Decision Support Systems (DSS) have emerged as important tools for enhancing community resilience due to their ability to provide timely and efficient solutions to disaster-related problems while reflecting the perspectives of different stakeholders and utilizing multiple data sources. This paper provides a comprehensive summary of DSS applications to community resilience, emphasizing how the different modeling techniques are used in different disaster phases. We found that optimization techniques are the most frequently used methods for building DSS. Furthermore, we found that DSS tend to focus more on the preparedness and response phases of disaster management, rather than the recovery and mitigation phases. Moreover, the study highlights the main challenges in developing and implementing DSS for resilience, such as data availability, the uncertainty of the disaster context, and the need for cross-disciplinary collaboration. Based on the reviewed papers, we provide some guidelines to practitioners to select the most suitable decision-support tools for the needs of their community. The study aims to help decision-makers and researchers build effective decision support systems for enhancing community resilience, considering the current challenges.

OBJECTIVE: To examine the relationship between nurses\' competency levels in disaster nursing management, their disaster preparedness and disaster preparedness beliefs.
BACKGROUND: Nurses\' competency in disaster nursing management makes disaster response easier. Factors that may affect this reason should be examined.
METHODS: The study was conducted between April and July 2023 with nurses working in a province in the first-degree earthquake zone in Turkey. The sample of the study consisted of a total of 207 nurses who were selected from primary, secondary, and tertiary care institutions by using the stratified sampling method. Data were collected with a personal information form, the Competencies for Disaster Nursing Management Questionnaire, the Disaster Preparedness Scale, and the General Disaster Preparedness Beliefs Scale. Mann-Whitney U and Kruskal-Wallis tests, Spearman regression coefficient, and multiple linear regression analysis were used to analyze the data.
RESULTS: There was a positive correlation between nurses\' competency levels regarding duties and responsibilities and their disaster preparedness levels. Having disaster-related training also positively affected the level of competence in duties and responsibilities. Belief in disaster preparedness and having \"partial\" knowledge about the disaster had no relationship with competencies.
CONCLUSIONS: According to the International Council of Nurses and current studies on disaster nursing, \"competence areas\" are among the priority study subjects.
CONCLUSIONS: According to the study results, disaster preparedness and having disaster-related education are effective factors in nurses\' competencies related to duties and responsibilities.
CONCLUSIONS: The results of this study may increase awareness in the healthcare system about nurses\' disaster management competency levels and the factors that may affect this. It is recommended that disaster preparedness and disaster-related education factors should be taken into account in the initiatives and policies to be planned to improve the duty and responsibility competence of nurses.

UNASSIGNED: Transnational drug trafficking, political unrest, gang violence, and paramilitarism, which are pervasive in Haiti, have resulted in a mental health crisis for the broader Haitian community. This study explores the mental well-being of Haitians in Haiti and the United States by identifying barriers and facilitators to mental health through the lived experiences of men and women.
UNASSIGNED: Four Focus group discussions conducted in April and November 2023 engaged 28 participants (20 women and eight men) aged between 23 and 60 years from locations in Haiti (Port-au-Prince, Cite Soleil, Cayes, Cap-Haitien, Saint-Marc) and the United States. Discussions revolved around the definition of mental health, stressors, coping mechanisms, risk and protective factors, and barriers to mental health care.
UNASSIGNED: Six principal themes emerged: 1- Chronic Traumatic Stress: continued violence, political instability, unemployment, lack of social support, adverse childhood experiences, family separation, and forced displacement were significant sources of stress. 2- Increased Health Burden: Participants reported experiencing chronic physical and psychological symptoms (i.e., hypertension, anxiety, depression, sleep issues, substance abuse, suicidal ideations, characteristics of post-traumatic stress disorder [PTSD]), which were attributed to Haiti\'s social, political, and infrastructure collapse. 3- Risk Factors: limited access to mental health services, pervasive hopelessness, scarcity of opportunities, and stigma were identified as significant risks. 4- Future Uncertainty: widespread concerns regarding the future predominated. 5- Multigenerational Concerns: Significant anxiety concerning the mental health and development of children, as well as the functionality of mental health practitioners, was noted. 6- Coping and Protective Factors: Effective coping strategies include mental stimulation, peer support, managing digital consumption, engaging in leisurely activities, such as listening to music, and faith/spirituality.
UNASSIGNED: The study\'s findings underscore the sociopolitical and economic crisis in Haiti, which has resulted in violence and a collapse of political, educational, financial, and health infrastructures. These factors were identified as the primary source of chronic distress, contributing to widespread mental health issues, adverse physical symptoms, and disruption in daily life. The implications for practice, healing, research & policy are discussed.

