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Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

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  • Additional Information
    • Publication Information:
      Elsevier
    • Publication Date:
      2021
    • Collection:
      University of Hull: Repository@Hull
    • Abstract:
      Background: Population characteristics can be used to infer vulnerability of communities to COVID-19, or to the likelihood of high levels of vaccine hesitancy. Communities harder hit by the virus, or at risk of being so, stand to benefit from greater resource allocation than their population size alone would suggest. This study reports a simple but efficacious method of ranking small areas of England by relative characteristics that are linked with COVID-19 vulnerability and vaccine hesitancy. Methods: Publicly available data on a range of characteristics previously linked with either poor COVID-19 outcomes or vaccine hesitancy were collated for all Middle Super Output Areas of England (MSOA, n=6790, excluding Isles of Scilly), scaled and combined into two numeric indices. Multivariable linear regression was used to build a parsimonious model of vulnerability (static socio-ecological vulnerability index, SEVI) in 60% of MSOAs, and retained variables were used to construct two simple indices. Assuming a monotonic relationship between indices and outcomes, Spearman correlation coefficients were calculated between the SEVI and cumulative COVID-19 case rates at MSOA level in the remaining 40% of MSOAs over periods both during and out with national lockdowns. Similarly, a novel vaccine hesitancy index (VHI) was constructed using population characteristics aligned with factors identified by an Office for National Statistics (ONS) survey analysis. The relationship between the VHI and vaccine coverage in people aged 12+years (as of 2021-06-24) was determined using Spearman correlation. The indices were split into quintiles, and MSOAs within the highest vulnerability and vaccine hesitancy quintiles were mapped. Findings: The SEVI showed a moderate to strong relationship with case rates in the validation dataset across the whole study period, and for every intervening period studied except early in the pandemic when testing was highly selective. The SEVI was more strongly correlated with case rates than any of its domains ...
    • Relation:
      https://hull-repository.worktribe.com/output/4450995; The Lancet Regional Health - Europe; Volume 14; https://hull-repository.worktribe.com/file/4450995/1/Published%20article
    • Accession Number:
      10.1016/j.lanepe.2021.100296
    • Online Access:
      https://hull-repository.worktribe.com/file/4450995/1/Published%20article
      https://hull-repository.worktribe.com/output/4450995
      https://doi.org/10.1016/j.lanepe.2021.100296
    • Rights:
      openAccess ; https://creativecommons.org/licenses/by-nc-nd/4.0/
    • Accession Number:
      edsbas.BEBB59FA