Information fusion is very effective and necessary to respond to a public epidemic outbreak such as COVID-19. Big data intelligent, as a product of information fusion, plays an important role in the prevention and control of COVID-19. The continuous mechanism of big data intelligent innovation (BDII) is fundamental to effectively prevent and control a public epidemic outbreak. In this study, the continuous mechanism of BDII was fused into a complex network, and a three-dimensional collaborative epidemic prevention model was constructed. Furthermore, adiabatic elimination principle was applied to explore the order parameter of the continuous mechanism. Finally, empirical analysis was conducted based on three-stage epidemic prevention strategies to reveal the effect of continuous epidemic prevention under different big data intelligent emergency management policy levels. The results of this study are as follows. Through the mutual influence and coupling of the subsystems, the continuous mechanism of BDII can be realized to manage a public epidemic outbreak emergency. The big data intelligent subsystem is integrated into the subsystems of public epidemic outbreak management and science and technology innovation. The big data intelligent emergency management policies play a positive role in the overall BDII for the continuous epidemic prevention of a public epidemic outbreak. The convention of BDII transformation is the continuous mechanism of BDII as the order parameter of a public epidemic outbreak. In the early stage of epidemic prevention, the convention is excessively pursued, while the neglect of BDII configuration is not conducive to the long-term collaborative governance of a public epidemic outbreak. The study provides practical guidelines for the formulation of fusion innovation policies, application of big data intelligent, and theoretical basis for the emergency management of a public epidemic outbreak in the medical field.

信息融合对于应对 COVID-19 等公共流行病爆发非常有效且必要。大数据智能化作为信息融合的产物，在COVID-19的防控中发挥着重要作用。大数据智能创新（BDII）持续机制是有效防控疫情的根本。本研究将BDII的持续机制融合成一个复杂的网络，构建了三维协同防疫模型。此外，应用绝热消除原理来探索连续机构的阶参数。最后，基于三阶段防疫策略进行实证分析，揭示不同大数据智能应急管理政策水平下持续防疫的效果。本研究的结果如下。通过子系统之间的相互影响和耦合，可以实现BDII的持续机制来管理突发公共卫生事件。大数据智能子系统融入公共疫情暴发管理和科技创新子系统。大数据智能应急管理政策在整体BDII中对突发公共卫生事件的持续防疫起到了积极的作用。BDII 转换的约定是 BDII 作为公共流行病爆发的顺序参数的连续机制。在防疫初期，过度追求公约，而忽视BDII配置，不利于公共疫情爆发的长期协同治理。该研究为融合创新政策的制定、大数据智能化的应用提供了实践指导，为医疗领域突发公共卫生事件的应急管理提供了理论依据。