The Pandemics in Artificial Society: Agent-Based Model to Reflect Strategies on COVID-19

Situngkir, Hokky and Lumbantobing, Andika Bernad (2020): The Pandemics in Artificial Society: Agent-Based Model to Reflect Strategies on COVID-19. Published in: BFI Working Paper Series No. WP-2020-02 (27 July 2020)

Abstract

Various social policies and strategies have been deliberated and used within many countries to handle the COVID-19 pandemic. Some of those basic ideas are strongly related to the understanding of human social interactions and the nature of disease transmission and spread. In this paper, we present an agent-based approach to model epidemiological phenomena as well as the interventions upon it. We elaborate on micro-social structures such as social-psychological factors and distributed ruling behaviors to grow an artificial society where the interactions among agents may exhibit the spreading of the virus. Capturing policies and strategies during the pandemic, four types of intervention are also applied in society. Emerged macro-properties of epidemics are delivered from sets of simulations, lead to comparisons between each policy/strategy’s effectivity.

• Item Type: MPRA Paper
• Language: English
• Keywords: COVID-19, coronavirus disease, policy, pandemic, social simulations, artificial society, agent-based modeling.
• Subjects: C - Mathematical and Quantitative Methods > C9 - Design of Experiments; C - Mathematical and Quantitative Methods > C9 - Design of Experiments > C99 - Other; H - Public Economics > H8 - Miscellaneous Issues > H89 - Other; I - Health, Education, and Welfare > I1 - Health; I - Health, Education, and Welfare > I1 - Health > I18 - Government Policy ; Regulation ; Public Health; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R0 - General; Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology > Z18 - Public Policy

References

Angulo, J. (1987). “Interdisciplinary Approaches in Epidemic Studies – II: Four Geographic Models of the Flow of Contagious Disease”. Social Science Methodology 24(1):57-69. Pergamon.

Clemente-Suárez, V. J., Hormeño-Holgado, A., Jiménez, M., Benitez-Agudelo, J. C., Navarro-Jiménez, E., Perez-Palencia, N., Maestre-Serrano, R., Laborde-Cárdenas, C. C., Tornero-Aguilera, J. F. (2020). “Dynamics of Population Immunity Due to the Herd Effect in the COVID-19 Pandemic:. Vaccines 8 (2).

Dahlberg, M., Edin, P-A., Grönqvist, E., Lyhagen, J., Östh, J., Siretskiy, A., Toger, M. (2020). Effects of the COVID-19 Pandemic on Population Mobility under Mild Policies: Causal Evidence from Sweden. arXiv:2004.09087 (econ).

Epstein, J. M., & Axtell, R. L. (1996). Growing Artificial Societies: Social Sciences from the Bottom Up”. Brookings Institution Press.

Gilbert, N. & Terna, P. (2000). “How to build and use agent-based models in social science”. Mind & Society 1 (1): 57-72. Springer.

Lau, H., Khosrawipour, V., Kocbach, P., Mikolajczyk, A., Schubert, J., Bania, J., Khosrawipour, T. (2020). “The positive impact of lockdown in Wuhan on containing the COVID-19 outbreak in China”. Journal of Travel Medicine 27(3)

Lee, M., You, M. (2020). “Psychological and Behavioral Responses in South Korea During the Early Stages of Coronavirus Disease 2019 (COVID-19)”. International Journal of Environmental Research and Public Health 17 (9). MDPI.

Lewnard, J. A., & Lo, N. C. (2020). Scientific and ethical basis for social-distancing interventions against COVID-19. The Lancet. Infectious diseases, 20(6). Elsevier.

Macy, M.W., & Willer, R. (2002). “From Factors to Actors: Computational Sociology and Agent Based Modeling. Annual Reviews Sociology 28: 143-66. Annual Reviews.

Miller, J. H. (2007). Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton UP.

Newman, M.J. (2002). The Spread of Epidemic Disease on Networks. Working Paper 02-04-020. Santa Fe Institute.

Rhodes, C.J. & Anderson, R.M. (1996). “Dynamics in a Lattice Epidemic Model”. Physics Letter A 210:183-188. Elsevier Science.

Reynolds, C. (1987). Flocks, herds and schools: A distributed behavioral model. SIGGRAPH '87: Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques. Association for Computing Machinery.

Situngkir, H. (2003). “Moneyscape: a generic agent-based model of corruption”. BFI Working Paper Series WPD2003. Bandung Fe Institute.

Situngkir, H. (2004). “How Far Can We Go Through Social System”. Journal of Social Complexity 2(1).

Situngkir, H. (2004). “Epidemiology Through Cellular Automata: Case of Study Avian Influenza in Indonesia”. BFI Working Paper Series WPG2004. Bandung Fe Institute.

Smelser, N. J. (1997). Problematics of Sociology: The Georg Simmel Lectures. University of California Press.

Sunjaya, A. P., & Jenkins, C. (2020). “Rationale for universal face masks in public against COVID-19”. Respirology (Carlton, Vic.), 25(7)

Qi, H., Xiao, S., Shi, R., Ward, M. P., Chen, Y., Tu, Wei., Su, Q., Wang, W., Wang, X., Zhang, Z. (2020). "COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis". Science of The Total Environment 728. Elsevier.

WHO. (2020). Coronavirus disease (COVID-19) advice for the public. URL: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public/