Progression of COVID-19 From Urban to Rural Areas in the United States: A Spatiotemporal Analysis of Prevalence Rates
Progression of COVID-19 From Urban to Rural Areas in the United States: A Spatiotemporal Analysis of Prevalence Rates
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DOI：
10.1111/jrh.12486
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发表时间：
2020-06-30
影响因子：
4.9
通讯作者：
Han, Dan
中科院分区：
文献类型：
--
作者：
Paul, Rajib;Arif, Ahmed A.;Han, Dan
目的越来越多的迹象表明，新冠肺炎病毒已经开始向农村地区传播，并可能影响已经捉襟见肘和缺乏资源的农村医疗保健系统。为了帮助立法决策过程和适当的资源疏导，我们估计并比较了3周内按城乡状况划分的县级新冠肺炎患病率的变化。此外，我们根据估计的患病率确定了热点。方法使用新冠肺炎上的众包数据，将其与县级人口统计学、吸烟率和慢性病联系起来。我们在R-STUDIO中使用马尔可夫链蒙特卡罗算法对贝叶斯分层时空模型进行了拟合。我们使用ArcGIS10.8绘制了估计的患病率，并使用Gettis-Ord当地统计数据确定了热点。在农村县的调查结果显示，从2020年4月3日到4月22日的3周内，新冠肺炎的平均患病率从3.6/10万人口上升到43.6/10万人口。在城市县，新冠肺炎的患病率中位数在同一时期从10.1‰上升到107.6‰。新冠肺炎调整后的农村县患病率在黑人人口、吸烟率和肥胖率较高的县大幅上升。25-49岁人口比例高的县新冠肺炎患病率也有所上升。结论我们的研究结果显示，在21天内，新冠肺炎在城市和农村迅速传播。需要基于高质量数据的研究来进一步解释健康的社会决定因素对新冠肺炎流行率的作用。
Purpose There are growing signs that the COVID-19 virus has started to spread to rural areas and can impact the rural health care system that is already stretched and lacks resources. To aid in the legislative decision process and proper channelizing of resources, we estimated and compared the county-level change in prevalence rates of COVID-19 by rural-urban status over 3 weeks. Additionally, we identified hotspots based on estimated prevalence rates. Methods We used crowdsourced data on COVID-19 and linked them to county-level demographics, smoking rates, and chronic diseases. We fitted a Bayesian hierarchical spatiotemporal model using the Markov Chain Monte Carlo algorithm in R-studio. We mapped the estimated prevalence rates using ArcGIS 10.8, and identified hotspots using Gettis-Ord local statistics. Findings In the rural counties, the mean prevalence of COVID-19 increased from 3.6 per 100,000 population to 43.6 per 100,000 within 3 weeks from April 3 to April 22, 2020. In the urban counties, the median prevalence of COVID-19 increased from 10.1 per 100,000 population to 107.6 per 100,000 within the same period. The COVID-19 adjusted prevalence rates in rural counties were substantially elevated in counties with higher black populations, smoking rates, and obesity rates. Counties with high rates of people aged 25-49 years had increased COVID-19 prevalence rates. Conclusions Our findings show a rapid spread of COVID-19 across urban and rural areas in 21 days. Studies based on quality data are needed to explain further the role of social determinants of health on COVID-19 prevalence.