# Study on Early Warning Methods for Shipping Input Risks Under Consideration of Public Health Events
## 6 Simulation and Result Analysis  
By selecting different transmission chains to simulate the risk propagation process, this study aims to control the final transmission risk from factors like transmission length. The article selects different nodes as risk starting points based on existing shipping data, with the endpoint consistently set as the Shanghai node. Simulations are carried out with an equal number of transmission chains but involving different nodes. Additionally, for the same starting point, different risk transmission chains are compared. The selected risk transmission chains and results are shown in Table 7 below:  
From the above results, it can be seen that with the same initial spread point and the same number of spread nodes, spreading through different nodes ultimately leads to different risks. This is specifically determined by the combination of the nodes' own risks and the spreading probability. Taking the New York as an initial node example, the risk situation of three propagation chains is illustrated in Figure 13:  
The final risk values in the figure are 0.0593, 0.0211, 0.0292. In the first chart, the nodes through which the transmission passes have low individual risk, but due to the tight connections within the shipping network between nodes, the probability of transmission is high, resulting in a higher final risk. Compared to the first chart, the second chart has nodes with higher individual risk, but due to a lower network transmission probability, the risk value is lower. Compared to the first chart, the third chart has a lower transmission probability for initial nodes, so even though subsequent nodes have a high transmission probability, the resulting value is still lower. This indicates that the overall risk value is not only related to individual node risk but also to the transmission probability of nodes it passes through; both factors together determine the complex process of risk transmission. Figure 14 shows the relationship between the average individual risk, average transmission probability, and final risk of the aforementioned transmission chains. The results demonstrate a positive correlation between final risk and both average individual risk and average transmission probability. This indicates that an increase in individual risk and transmission probability will lead to an increase in final risk. Individual risk is related to the node's importance in the network, as well as climatic, economic, and health-related factors. It may become the starting point of risk transmission or a node in the transmission process, causing risk to spread to surrounding areas. Therefore, when the individual risk of a node increases, the final risk also increases. The transmission probability measures \begin{table}
\begin{tabular}{c c} \hline
**Serial No.** & **Transmission Nodes** & **Risk Value** \\ \hline
1 & NY-Manzanillo-Jakarta–Ho Chi Minh City–Shanghai & 0.0593 \\
2 & NY-Casablanca–Jedda–Mumbai–Shanghai & 0.0211 \\
3 & NY-Buenaventura–Sydney–Yokohama–Shanghai & 0.0292 \\
4 & Sao Paulo–Buenos Aires–Sydney–Singapore–Shanghai & 0.1125 \\
5 & Sao Paulo–Buenaventura–Guayaquil–Panama–Shanghai & 0.0258 \\
6 & Sao Paulo–Callao–Sydney–Krung Thep Maha Nakhon–Shanghai & 0.0211 \\
7 & London–Antwerp–Marseille–Singapore–Shanghai & 0.0931 \\
8 & London–Jedda–Colombo–Kuala Lumpur–Shanghai & 0.029 \\
9 & London-Vancouver–Yokohama–Busan–Shanghai & 0.0954 \\
10 & Durban–Colombo–Kuala Lumpur–Ho Chi Minh City–Shanghai & 0.0563 \\
11 & Durban–Jakarta–Singapore–Manila–Shanghai & 0.1012 \\
12 & Durban–Maputo–Mumbai–Krung Thep Maha Nakhon–Shanghai & 0.0251 \\
13 & Auckland–Sydney–Yokohama–Busan–Shanghai & 0.1209 \\
14 & Auckland–Sydney–Port Moresby–Jakarta–Shanghai & 0.0248 \\
15 & Auckland–Sydney–Singapore–Krung Thep Maha Nakhon–Shanghai & 0.0577 \\ \hline \end{tabular}
\end{table} 
Table 7: Risk transmission chains and results. the closeness of connections in the shipping network. If a node has a high transmission probability, it can more easily connect with other nodes and spread risk.