Evidence map›Paper›PMID 32743597›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Mapping physical access to healthcare for older adults in sub-Saharan Africa: A cross-sectional analysis with implications for the COVID-19 response.

Pascal Geldsetzer, Marcel Reinmuth, Paul O Ouma, Sven Lautenbach, Emelda A Okiro, Till Bärnighausen, Alexander Zipf

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Pascal GeldsetzerDivision of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA, USA.
Marcel ReinmuthInstitute of Geography, Heidelberg University, Heidelberg, Germany.
Paul O OumaPopulation Health Unit, Kenya Medical Research Institute (MFL)-Wellcome Trust Research Programme, Nairobi, Kenya.
Sven LautenbachHeiGIT at Heidelberg University, Heidelberg, Germany.
Emelda A OkiroPopulation Health Unit, Kenya Medical Research Institute (MFL)-Wellcome Trust Research Programme, Nairobi, Kenya.
Till BärnighausenDivision of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA, USA.
Alexander ZipfInstitute of Geography, Heidelberg University, Heidelberg, Germany.

Funding

Institutional Career Development Core (KL2)KL2TR003143 · NCATS · STANFORD UNIVERSITY · PI ASCH, STEVEN M. · 2019 to 2023
$8.7M
EPA EP-C-15-003NCATS NIH HHS KL2 TR003143Wellcome Trust 201866/Z/16/Z
6 · The paper itself

Abstract

Background: SARS-CoV-2, the virus causing coronavirus disease 2019 (COVID-19), is rapidly spreading across sub-Saharan Africa (SSA). Hospital-based care for COVID-19 is particularly often needed among older adults. However, a key barrier to accessing hospital care in SSA is travel time to the healthcare facility. To inform the geographic targeting of additional healthcare resources, this study aimed to determine the estimated travel time at a 1km × 1km resolution to the nearest hospital and to the nearest healthcare facility of any type for adults aged 60 years and older in SSA. Methods: We assembled a unique dataset on healthcare facilities' geolocation, separately for hospitals and any type of healthcare facility (including primary care facilities) and including both private- and public-sector facilities, using data from the OpenStreetMap project and the KEMRI Wellcome Trust Programme. Population data at a 1km × 1km resolution was obtained from WorldPop. We estimated travel time to the nearest healthcare facility for each 1km × 1km grid using a cost-distance algorithm. Findings: 9.6% (95% CI: 5.2% - 16.9%) of adults aged ≥60 years had an estimated travel time to the nearest hospital of longer than six hours, varying from 0.0% (95% CI: 0.0% - 3.7%) in Burundi and The Gambia, to 40.9% (95% CI: 31.8% - 50.7%) in Sudan. 11.2% (95% CI: 6.4% - 18.9%) of adults aged ≥60 years had an estimated travel time to the nearest healthcare facility of any type (whether primary or secondary/tertiary care) of longer than three hours, with a range of 0.1% (95% CI: 0.0% - 3.8%) in Burundi to 55.5% (95% CI: 52.8% - 64.9%) in Sudan. Most countries in SSA contained populated areas in which adults aged 60 years and older had a travel time to the nearest hospital of more than 12 hours and to the nearest healthcare facility of any type of more than six hours. The median travel time to the nearest hospital for the fifth of adults aged ≥60 years with the longest travel times was 348 minutes (equal to 5.8 hours; IQR: 240 - 576 minutes) for the entire SSA population, ranging from 41 minutes (IQR: 34 - 54 minutes) in Burundi to 1,655 minutes (equal to 27.6 hours; IQR: 1065 - 2440 minutes) in Gabon. Interpretation: Our high-resolution maps of estimated travel times to both hospitals and healthcare facilities of any type can be used by policymakers and non-governmental organizations to help target additional healthcare resources, such as new make-shift hospitals or transport programs to existing healthcare facilities, to older adults with the least physical access to care. In addition, this analysis shows precisely where population groups are located that are particularly likely to under-report COVID-19 symptoms because of low physical access to healthcare facilities. Beyond the COVID-19 response, this study can inform countries' efforts to improve care for conditions that are common among older adults, such as chronic non-communicable diseases.

Identifiers

PMID32743597
PMCPMC7386521

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.