Spatio-temporal Simulation of Epidemiological SIQR Model Based on the Multi-Agent System with Focus on Influenza A (H1N1)
Influenza A (H1N1) has caused tremendous damage in the world, so to learn its law is of great significance in the epidemic prevention and social stability. Taking the multi-agent system (MAS), geo-spatial environment to build the simulation model, SIQR epidemic model is introduced to simulate the process of the spread of influenza A (H1N1), test the multiple sets of preventive and control measures proposed from the perspectives of administrators and the public and do comparisons with the testing results. The testing results indicate that: the control of short-term epidemic spread requires administrators to implement powerful effective measures in public places to isolate patients, while inhibition of spread and rebound of the epidemic in a long-term way hereof needs administrators and the public working together to strengthen the self-protection, and timely medical treatment; repeated trials of the disease shows that the occurrence of rebound in the vicinity of 100d; the number of the immune and the susceptible are negatively correlated.
Keywordsinfluenza A (H1N1) multi-agent system SIQR model spread simulation
Unable to display preview. Download preview PDF.
- 2.Bates, J.M., Granger, C.W.J.: Combination of forecasts. Opelations Research uarterly 4, 451–468 (1969)Google Scholar
- 6.Rodrigo, M.J., Morell, F., Helm, R.M., et al.: Identification and partial characterization of the soybean-dust allergens involved in the Barcelona asthma epidemic. J. Allergy Clin. Immunol. 4, 78–84 (1990)Google Scholar
- 7.Sanden, A., Jarvholm, B., Larsson, S., et al.: The risk of lung cancer and mesothelioma after cessation of asbestos exposure: a prospective cohort study of shipyard workers. Eur. Respir. 5, 281–285 (1992)Google Scholar
- 8.Dong-qing, Y.E.: Pandemic and response of influenza A (H1N1). Chinese Journal of Disease Control and Prevention 3, 216–218 (2009)Google Scholar
- 9.John Oommen, B., Calitoiu, D.: Modeling and simulating a disease outbreak by learning a contagion parameter-based model. In: Proceedings of the 2008 Spring simulation multiconference. Society for Computer Simulation International, Ottawa, Canada, pp. 14–17 (2008)Google Scholar
- 10.Macal, C.M., North, M.J.: Tutorial on agent-based modeling and simulation part 2: how to model with agents. In: Perrone, L.F., Lawson, B.G., Liu, J., Wieland, F.P. (eds.) Proceedings of the 37th Winter Simulation Conference, Monterey, CA (2006)Google Scholar
- 13.National Bureau of Statistics of China, http://som.xjtu.edu.cn/somlab/zhonguotong-jinianjian/2009/indexce.htm