Exploring the risk factors of COVID-19 Delta variant in the United States based on Bayesian spatio-temporal analysis.

ABSTRACT: The transmission of coronavirus disease-2019 (COVID-19) epidemic is a global emergency, which is worsened by the genetic mutations of SARS-CoV-2. However, till date, few statistical studies have researched the COVID-19 spread patterns in terms of the variant cases. Hence, this paper aims to explore the associated risk factors of Delta variant, the most contagious strain of COVID-19. The study collected the state-level COVID-19 Delta variant cases in the United States during a 12-week period and included potential environmental, socioeconomic, and public prevention factors as independent variables. Instead of regarding the covariate effects as constant, this paper proposes a flexible Bayesian hierarchical model with spatio-temporally varying coefficients to account for data heterogeneity. T

SUBMITTER: Ma S 

PROVIDER: S-EPMC9349916 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature