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Population-Based Denominators Matter: Bias in U.S. Virgin Islands COVID-19 Vaccination Coverage Under Changing Population Counts

Supporting Files
File Language:
English


Details

  • Alternative Title:
    Ann Epidemiol
  • Personal Author:
  • Description:
    Purpose:

    The U.S. Virgin Islands (USVI) receives an updated population count once every 10 years and used 2010 decennial census population counts to estimate COVID-19 vaccination coverage during the COVID-19 emergency response. We investigated whether using outdated (2010) or modeled (2020 international database [IDB]) population counts biased vaccination coverage estimates used to inform public health priorities during the 2020–2022 COVID-19 response.

    Methods:

    We estimated percentage of USVI residents with a completed primary COVID-19 vaccination series during December 16, 2020–September 20, 2022. Vaccination coverage was calculated as number of persons who completed the vaccination series divided by 2010 and 2020 decennial census population counts and 2020 IDB intercensal estimate.

    Results:

    COVID-19 vaccination coverage using the 2020 population count was 12 percentage points higher than coverage using 2010 denominator (2010 denominator: 51%; 2020 denominator: 63%). Vaccination coverage estimated using 2020 IDB was approximately equal with the 2010 decennial census estimate (52%).

    Conclusions:

    Using 2010 and modeled population counts underestimated 2020 USVI COVID-19 vaccination coverage given the 18% population decline during 2010–2020, potentially limiting USVI’s ability to assess vaccination progress. Identifying mechanisms for more reliable population enumeration or improved estimate modeling are essential for accurately guiding USVI public health decision-making.

  • Subjects:
  • Source:
    Ann Epidemiol. 95:1-5
  • Pubmed ID:
    38740077
  • Pubmed Central ID:
    PMC11235870
  • Document Type:
  • Funding:
  • Volume:
    95
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:512b00b1e54bca48b4545f326bbe400595aa8cce5c70ec68b3b58742136d2fd956ab20f6c7e7e2e7ee1292a6bba648556e8db861fdb234dd1c354f092b7e4143
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  • File Type:
    Filetype[PDF - 186.90 KB ]
File Language:
English
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