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A Comparison of Simulation Models Applied to Epidemics

Author

Listed:
  • Raul Bagni
  • Roberto Berchi
  • Pasquale Cariello

Abstract

This paper presents a new approach to infectious disease analysis through computer simulation. The case study concerns the spread of Bovine Leukemia, a viral pathology sustained by a retrovirus from the same family as HIV that exclusively strikes cattle within dairy farms. Although analytical models of epidemic spread have been implemented, their practical use is often difficult, above all for predictive and quantitative analysis. Computer simulation provides a new possible approach, and here we apply two methodologies: "System Dynamics" and "Agent Based". Furthermore the case study is used like a workbench to illustrate the differences between the two approaches and to explain how these techniques can help with the understanding of the problem. At the same time epidemiological researchers are able to do a preliminary "what-if" analysis with the purpose of assessing the system's behaviour under various conditions and evaluating which alternative sanitary policies to adopt. Thanks to model results, experts have reached their first suppositions in order to fight the endemic behaviour of Bovine Leukemia. The models implemented can easily be extended to collect the details of the system to be investigated more efficiently and to allow more refined analyses to be made.

Suggested Citation

  • Raul Bagni & Roberto Berchi & Pasquale Cariello, 2002. "A Comparison of Simulation Models Applied to Epidemics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-5.
  • Handle: RePEc:jas:jasssj:2001-18-2
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    Citations

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    Cited by:

    1. Jozwiak, Akos & Milkovics, Matyas & Lakner, Zoltan, 2016. "A Network-Science Support System for Food Chain Safety: A Case from Hungarian Cattle Production," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-26, June.
    2. François Rebaudo & Verónica Crespo-Pérez & Jean-François Silvain & Olivier Dangles, 2011. "Agent-Based Modeling of Human-Induced Spread of Invasive Species in Agricultural Landscapes: Insights from the Potato Moth in Ecuador," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(3), pages 1-7.
    3. Heinrich, Torsten, 2021. "Epidemics in modern economies," MPRA Paper 107578, University Library of Munich, Germany.
    4. François Rebaudo & Olivier Dangles, 2011. "Coupled Information Diffusion–Pest Dynamics Models Predict Delayed Benefits of Farmer Cooperation in Pest Management Programs," PLOS Computational Biology, Public Library of Science, vol. 7(10), pages 1-10, October.
    5. Weiwei Zhang & Shiyong Liu & Nathaniel Osgood & Hongli Zhu & Ying Qian & Peng Jia, 2023. "Using simulation modelling and systems science to help contain COVID‐19: A systematic review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(1), pages 207-234, January.
    6. Huiyu Xuan & Lida Xu & Lu Li, 2009. "A CA-based epidemic model for HIV/AIDS transmission with heterogeneity," Annals of Operations Research, Springer, vol. 168(1), pages 81-99, April.
    7. Torsten Heinrich, 2021. "Epidemics in modern economies," Papers 2105.02387, arXiv.org, revised May 2021.
    8. K Katsaliaki & N Mustafee, 2011. "Applications of simulation within the healthcare context," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1431-1451, August.
    9. Torsten Heinrich, 2021. "Epidemics in modern economies," Chemnitz Economic Papers 045, Department of Economics, Chemnitz University of Technology, revised May 2021.
    10. Tobias Buchmann & Patrick Wolf & Stefan Fidaschek, 2021. "Stimulating E-Mobility Diffusion in Germany (EMOSIM): An Agent-Based Simulation Approach," Energies, MDPI, vol. 14(3), pages 1-25, January.

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