Networks and Spatial Economics

, Volume 15, Issue 2, pp 253–270 | Cite as

Analysis of Critical Infrastructure Network Failure in the European Union: A Combined Systems Engineering and Economic Model

  • Olaf Jonkeren
  • Ivano Azzini
  • Luca Galbusera
  • Stavros Ntalampiras
  • Georgios Giannopoulos


Over the past few years, the European Commission has placed Critical Infrastructure Protection under the spotlight. Therefore, the Joint Research Centre is developing a tool to estimate the economic impact of Critical Infrastructure (CI) network failure, resulting from a hazard, on the regional or national level. This tool, which is presented in this study, is a combined Systems Engineering and Dynamic Inoperability Input–output model (SE-DIIM). The resilience of infrastructures and economic sectors, in terms of their ability to withstand and recover from disruptions, is included in the model. We discuss the model by analyzing the economic losses incurred in the 2003 Italian electricity network outage. The losses are estimated at both national and regional levels i.e. northern, central and southern parts of Italy and Sicily with a focus on 9 CI’s. We estimate that the economic loss for the case study under consideration is between €46 million and €173 million. We conclude that the combination of the SE and the DIIM components provides a complete framework for assessing the economic impact of critical infrastructure network failure on the national or regional level taking account of resilience.


Critical infrastructure network failure Systems engineering model Dynamic inoperability input–output model Static resilience Dynamic resilience 



We would like to thank two anonymous referees for their valuable comments. This work is supported by the Annual Work Programme 2010 and Annual Work Programme 2011 for the specific programme on the “Prevention and fight against crime” which is financed by Directorate General Home Affairs of the European Commission. The authors would like to express their gratitude for this support.


