Mapping urban physical distancing constraints, sub-Saharan Africa: a case study from Kenya
Mapping urban physical distancing constraints, sub-Saharan Africa: a case study from Kenya
With the onset of the coronavirus disease 2019 (COVID-19) pandemic, public health measures such as physical distancing were recommended to reduce transmission of the virus causing the disease. However, the same approach in all areas, regardless of context, may lead to measures being of limited effectiveness and having unforeseen negative consequences, such as loss of livelihoods and food insecurity. A prerequisite to planning and implementing effective, context-appropriate measures to slow community transmission is an understanding of any constraints, such as the locations where physical distancing would not be possible. Focusing on sub-Saharan Africa, we outline and discuss challenges that are faced by residents of urban informal settlements in the ongoing COVID-19 pandemic. We describe how new geospatial data sets can be integrated to provide more detailed information about local constraints on physical distancing and can inform planning of alternative ways to reduce transmission of COVID-19 between people. We include a case study for Nairobi County, Kenya, with mapped outputs which illustrate the intra-urban variation in the feasibility of physical distancing and the expected difficulty for residents of many informal settlement areas. Our examples demonstrate the potential of new geospatial data sets to provide insights and support to policy-making for public health measures, including COVID-19.
COVID-19/epidemiology, Humans, Kenya/epidemiology, Pandemics/prevention & control, Physical Distancing, Policy Making
562-569
Chamberlain, Heather R.
cb939de7-ac47-440e-aeb8-a2e36c110785
Macharia, Peter M.
d59b1115-674a-4dc5-9148-da6aa06c85b6
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
1 September 2022
Chamberlain, Heather R.
cb939de7-ac47-440e-aeb8-a2e36c110785
Macharia, Peter M.
d59b1115-674a-4dc5-9148-da6aa06c85b6
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Chamberlain, Heather R., Macharia, Peter M. and Tatem, Andrew J.
(2022)
Mapping urban physical distancing constraints, sub-Saharan Africa: a case study from Kenya.
Bulletin of the World Health Organization, 100 (9), .
(doi:10.2471/BLT.21.287572).
Abstract
With the onset of the coronavirus disease 2019 (COVID-19) pandemic, public health measures such as physical distancing were recommended to reduce transmission of the virus causing the disease. However, the same approach in all areas, regardless of context, may lead to measures being of limited effectiveness and having unforeseen negative consequences, such as loss of livelihoods and food insecurity. A prerequisite to planning and implementing effective, context-appropriate measures to slow community transmission is an understanding of any constraints, such as the locations where physical distancing would not be possible. Focusing on sub-Saharan Africa, we outline and discuss challenges that are faced by residents of urban informal settlements in the ongoing COVID-19 pandemic. We describe how new geospatial data sets can be integrated to provide more detailed information about local constraints on physical distancing and can inform planning of alternative ways to reduce transmission of COVID-19 between people. We include a case study for Nairobi County, Kenya, with mapped outputs which illustrate the intra-urban variation in the feasibility of physical distancing and the expected difficulty for residents of many informal settlement areas. Our examples demonstrate the potential of new geospatial data sets to provide insights and support to policy-making for public health measures, including COVID-19.
Text
BLT.21.287572 (1)
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e-pub ahead of print date: 1 September 2022
Published date: 1 September 2022
Additional Information:
Funding Information:
PMM is also affiliated with the Centre for Health Informatics, Computing, and Statistics, Lancaster University, Lancaster, England. PMM is supported by the Newton International Fellow ship (#NIF/R1/201418) of the Royal Society and acknowledges the support of the Wellcome Trust to the Kenya Major Overseas Programme (#203077). This work is part of the GRID3 project (Geo-Referenced Infrastructure and Demographic Data for Development), funded by the Bill & Melinda Gates Foundation and the United Kingdom Foreign, Commonwealth and Development Office (#INV009579: AJT, HRC). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund, the Center for International Earth Science Information Network in the Columbia Climate School at Columbia University and the Flowminder Foundation.
Funding Information:
PMM is also affiliated with the Centre for Health Informatics, Computing, and Statistics, Lancaster University, Lancaster, England. PMM is supported by the Newton International Fellow-ship (#NIF/R1/201418) of the Royal Society and acknowledges the support of the Wellcome Trust to the Kenya Major Overseas Programme (#203077). This work is part of the GRID3 project (Geo-Referenced Infrastructure and Demographic Data for Development), funded by the Bill & Melinda Gates Foundation and the United Kingdom Foreign, Commonwealth and Development Office (#INV009579: AJT, HRC). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund, the Center for International Earth Science Information Network in the Columbia Climate School at Columbia University and the Flowminder Foundation.
Publisher Copyright:
© 2022, World Health Organization. All rights reserved.
Keywords:
COVID-19/epidemiology, Humans, Kenya/epidemiology, Pandemics/prevention & control, Physical Distancing, Policy Making
Identifiers
Local EPrints ID: 470376
URI: http://eprints.soton.ac.uk/id/eprint/470376
ISSN: 0042-9686
PURE UUID: a1c154b3-1f9d-4448-8c90-94a36cc90e32
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Date deposited: 07 Oct 2022 16:34
Last modified: 17 Mar 2024 03:29
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Author:
Peter M. Macharia
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