About: A spatial analysis of COVID-19 period prevalence in US counties through June 28, 2020: Where geography matters?

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A spatial analysis of COVID-19 period prevalence in US counties through June 28, 2020: Where geography matters?
Creator	Matthews, Stephen Clinical, Hu, Ming-Hsiao Sun, Feinuo Yang, Tse-Chuan
Source	Elsevier; Medline; PMC
abstract	PURPOSE: This study aims to understand how spatial structures, the interconnections between counties, matter in understanding COVID-19 period prevalence across the US. METHODS: We assemble a county-level dataset that contains COVID-19 confirmed cases through June 28, 2020 and various sociodemographic measures from multiple sources. In addition to an aspatial regression model, we conduct spatial lag, spatial error, and spatial autoregressive combined models to systematically examine the role of spatial structure in shaping geographical disparities in COVID-19 period prevalence. RESULTS: The aspatial ordinary least squares regression model tends to overestimate the COVID-19 period prevalence among counties with low observed rates, but this issue can be effectively addressed by spatial modeling. Spatial models can better estimate the period prevalence for counties, especially along the Atlantic coasts and through the Black Belt. Overall, the model fit among counties along both coasts is generally good with little variability evident, but in the Plain states, model fit is conspicuous in its heterogeneity across counties. CONCLUSIONS: Spatial models can help partially explain the geographic disparities in COVID-19 period prevalence. These models reveal spatial variability in model fit including identifying regions of the country where fit is heterogeneous and worth closer attention in the immediate short term.
has issue date	2020-07-28(xsd:dateTime)
bibo:doi	10.1016/j.annepidem.2020.07.014
bibo:pmid	32736059
has license	no-cc
sha1sum (hex)	14f67b5a1fd17a242532cf8f0bf6641478f8abb0
schema:url	https://doi.org/10.1016/j.annepidem.2020.07.014
resource representing a document's title	A spatial analysis of COVID-19 period prevalence in US counties through June 28, 2020: Where geography matters?
has PubMed Central identifier	PMC7386391
has PubMed identifier	32736059
schema:publication	Ann Epidemiol
resource representing a document's body	covid:14f67b5a1fd17a242532cf8f0bf6641478f8abb0#body_text
is schema:about of	named entity 'period prevalence' named entity 'GIS data' named entity 'COVID-19' named entity 'COVID-19' named entity '0.45' named entity 'explanatory variables' named entity 'population density' named entity 'period prevalence' named entity 'dependent variable' named entity 'Texas' named entity 'Public health' named entity 'socioeconomic' named entity 'asymptomatic' named entity 'infectious diseases' named entity 'OLS' named entity 'Mexico' named entity 'Idaho' named entity 'error term' named entity 'average life expectancy' named entity 'Binomial distribution' named entity 'reference group' named entity 'life expectancy' named entity 'period prevalence' named entity 'infectious disease' named entity 'variance' named entity 'COVID-19' named entity 'non-random' named entity 'COVID-19' named entity 'King county' named entity 'Nebraska' named entity 'infectious disease' named entity 'COVID-19' named entity 'period prevalence' named entity 'Great Plains' named entity 'COVID-19' named entity 'period prevalence' named entity 'infection' named entity 'COVID-19 pandemic' named entity 'decision-making' named entity 'service provisioning' named entity 'Population density' named entity 'Wyoming' named entity 'non-significant' named entity 'COVID-19' named entity 'dissimilarity index' named entity 'Descriptive statistics' named entity 'CHRR' named entity 'COVID-19' named entity 'Native Americans' named entity 'life expectancy' named entity 'social distancing' named entity 'health professional' named entity 'HPSA' named entity 'reported cases' named entity 'period prevalence' named entity 'Montana' named entity 'OLS' named entity 'social science research' named entity 'explanatory variables' named entity 'period prevalence' named entity 'Native Americans' named entity 'public health' named entity 'spatial models' named entity '0.51' named entity 'spatial dependence' named entity 'contextual variables' named entity 'life expectancy' named entity 'virus' named entity 'Appalachia' named entity 'period prevalence' named entity 'Sensitivity analysis' named entity 'OLS' named entity 'PCA' named entity 'socioeconomic' named entity 'OLS' named entity 'Decision makers' named entity 'Level of significance'

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