Suggestions for Developing Tools to Improve the Effectiveness of Management in the Context of Epidemics
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Abstract
The article is devoted to the consideration of methods for modeling epidemics in relation to COVID-19 and substantiation of ways to improve the efficiency of management decisions, taking into account the predicted consequences. The paper provides an overview of modeling methods for predicting and assessing the consequences of the epidemiological situation. The scientific novelty of the work lies in the use of decision support tools for the operational assessment of the situation and forecast of its development. For the task at hand, it is proposed to use a multi-agent approach to simulation.
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References
2. Балута В.И., Осипов В.П., Яковенко О.Ю. Среда моделирования, прогнозирования и экспертиз как интеллектуальное ядро поддержки управления сложными системами // М.: Препринты ИПМ им. М.В. Келдыша. 2015. №82. 16 с. URL: https://keldysh.ru/papers/2015/prep2015_82.pdf
3. Зацаринный А.А., Ильин Н.И., Колин К.К., Лепский В.Е., Малинецкий Г.Г., Новиков Д.А., Райков А.Н., Сильвестров С.Н., Славин Б.Б. Ситуационные центры развития в полисубъектной среде // Проблемы управления. 2017. №5. С. 31–42.
4. Ильин Н.И. Интервью Национальному центру цифровой экономики МГУ им. М.В. Ломоносова, 10.12.2018 г. URL: https://digital.msu.ru
5. Макаров В.Л., Бахтизин А.Р. Современные методы прогнозирования последствий управленческих решений // Управленческое консультирование. 2015. №7. С. 12–24.
6. Hunter E., Mac Namee B., Kelleher D. A taxonomy for agent-based models in human infectious disease epidemiology // Journal of Artificial Societies and Social Simulation. 2017. V. 20, No. 3. P. 2. URL: http://jasss.soc.surrey.ac.uk/20/3/2.html
7. Dunham J.B. An agent-based spatially explicit epidemiological model in MASON // Journal of Artificial Societies and Social Simulation. 2005. V. 9, No. 1. P. 3.
8. Perez L., Dragicevic S. An agent-based approach for modeling dynamics of contagious disease spread // International Journal of Health Geographics. 2009. V. 8. No. 50. P. 1–17. URL: https://doi.org/10.1186/1476-072X-8-50
9. Skvortsov A.T., Connell R.B., Dawson P.D. and Gailis R.M. Epidemic modelling: Validation of agentbased simulation by using simplemathematical models // MODSIM 2007 International Congress Modelling on and Simulation. Modelling and Simulation Society of Australia and New Zealand. 2007. P. 657–662.
URL: https://www.mssanz.org.au/MODSIM07/papers/13_s20/EpidemicModeling_s20_Skvortsov_.pdf
10. Crooks A.T., Hailegiorgis A.B. An agent-based modeling approach applied to the spread of cholera // Environmental Modelling&Soware. 2014. V. 62. P. 164– 77. URL: https://doi.org/10.1016/j.envsoft.2014.08.027
11. Rakowski F., Gruziel M., Bieniasz-Krzywiec L., Radomski J.P. Influenza epidemic spread simulation for Poland – a large scale, individual based model study // Physica A: Statistical Mechanics and its Applications. 2010. V. 389 (16). P. 3149–3165. URL: https://doi.org/10.1016/j.physa.2010.04.029
12. Armstrong J.S., Green K.C. Demand Forecasting: Evidence-based Methods // Strategic Marketing Management: A Business Process Approach. 2005. V. 24. URL: https://www.researchgate.net/publication/5179920_Demand_Forecasting_Evidence-Based_Methods
13. McFadden D.L.; Train K. Mixed MNL Models for Discrete Response // Journal of Applied Econometrics. 2000. V. 15. No. 5. P. 447–470.
URL: https://doi.org/10.1002/1099-1255(200009/10)15:5<447::AID-JAE570>3.0.CO;2-1
14. Duan W., Qiu X., Cao Z., Zheng X., Cui K. Heterogeneous and stochastic agent-based models for analyzing infectious diseases’ super spreaders // IEEE Intelligent Systems. 2013. V. 13. P. 1541–1672.
15. Mao L. Modeling triple-diusions of infectious diseases, information, and preventive behaviors through a metropolitan social network – an agent-based simulation // Applied Geography. 2014. V. 50. P. 31–39.
URL: https://doi.org/10.1016/j.apgeog.2014.02.005
16. Lee B.Y., Brown S.T., Cooley P., Potter M.A., Wheaton W.D., Voorhees R.E. Stebbins S., Grefenstette J.J., Zimmer S.M., Zimmerman R.K., Assi T.-M., Bailey R.R., Wagener D.K., Burke D.S. Simulating school closure strategies to mitigate an influenza epidemic // Journal of Public Health Managmentand Practice. 2008. V. 16. No. 3. P. 252–261. URL: https://doi.org/10.1097/PHH.0b013e3181ce594e
17. Crooks A.T., Hailegiorgis A.B. An agent-based modeling approach applied to the spread of cholera // Environmental Modelling&Sofware. 2014. V. 62. P. 164–177. URL: https://doi.org/10.1016/j.envsoft.2014.08.027
18. Merler S., Ajelli M., Fumanelli L., Gomes M.F.C., Y Piontti A.P., Rossi L., Chao D.L., Jr I. M.L., Halloran M.E., Vespignani A. Spatiotemporal spread of the 2014 outbreak of ebola virus disease in Liberia and the effectiveness of non-pharmaceutical interventions: A computational modelling analysis. The Lancet Infectious Diseases. 2015. V. 15. No. 2. P. 204–211. URL: https://doi.org/10.1016/S1473-3099(14)71074-6
19. Wolfram C. An Agent-Based Model of COVID-19 // Complex Systems. 2020. V. 29. No. 1. P. 87–105.
URL: https://doi.org/10.25088/ComplexSystems.29.1.87
20. Адарченко В.А. и др. Моделирование развития эпидемии коронавируса по дифференциальной и статистической моделям // Снежинск. Изд-во РФЯЦ-ВНИИТФ. 2020. Препринт №264. 29 с.
URL: http://vniitf.ru/data/files/pdf/corona.pdf
21. Silva P.C.L., Batista P.V.C., Lima H.S., Alves M.A., Guimarães F.G., Silva R.C.P. COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions // Chaos, Solitons & Fractals. 2020. P. 37. E-print: arXiv:2006.10532 [cs.AI]
URL: https://doi.org/10.1016/j.chaos.2020.110088
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