论文标题
分析发生率模式和估计复制数量的时间序列方法
A time series method to analyze incidence pattern and estimate reproduction number of COVID-19
论文作者
论文摘要
2019年底，冠状病毒病（Covid-19）的持续大流行出现在中国武汉。它已经影响了30万人，死亡人数接近世界13000人。由于它一直对全球公共卫生构成巨大威胁，因此确定疾病传播的速度至关重要。在这项研究中，我们提出了一个时间序列模型，以分析Covid-19-19-19的趋势模式。我们还将有关总或部分锁定的信息（无论在任何地方提供）都将其纳入模型中。该模型在结构上是简洁的，并且使用适当的诊断措施，我们表明，时间依赖的二次趋势成功地捕获了该疾病的发生率模式。我们还估计了不同国家的基本繁殖数，并发现除了美利坚合众国，它是一致的。以上统计分析能够阐明了解爆发趋势的趋势，并深入了解一个地区所在的流行病学阶段。这有可能帮助促使政策解决不同国家的Covid-19-19大流行。
The ongoing pandemic of Coronavirus disease (COVID-19) emerged in Wuhan, China in the end of 2019. It has already affected more than 300,000 people, with the number of deaths nearing 13000 across the world. As it has been posing a huge threat to global public health, it is of utmost importance to identify the rate at which the disease is spreading. In this study, we propose a time series model to analyze the trend pattern of the incidence of COVID-19 outbreak. We also incorporate information on total or partial lockdown, wherever available, into the model. The model is concise in structure, and using appropriate diagnostic measures, we showed that a time-dependent quadratic trend successfully captures the incidence pattern of the disease. We also estimate the basic reproduction number across different countries, and find that it is consistent except for the United States of America. The above statistical analysis is able to shed light on understanding the trends of the outbreak, and gives insight on what epidemiological stage a region is in. This has the potential to help in prompting policies to address COVID-19 pandemic in different countries.
