Evidence map›Paper›PMID 31888667›Full record

ArticleBMC medicine2019

Travel time to health facilities in areas of outbreak potential: maps for guiding local preparedness and response.

E N Hulland, K E Wiens, S Shirude, J D Morgan, A Bertozzi-Villa, T H Farag, N Fullman, M U G Kraemer, M K Miller-Petrie, V Gupta and 7 more

Abstract read
In one paragraph

Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
  2. Urban-Rural Disparities in Geographic Healthcare Accessibility: A Comparative Study of Nigeria and Zambia.Journal of urban health : bulletin of the New York Academy of Medicine · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Dengue Treatment-Seeking Behavior: A Qualitative Study With Costa Rican Residents.Health education & behavior : the official publication of the Society for Public Health Education · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak.International journal of environmental research and public health · 2023
    Article
  11. Article
  12. Observational
  13. Article
  14. Spatial Variability of COVID-19 Hospitalization in the Silesian Region, Poland.International journal of environmental research and public health · 2022
    Article
  15. Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment.International journal of environmental research and public health · 2022
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

17 authors.

E N HullandInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
K E WiensInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
S ShirudeInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
J D MorganInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
A Bertozzi-VillaMalaria Atlas Project, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK.
T H FaragInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
N FullmanInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
M U G KraemerDepartment of Zoology, University of Oxford, Oxford, UK.
M K Miller-PetrieInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
V GuptaInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
R C ReinerInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
P RabinowitzDepartment of Global Health, University of Washington, Seattle, WA, 98195, USA.
J N WasserheitDepartment of Global Health, University of Washington, Seattle, WA, 98195, USA.
B P BellDepartment of Global Health, University of Washington, Seattle, WA, 98195, USA.
S I HayInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA.
D J WeissMalaria Atlas Project, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK.
D M PigottInstitute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA, 98121, USA. pigottdm@uw.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRepeated outbreaks of emerging pathogens underscore the need for preparedness plans to prevent, detect, and respond. As countries develop and improve National Action Plans for Health Security, addressing subnational variation in preparedness is increasingly important. One facet of preparedness and mitigating disease transmission is health facility accessibility, linking infected persons with health systems and vice versa. Where potential patients can access care, local facilities must ensure they can appropriately diagnose, treat, and contain disease spread to prevent secondary transmission; where patients cannot readily access facilities, alternate plans must be developed. Here, we use travel time to link facilities and populations at risk of viral hemorrhagic fevers (VHFs) and identify spatial variation in these respective preparedness demands. METHODS AND

findingsWe used geospatial resources of travel friction, pathogen environmental suitability, and health facilities to determine facility accessibility of any at-risk location within a country. We considered in-country and cross-border movements of exposed populations and highlighted vulnerable populations where current facilities are inaccessible and new infrastructure would reduce travel times. We developed profiles for 43 African countries. Resulting maps demonstrate gaps in health facility accessibility and highlight facilities closest to areas at risk for VHF spillover. For instance, in the Central African Republic, we identified travel times of over 24 h to access a health facility. Some countries had more uniformly short travel times, such as Nigeria, although regional disparities exist. For some populations, including many in Botswana, access to areas at risk for VHF nationally was low but proximity to suitable spillover areas in bordering countries was high. Additional analyses provide insights for considering future resource allocation. We provide a contemporary use case for these analyses for the ongoing Ebola outbreak.

conclusionsThese maps demonstrate the use of geospatial analytics for subnational preparedness, identifying facilities close to at-risk populations for prioritizing readiness to detect, treat, and respond to cases and highlighting where gaps in health facility accessibility exist. We identified cross-border threats for VHF exposure and demonstrate an opportunity to improve preparedness activities through the use of precision public health methods and data-driven insights for resource allocation as part of a country's preparedness plans.

Indexed as

Civil DefenseDisease OutbreaksHealth FacilitiesHumansTime FactorsTravelCCHFEbolaHealth facility accessLassa feverMarburgPreparednessTravel timeViral hemorrhagic fevers

Identifiers

PMID31888667
PMCPMC6937971

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.