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A vulnerability index for COVID-19: spatial analysis at the subnational level in Kenya
  1. Peter M Macharia1,
  2. Noel K Joseph1,
  3. Emelda A Okiro1,2
  1. 1 Population Health Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya
  2. 2 Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
  1. Correspondence to Peter M Macharia; pmacharia{at}kemri-wellcome.org

Abstract

Background Response 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.

Methods Geospatial 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.

Results The 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.

Conclusion The 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.

  • public health
  • indices of health and disease and standardisation of rates
  • geographic information systems
  • epidemiology
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This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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Footnotes

  • PMM and NKJ are joint first authors.

  • Handling editor Seye Abimbola

  • Twitter @Pete_M_M

  • Contributors All authors contributed to the development of the project, analysis, interpretation of the study findings and writing of the manuscript. All authors read and approved the final manuscript.

  • Funding PMM is funded under the IDeAL’s Project, DELTAS Africa Initiative [DEL-15-003]. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)'s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa's Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust [number 107769/Z/10/Z] and the UK government. PMM is also supported by funds provided under Professor RW Snow’s Wellcome Trust Principal Fellowship (numbers’ 103602 & 212176). EAO is supported as Wellcome Trust Intermediate Fellow (number 201866) that provided support for NJK; NJK, PMM and EAO, acknowledge the support of the Wellcome Trust to the Kenya Major Overseas Programme (number 203077). The views expressed in this publication are those of the authors and not necessarily those of AAS, NEPAD Agency, Wellcome Trust or the UK government. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available in a public, open access repository. All data and links (table1) relevant to the study are included in the article or uploaded as supplementary information. The digitised shapefile can be accessed at https://doi.org/10.6084/m9.figshare.12501455.v1

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