers/field offices, external stakeholders, and medical facilities. A mixed-integer nonlinear model is formulated to minimize overall costs, considering factors such as penalty costs for untreated injuries and demand, delays in rescue and relief item distribution operations, and waiting costs for the injured in emergency medical vehicles and air ambulances. The model is implemented using GAMS software 47.1.0 for various test problems across different scales, with the Grasshopper Optimization Algorithm proposed for larger-scale scenarios. Numerical examples are provided to show the effectiveness and feasibility of the proposed model and to validate the metaheuristic approach. Sensitivity analysis is conducted to assess the model’s performance under different conditions, and key managerial insights and implications are discussed.

Roles and responsibilities of stakeholders involved in local-level flood risk management: a study in the Deduru Oya basin in Sri Lanka

PurposeDisasters are occurring worldwide, and Sri Lanka has also become a victim of multiple disasters. Though there is a disaster management mechanism from the national level to the local level in Sri Lanka, several gaps are identified in pre- and postdisaster management activities. Among them, the responsibilities of local-level stakeholders in flood management activities are not performing at a satisfactory level. Therefore, the flood damage from the previous events was too great. Accordingly, the purpose of this study is to assess the roles, responsibilities and performance of stakeholders involved in local-level flood risk management activities.Design/methodology/approachThe Deduru Oya basin in Sri Lanka was selected as the study area. The study hypothesized that “ineffective roles, responsibilities and performance of local level stakeholders have weakened the flood risk management in the Deduru Oya basin.” The stratified random sampling method selected the sample (n = 425) from the flood-vulnerable population. Primary data were collected through a questionnaire survey, key informant interviews and field observations. Secondary data were collected from reports, work plans, journal papers and published maps. Descriptive data analysis methods and thematic data analysis methods were used in the study.FindingsAbout 69% of the respondents state that they are not satisfied with the involvement of government agencies in local-level flood risk management activities, while 10% of the respondents state that they are satisfied. The thematic analysis reveals several gaps, such as the lack of reservations in the Deduru Oya, improper land use practices, no inundation areas are identified and mapped out and the effects of illegal sand mining in the Deduru Oya. In addition to that, the lack of legal power vested in local governments in disaster management and the weaknesses of current legislation on flood risk management are the other major courses of local-level ineffectiveness.Research limitations/implicationsThe current research was limited to studying the involvement of local-level stakeholders in flood risk management, but the involvement of subnational and national-level stakeholders should be studied in future research.Originality/valueThis paper examines the involvement of local-level stakeholders in flood risk management. The results of the study confirm that the roles and responsibilities of local-level stakeholders are not well-defined and mandated, and therefore, the performance of stakeholders involved is minimal. Therefore, the results highlight the need for a well-established community-based flood risk management mechanism.

Principles of integrated disaster emergency response management in Indonesia

Disaster problems in recent years have become an interesting study, not only discussed by the government but also non-governmental organizations and the community. Facing this situation, the government must react and look for strategies to prevent natural (man-made) disasters or reduce the negative impacts following natural disasters.. Disaster phenomena can be studied from various scientific perspectives, including public administration. Disaster emergency response is a series of activities to deal with the direct negative impacts of disasters. According to BNPB Regulation Number 3 of 2018 concerning Handling Refugees in Disaster Emergency Situations, the Government's responsibilities in implementing Disaster Management include protecting the community from the impacts of disasters and ensuring the fulfillment of the rights of communities and refugees affected by disasters fairly and in accordance with minimum service standards. Based on the discussion above, it can be concluded that disaster management is part of a series implemented by the central and/or regional government through BNPB and/or BPBD in implementing post-disaster management or after a disaster by implementing in an integrated and comprehensive manner the principles that have been established which will implemented in stages determined by government regulations.

Quantitative assessment of earthquake-induced building damage at regional scale using LiDAR data

Regional-scale assessment of the damage caused by earthquakes to structures is crucial for post-disaster management. While remote sensing techniques can be of great help for a quick post-event structural assessment of large areas, currently available methods are limited to the detection of severely-damaged buildings. Furthermore, remote sensing-based assessment methods typically provide only qualitative results, as they lack integration with information on the building’s behaviour in response to seismic-induced ground shaking. In this study, we developed a new methodology that uses airborne Light Detection And Ranging (LiDAR) data in combination with structural indicators of building response to provide a quantitative assessment of earthquake-induced damage at a regional scale. LiDAR datasets collected before and after an earthquake are used to measure residual displacements of building roofs. The resulting lateral drift estimations are used to quantify the level of damage for a specific building typology. Application to the LiDAR datasets collected before and after the 2014 earthquake in Napa Valley, California, demonstrates the capability of the proposed method to detect moderate levels of structural damage, proving its potential for faster and more accurate support to post-disaster management.

