Abstract:

In order to respond to various public health emergencies in a timely and effective manner, a resilient emergency governance organizational structure is the key guarantee. Taking the prevention and control of novel coronavirus infection in China as the research object, this study collected 951 policy publications at the central level since the outbreak of novel coronavirus epidemic in China, sorted out the joint relations among the issuers, and obtained a government collaborative governance relationship matrix. On this basis, we applied the complex network theory to build a government collaborative governance network for public health emergencies in China. Finally, using the social network analysis method, this paper put forward five dimensions of indicators that systematically represent the resilience of the network structure: hierarchy, matching, accessibility, clustering and diversity, and then realized the evaluation of the resilience of government collaborative governance organization in China from the perspective of structural topology. The results show that the network degree distribution coefficient is -0.591 6. The degree correlation coefficient is -0.188 3. The average path length is 2.129 0. The network efficiency is 0.403 5. The average clustering coefficient is 0.598 9. The average number of independent paths in the network is 4.095 5. The results show that the government collaborative governance network of public health emergencies in China has heterogeneity and obvious hierarchy, with good redundancy, but the network circulation level is low. The network has a poor ability to resist and absorb attacks, and it should be adjusted to improve the overall network early warning and anti-interference ability.

Key words: public health emergencies, government collaborative governance, network resilience, novel coronavirus, social network analysis, organizational resilience