香港新冠肺炎变异的数据驱动研究

Yongmei Ding, Lingxiao Xiang
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摘要

中国香港新一波新冠肺炎疫情再次以“动态零”战略和非药物干预措施(dz - npi)压倒,这给控制疫情的变型带来了时间挑战。我们首先通过统计度量将香港的Covid-19变异描述为按年龄组划分的人口感染比例、累计确诊病例、累计死亡病例和当前住院病例,然后建立时间序列模型对累计确诊病例进行拟合,进一步预测趋势,寻找可能的转折时间点。通过建立非线性回归模型,对死亡序列进行特征化,求出参数并推导出控制条件。我们希望我们的数据驱动建模过程能够为香港甚至中国大陆的新一波Covid-19变体的控制策略提供一些见解。
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A Data Driven Study on the Variant of Covid-19 in Hong Kong
The new wave of COVID-19 in Hong Kong, China was overwhelming again by “dynamic zero” strategy and non-pharmaceutical interventions (DZ-NPIs), which makes a time challenge to control the variant of this epidemic. We describe the variant of Covid-19 in Kong Hong to the infected proportion of the population, cumulative confirmed cases, cumulative deaths and current hospitalizations by age group via statistical measure firstly, then establish time series model for fitting the accumulative confirmed cases, further to predict the trend for searching out possible turning time-points. Non-linear regression model is created to feature the deaths series, then we figure out the parameters and educe the controlling condition for this epidemic. We expect our data-driven modeling process providing some insights to the controlling strategy for the new wave of the Covid-19 variant in Hong Kong, even in the mainland of China.
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