In a situation of an unexpected catastrophe, uncertainty and demand for information are constant. In such a disaster scenario, the CRISIS system arises as a tool to contribute to previous coordination, procedure validation, exercise execution, a good and frequent communication among organizations, and weakness and threat assessment for an appropriate risk management. It offers a wide variety of tools for online communication, consultation and collaboration that, up to this day, includes cartography, tasks, resources, news, forums, instant messaging and chat. As a complement, mathematical models for training and emergency management are being researched and developed. For Argentinean society, it is a necessity to switch from the current handcrafted, bureaucratic emergency management method to a decision-making management model. Previous coordination, exercise execution, a fluid communication among institutions, and threats and weaknesses assessment are required for a proper risk management. With that goal in mind, it is important to reduce confusion, avoid the duplication of efforts to fulfill the same tasks, and have access to a complete vision of the situation, generated from the data of all the organizations taking part. The CRISIS system is a secure web application, accessible to every node in a network formed by the organizations which have complementary responsibilities during prevention and response. It offers a wide variety of tools for online communication, consultation and collaboration that, up to this day, includes cartography, tasks, media (organization and resources), news, forums, instant messaging and chat. As a complement, mathematical models for training and emergency management are being researched and developed. Currently, there are toxicological and epidemiological emergency models available. The present paper analyses, from the perspectives related to risk management for emergencies and disasters, the strengths and weaknesses of the CRISIS system to be used for prevention, response and recoveries in the case of a catastrophe.
References
[1]
Sphere Project. In The Sphere Handbook: Humanitarian Charter and Minimum Standards in Humanitarian Response, 3rd ed.; Practical Action Publishing: Rugby, UK, 2011; pp. 63–87. ISBN 978-1-908176-02-8.
Decreet 1250/99. Available online: http://www.disaster-info.net/PED-Sudamerica/leyes/leyes/suramerica/argentina /sistemnac/Decreto_1250-SIFEM.pdf (accessed on 13 June 2012).
[4]
Chen, T.H.; Chen, C.W. Application of data mining to the spatial heterogeneity of foreclosed mortgages. Expert Syst. Appl. 2010, 37, 993–997.
[5]
Rizo, R.; Llorens, F.; Pujol, M. Architectures and communication between agents. In Agentes Inteligentes: Sistemas Multiagentes y Aplicaciones; Skarmeta, A.G., Pujol, M., Rizo, R., Eds.; Alicante, Espa?a, 2002; pp. 181–214. ISBN: 84-8454-182-7.
[6]
García Serrano, A.; Ossowski, S. Distributed artificial intelligence and multiagent systems. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 1998, 1–12.
[7]
Sahana-Software Foundation site. Available online: http://sahanafoundation.org/~~V (accessed on 15 August 2012).
[8]
Chen, X.; Kwan, M.; Li, Q.; Chen, J. A model for evacuation risk assessment with consideration of pre- and post-disaster factors. Comput. Environ. Urban Syst. 2012, 36, 207–217, doi:10.1016/j.compenvurbsys.2011.11.002.
[9]
CRISIS system site. Available online: http://www.sistema-crisis.gob.ar/ (accessed on 15 August 2012).
[10]
Sanchez, E.Y.; Colman Lerner, J.E.; Porta, A.; Jacovkis, P.M. Accidental release of chlorine in Chicago: Coupling of an exposure model with a computational fluid dynamics model. Atmos. Environ. 2013, 64, 47–55, doi:10.1016/j.atmosenv.2012.09.037.
[11]
US EPA, 2012, Support Center for Regulatory Atmospheric Modeling. Available online: http://www.epa.gov/scram001/ (accessed on 02 November 2012).
[12]
Chen, C.W.; Tseng, C.P. Default risk-based probabilistic decision model for risk management and control. Nat. Hazards 2012, 63, 659–671, doi:10.1007/s11069-012-0183-8.
Calvo, B.; Savi, F. A real-world application of Monte Carlo procedure for debris flow risk assessment. Comput. Geosci. 2009, 35, 967–977, doi:10.1016/j.cageo.2008.04.002.
[15]
Chen, S.C.; Wu, C.Y.; Wu, T.Y. Resilient capacity assessment for geological failure areas: Examples from communities affected by debris flow disaster. Environ. Geol. 2009, 56, 1523–1532, doi:10.1007/s00254-008-1251-y.
[16]
Archetti, R.; Lamberti, A. Assessment of risk due to debris flow events. Nat. Hazards Rev. 2003, 4, 115–125, doi:10.1061/(ASCE)1527-6988(2003)4:3(115).
[17]
Liu, X.; Yue, Z.Q.; Tham, L.G.; Lee, C.F. Empirical assessment of debris flow risk on a regional scale in Yunnan province, Southwestern China. Environ. Manag. 2002, 30, 249–264, doi:10.1007/s00267-001-2658-3.
[18]
Acquesta, A.D.; Sanchez, E.Y.; Jacovkis, P.M. CRISIS System for Risk Management and Emergencies. In Proceedings of the Second Congress SRA-LA-Regional Society for Risk, Bogotá, Colombia, May 2012; Mu?oz, F., Ed.; Society for Risk Analysis Latin American; pp. 370–371.
