国际贸易网络：国家中心性与COVID-19大流行
International Trade Network: Country centrality and COVID-19 pandemic
AI总结：
本文通过计算贸易网络中心性并结合基于可传播距离的社区检测与负二项回归，发现全球贸易网络中中心性更高的国家COVID-19感染和死亡人数更多。
摘要：
国际贸易建立在不同国家之间一系列复杂关系的基础上，这些关系可以被建模为一个由相互连接的主体构成的极其密集的网络。一方面，该网络可能促进各国的经济增长，但另一方面，它也可能促进诸如COVID-19之类疾病的传播。在本文中，我们研究贸易网络的拓扑结构是否以及在多大程度上能够解释各国之间COVID-19传播率和死亡率的差异。我们计算了各国的中心性测度，并应用了基于可传播距离的社区检测方法。随后，我们将这些测度作为负二项回归框架中的核心回归变量。在此过程中，我们还比较了不同中心性测度的效应。我们的结果表明，在全球贸易网络中具有更高中心性的国家，感染人数和死亡人数也更多。
英文摘要：
International trade is based on a set of complex relationships between different countries that can be modelled as an extremely dense network of interconnected agents. On the one hand, this network might favour the economic growth of countries, but on the other, it can also favour the diffusion of diseases, like the COVID-19. In this paper, we study whether, and to what extent, the topology of the trade network can explain the rate of COVID-19 diffusion and mortality across countries. We compute the countries' centrality measures and we apply the community detection methodology based on communicability distance. Then, we use these measures as focal regressors in a negative binomial regression framework. In doing so, we also compare the effect of different measures of centrality. Our results show that the number of infections and fatalities are larger in countries with a higher centrality in the global trade network.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
