Abstract
Based on a statistical analysis, we developed a methodology to determine the Risk Management Index (RMI) at the local level. The algorithm is transparent, relatively easy to update periodically by the affected communities themselves, and the results are easy to understand by public policymakers. The main characteristics of this tool are: (1) It considers disaster management issues at the local level; (2) RMI values are obtained using a statistical analysis; (3) levels of performance are classified in a scale of numbers ranging from 0 to 5, where 0 = nonexistent, 1 = low, 2 = incipient, 3 = significant, 4 = outstanding, and 5 = optimal; (4) the weight of the indicators is determined using the analytic hierarchy process. As case studies we applied this methodology to the districts of Iztapalapa and Xochimilco in Mexico City, Mexico. Our results indicate that, to date, the Xochimilco District has not implemented any actions designed to reduce risk or to provide financial protection. Low performance was measured also in risk identification and disaster management. The Iztapalapa District has an outstanding level of performance in risk identification. However, its score is low in activities related to risk reduction, disaster management, and financial protection. The RMIs obtained in both communities highlight the need for developing permanent programs for disaster prevention, mitigation, and response. The methodology used here is designed to aid in evaluating and understanding existing disaster management problems in a community and in guiding the decision-making processes to reduce the hazard and to conduct remedial actions at the local level.
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Acknowledgments
The authors are grateful to an anonymous reviewer for his/her thoughtful review of this paper and providing helpful comments. We also express our appreciation to the staff of the Xochimilco and Iztapalapa districts of Mexico City who kindly provided their expertise, time, and data to estimate the Risk Management Index as case studies. We thank M. Viesca-Gold for her help in processing the data and preparing the initial figures. The project received grants from the Instituto de Geofísica and the Program to Support Research Projects and Technology Innovation of the National Autonomous University of Mexico (UNAM; PAPIIT Project No. IN118614).
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Novelo-Casanova, D.A., Suárez, G. Estimation of the Risk Management Index (RMI) using statistical analysis. Nat Hazards 77, 1501–1514 (2015). https://doi.org/10.1007/s11069-015-1663-4
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DOI: https://doi.org/10.1007/s11069-015-1663-4