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Geostatistical Analysis of SARS-CoV-2 in the United States

Authors: Peter K Rogan;

Geostatistical Analysis of SARS-CoV-2 in the United States

Abstract

Geostatistics analyzes and predicts the values associated with spatial or spatio-temporal phenomena. It incorporates the spatial (and in some cases temporal) coordinates of the data within the analyses. It is a practical means of describing spatial patterns and interpolating values for locations where samples were not taken (and measures the uncertainty of those values, which is critical to informed decision making). This Zenodo archive consists of two archives consisting of geostatistical analyses of SARS-CoV-2 testing data: 1. "Louisiana-SARS-CoV-2-Geostatistical-Analysis.zip": Geostatistical analysis of SARS-CoV-2 cases across Louisiana in March and early April 2020. 2. "Entire-US-SARS-CoV-2-Geostatistical-Analysis.zip": Geostatistical analysis of SARS-CoV-2 cases across the entire U.S. during the month of May 2020, with additional analyses covering SARS-CoV-2 cases from March 24th to June 10th 2020. These archives consist of map files (as both static images and as animations) and data files (including text files which contain the underlying data of said map files [where applicable]) which were generated when performing the following Geostatistical analyses: Hot Spot analysis (Getis-Ord Gi*), Cluster and Outlier analysis (Anselin Local Moran's I), Kriging and Densification analysis (Louisiana only), and Spatial Autocorrelation (Global Moran's I; United States only). The Word document ("Description-of-Archive.Geostatistical-Analysis-of-SARS-CoV-2.docx") describes in detail the contents of each file and folder within these two archives.

Keywords

SARS-CoV-2, COVID-19, Geostatistics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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