论文标题
评估社交网络结构对冠状病毒疾病扩散的影响（COVID-19）：广义的空间SEIRD模型
Assessing the Impact of Social Network Structure on the Diffusion of Coronavirus Disease (COVID-19): A Generalized Spatial SEIRD Model
论文作者
论文摘要
在本文中，我研究了广义的空间SEIRD模型中的流行病扩散，该模型最初是在社会或地理网络中连接的。随着病毒在网络中的传播，由于隔离措施和/或空间抗势的策略，人们之间的相互作用的结构可能会随着时间而变化。我通过模拟探索共同进化过程的动态特性，该过程动态地联系了疾病扩散和网络特性。结果表明，为了预测网络人群中流行现象的发展，不足以关注初始相互作用结构的性质。实际上，网络结构和隔间的共同发展强烈影响流行病的过程，尤其是在其速度方面。此外，我表明，空间统治政策的时机和特征可能会极大地影响其有效性。
In this paper, I study epidemic diffusion in a generalized spatial SEIRD model, where individuals are initially connected in a social or geographical network. As the virus spreads in the network, the structure of interactions between people may endogenously change over time, due to quarantining measures and/or spatial-distancing policies. I explore via simulations the dynamic properties of the co-evolutionary process dynamically linking disease diffusion and network properties. Results suggest that, in order to predict how epidemic phenomena evolve in networked populations, it is not enough to focus on the properties of initial interaction structures. Indeed, the co-evolution of network structures and compartment shares strongly shape the process of epidemic diffusion, especially in terms of its speed. Furthermore, I show that the timing and features of spatial-distancing policies may dramatically influence their effectiveness.
