Background: Over recent years, the exposure of people and assets to disasters has been faster than reducing vulnerability in all countries. As a result, new risks have been formed and losses due to disaster are progressively increasing. Suffering from significant losses in the aftermath of disasters every year, Iran is no exception. Governmental and non-governmental stakeholders are jointly responsible for managing the risks of disasters. Hence, appropriate, collaborative and timely interactions of involved organizations will play an important role in their operation, especially during disasters. Methods: In this study, we used the Social Network Analysis (SNA) to analyze the network of stakeholders in disaster risk management in Iran. Our review of literature, laws, and regulations of disaster risk management plus brainstorming identified a list of 85 stakeholders. We used the Delphi method among purposefully selected experts to score the relationship between the stakeholders. We then used the modularity optimization method to identify groups with greater interaction. Organizations with key-roles in the network and the ones in need of stronger relationships were identified through centrality measurements. Results: The density of this network was 0.75, which represented that not all the stakeholders were connected. Among all organizations identified, the National Disaster Management Organization and Civil Defense Organization showed higher influences considering their responsibilities. Conclusion: To provide a visual and tangible picture of the status and interrelationships among the stakeholders, this method identified groups with better interaction using community/cluster detection and modularity optimization methods. Understanding the current structure of the network and strengths and weaknesses of the interactions among stakeholders may help improve disaster risk management in Iran. Results of this research determine the role and importance of different organizations, their weakness, and strong points. Also, results help them to plan to strengthen their roles and solve their problems.
Background: Stakeholders are responsible for managing the risks of disasters. Hence, appropriate, collaborative, timely interactions of involved organizations, and having a collective view of these interactions, have an important influence on the operation of the whole system. This study was aimed at social network analysis (SNA) for the implementation of the Sendai framework for disaster risk reduction in Iran. Methods: SNA was used in this study. A review of literature on disaster risk management (DRM) plus snowball sampling technique identified a list of 85 stakeholders. Delphi method among purposefully selected experts was used to score the relationship between the stakeholders. Louvain method, along with the modularity optimization method, was applied to identify groups of stakeholders with greater interactions. Centrality measurements were used to define organizations with key-roles in the network. Results: The density of this network was 0.75, which showed that not all the stakeholders were connected. The National Disaster Management Organization and Civil Defense Organization showed higher influences considering their responsibilities. A total of 3 clusters of stakeholders with specific duties that mostly interact with each other and have some interaction with other groups were recognized. Conclusion: Understanding the pre-disaster interaction of the network and the strengths and weaknesses of the interactions among stakeholders could help improve DRM.
Benchmarking is one of the superior methods and processes for performance and organizational improvement. This study was conducted to determine benchmarking rate of disaster management committee members in Iranian public hospitals in effective disaster response. Methods: This cross-sectional study was conducted in 2018. The research community was Iranian public hospitals that were randomly selected based on spatial planning. The data were collected using a researcher-made questionnaire including two parts of individual variables, and amount and technique of benchmarking using 14 open-ended and closed-ended questions. The data were analyzed by SPSS-23 software. Results: Out of 410 members available from the hospital crisis and disaster management committee who were studied, 103 persons (25.1%) had from 1 to 8 benchmarking cases during the period of cooperation with this committee, and a total of 237 cases of benchmarking were recorded. Thus, the mean number of benchmarking cases was 0.58±1.2. Thus, the mean score of benchmarking was 0.58±1.2. There was a significant relationship among the number of benchmarking cases and the duration of cooperation in the Disaster Management Committee (P=0.001 & r=+0.177), the number of active beds in the hospital (P=0.024 & r=+0.117), educational level (P=0.029 & r=+0.109), and the city of hospital (28.4% in metropolitan areas and 15.9% in non-metropolitan areas) (P=0.010). Conclusion: This study showed that benchmarking rate per capita among the studied members was in a lower level compared to other similar studies. Therefore, it is suggested that appropriate intervention programs be designed and implemented.
During the first half of 2019, many provinces of Iran were affected by floods, which claimed the lives of 82 people. The present study aimed to investigate the behavioral, health related and demographic risk factors associated with deaths due to floods. We measured the odds ratio and investigated the contribution and significance of the factors in relation to mortality. This case-control study was conducted in the cities affected by flood in Iran. Data were collected on the flood victims using a questionnaire. Survivors, a member of the flood victim’s family, were interviewed. In total, 77 subjects completed the survey in the case group, and 310 subjects completed the survey in the control group. The findings indicated that factors such as the age of less than 18 years, low literacy, being trapped in buildings/cars, and risky behaviors increased the risk of flood deaths. Regarding the behavioral factors, perceived/real swimming skills increased the risk of flood deaths although it may seem paradoxical. This increment is due to increased self confidence in time of flood. On the other hand, skills and abilities such as evacuation, requesting help, and escape decreased the risk of flood deaths. According to the results, the adoption of support strategies, protecting vulnerable groups, and improving the socioeconomic status of flood-prone areas could prevent and reduce the risk of flood deaths.
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