OBJECTIVE: COVID-19 revealed major shortfalls in healthcare workers (HCWs) trained in acute and critical care worldwide, especially in low-resource settings. We aimed to assess mass online courses\' efficacy in preparing HCWs to manage COVID-19 patients and to determine whether rapidly deployed e-learning can enhance their knowledge and confidence during a pandemic.
METHODS: Retrospective cohort study.
METHODS: This international retrospective cohort study, led by a large Academic Medical Centre (AMC), was conducted via YouTube and the AMC\'s online learning platform. From 2020 to 2021, multidisciplinary experts developed and deployed six online training courses based on the latest evidence-based management guidelines. Participants were selected through a voluntary sample following an electronic campaign. Training outcomes were assessed using pre-and post-test questionnaires, evaluation forms, and post-training assessment surveys. Kirkpatrick\'s Model guided training evaluation to measure self-reported knowledge, clinical skills, and confidence improvement. We also captured the number and type of COVID-19 patients managed by HCWs after the trainings.
RESULTS: Every 22.8 reach/impression and every 1.2 engagements led to a course registration. The 10,425 registrants (56.8% female, 43.1% male) represented 584 medical facilities across 154 cities. The largest segments of participants were students/interns (20.6%) and medical officers (13.4%). Of the 2169 registered participants in courses with tests, 66.9% completed post-tests. Test scores from all courses increased from the initial baseline to subsequent improvement post-course. Participants completing post-training assessment surveys reported that the online courses improved their knowledge and clinical skills (83.5%) and confidence (89.4%). Respondents managed over 19,720 COVID-19 patients after attending the courses, with 47.7% patients being moderately/severely ill.
CONCLUSIONS: Participants\' confidence in handling COVID-19 patients is increased by rapidly deploying mass training to a substantial target population through digital tools. The findings present a virtual education and assessment model that can be leveraged for future global public health issues, and estimates for future electronic campaigns to target.

Recent policy discourse on the localisation of disaster management and humanitarian assistance lacks attention to the culture, history, and traditions of the Global South. This special issue of Disasters argues that it is imperative to recognise the dynamic, interactive, contested, and negotiated nature of local knowledge. Such local knowledge saves lives by enabling responders to situate ad hoc, one-off events such as disasters in the broader and deeper context of community relationships, thereby providing more appropriate and more effective aid. Through the cases of China, Japan, Indonesia, and the Philippines, this special issue examines such dynamic local knowledge using an analytical framework consisting of three manifestations of local knowledge, namely: social capital; contextual historical memories; and adaptation to new ideas. These three manifestations show the ways in which local knowledge creates local capacity, via which local, national, and international disaster respondents can centre their response coordination, and in turn, demonstrate how local capacity reformulates local knowledge.
災害管理と人道支援の現地化に関する近年の政策議論には、アジア諸国を含むグローバル・サウスの文化、歴史、伝統への配慮が欠けている。本特集論文では、災害管理と人道支援のサイクルのすべての要素を分析する際に、ローカルナレッジの対話的でダイナミック、論争的、交渉的な性質を認識することが不可欠であることに関して議論する。これにあたり、本特集論文では、こうしたダイナミックなローカルナレッジを、社会資本、文脈記憶、新しいアイデアへの適応というローカルナレッジの3つの具現型を通じて包括的に検討する。これら3つの具現型は、ローカルナレッジが地域の力を生み出し、それをもとに地域、国、そして国際的な災害対応者がどのように対応調整を行うか、そして逆に、地域の力がローカルナレッジをどのように再形成するかを示している。.
最近关于灾害管理和人道主义援助本地化的政策讨论缺乏对包括亚洲国家在内的全球南方国家的文化、历史和传统的关注。本期特刊指出，在分析灾害管理和人道主义援助周期的所有要素时，必须认识到当地知识的互动性、动态性、争议性和协商性。为此，本特刊通过地方知识的三种表现形式，即社会资本、情境记忆和对新思想的适应，对这种动态的地方知识进行了全面研究。这三种表现形式展示了地方知识如何创造地方能力，地方、国家和国际灾害应对人员可以以此为中心进行响应协调；反过来，也展示了地方能力如何重新形成地方知识。.

