Space-Time Cluster's Detection and Geographical Weighted Regression Analysis of COVID-19 Mortality on Texas Counties.
Int J Environ Res Public Health
; 18(11)2021 May 22.
Article
em En
| MEDLINE
| ID: mdl-34067291
ABSTRACT
As COVID-19 run rampant in high-density housing sites, it is important to use real-time data in tracking the virus mobility. Emerging cluster detection analysis is a precise way of blunting the spread of COVID-19 as quickly as possible and save lives. To track compliable mobility of COVID-19 on a spatial-temporal scale, this research appropriately analyzed the disparities between spatial-temporal clusters, expectation maximization clustering (EM), and hierarchical clustering (HC) analysis on Texas county-level. Then, based on the outcome of clustering analysis, the sensitive counties are Cottle, Stonewall, Bexar, Tarrant, Dallas, Harris, Jim hogg, and Real, corresponding to Southeast Texas analysis in Geographically Weighted Regression (GWR) modeling. The sensitive period took place in the last two quarters in 2020 and the first quarter in 2021. We explored PostSQL application to portray tracking Covid-19 trajectory. We captured 14 social, economic, and environmental impact's indices to perform principal component analysis (PCA) to reduce dimensionality and minimize multicollinearity. By using the PCA, we extracted five factors related to mortality of COVID-19, involved population and hospitalization, adult population, natural supply, economic condition, air quality or medical care. We established the GWR model to seek the sensitive factors. The result shows that adult population, economic condition, air quality, and medical care are the sensitive factors. Those factors also triggered high increase of COVID-19 mortality. This research provides geographical understanding and solution of controlling COVID-19, reference of implementing geographically targeted ways to track virus mobility, and satisfy for the need of emergency operations plan (EOP).
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
4_TD
/
6_ODS3_enfermedades_notrasmisibles
Base de dados:
MEDLINE
Assunto principal:
COVID-19
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Adult
/
Humans
País/Região como assunto:
America do norte
Idioma:
En
Revista:
Int J Environ Res Public Health
Ano de publicação:
2021
Tipo de documento:
Article