DOI QR코드

DOI QR Code

System Dynamics Approach to Epidemic Compartment Model: Translating SEIR Model for MERS Transmission in South Korea

전염병 구획 모형에 대한 시스템다이내믹스 접근법: 국내 MERS 전염 SEIR 모형의 해석 및 변환

  • Jung, Jae Un (Department of Management Information Systems, Dong-A University)
  • Received : 2018.05.28
  • Accepted : 2018.07.20
  • Published : 2018.07.28

Abstract

Compartment models, a type of mathematical model, have been widely applied to characterize the changes in a dynamic system with sequential events or processes, such as the spread of an epidemic disease. A compartment model comprises compartments, and the relations between compartments are depicted as boxes and arrows. This principle is similar to that of the system dynamics (SD) approach to constructing a simulation model with stocks and flows. In addition, both models are structured using differential equations. With this mutual and translatable principle, this study, in terms of SD, translates a reference SEIR model, which was developed in a recent study to characterize the transmission of the Middle East respiratory syndrome (MERS) in South Korea. Compared to the replicated result of the reference SEIR model (Model 1), the translated SEIR model (Model 2) demonstrates the same simulation result (error=0). The results of this study provide insight into the application of SD relative to constructing an epidemic compartment model using schematization and differential equations. The translated SD artifact can be used as a reference model for other epidemic diseases.

수학모형의 한 유형인 구획모형은 전염병의 확산처럼 순차적인 이벤트나 프로세스로 구성된 동적 시스템의 변화를 분석하는 데 폭넓게 활용되어 왔다. 구획모형은 상자와 화살표로 표현되는 구획과 구획 간 관계로 구성된다. 이러한 원리는 stock과 flow로 구성되는 시스템다이내믹스(SD)의 모델링 원리와 비슷하다. 두 모형 모두 미분방정식을 이용하여 구조화된다. 이와 같은 두 모형 간 변환 가능성을 이용하여 국내 MERS 전염의 특징을 분석한 최근 연구의 SEIR 참조모형을 SD 관점에서 해석 변환한다. 변환된 SEIR 모형(Model 2)은 참조모형(Model 1)의 재현 결과와 비교하여 동일한 시뮬레이션 결과를 나타내었다. 본 연구는 전염병 구획모형의 구축에 도식과 미분방정식을 이용한 SD 방법론의 활용에 대한 인사이트를 제공하며, 변환된 SD 모형은 다른 전염병을 위한 참조모형으로 활용 가능하다.

