论文标题
使用KCDC患者数据来表征韩国的COVID-19传播
Characterizing the COVID-19 Transmission in South Korea Using the KCDC Patient Data
论文作者
论文摘要
随着世界卫生组织（WHO）及其成员国一直在大力依靠呆在家里并锁定措施来控制病毒传播的措施，世界卫生组织（WHO）及其成员国一直在全球范围内发展。在过去的几个月中，各种迹象表明，Covid-19曲线正在变平，但即使是部分遏制措施（例如，学校关闭和远程办公）的部分提升似乎也有利于第二波疾病。因此，准确评估可能的对策及其成熟的吊销对于避免将来的波浪或减少持续时间至关重要。在本文中，我们分析了韩国疾病控制与预防中心（KCDC）收集的，从2020年1月20日至2020年5月31日，从2020年1月20日至2020年5月31日分析了患者和路线数据。此数据分析有助于我们表征患者的移动模式，然后使用此表征来参数化模拟以评估不同的情况。尽管这不是Covid-19如何在人群中传播的明确模型，但使用现实世界中的数据来探索在各种情况下探索病毒蔓延的现实数据来说明其有用性和灵活性。
As the COVID-19 outbreak evolves around the world, the World Health Organization (WHO) and its Member States have been heavily relying on staying at home and lock down measures to control the spread of the virus. In the last months, various signs showed that the COVID-19 curve was flattening, but even the partial lifting of some containment measures (e.g., school closures and telecommuting) appear to favor a second wave of the disease. The accurate evaluation of possible countermeasures and their well-timed revocation are therefore crucial to avoid future waves or reduce their duration. In this paper, we analyze patient and route data of infected patients from January 20, 2020, to May 31, 2020, collected by the Korean Center for Disease Control & Prevention (KCDC). This data analysis helps us to characterize patient mobility patterns and then use this characterization to parameterize simulations to evaluate different what-if scenarios. Although this is not a definitive model of how COVID-19 spreads in a population, its usefulness and flexibility are illustrated using real-world data for exploring virus spread under a variety of circumstances.
