Temporal Analysis of Epidemiology indicators and Air Travel Data for Covid-19
Temporal Analysis of Epidemiology indicators and Air Travel Data for Covid-19
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发表时间：
2021
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通讯作者：
Sumit Purohit;L. Holder;G. Chin
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作者：
Sumit Purohit;L. Holder;G. Chin
2019冠状病毒病（Covid-19）是一场持续爆发的疫情，也是对全球健康的最新威胁。了解社会交往对新冠肺炎指标的影响，有助于政府和地方当局制定政策和指导方针。我们提出了一个案例研究，在美国策划了州一级的Covid-19指标，如活跃病例、死亡、住院率等。我们还整理了开源的美国国内航空旅行数据，并介绍了其对Covid-19指标的影响。我们使用独立时间Motif （ITeM）对数据集进行时间序列分析，以发现数据中的每周趋势。我们发布数据集和结果，供研究界进一步探索。
Coronavirus Disease 2019 (Covid-19) is an ongoing outbreak and the latest threat to global health. It is imperative to understand the implications of social interaction on Covid-19 indicators in order to help formulate policies and guidelines by governments and local authorities. We present a case-study of curating state-level Covid-19 indicators such as Active Cases, Deaths, Hospitalization Rate, etc. for the United States. We also curate open source domestic US air travel data and present its impact on Covid-19 indicators. We perform a time-series analysis of the dataset using Independent Temporal Motif (ITeM) to find weekly trends in the data. We publish the dataset and the results for further exploration by the research community.