Applying a Bayesian spatiotemporal model to examine excess county-level cardiovascular disease death rates during the COVID-19 pandemic.
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| Title: | Applying a Bayesian spatiotemporal model to examine excess county-level cardiovascular disease death rates during the COVID-19 pandemic. |
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| Authors: | Vaughan, Adam S1, Quick, Harrison2, Beck, Kara B1,3, Woodruff, Rebecca C1, DeLara, David1, Casper, Michele1 |
| Source: | American Journal of Epidemiology. Jun2025, Vol. 194 Issue 6, p1556-1565. 10p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 186054359 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=186054359 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/aje/kwae330 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 1556 Titles: – TitleFull: Applying a Bayesian spatiotemporal model to examine excess county-level cardiovascular disease death rates during the COVID-19 pandemic. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Vaughan, Adam S – PersonEntity: Name: NameFull: Quick, Harrison – PersonEntity: Name: NameFull: Beck, Kara B – PersonEntity: Name: NameFull: Woodruff, Rebecca C – PersonEntity: Name: NameFull: DeLara, David – PersonEntity: Name: NameFull: Casper, Michele IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00029262 Numbering: – Type: volume Value: 194 – Type: issue Value: 6 Titles: – TitleFull: American Journal of Epidemiology Type: main |
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