Evidence map›Paper›PMID 36400812›Full record

ArticleScientific data2022

High-resolution estimates of social distancing feasibility, mapped for urban areas in sub-Saharan Africa.

Heather R Chamberlain, Attila N Lazar, Andrew J Tatem

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Advances in small area population estimation in the absence of national census data.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Heather R ChamberlainWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK. h.chamberlain@soton.ac.uk.ORCID 0000-0003-0828-6974
Attila N LazarWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.ORCID 0000-0003-2033-2013
Andrew J TatemWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.ORCID 0000-0002-7270-941X

Funding

Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation) OPP1182425Bill & Melinda Gates Foundation INV-009579Bill & Melinda Gates Foundation INV-018067
6 · The paper itself

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.

Indexed as

COVID-19Physical DistancingFeasibility StudiesHumansPandemicsPublic Health

Identifiers

PMID36400812
PMCPMC9673897

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.