Integrated System Design for Post-Disaster Management: Multi-Facility, Multi-Period, and Bi-Objective Optimization Approach

Disaster management requires efficient allocation of essential facilities with consideration of various objectives. During the response and recovery phase of disaster management (RRDM), various types of missions occur in multiple periods, and each of them needs different support from facilities. In this study, a bi-objective mathematical model was derived to support multi-period RRDM by optimal allocation of required facilities such as drone stations, shelters, emergency medical facilities, and warehouses according to the mission life cycle. Connectivity between facilities was considered to ensure inter-facility complementarity. For efficient derivation of Pareto solutions, a modified epsilon-constraint algorithm for bi-objective optimization was developed. The algorithm was tested with a realistic disaster simulation scenario using HAZUS 4.0 as a demonstration of the benefits of the proposed approach. With the simulation experiments, the proposed approach was expected to provide efficient operational plans and guidelines to decision makers for the bi-objective optimization problem in RRDM systems. In addition, the consideration of inter-facility connectivity can play an important role in the RRDM, especially for robustness and readiness.

Joint User Association and Power Control in UAV Network: A Graph Theoretic Approach

Unmanned aerial vehicles (UAVs) have recently been widely employed as effective wireless platforms for aiding users in various situations, particularly in hard-to-reach scenarios like post-disaster relief efforts. This study employs multiple UAVs to cover users in overlapping locations, necessitating the optimization of UAV-user association to maximize the spectral and energy efficiency of the UAV network. Hence, a connected bipartite graph is formed between UAVs and users using graph theory to accomplish this goal. Then, a maximum weighted matching-based maximum flow (MwMaxFlow) optimization approach is proposed to achieve the maximum data rate given users’ demands and the UAVs’ maximum capacities. Additionally, power control is applied using the M-matrix theory to optimize users’ transmit powers and improve their energy efficiency. The proposed strategy is evaluated and compared with other benchmark schemes through numerical simulations. The simulation outcomes indicate that the proposed approach balances spectral efficiency and energy consumption, rendering it suitable for various UAV wireless applications, including emergency response, surveillance, and post-disaster management.

Informing disaster-risk management policies for education infrastructure using scenario-based recovery analyses

Recent natural-hazard events have shown that post-disaster education continuity is still a significant global challenge. Here, we propose a methodology to support various stakeholders in quantifying the impact of disaster management policies on education continuity in low- and lower-middle-income countries. We then apply the proposed methodology to a hypothetical earthquake scenario impacting a testbed education infrastructure in Central Sulawesi, Indonesia. This case study accounts for local practice influencing recovery through interviews with stakeholders involved in post-disaster management in the region. The analyses reveal that early response financing mechanisms can help speed up education recovery by a factor of three. Also, community-managed school reconstruction projects are likely to be completed up to three to five times faster than agency-managed projects. Furthermore, we demonstrate how the framework can be used to prioritize school reconstruction projects to ensure inclusive education continuity at the community level.

Assessing the Post-Disaster Effects of COVID-19 Pandemic Towards Malaysian Construction Industry

Amidst the global upheaval caused by the Coronavirus 2019 (COVID-19) pandemic, substantial disruptions reverberated across nations, including Malaysia, prompting extensive lockdown measures. In response to the virus’s transmission, the Malaysian government enforced the Movement Control Order (MCO) starting on the 18th March 2020. This directive wielded a profound influence, notably impacting diverse sectors within Malaysia, including the construction industry. This study aimed to assess the effects of the COVID-19 pandemic as a post-disaster scenario, with the construction sector as the focal point. The study is executed within the framework of two primary parameters: the occurrence and the significance of the ramifications from the pandemic. A quantitative research methodology was employed, wherein a questionnaire survey was distributed to active industry participants in the construction industry in East and West Malaysia. In total, 197 responses were collected and analysed using the relative importance index technique. Across nine construction domains, 49 effects were investigated. Findings show that the scarcity of materials and workforce, followed by the shortage of labour force especially foreign labour, construction delays stemming from restrictive mandates, revisions in scheduling and work scope and an escalation in material costs are among the top five rankings of the post COVID-19 effects on the construction industry. The outcomes of this research have substantially contributed to the comprehension of the effects induced by the COVID-19 pandemic on the construction industry. The main aim is to amass data that can be leveraged by policy makers to bolster post-disaster management strategies within Malaysia, thereby facilitating the transfer of knowledge for future post disaster management endeavours. Additionally, the study has shed light on the disparities delineated along the regional demarcation of East and West Malaysia.

Natural disaster is a wakeup call before it becomes social disaster and tourophobia of eco-destinations

ABSTRACT This paper summarizes the current state of crisis and disaster at the eco-destination of Thailand and investigates its impact on tourists’ preferences. The study authenticates the claim of the inevitability of disasters at eco-destinations, explains the effects of timely response by relevant authorities, and provides inputs to diffuse the chaotic post-disaster situation and the development of tourophobia. It further notes the contribution of destination reputation and crisis communication to maintaining tourists’ trust and making Thailand the first choice for eco-tourism enthusiasts. This paper provides insights into effective post-disaster management before it turns eco-destinations into tourophobic destinations.

