Abstract
The paper discusses the simulation model that uses system dynamics method to study the demographic changes forecasted for the population, based on the aging chain approach. The goal of the study was to elaborate the method to overcome the drainage problem that manifests itself in the smaller number of individuals belonging to the simulated cohorts, as compared to the real population data. The solution for the drainage problem is presented. We propose the original modelling methodology that assumes the coexistence of main and elementary population cohorts. The simulation model was verified based on the historical data for Wrocław Region population and the results of the experiments prove the high degree of compatibility of the simulated age and gender related characteristics with the empirical data, which entitles us to formulate the perspectives of using this approach in the next stages of our research.
Keywords
- Simulation
- System dynamics
- Ageing chain
- Population
This is a preview of subscription content, access via your institution.
Buying options
References
Ansah, J.P., Eberlein, R.L., Love, S.R., Bautista, M.A., Thompson, J.P., Malhotra, R., Matchar, D.B.: Implications of long-term care capacity response policies for an aging population: a simulation analysis. Health Policy 116(1), 105–113 (2014)
Diamond, B., Krahl, D., Nastasi, A., Tag, P.: Extendsim advanced techology: integrated simulation database. In: Johansson, B., Jain, S., Montoya-Torres, J., Hugan, J., Yücesan, E. (eds.) Proceedings of the Winter Simulation Conference (WSC), pp. 32–39. IEEE (2010)
Eberlein, R.L., Thompson, J.P., Matchar, D.B.: Chronological aging in continuous time. In: Husemann, E., Lane, D. (eds.) Proceedings of the 30th International Conference of the System Dynamics Society, St. Gallen, Switzerland (2012)
Eberlein, R.L., Thompson, J.P.: Precise modeling of aging populations. Syst. Dyn. Rev. 29(2), 87–101 (2013)
Forrester, J.W.: Industrial dynamics-after the first decade. Manag. Sci. 14(7), 398–415 (1968)
GUS Główny Urząd Statystyczny. http://www.stat.gov.pl. Accessed Jan 2017
Jagger, C., Matthews, R., Lindesay, J., Robinson, T., Croft, P., Brayne, C.: The effect of dementia trends and treatments on longevity and disability: a simulation model based on the MRC cognitive function and ageing study (MRC CFAS). Age Ageing 38(3), 319–325 (2009)
Krahl, D.: Extend: the extend simulation environment. In: Yücesan, E., Chen, C.-H., Snowdom, J., Charnes, J. (eds.) Proceedings of the 2002 Winter Simulation Conference: Exploring New Frontiers, pp. 205–213 (2002)
Krahl, D.: Extendsim 7. In: Mason, S., Hill, R., Mönch, L., Rose, O., Jefferson, T., Fowler, J. (eds.) Proceedings of the 2008 Winter Simulation Conference, pp. 215–221 (2008)
Krahl, D.: Extendsim 9. In: Pasupathy, R., Kim, S.-H., Tolk, A., Hill, R., Kuhl, M. (eds.) Proceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World, pp. 4065–4072. IEEE Press, Piscataway (2013)
Lagergren, M.: What happened to the care of older persons in Sweden? A retrospective analysis based upon simulation model calculations, 1985–2000. Health Policy 74(3), 314–324 (2005)
Loumrhari, G.: Ageing, longevity and savings: the case of Morocco. Int. J. Econ. Finan. Issues 4(2), 344–352 (2014)
Mielczarek, B., Zabawa, J.: Modeling healthcare demand using a hybrid simulation approach. In: Roeder, T., Frazier, P., Szechtman, R., Zhou, E., Huschka, T., Chick, S. (eds.) Proceedings of the 2016 Winter Simulation Conference, pp. 1535–1546. IEEE Press, Piscataway (2016)
Mielczarek, B., Zabawa, J.: Modelling population growth, shrinkage and aging using a hybrid simulation approach: application to healthcare. In: Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH, vol. 1, pp. 75–83. Scitepress (2016)
Population Modeling Working Group: Population modeling by examples (WIP). In: Proceedings of the Symposium on Modeling and Simulation in Medicine (MSM 2015), pp. 61–66. Society for Computer Simulation International, San Diego, CA, USA (2015). http://dl.acm.org/citation.cfm?id=2887741#authors
Sato, J., Chalise, N., Hovmand, P., Zoellner, N., Carson, K., Brown, A.: Birth cohorts approach to modeling aging populations. In: 33rd International Conference of the System Dynamics Society 2015, Cambridge, Massachusetts, pp. 2882–2889 (2015)
Senese, F., Tubertini, P., Mazzocchetti, A., Lodi, A., Ruozi, C., Grilli, R.: Forecasting future needs and optimal allocation of medical residency positions: the Emilia-Romagna region case study. Hum. Resour. Health 13(7) (2015). doi:10.1186/1478-4491-13-7
Tian, Y., Zhao, X.: Stochastic forecast of the financial sustainability of basic pension in China. Sustainability 8(46) (2016). doi:10.3390/su8010046
Acknowledgements
This project was financed by the grant Simulation modeling of the demand for healthcare services from the National Science Centre, Poland, and was awarded based on the decision 2015/17/B/HS4/00306.
ExtendSim blocks copyright © 1987–2016 Imagine That Inc. All rights reserved.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Zabawa, J., Mielczarek, B., Hajłasz, M. (2018). Simulation Approach to Forecasting Population Ageing on Regional Level. In: Wilimowska, Z., Borzemski, L., Świątek, J. (eds) Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017. ISAT 2017. Advances in Intelligent Systems and Computing, vol 657. Springer, Cham. https://doi.org/10.1007/978-3-319-67223-6_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-67223-6_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67222-9
Online ISBN: 978-3-319-67223-6
eBook Packages: EngineeringEngineering (R0)