Based on the parallel system theory and the CPP multi-space intelligent analysis theory, this paper discusses the relationship among the network virtual space,the real physical space and the social-psychological space, to find a way to build a big data analysis framework for the epidemic prevention and control, by using the mass real-time interaction data to carry out an empirical analysis from three aspects:the prediction of COVID-19, the feed back of the work resumption, and the influences on the public awareness of COVID-19. It is found that the interactive data of the online games can be used to predict the outbreak and the evolution of the epidemics to a certain extent, to accurately restore the status of work resumption, and to effectively improve the public awareness of the epidemics. As an important analysis tool, the online game interactive data can effectively fill the "blind area" and break the limitations of the traditional network big data tools in the epidemic prevention and control, enrich the epidemic prevention and control response mechanism, and play a positive role in building a more comprehensive social management system.

COVID-19 prevention and control  /  online games  /  big data  /  parallel systems  /  cyber psychosocial and physical computation