  1. Abrell J, Weigt H (2012) Combining energy networks. Netw and Spat Econ 12:377–401CrossRefGoogle Scholar
  2. Ali J, Santos JR (2012) Framework for Evaluating Economic Impact of IT based Disasters on the Interdependent Sectors of the US Economy. Proceedings of the 2012 I.E. Systems and Information Engineering Design Symposium, University of Virginia, Charlottesville, USA, April 27, 2012Google Scholar
  3. Anderson CW, Santos JR, Haimes YY (2007) A risk-based input–output methodology for measuring the effects of the August 2003 northeast blackout. Econ Syst Res 19(2):183–204CrossRefGoogle Scholar
  4. Barker K, Santos JR (2010) Measuring the efficacy of inventory with a dynamic input–output model. Int J Prod Econ 126:130–143CrossRefGoogle Scholar
  5. Berizzi A (2004) The Italian 2003 blackout. Power Engineering Society General Meeting 1673–1679Google Scholar
  6. Bird BR, Stewart WE, Lightfoot EN (2002) Transport Phenomena. John Wiley & SonsGoogle Scholar
  7. Buldyrev SV, Parshani R, Paul P, Stanley HE, Havlin S (2010) Catastrophic cascade of failures in interdependent networks. Nature 464:1025–1028CrossRefGoogle Scholar
  8. Crowther KG, Haimes YY (2005) Application of the inoperability input–output model (IIM) for systemic risk assessment and management of interdependent infrastructures. Syst Eng 8(4):323–341CrossRefGoogle Scholar
  9. Crowther KG, Haimes YY (2010) Development of the multiregional inoperability input–output model (MRIIM) for spatial explicitness in preparedness of interdependent regions. Syst Eng 13(1):28–46Google Scholar
  10. De Nooij M, Koopmans C, Bijvoet C (2007) The value of supply security: the cost of power interruptions: economic input for damage reduction and investment in networks. Energy Econ 29:277–295CrossRefGoogle Scholar
  11. Deckers SLJ, Jepsen ON (2003) Conditions monitoring and failure diagnosis in plants of the metals industry. In: Fault Detection, Supervision and Safety of Technical Processes 2003. A Proceedings Volume from the 5th IFAC Symposium, Washington D.C., USA 9–11 June 2003Google Scholar
  12. Devogelaer D, Gusbin D (2004) Een kink in de kabel: de kosten van een storing in de stroomvoorziening. Federaal Planbureau, BrusselGoogle Scholar
  13. Di Mauro C, Bouchon S, Logtmeijer C, Pride RD, Hartung T, Nordvik JP (2010) A structured approach to identifying European critical infrastructures. Int J of Crit Infrastruct 6(3):277–292CrossRefGoogle Scholar
  14. Dietzenbacher E, Los B, Stehrer R, Timmer MP, de Vries GJ (2013) The construction of world input–output tables in the WIOD project. Econ Syst Res 25:71–98CrossRefGoogle Scholar
  15. Du L, Peeta S (2014) A stochastic optimization model to reduce expected post-disaster response time through Pre-disaster investment decisions. Netw and Spatial Econ. doi: 10.1007/s11067-013-9219-1 Google Scholar
  16. Ferrari M, Schupp B, Trucco P, Ward D, Nordvik J (2011) Assessing supply chain dependency on critical infrastructures using fuzzy cognitive maps. Int J of Risk Assess and Manag 15(2–3):149–170CrossRefGoogle Scholar
  17. Filippini R, Silva A (2014) A modeling framework for the resilience analysis of networked systems-of-systems based on functional dependencies. Reliab Eng Syst Saf 125:82–91CrossRefGoogle Scholar
  18. Gao J, Buldyrev SV, Stanley HE, Havlin S (2012) Networks formed from interdependent networks. Nat Phys 8:40–48CrossRefGoogle Scholar
  19. Greenberg M, Haas C, Cox A Jr, Lowrie K, McComas K, North W (2012) Ten most important accomplishments in risk analysis, 1980–2010. Risk Anal 32(5):771–781CrossRefGoogle Scholar
  20. GRTN (2004) Rapporto sulle activita’ del gestore della rete di trasmissione nazionale Aprile 2003 – Marzo 2004Google Scholar
  21. Haimes YY, Horowitz BM, Lambert JH, Santos JR, Lian C, Crowther KG (2005a) Inoperability input–output model for interdependent infrastructure sectors. I: theory and methodology. J Infrastruct Syst 11(2):67–79CrossRefGoogle Scholar
  22. Haimes YY, Horowitz BM, Lambert JH, Santos JR, Crowther KG, Lian C (2005b) Inoperability input–output model for interdependent infrastructure sectors, II: case studies. J Infrastruct Syst 11(2):80–92CrossRefGoogle Scholar
  23. Leontief WW (1951a) Input–output economics. Sci Am 185:15–21CrossRefGoogle Scholar
  24. Leontief WW (1951b) The structure of the american economy, 1919–1939, 2nd edn. Oxford University Press, New YorkGoogle Scholar
  25. Lian C, Haimes YY (2006) Managing the risk of terrorism to interdependent infrastructure systems through the dynamic inoperability input–output model. Syst Eng 9(3):241–258Google Scholar
  26. Matisziw TC, Murray AT, Grubesic TH (2010) Strategic network restoration. Netw and Spatial Econ 10(3):345–361CrossRefGoogle Scholar
  27. Miller RE, Blair PD (2009) Input–output analysis: foundations and extensions, 2nd edn. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  28. Oliva G, Panzieri S, Setola R (2011) Fuzzy dynamic input–output inoperability model. Int J Crit Infrastruct Prot 4:165–175CrossRefGoogle Scholar
  29. Reggiani A, De Graaff T, Nijkamp P (2002) Resilience: an evolutionary approach to spatial economic systems. Netw and Spatial Econ 2(2):211–229CrossRefGoogle Scholar
  30. Rigole T, Deconinck G (2006) A survey on modeling and simulation of interdependent critical infrastructures. 3rd IEEE Benelux Young Researchers Symposium in Electrical Power Engineering, Paper 44Google Scholar
  31. Rocco CM, Ramirez-Marquez JE, Salazar DE (2012) Some metrics for assessing the vulnerability of complex networks: An application to an electric power system. Advances in Safety, Reliability and Risk Management 2556–2561Google Scholar
  32. Rosato V, Bologna S, Tiriticco F (2007) Topological properties of high-voltage electrical transmission networks. Electr Power Syst Res 77:99–105CrossRefGoogle Scholar
  33. Rosato V, Issacharoff L, Gianese G, Bologna S (2011) Influence of the topology on the power flux of the Italian high-voltage electrical network. Available at (accessed on December 2011)
  34. Rose AZ (2007) Economic resilience to natural and man-made disasters: multidisciplinary origins and contextual dimensions. Environ Hazards 7:383–398CrossRefGoogle Scholar
  35. Rose AZ (2009) A Framework for Analyzing the Total Economic Impacts of Terrorist Attacks and Natural Disasters. Journal of Homeland Security and Emergency Management 6, 1, art.9Google Scholar
  36. Rose AZ, Lim D (2002) Business interruption losses from natural hazards: conceptual and methodological issues in the case of the Northridge earthquake. Environ Hazards 4:1–14Google Scholar
  37. Santos JR, Haimes YY (2004) Modeling the demand reduction input–output (I-O) inoperability Due to terrorism of interconnected infrastructures. Risk Anal 24(6):1437–1451CrossRefGoogle Scholar
  38. Sforna M, Delfanti M (2006) Overview of the events and causes of the 2003 Italian blackout. In Proc. IEEE PSCE’06, Atlanta, Nov. 2006: 301–308Google Scholar
  39. Simonsen I (2005) Diffusion and Networks: from simple models to applications. Presentation at 41th Winter School in Theoretical Physics, LadekGoogle Scholar
  40. UCTE (2004) Final report of the Investigation Committee on the 28 September 2003 Blackout in ItalyGoogle Scholar
  41. Wilde WD, Warren MJ (2008) Visualisation of critical infrastructure failure. Proceedings of the 9th Australian Information Warfare and Security Conference, 48–96Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Olaf Jonkeren
    • 1
    • 2
  • Ivano Azzini
    • 1
  • Luca Galbusera
    • 1
  • Stavros Ntalampiras
    • 1
  • Georgios Giannopoulos
    • 1
  1. 1.European Commission, Joint Research Centre (JRC)Institute for the Protection and Security of the Citizen (IPSC), Security Technology Assessment UnitIspra VAItaly
  2. 2.PBL Netherlands Environmental Assessment AgencyThe HagueNetherlands

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