Estimating and explaining the spread of COVID-19 at the county level in the USA.
Estimating and explaining the spread of COVID-19 at the county level in the USA.
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DOI：
10.1038/s42003-020-01609-6
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发表时间：
2021-01-05
影响因子：
5.9
通讯作者：
Bozzuto C
中科院分区：
文献类型：
--
作者：
Ives AR;Bozzuto C
基本繁殖数R0决定了传染病的传播速度，因此提供了规划公共卫生干预措施所需的基本信息。利用死亡率记录，我们估计了疫情开始时美国160个县和县总数中COVID-19的传播速度。我们发现，大多数县间差异高的原因是四个因素（R2 = 0.70）：爆发时间、人口规模、人口密度和空间位置。对于未来传播的预测，人口密度和空间位置是重要的，对于后者，我们表明含有刺突基因G614突变的SARS-CoV-2菌株与更高的传播率相关。最后，R0的高可预测性允许将估计扩展到相邻48个州的所有3109个县。R0的高变化证明了在县一级制定控制COVID-19的公共卫生政策。Ives和Bozzuto在疫情开始时估计了COVID-19在美国的传播率，推断了3109个县在采取措施减少传播之前的R0值。县级R0预测值的差异主要与人口密度和空间位置有关，不同地点的差异与不同SARS-CoV-2病毒株的差异有关。
The basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA at the start of the epidemic. We show that most of the high among-county variance is explained by four factors (R2 = 0.70): the timing of outbreak, population size, population density, and spatial location. For predictions of future spread, population density and spatial location are important, and for the latter we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread. Finally, the high predictability of R0 allows extending estimates to all 3109 counties in the conterminous 48 states. The high variation of R0 argues for public health policies enacted at the county level for controlling COVID-19. Ives and Bozzuto estimate the spread rate of COVID-19 in the USA at the start of the epidemic, extrapolating values of R0 for 3109 counties during the period before measures were taken to reduce the spread. Most of predictive variation in county-level values of R0 is explained by population density and spatial location, with differences among locations associated with differences among strains of SARS-CoV-2.
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影响因子：
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DOI：
10.1073/pnas.0307506101
发表时间：
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影响因子：
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