Evidence map›Paper›PMID 32161711›Full record

ArticleAfrican journal of emergency medicine : Revue africaine de la medecine d'urgence2020

Impact of traffic, poverty and facility ownership on travel time to emergency care in Nairobi, Kenya.

Maya S Fraser, Benjamin W Wachira, Abraham D Flaxman, Aaron Y Lee, Herbert C Duber

Abstract read
In one paragraph

Article in African journal of emergency medicine : Revue africaine de la medecine d'urgence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Emergency Services Capacity of a Rural Community in Guatemala.The western journal of emergency medicine · 2022
    Article
  7. Article
  8. 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

5 authors.

Maya S FraserInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Benjamin W WachiraAccident & Emergency Department, The Aga Khan University, Nairobi, Kenya.
Abraham D FlaxmanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Aaron Y LeeDepartment of Ophthalmology, University of Washington, Seattle, WA, USA.
Herbert C DuberInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Funding

Epidemiology and clinical outcomes of diabetic macular edemaK23EY029246 · NEI · UNIVERSITY OF WASHINGTON · PI LEE, AARON · 2018 to 2022
$1.1M
6 · The paper itself

Abstract

backgroundIn many low and middle-income countries (LMICs), timely access to emergency healthcare services is limited. In urban settings, traffic can have a significant impact on travel time, leading to life-threatening delays for time-sensitive injuries and medical emergencies. In this study, we examined travel times to hospitals in Nairobi, Kenya, one of the largest and most congested cities in the developing world.

methodsWe used a network approach to estimate average minimum travel times to different types of hospitals (e.g. ownership and level of care) in Nairobi under both congested and uncongested traffic conditions. We also examined the correlation between travel time and socioeconomic status.

resultsWe estimate the average minimum travel time during uncongested traffic conditions to any level 4 health facility (primary hospitals) or above in Nairobi to be 4.5 min (IQR 2.5-6.1). Traffic added an average of 9.0 min (a 200% increase). In uncongested conditions, we estimate an average travel time of 7.9 min (IQR 5.1-10.4) to level 5 facilities (secondary hospitals) and 11.6 min (IQR 8.5-14.2) to Kenyatta National Hospital, the only level 6 facility (tertiary hospital) in the country. Traffic congestion added an average of 13.1 and 16.0 min (166% and 138% increase) to travel times to level 5 and level 6 facilities, respectively. For individuals living below the poverty line, we estimate that preferential use of public or faith-based facilities could increase travel time by as much as 65%.

conclusionAverage travel times to health facilities capable of providing emergency care in Nairobi are quite low, but traffic congestion double or triple estimated travel times. Furthermore, we estimate significant disparities in timely access to care for those individuals living under the poverty line who preferentially seek care in public or faith-based facilities.

Indexed as

Emergency careKenyaPovertyTraffic

Identifiers

PMID32161711
PMCPMC7058857

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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.