Numeric, Agent-based or System Dynamics Model? Which Modeling Approach is the Best for Vast Population Simulation?

被引:12
作者
Cimler, Richard [1 ]
Tomaskova, Hana [2 ]
Kuhnova, Jitka [1 ]
Dolezal, Ondrej [2 ]
Pscheidl, Pavel [2 ]
Kuca, Kamil [2 ]
机构
[1] Univ Hradec Kralove, Fac Sci, Rokitanskeho 62, Hradec Kralove, Czech Republic
[2] Univ Hradec Kralove, Fac Informat & Management, Rokitanskeho 62, Hradec Kralove, Czech Republic
关键词
Alzheimer's disease; population modeling; system dynamics; agent-based model; numerical model; population prediction; ALZHEIMERS-DISEASE; BALANCE MODEL; GLOBAL PREVALENCE; DEMENTIA; SURVIVAL; GRANULATION; MORTALITY; HEALTH;
D O I
10.2174/1567205015666180202094551
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background: Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Methods: Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. Results: The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. Conclusion: In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population.
引用
收藏
页码:789 / 797
页数:9
相关论文
共 49 条
  • [1] [Anonymous], 2015, SYST THINK
  • [2] [Anonymous], 2001, An Introduction to Genetic Algorithms. Complex Adaptive Systems
  • [3] [Anonymous], 2003, Genetic programming IV: routine human-competitive machine intelligence
  • [4] [Anonymous], 2000, BUSINESS DYNAMICS SY
  • [5] Arizaga RL, 2005, DEMENTIA MULTIDISCIP, P7
  • [6] Back T., 1996, EVOLUTIONARY ALGORIT, DOI DOI 10.1093/OSO/9780195099713.001.0001
  • [7] POPULATION PREVALENCE ESTIMATES FROM COMPLEX SAMPLES
    BECKETT, LA
    SCHERR, PA
    EVANS, DA
    [J]. JOURNAL OF CLINICAL EPIDEMIOLOGY, 1992, 45 (04) : 393 - 402
  • [8] Agent-based modeling: Methods and techniques for simulating human systems
    Bonabeau, E
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2002, 99 : 7280 - 7287
  • [9] Survival following a diagnosis of Alzheimer disease
    Brookmeyer, R
    Corrada, MM
    Curriero, FC
    Kawas, C
    [J]. ARCHIVES OF NEUROLOGY, 2002, 59 (11) : 1764 - 1767
  • [10] Projections of Alzheimer's disease in the United States and the public health impact of delaying disease onset
    Brookmeyer, R
    Gray, S
    Kawas, C
    [J]. AMERICAN JOURNAL OF PUBLIC HEALTH, 1998, 88 (09) : 1337 - 1342