Prediction of Epidemic Transmission and Evaluation of Prevention and Control Measures Based on Artificial Society

doi:10.16182/j.issn1004731x.joss.20-FZ0460

Abstract

Abstract: The COVID-19 has been controlled under the strict measures,but how to normalize it deserves in-depth study.The COVID-19 transmission model and the human contact network are established separately based on SEIR model and the artificial social scenario.With the support of the multi-agent computational experiment method,a large sample calculation experiment was performed on the Tianhe supercomputer to simulate the epidemic transmission in typical areas such as communities,schools,and workplaces in artificial cities,and to predict and evaluate the risk of epidemic spread after resumption of work and school.The results show that epidemic prevention and control must be prepared for a protracted battle,the emergency measures should be activated before the outbreak.

Key words: COVID-19, transmission prediction, evaluation of prevention and control measures, artificial society, computational experiment

CLC Number:

TP391.9

Chen Bin, Yang Mei, Ai Chuan, Ma Liang, Zhu Zhengqiu, Chen Hailiang, Zhu Mengna, Xu Wei. Prediction of Epidemic Transmission and Evaluation of Prevention and Control Measures Based on Artificial Society[J]. Journal of System Simulation, 2020, 32(12): 2507-2514.

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