Owing to the complexity of and changes associated with modern public health emergencies, cross-departmental collaborative governance is an inevitable choice for ensuring effective emergency management. In the context of emergency management research, the way in which taking full advantage of synergy can be used to enhance the effectiveness of emergency prevention and control approaches is an important issue that must be addressed urgently.
Combined with China's responses to the management of public health emergencies, in this study, we construct a theoretical analysis framework involving three dimensions: information, organization, and environment. Our proposed framework relies on the fuzzy-set qualitative comparative analysis (fsQCA) method to analyze the mechanisms behind the prevention and control of coronavirus disease 2019 (COVID-19) cases across 15 cities located in typical provinces throughout China and explore the roles of cross-departmental collaboration in the processing of various elements as well as the effects of their combination on the action mechanisms for ensuring the effectiveness of emergency management approaches.
The results show a significant conditional correlation between the effectiveness of emergency management and the factors affecting cross-departmental coordination. Based on the characteristics of multiple concurrent paths, the driving paths can be classified into four categories: organizational, environmental, environment-balanced, and organization environment-based dual-core categories.
The effectiveness of public health emergency management is the result of multiple factors. Local governments should strengthen the coordination and integration of information, organization, and environment, improve the coordinated system associated with emergency management, promote the “two-wheel drive” of high-quality development as well as accurate prevention and control, explore and perfect the adaptive combinatorial optimization path, and effectively transform the advantages of linking multi-dimensional factors with governance efficiency.