# Study on Early Warning Methods for Shipping Input Risks Under Consideration of Public Health Events
## 7 Conclusions  
This paper considers the mechanisms of risk transmission and early warning models within shipping node areas and the cross-border risk transmission models and early warning research under shipping networks, focusing on China's maritime import risk warning methods and response mechanisms in the context of public health events.  
By studying the mechanisms of risk transmission and early warning models within shipping node areas, we analyze the self-risk of each node. First, we examine the transmission mechanisms of mosquito-borne infectious diseases and analyze their influencing factors. Then, based on these influencing factors and transmission dynamics, we construct an improved SEIR-SEI model. The basic accuracy of the model is verified through mean-field analysis. The derived infection threshold confirms that the infection vector factor is not zero, meaning a vector is required for transmission, aligning with actual conditions. Finally, the approach uses simulation to determine the number of infections within the area, which is utilized to analyze the transmission risk within the region.  
In the research on cross-border risk propagation models and early warning under shipping networks, the mechanism of cross-border risk propagation under shipping networks is first analyzed, explaining the process of cross-border propagation of public health events through passenger and freight transport. Then, a globally interconnected network of aviation and maritime shipping is constructed based on complex networks, and its network structure and attribute characteristics are analyzed. A global freight and passenger inter  
Figure 15: Final number of infections with different initial infection nodes.  
coupled network node propagation risk model is developed, taking into comprehensive consideration the network's clustering coefficient, betweenness centrality, closeness centrality, degree centrality, and eigenvector centrality. Finally, the cross-border risk propagation under the shipping network is analyzed through simulation. From the simulation results, it can be concluded that, firstly, selecting nodes with the same quantity but different node inter-coupling importance as the initial infection points shows that the number of infected nodes in the final network is positively correlated with the importance of nodes, verifying the rationality of using node inter-coupling importance as a measure of risk propagation. Secondly, by choosing different nodes as the starting point of risk and setting the endpoint as a Chinese node, with simulations through an equal number of, but different, nodes in the propagation chain, it is found that although the same number of nodes is passed, due to the different inherent risks of the nodes and the different probabilities of propagation between the nodes, the final risk presents differently. This verifies the rationale and importance of considering both internal regional risk propagation and cross-border risk propagation when studying overall input risks.  
Thus, it provides multi-dimensional policy recommendations for establishing a sound input risk early warning mechanism, such as establishing a real-time tracking system based on border monitoring data and constructing a cross-border risk assessment model. This, in turn, helps to enhance the emergency response capabilities of the state and localities, minimize the risk of epidemic spread to the greatest extent possible, provide a scientific basis for national prevention and control strategies, and promote international cooperation and information sharing to jointly address the challenges brought about by public health incidents.