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High-resolution estimates of social distancing feasibility, mapped for urban areas in sub-Saharan Africa.
Chamberlain, Heather R; Lazar, Attila N; Tatem, Andrew J.
  • Chamberlain HR; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK. h.chamberlain@soton.ac.uk.
  • Lazar AN; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
  • Tatem AJ; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
Sci Data ; 9(1): 711, 2022 11 18.
Article in English | MEDLINE | ID: covidwho-2133501
ABSTRACT
Social distancing has been widely-implemented as a public health measure during the COVID-19 pandemic. Despite widespread application of social distancing guidance, the feasibility of people adhering to such guidance varies in different settings, influenced by population density, the built environment and a range of socio-economic factors. Social distancing constraints however have only been identified and mapped for limited areas. Here, we present an ease of social distancing index, integrating metrics on urban form and population density derived from new multi-country building footprint datasets and gridded population estimates. The index dataset provides estimates of social distancing feasibility, mapped at high-resolution for urban areas across 50 countries in sub-Saharan Africa.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Physical Distancing / COVID-19 Limits: Humans Language: English Journal: Sci Data Year: 2022 Document Type: Article Affiliation country: S41597-022-01799-0

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Physical Distancing / COVID-19 Limits: Humans Language: English Journal: Sci Data Year: 2022 Document Type: Article Affiliation country: S41597-022-01799-0