# Study on Early Warning Methods for Shipping Input Risks Under Consideration of Public Health Events
## 5 Shipping Network Node Ranking Based on Node Importance
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Node** & **Clustering** & **Betweenness** & **Closeness** & **Degree** & **Eigenvector** \\  & **Coefficient** & **Centrality** & **Centrality** & **Centrality** & **Centrality** \\ \hline Marseille & 0.253 & 0.079 & 0.636 & 0.983 & 0.994 \\ Alexandria & 0.487 & 0.007 & 0.540 & 0.492 & 0.671 \\ Istanbul & 0.291 & 0.043 & 0.621 & 0.913 & 0.980 \\ Copenhagen & 0.579 & 0.004 & 0.525 & 0.458 & 0.656 \\ Barcelona & 0.367 & 0.025 & 0.572 & 0.688 & 0.817 \\ Rotterdam & 0.351 & 0.030 & 0.595 & 0.750 & 0.878 \\ Tromso & 0.644 & 0.003 & 0.506 & 0.342 & 0.510 \\ Mumbai & 0.483 & 0.009 & 0.550 & 0.500 & 0.646 \\ Saint Petersburg & 0.350 & 0.044 & 0.591 & 0.754 & 0.865 \\ Gothenburg & 0.647 & 0.002 & 0.521 & 0.400 & 0.605 \\ Gd\(\ddot{\text{a}}\)nsk & 0.585 & 0.003 & 0.537 & 0.471 & 0.676 \\ Hamburg & 0.307 & 0.040 & 0.615 & 0.879 & 0.974 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Importance indicators of aviation passenger network nodes. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Node** & **Clustering Coefficient** & **Betweenness Centrality** & **Closeness Centrality** & **Degree Centrality** & **Eigenvector Centrality** \\ \hline Marseille & 0.804 & 0.000 & 0.536 & 0.288 & 0.841 \\ Alexandria & 0.835 & 0.000 & 0.530 & 0.288 & 0.952 \\ Istanbul & 0.206 & 0.056 & 0.832 & 0.713 & 0.966 \\ Copenhagen & 0.837 & 0.000 & 0.529 & 0.263 & 0.825 \\ Barcelona & 0.205 & 0.054 & 0.835 & 0.725 & 0.814 \\ Rotterdam & 0.805 & 0.000 & 0.535 & 0.279 & 0.816 \\ Tromso & 0.846 & 0.000 & 0.529 & 0.279 & 0.935 \\ Mumbai & 0.814 & 0.000 & 0.537 & 0.313 & 0.977 \\ Saint Petersburg & 0.840 & 0.000 & 0.530 & 0.288 & 0.977 \\ Gothenburg & 0.215 & 0.039 & 0.758 & 0.475 & 0.816 \\ Gd\(\acute{\text{a}}\)nsk & 0.832 & 0.000 & 0.528 & 0.258 & 0.816 \\ Hamburg & 0.190 & 0.071 & 0.862 & 0.763 & 0.862 \\ Shanghai & 0.789 & 0.000 & 0.540 & 0.325 & 0.974 \\ NY & 0.801 & 0.000 & 0.538 & 0.317 & 0.974 \\ Porto & 0.234 & 0.035 & 0.785 & 0.563 & 0.814 \\ Mombasa & 0.882 & 0.000 & 0.528 & 0.254 & 0.830 \\ Manila & 0.868 & 0.000 & 0.529 & 0.267 & 0.904 \\ Manzanillo & 0.811 & 0.000 & 0.537 & 0.308 & 0.952 \\ Zurich & 0.837 & 0.000 & 0.530 & 0.288 & 0.934 \\ Vancouver & 0.815 & 0.000 & 0.538 & 0.308 & 0.934 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Importance indicators of nodes in the maritime network. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Node** & **Clustering Coefficient** & **Betweenness Centrality** & **Closeness Centrality** & **Degree Centrality** \\ \hline Shanghai & 0.326 & 0.053 & 0.586 & 0.692 & 0.752 \\ NY & 0.203 & 0.158 & 0.649 & 0.946 & 0.831 \\ Porto & 0.516 & 0.007 & 0.515 & 0.408 & 0.545 \\ Mombasa & 0.319 & 0.022 & 0.541 & 0.433 & 0.447 \\ Manila & 0.405 & 0.010 & 0.520 & 0.325 & 0.353 \\ Manzanillo & 0.542 & 0.004 & 0.500 & 0.275 & 0.346 \\ Zurich & 0.431 & 0.012 & 0.569 & 0.629 & 0.800 \\ Vancouver & 0.298 & 0.040 & 0.563 & 0.583 & 0.605 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{c c c c} \hline \hline
**City** & **Node Importance** & **City** & **Node Importance** \\ \hline NY & 0.830 & Casablanca & 0.375 \\ Marseille & 0.636 & Addis Ababa & 0.366 \\ London & 0.618 & Vienna & 0.355 \\ Istanbul & 0.523 & United Arab Emirates & 0.351 \\ Hamburg & 0.508 & Dubai & 0.350 \\ Saint Petersburg & 0.490 & Alexandria & 0.331 \\ Shanghai & 0.487 & Mumbai & 0.330 \\ Rotterdam & 0.453 & Gd\(\acute{\text{a}}\)nsk & 0.327 \\ Barcelona & 0.423 & Copenhagen & 0.322 \\ Genoa & 0.421 & Piraeus & 0.317 \\ Vancouver & 0.399 & Krung Thep Maha Nakhon & 0.309 \\ Antwerp & 0.389 & Sao Paulo & 0.308 \\ Zurich & 0.386 & Odesa & 0.307 \\ Doha & 0.379 & Haifa & 0.303 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Calculation results of node importance in the air passenger transport network. Similar to the air freight network, highly important country nodes in the maritime network, such as Hamburg, Istanbul, and Barcelona, also have a high degree of centrality and eigenvector centrality.