论文标题
集中和分散的隔离策略及其对COVID-19大流行动态的影响
Centralized and decentralized isolation strategies and their impact on the COVID-19 pandemic dynamics
论文作者
论文摘要
由于各种社交网络实现了人类互动，传染病正在传播。因此，当像SARS-COV-2这样的新病原体引起爆发时，非药物隔离策略（例如，社会距离）是破坏其扩散的唯一可能反应。为此，我们介绍了新的流行病模型（SICARS），并比较集中式（C），分散（D）和联合（C+D）社会疏远策略，并分析其效率，以控制Covid-19对异构复合物网络的动力学。我们的分析表明，在最大程度地减少大流行蔓延是必要的集中社会距离。分散的策略在单独使用时不足，但与集中式策略相结合时，可以提供最佳的结果。实际上，（C+D）是减轻网络超级传播者并将最高节点度减少到其初始值的10％的最有效隔离策略。我们的结果还表明，更强大的社会距离，例如，削减75％的社会关系可以使C隔离的爆发减少75％，而D隔离为33％，而（c+d）隔离策略则减少了87％。最后，我们研究了主动隔离策略的影响，及其延迟执法的影响。我们发现，对大流行的反应反应效率较低，并且将隔离措施的采用延迟一个月以上（因为该地区的爆发发作）可能会产生令人震惊的影响；因此，我们的研究有助于理解时空中的Covid-19大流行。我们认为，我们的调查具有很高的社会相关性，因为它们提供了了解不同程度的社会距离如何可以大大降低峰值感染比率的见解；这可以使Covid-19的大流行更加容易理解和控制。
The infectious diseases are spreading due to human interactions enabled by various social networks. Therefore, when a new pathogen such as SARS-CoV-2 causes an outbreak, the non-pharmaceutical isolation strategies (e.g., social distancing) are the only possible response to disrupt its spreading. To this end, we introduce the new epidemic model (SICARS) and compare the centralized (C), decentralized (D), and combined (C+D) social distancing strategies, and analyze their efficiency to control the dynamics of COVID-19 on heterogeneous complex networks. Our analysis shows that the centralized social distancing is necessary to minimize the pandemic spreading. The decentralized strategy is insufficient when used alone, but offers the best results when combined with the centralized one. Indeed, the (C+D) is the most efficient isolation strategy at mitigating the network superspreaders and reducing the highest node degrees to less than 10% of their initial values. Our results also indicate that stronger social distancing, e.g., cutting 75% of social ties, can reduce the outbreak by 75% for the C isolation, by 33% for the D isolation, and by 87% for the (C+D) isolation strategy. Finally, we study the impact of proactive versus reactive isolation strategies, as well as their delayed enforcement. We find that the reactive response to the pandemic is less efficient, and delaying the adoption of isolation measures by over one month (since the outbreak onset in a region) can have alarming effects; thus, our study contributes to an understanding of the COVID-19 pandemic both in space and time. We believe our investigations have a high social relevance as they provide insights into understanding how different degrees of social distancing can reduce the peak infection ratio substantially; this can make the COVID-19 pandemic easier to understand and control over an extended period of time.
