ArticleTransboundary and emerging diseases2022
Exploring the risk factors of COVID-19 Delta variant in the United States based on Bayesian spatio-temporal analysis.
Article in Transboundary and emerging diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Respiratory viral infections: when and where? A scoping review of spatiotemporal methods.Journal of global health · 2025Article
- Article
- Bayesian spatio-temporal analysis of the COVID-19 pandemic in Catalonia.Scientific reports · 2024Article
- Exploring the risk factors of COVID-19 Delta variant in the United States based on Bayesian spatio-temporal analysis.Transboundary and emerging diseases · 2022Article
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Authors and funding
8 authors.
Funding
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. The method enables us to cluster the states into distinctive groups based on the temporal trends of the coefficients and simultaneously identify significant risk factors for each cluster. The findings contribute novel insight into the dynamics of covariate effects on the COVID-19 Delta variant over space and time, which could help the government develop targeted prevention measures for vulnerable regions based on the selected risk factors.
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