Deprem sonrası erken dönemde travma belirtileri, uyku kalitesi ve ilişkili faktörler

Aim: Traumatic life events such as earthquake are frequently encountered problems both in our country and all over the world. The aim of this study was to determine sleep quality, trauma level and related factors and to evaluate the effects of gender, damage status and losses in adults who were admitted to the psychiatry outpatient clinic among individuals who were placed in Kırıkkale University student dormitories immediately after the 6 February 2023 earthquakes that affected a wide geography in our country.
 Methods: 64 volunteers were included in the study between March 2023 and June 2023. After the participants' complaints and sociodemographic characteristics were questioned, the Pittsburgh Sleep Quality Index (PSQI) and the Scale That Determines the Level of the Trauma after the Earthquake (PETLDS) were applied to the participants to determine their sleep quality and trauma levels after the earthquake.
 Results: 
 The mean age of the participants was 45.5±15.5, and 75.0% of them were women. Fear/anxiety and insomnia were the most frequently reported complaints by the participants. The mean of the participants' PSQI scores was 10.5±4.4, and 43 participants (79.6%) had poor sleep quality in the last month. The mean score of the participants' PETLDS was determined as 76.6±17.9. When the subscales were examined, it was determined that the emotional limitation and cognitive restructuring scores were higher than the behavioral, affective and sleep problems. When the participants were compared in terms of damage in their homes, it was found that the participants with moderately or more damaged houses had statistically higher emotional, cognitive restructuring and sleep problems and total trauma scores compared to the participants with a solid or slightly damaged house (respectively; p=.017, p=.023, p=.010, p=.040). Individuals with moderately or more damaged houses had higher PSQI scores but this difference did not reach statistical significance (p=.061).
 Conclusion: The earthquakes that occurred in our country on and after 6 February 2023 affected a large area and resulted in millions of people being directly or indirectly affected. To minimize the physical and psychological damage that earthquakes may cause, post-disaster management should be carried out well, and it should be noted that it is a priority to support earthquake victims psychologically as well as their social and medical needs.

A Mapping Study of Psychological Preparedness in Dealing with Extreme Temperature Changes and Natural Disasters

Background: Natural disasters and extreme temperature changes are increasing every year in various parts of the world. Disasters and extreme temperatures have physical, material, and psychological impacts on society. Because of the local community's low psychological readiness, this impact frequently causes mental health problems. Study Aims: This study aims to reveal research mapping related to psychological preparedness for natural disasters and extreme temperatures in population groups in Indonesia and in non-Indonesia countries. Method: The method used in this study is a systematic literature review (SLR) of psychological preparedness, disaster, and climate change-related extreme temperature research. Data collection was carried out with the PoP8 software and the PRISMA chart. The research data were analyzed by bibliometric visualization and narrative analysis with the VOS Viewers software. There are 60 eligible articles for analysis. Result: 1) Disaster research in the world has increased in the last ten years, but there is a decreasing trend in 2020-2022 due to a focus on the COVID-19 pandemic. 2) Disaster studies in non-Indonesia countries and in Indonesia differ. non-Indonesia countries research focuses on disaster anticipation and post-disaster management. Meanwhile, in Indonesia is focusing on the psychological impact of disasters, environmental damage, and non-psychological disaster preparedness. 3) Research on psychological preparedness and risk perception in foreign countries is developing quite rapidly. In Indonesia, studies regarding the identification of risk factors and efforts to overcome disasters based on local wisdom are quite prevalent. Conclusion: According to the findings of these studies, there hasn't been much research on psychological preparedness for disasters in Indonesia. This indicates that the opportunity to conduct psychological preparedness research in Indonesia is still open and needed.

Rakshak: Post-Disaster Management through an Android Mobile Application

In the aftermath of a natural or man-made disaster, the most important thing is rescue and reconstruction. Large-scale disasters cause significant damage to lives, livelihood, and infrastructure. The breakdown of existing infrastructure is particularly detrimental since it also hampers rescue efforts and emergency services. From an administrative standpoint, effective logistical management and allocation of resources, as well as getting real-time reports, is highly imperative. Key Words: Disaster Management, Application, GIS, SOS

Blockchain Disaster Management for Humanitarian Logistic as Post-Disaster Response Measures

Indonesia has a high risk of earthquake and tsunami disasters because there's many tectonic plates meet. This also causes Indonesia to have many geological changes compared to other countries. Therefore, an explicit scheme to provide information related to disasters, like an information system in post-disaster management is important. The purpose of this research is to provide transparent information regarding the data on the goods needed and the data on goods to be distributed to ensure the amount used and not used, so that victims affected by disasters can be handled quickly and appropriately. The method used in this research is a literature review. The results of this study indicate the existence of a Blockchain Disaster Management Information System as a form of a new scheme in the post-disaster management process and is an upgraded form of information system that has been developed previously. This scheme uses the blockchain concept to provide transparency and data immutability. This scheme coordinates with various institutions such as BPBD (Regional Disaster Management Agency), BNPB (National Disaster Management Agency), BASARNAS (National Search and Rescue Agency), PMI (Indonesian Red Cross Society), the nearest hospital, and other related institutions. © 2023 Universitas Pendidikan Indonesia