论文标题
COVID-19的视觉数据分析和模拟预测
Visual Data Analysis and Simulation Prediction for COVID-19
论文作者
论文摘要
Covid-19(以前是2019-NCOV)流行病已成为全球卫生紧急情况,因此宣布为Pheic。自从病毒爆发以来,中国取得了最大的打击,一些专家可以追溯到11月下旬。直到1月23日,武汉政府才最终认识到这种流行病的严重性,并采取了巨大的措施,通过关闭将外界连接的所有运输来掩盖病毒的传播。在这项研究中,我们试图回答一些问题:该病毒是如何从陶汉市传播到该国其他地区的?这些措施在多大程度上有助于控制局势?更重要的是,我们可以预测该事件的未来未来发展是否有所改变?通过收集和可视化公共数据,我们首先显示流行病发展的模式和特征。然后,我们采用疾病传播动力学的数学模型来评估某些流行病控制措施的有效性,更重要的是,提供了一些有关预防措施的技巧。
The COVID-19 (formerly, 2019-nCoV) epidemic has become a global health emergency, as such, WHO declared PHEIC. China has taken the most hit since the outbreak of the virus, which could be dated as far back as late November by some experts. It was not until January 23rd that the Wuhan government finally recognized the severity of the epidemic and took a drastic measure to curtain the virus spread by closing down all transportation connecting the outside world. In this study, we seek to answer a few questions: How did the virus get spread from the epicenter Wuhan city to the rest of the country? To what extent did the measures, such as, city closure and community quarantine, help controlling the situation? More importantly, can we forecast any significant future development of the event had some of the conditions changed? By collecting and visualizing publicly available data, we first show patterns and characteristics of the epidemic development; we then employ a mathematical model of disease transmission dynamics to evaluate the effectiveness of some epidemic control measures, and more importantly, to offer a few tips on preventive measures.