ArticleThe Lancet regional health. Europe2022
Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England.
Article in The Lancet regional health. Europe, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Spillover between influenza and COVID-19 vaccination behaviors across pandemic phases and implications for general vaccine hesitancy.NPJ vaccines · 2026Article
- Social Vulnerability and Compliance With World Health Organization Advice on Protective Behaviors Against COVID-19 in African and Asia Pacific Countries: Factor Analysis to Develop a Social Vulnerability Index.JMIR public health and surveillance · 2024Article
- An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI).BMC public health · 2023Article
- Development of a COVID-19 Vulnerability Index (CVI) for the Counties and Residents of New Jersey, USA.International journal of environmental research and public health · 2023Article
- Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska.BMJ global health · 2023Review
- Uncovering COVID-19 infection determinants in Portugal: towards an evidence-based spatial susceptibility index to support epidemiological containment policies.International journal of health geographics · 2023Article
- Data driven contagion risk management in low-income countries using machine learning applications with COVID-19 in South Asia.Scientific reports · 2023Article
- Undergraduate Vaccine Hesitancy and the Influence of "Home" Locales.International journal of environmental research and public health · 2022Article
- Social vulnerability indices: A pragmatic tool for COVID-19 policy and beyond.The Lancet regional health. Europe · 2022Article
- Social vulnerability amplifies the disparate impact of mobility on COVID-19 transmissibility across the United States.Humanities & social sciences communications · 2022Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPopulation 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.
methodsPublicly 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.
findingsThe 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 (
interpretationThe indices presented offer an efficacious way of identifying geographical disparities in COVID-19 risk, thus helping focus resources according to need.
fundingFunder: Integrated Covid Hub North East. AWARD NUMBER: n/a. GRANT RECIPIENT: Fiona Matthews.
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