Author: Charles C Branas; Andrew Rundle; Sen Pei; Wan Yang; Brendan G Carr; Sarah Sims; Alexis Zebrowski; Ronan Doorley; Neil Schluger; James W Quinn; Jeffrey Shaman
Title: Flattening the curve before it flattens us: hospital critical care capacity limits and mortality from novel coronavirus (SARS-CoV2) cases in US counties Document date: 2020_4_6
ID: b23301ac_5
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.01.20049759 doi: medRxiv preprint considering both their population size and proximity to metropolitan areas. In doing this it provides useful added information over and above simple categorizing of counties on the basis of population size, land area, proximity to metropolitan areas, or population density, as singular variables. 15, 16 Va.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.01.20049759 doi: medRxiv preprint considering both their population size and proximity to metropolitan areas. In doing this it provides useful added information over and above simple categorizing of counties on the basis of population size, land area, proximity to metropolitan areas, or population density, as singular variables. 15, 16 Various estimated parameters of spatio-temporal COVID-19 demand and medical system critical care supply were then calculated for all continental US counties. These estimates were then statistically summarized and mapped for US counties, regions and urban versus non-urban areas. Geographic Information Systems software, ArcGIS Pro 2.5 (ESRI Inc., 2020, Redlands, CA), was used to manage analytic polygons and create maps.
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