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首页> 外文期刊>Results in Physics >Modeling COVID-19 spreading dynamics and unemployment rate evolution in rural and urban counties of Alabama and New York using fractional derivative models
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Modeling COVID-19 spreading dynamics and unemployment rate evolution in rural and urban counties of Alabama and New York using fractional derivative models

机译：使用分数衍生模型建模Covid-19在农村和纽约农村和城市县的传播动力学和失业率演变

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The COVID-19 pandemic has been affecting the United States (U.S.) since the outbreak documented on 2/29/2020, and understanding its dynamics is critical for pandemic mitigation and economic recovery. This study proposed and applied novel time fractional derivative models (FDMs) to quantify the spatiotemporal dynamics of the COVID-19 pandemic spreading in the states of Alabama and New York, U.S., two states with quite different population compositions, urbanization, and industry structures. Model applications revealed that the pandemic evolving in the two states exhibited an overall similar time-dependent trend with subtle differences in propagation rates. Alabama may have more inter-county communications in rural areas than urban areas, while the opposite may be true for the New York State. Further analysis using the space FDM showed that the COVID-19 pandemic spread in rural/urban areas of the two states by following the tempered stable density distributions with different indexes, while the number of the state’s pandemic epicenters affected the pattern of the COVID-19 pandemic spreading in space. Finally, applications of a novel time FDM revealed that the evolution of the economy, represented by the weekly unemployment insurance claims in the two states, exhibited different spreading and recovery rates, most likely due to their different exposures and responses to the pandemic. Therefore, COVID-19 spreading dynamics exhibited strong and subtly different spatiotemporal memories in rural and urban areas in the Alabama and New York States, motivating the application of FDMs.
机译：Covid-19 Pandemase在2012年29日爆发后一直影响美国（美国），并理解其动态对于大流行缓解和经济复苏至关重要。本研究提出并应用了新型时间分数衍生模型（FDMS），以量化阿拉巴马州和纽约，美国两国州的Covid-19大流行蔓延的时空动态，具有相当不同的人口组成，城市化和行业结构。模型申请表明，两国的大流行演变呈现了一个整体类似的时间依赖趋势，传播率的微妙差异。阿拉巴马州可能在农村地区拥有更多的县间通信，而纽约州的对立面可能是正确的。使用空间FDM的进一步分析表明，通过追随不同指标的钢化稳定密度分布，康复稳定密度分布的农村/城市地区的Covid-19大流行蔓延，而州大流行震中的人数影响了Covid-19的模式流行蔓延在太空中。最后，新型时间FDM的应用透露，经济的演变，由两国每周失业保险索赔所代表，呈现出不同的传播和恢复率，最有可能由于其不同的暴露和对大流行的回应而造成的。因此，Covid-19传播动态在阿拉巴马州和纽约州的农村和城市地区发表了强大且巧妙的时空存储，激励了FDMS的应用。

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