Keywords

References

  1. C. Cobelli, A. Lepschy, G. Romanin Jacur & U. Viaro. (1986). On the Relationship Between Forrester's Schematics and Compartmnental Graphs, IEEE Transactions on Systems, Man, and Cybernetics, 16(5), 723-726. DOI: 10.1109/TSMC.1986.289316
  2. M. M. Blomhoj, T. H. Kjeldsen & J. Ottesen. (2018). Compartment Models. NCSU(Online). http://www4.ncsu.edu/-msolufse/Compartmentmodels.pdf
  3. E. Eriksson. (1971). Compartment Models and Reservoir Theory, Annual Review of Ecology and Systematics, 2(1), 67-84. DOI: 10.1146/annurev.es.02.110171.000435
  4. J. D. Sterman. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: McGraw-Hill.
  5. M. Kljajiae, A. Skraba & I. Bernik. (1999, July). System Dynamics and Decision Support in Complex Systems, The 17th International Conference of the System Dynamics Society and the 5th Australian and New Zealand Systems Conference. (paper ID 183). Wellington: System Dynamics Society.
  6. W. O. Kermack & A. G. McKendrick. (1927, August). A Contribution to the Mathematical Theory of Epidemics, Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 115(772), (pp. 700-721). London: Royal Society. https://doi.org/10.1098/rspa.1927.0118
  7. W. O. Kermack & A. G. McKendrick. (1932, October). Contributions to the Mathematical Theory of Epidemics II. The Problem of Endemicity, Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 138(834), (pp.55-83). London: Royal Society. https://doi.org/10.1098/rspa.1932.0171
  8. W. O. Kermack & A. G. McKendrick. (1933). Contributions to the Mathematical Theory of Epidemics. III. Further Studies of the Problem of Endemicity. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 141(843), (pp.94-112). London: Royal Society. https://doi.org/10.1098/rspa.1933.0106
  9. F. Brauer. (2005). The Kermack-McKendrick epidemic model revisited, Mathematical Biosciences, 198, 119-131. DOI : 10.1016/j.mbs.2005.07.006
  10. F. Brauer, P. V. D. Driessche & J. Wu(Eds). (2008). Mathematical Epidemiology. Berlin: Springer.
  11. P. Yan & S. Liu. (2006). SEIR Epidemic Model with Delay, The ANZIAM Journal, 48(1), 119-134. DOI : 10.1017/S144618110000345X
  12. J. B. Homer & G. B. Hirsch. (2006). System Dynamics Modeling for Public Health: Background and Opportunities, American Journal of Public Health, 96(3), 452-458. DOI : 10.2105/AJPH.2005.062059
  13. T. Habtemariam, B. Tameru, D. Nganwa, G. Beyene, L. Ayanwale & V. Robnett. (2008). Epidemiologic Modeling of HIV/AIDS: Use of Computational Models to Study the Population Dynamics of the Disease to Assess Effective Intervention Strategies for Decision-making, Advances in Systems Science and Applications, 8(1), 35-39.
  14. J. W. Forrester. (1969). Urban Dynamics, MA : Pegasus Communications.
  15. A. Ahmed, J. Greensmith & U. Aickelin. (2012, May). Variance in System Dynamics and Agent Based Modelling Using the SIR Model of Infectious Disease, The 26th European Conference on Modelling and Simulation. (pp 9-15). Koblenz : ECMS.
  16. R. Bagni, R. Berchi & P. Cariello. (2002). A Comparison of Simulation Models Applied to Epidemics, Journal of Artificial Societies and Social Simulation, 5(3).
  17. N. Schiertz. (2002). Integrating System Dynamics and Agent-Based Modeling, The XX International Conference of the System Dynamics Society, Palermo : System Dynamics Society.
  18. H. V. D. Parunak, R. Savit & R. L. Riolo. (1998). Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users' Guide, Lecture Notes in Computer Science, 1534, 10-25. DOI : https://doi.org/10.1007/10692956_2
  19. C. M. Kwon & J. U. Jung. (2016). Applying discrete SEIR model to characterizing MERS spread in Korea, International Journal of Modeling, Simulation, and Scientific Computing, 7(4), Article ID 1643003. DOI : https://doi.org/10.1142/S1793962316430030
  20. Centers for Disease Control and Prevention (Online) https://www.cdc.gov/coronavirus/mers/about/index.html
  21. MERS (Middle East Respiratory Syndrome). (2015). Danish Health and Medicines Authority.
  22. K. Kupferschmidt. (2015). 'Superspreading event' triggers MERS explosion in South Korea, Science(Online). http://www.sciencemag.org/news/2015/06/superspreading-event-triggers-mers-explosion-south-korea
  23. S. H. Park, W. J. Kim, J. H. Yoo & J. H. Choi. (2016). Epidemiologic Parameters of the Middle East Respiratory Syndrome Outbreak in Korea, 2015, Infection & Chemotherapy, 48(2), 108-117. DOI : http://dx.doi.org/10.3947/ic.2016.48.2.108
  24. H. S. Nama, J. W. Park, M. Ki, M. Y. Yeon, J. Kim & S. W. Kim. (2017). High Fatality Rates and Associated Factors in Two Hospital Outbreaks of MERS in Daejeon, the Republic of Korea, International Journal of Infectious Diseases, 58, 37-42. DOI : https://doi.org/10.1016/j.ijid.2017.02.008
  25. The 2015 MERS Outbreak in the Republic of Korea: Learning from MERS. (2016). Korean Ministry of Health and Welfare.
  26. M. Ki. (2015). 2015 MERS Outbreak in Korea: Hospital-to-Hospital Transmission, Epidemiology and Health, 37, ID 2015033. DOI : 10.4178/epih/e2015033