Studying the mechanisms by which climate change interacted with human societies during the historical period can provide historical insights and cultural roots for climate policy building in the region. In this study, we constructed Stability-Robustness-Resilience Model (SSR model) and used the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) and the entropy weight method to assess the change processes of robustness, resilience, and stability of Ming\'s society in response to climate threats. We have also compared three extreme droughts that occurred in different periods of social robustness-resilience combinations by using the SRR model. The results are as follows. (1) The stability of the Ming society was high in YongLe - HongZhi period (1402-1505 CE), when both social robustness and resilience were higher than the average level of Ming Dynasty (0.5611 for the former and 0.4215 for the latter), but there was a significant decline in social stability in TianShun period (1457-1464 CE). In ZhengDe - ChongZhen period (1506-1644 CE), the stability of Ming society gradually decreased, and it rebounded shortly in the LongQing-WanLi period (1506-1620 CE). (2) The high stability benefited from higher socio-economic levels, better government finance levels, larger national food reserves, safer social environments (high robustness), and higher levels of ruling class governance and risk response (high resilience); whereas insecure social environment induced by war, declining socio-economic levels and government finance levels were the main reasons for the decline in society\'s stability. (3)The ChengHua and WanLi droughts both happened at a time with high social robustness, so although their meteorological anomalies were severe, their impact on society was small. While the JiaJing drought happened at a time with low social robustness and resilience, so although the meteorological anomaly was relatively weak, it resulted in a more severe social consequence than the other two events.

Collaboration between government and communities in disaster management has been demonstrated to create disaster risk reduction initiatives. However, implementing such collaboration poses challenges within regions characterised by dualism in governance. This study aims to investigate the disaster management system for coronavirus disease 2019 (COVID-19) in the context of dualism governance, where the state holds administrative control. Traditional authority (Adat) simultaneously regulates various facets of human life in Bali, Indonesia. The study used a qualitative approach, and data were gathered through in-depth interviews with 10 informants, 3 rounds of focus group discussions, and participant observations. The findings reveal that the dualism governance in Bali is manifested through responses to vulnerabilities within the community, Adat versus state laws, and the communication systems established between state administrative and traditional authorities during the COVID-19 response.
UNASSIGNED: This study highlights the significant role of traditional governance in enhancing community resilience amid the limitations of state capacity in handling the COVID-19 pandemic. Despite conflicting interests with the state, traditional government plays a crucial role in fostering collective community action to address vulnerabilities. The study underscores the importance of greater involvement of Adat actors in disaster management within the context of dualism in governance, spanning from mitigation planning to preparedness, response and recovery. This involvement has the potential to bolster community resilience.

Effective relief reduces damages and protects people during natural disasters, such as earthquakes. This research proposes a data-driven model based on sustainability, taking into account the pre and post-crisis simultaneously. Real data was used to validate the model in various earthquake scenarios. The study addresses questions regarding the amount and allocation of relief goods during earthquakes. This research is carried out in two phases: simulation and modeling. The purpose of the simulation phase is to estimate the number of relief goods in different scenarios. Additionally, in the modeling phase, a data-based multi-objective model is presented, considering sustainability, to minimize the lack of relief goods, the number of untreated wounded, and supply chain costs. Using the dynamic simulation system, and after designing the structure of the earthquake effects on urban infrastructure, the actions and effects of the earthquake on vital arteries are investigated in different scenarios, and scenarios with a higher degree of risk are identified. The results showed that the highest and lowest demands for relief goods were related to the \"Mosha-day fault\" and \"North Tehran-night fault\" scenarios, respectively.

A rapid and comprehensive assessment of flood impacts is critical to assist emergency managers in conducting effective relief operations. With advances in information technologies, various types of sensors have been widely used to assess flood impacts promptly as they are capable of providing rapid flood impact information. However, sensor-driven approaches are limited in the provision of a comprehensive impact assessment as sensors are often sparsely distributed. In this research, the authors integrate the sparse flood impact information obtained from sensors and the spatial autocorrelation of flood-impacted areas, in order to achieve a rapid and comprehensive flood impact assessment. To achieve such a purpose, a systematic approach is proposed to (1) extract flood impact information from sparsely distributed sensors; (2) model the spatial autocorrelation of flood-impacted areas based on flood evolution and geography principles; (3) learn the parameters of the spatial autocorrelation model through a gradient descent method; (4) infer the flood impacts of sensor-uncovered areas based on the sparsely sensed impacts and the modeled spatial autocorrelation. To illustrate the proposed approach, we studied flood impacts on Highways in Houston, Texas during Hurricane Harvey. Results show that the spatial autocorrelation model presents a decent generalization capability in inferring the probability of neighboring highway blocks having the same flood impacts. Compared to purely sensor-driven approaches, the proposed approach is capable of greatly extending the coverage of flood impact assessment while maintaining the nearly same accuracy.

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