[19]
Sánchez, E.Y.; Acquesta, A.D. El Sistema CRISIS para la Gestión de Riesgos. Master Thesis, Consejo Provincial de Emergencias e Instituto Provincial para la Administración Pública, PBA, La Plata, Argentina, 2011. (in Spanish).
[20]
La Crisis Bajo Control. Miradas Al Sur, Year 3, 3 April 2011. Available online: http://sur.elargentino.com/notas/la-crisis-bajo-control (accessed on 15 August 2012).
[21]
Acquesta, A.D.; Defeo, G.; Tarulla, F.; Giraldez, G.; Gonzalez, E.M.; Kuntscher, L.; Jacovkis, P.M.; Porta, A.A.; Sánchez, E.Y.; Filkensteyn, A. Computer Systems for Interagency Emergency Management. In Proceedings of the I Congreso Latinoamericano SRA-LA 2010: “El estado del análisis de riesgo en América Latina”, Santiago de Chile, Chile, August 2010.
[22]
Acquesta, A.D.; Sevilla, A.G.; Giraldez, G.; Defeo, G.; Tarulla, F.; Sánchez, E.Y.; Filkensteyn, A.; Porta, A.; Jacovkis, P. CRISIS System. In Proceedings of the XVI Congreso Argentino de Toxicologia, Puerto Madryn, Argentina, September 2009.
[23]
Acquesta, A.D.; Sevilla, A.G.; Giraldez, G.; Defeo, G.; Tarulla, F.; Sánchez, E.Y.; Filkensteyn, A.; Porta, A.; Jacovkis, P.M. CRISIS Project: Computational Models for Emergency Management in Real Time. In Proceedings of the II Congreso Argentino de la Sociedad de Toxicología y Química Ambiental (SETAC), Buenos Aires, Argentina, November 2008. Summary book.
[24]
FUNDESUMA, Manejo logístico de suministros de emergencia, Version 1.0, Curso manejo logístico de suministros de emergencia, San José, Costa Rica, 1999.
[25]
Communal Projects Association of El Salvador (PROCOMES), Manual de Conceptos básicos sobre gestión de riesgo y preparación local ante desastres, OXFAM, ECHO, 2008.
[26]
Sánchez, E.Y.; Gonzalez, E.M.; Colman, J.E.; Porta, A.A.; Jacovkis, P.M.; Acquesta, A.D. Model and Simulation of Regions Affected by a Chemical Incident, Ciencia y Tecnología Ambiental: Un Enfoque Integrador; Asociación Argentina para el Progreso de las Ciencias: Mar del Plata, Argentina, 2012; pp. 333–338. ISBN 978-987-28123-1-7 (in Spanish).
[27]
Sanchez, E.Y.; Acquesta, A.D.; Colman Lerner, J.E.; Porta, A.A.; Jacovkis, P.M. Analysis with DDC Coupled to Different Models of Dispersion in Air of Chlorine Releases. In Proceedings of the Second Congress SRA-LA-Regional Society for Risk, Bogotá, Colombia, May 2012; Mu?oz, F., Ed.; Society for Risk Analysis Latin American; pp. 119–125.
[28]
Sánchez, E.Y.; Gonzalez, E.M.; Porta, A.A.; Jacovkis, P.M.; Acquesta, A.D. Simulation of a Chemical Incident with the Tool CFD-DDC: Emergency Response Planning in Cities. In Contaminación Atmosférica e Hídrica en Argentina; Puliafito, E., Ed.; Universidad Tecnológica Nacional: Mendoza, Argentina, 2011; pp. 257–268. ISBN 978-950-42-0136-6.
[29]
Acquesta, A.D.; Sánchez, E.Y.; Porta, A.; Jacovkis, P.M. A method for computing the damage level due to the exposure to an airborne chemical with a time-varying concentration. Risk Anal. 2011, 31, 1451–1469, doi:10.1111/j.1539-6924.2011.01594.x.
[30]
Sanchez, E.Y.; Acquesta, A.D.; Porta, A.A.; Jacovkis, P.M. Simulation of Chemical Accidents: Assessment of Exposure to Non-Stationary Models. In Proceedings of the I Congreso Latinoamericano SRA-LA 2010: “El estado del análisis de riesgo en América Latina”, Santiago de Chile, Chile, August 2010. (in Spanish).
[31]
Acquesta, A.D.; Sánchez, E.Y.; Porta, A.; Jacovkis, P. Método de cálculo del da?o provocado por la exposición a un perfil variable en el tiempo, de concentración de contaminantes en el aire. In Proceedings of the II Congreso Argentino de la Sociedad de Toxicología y Química Ambiental (SETAC), Mar del Plata, Argentina, November 2008.
[32]
Crowther, K.G. Risk-informed assessment of regional preparedness: A case study of emergency potable water for hurricane response in Southeast Virginia. Int. J. Crit. Infrastructure Protection 2010, 3, 83–98, doi:10.1016/j.ijcip.2010.03.001.
[33]
Crowther, K.G.; Haimes, Y.Y. Development of the multiregional inoperability input-output model (MRIIM) for spatial explicitness in preparedness of interdependent regions. Syst. Engineering 2010, 13, 28–46.
[34]
Stephan, R. National Infrastructure Protection Plan Represents Collaboration between Government and the Private Sector; The CIP Report; Zeichner Risk Analytics: Arlington, VA, USA, 2006; pp. 2–5.