ArticleBMJ global health2020
A vulnerability index for COVID-19: spatial analysis at the subnational level in Kenya.
Article in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it, 96 citations in OpenAlex.
- Pooled it
- Historic drought in northern Kenya shifts diet and mobility away from traditional pastoralism as resource security and nutrition falter.Global environmental change : human and policy dimensions · 2026Article
- Rethinking the evidence on COVID-19 in Africa.The Lancet. Infectious diseases · 2025Review
- Precision public health after Covid-19: a scoping review.International journal for equity in health · 2025Article
- Spatial Analysis of Tuberculosis, COVID-19, and Tuberculosis/COVID-19 Coinfection in Recife, PE, Brazil.International journal of environmental research and public health · 2025Article
- The refugees and health crisis: migration policy management and government response to Afghan migrants.BMC health services research · 2025Article
- Mapping Community Vulnerability to reduced Vaccine Impact in Uganda and Kenya: A spatial Data-driven Approach.NIHR open research · 2025Article
- Social vulnerability index associated with higher COVID-19 seroprevalence in Nigeria.Global health action · 2024Article
- Global research landscape of health care-associated infections among immunocompromised people before and after the start of the COVID-19 pandemic.Infectious medicine · 2024Review
- 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
- Mapping Vulnerability to Potential Crisis Events in Surabaya City: A GIS-Based Approach.F1000Research · 2024Article
- Socio-Economic and Demographic Factors Associated with the Spatial Distribution of COVID-19 in Africa.Journal of racial and ethnic health disparities · 2023Article
- 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
- Preparing for the next outbreak: A review of indices measuring outbreak preparedness, vulnerability, and resilience.Preventive medicine reports · 2023Review
- 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
- Analyzing COVID-19 data in the Canadian province of Manitoba: A new approach.Spatial statistics · 2023Article
- 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
- The shortfalls of vulnerability indexes for public health decision-making in the face of emergent crises: the case of COVID-19 vaccine uptake in Virginia.Frontiers in public health · 2023Article
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Corrections and comments
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundResponse to the coronavirus disease 2019 (COVID-19) pandemic calls for precision public health reflecting our improved understanding of who is the most vulnerable and their geographical location. We created three vulnerability indices to identify areas and people who require greater support while elucidating health inequities to inform emergency response in Kenya.
methodsGeospatial indicators were assembled to create three vulnerability indices; Social VulnerabilityIndex (SVI), Epidemiological Vulnerability Index (EVI) and a composite of the two, that is, Social Epidemiological Vulnerability Index (SEVI) resolved at 295 subcounties in Kenya. SVI included 19 indicators that affect the spread of disease; socioeconomic deprivation, access to services and population dynamics, whereas EVI comprised 5 indicators describing comorbidities associated with COVID-19 severe disease progression. The indicators were scaled to a common measurement scale, spatially overlaid via arithmetic mean and equally weighted. The indices were classified into seven classes, 1-2 denoted low vulnerability and 6-7, high vulnerability. The population within vulnerabilities classes was quantified.
resultsThe spatial variation of each index was heterogeneous across Kenya. Forty-nine northwestern and partly eastern subcounties (6.9 million people) were highly vulnerable, whereas 58 subcounties (9.7 million people) in western and central Kenya were the least vulnerable for SVI. For EVI, 48 subcounties (7.2 million people) in central and the adjacent areas and 81 subcounties (13.2 million people) in northern Kenya were the most and least vulnerable, respectively. Overall (SEVI), 46 subcounties (7.0 million people) around central and southeastern were more vulnerable, whereas 81 subcounties (14.4 million people) were least vulnerable.
conclusionThe vulnerability indices created are tools relevant to the county, national government and stakeholders for prioritisation and improved planning. The heterogeneous nature of the vulnerability indices underpins the need for targeted and prioritised actions based on the needs across the subcounties.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.