Evidence map›Paper›PMID 33085682›Full record

ArticlePloS one2020

Geographical accessibility and spatial coverage modelling of public health care network in rural and remote India.

Veenapani Rajeev Verma, Umakant Dash

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 3 pooled it
7.0field-weighted citation impact, top 4% of its field
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

25 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

  1. Geo-Enabling Public Health: A Systematic Review of GIS Applications.Advances in experimental medicine and biology · 2026
    Pooled it
  2. Pooled it
  3. Pharmacy-based immunization: a systematic review.Frontiers in public health · 2023
    Pooled it
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  18. Geospatial determinants of health: A global surgery lens.Journal of the colleges of medicine of South Africa · 2024
    Article
  19. Review
  20. Metabolic Syndrome and Associated Factors in Farmers in Southeastern Brazil: A Cross-Sectional Study.International journal of environmental research and public health · 2023
    Observational
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

2 authors at 1 institution in 1 country.

Veenapani Rajeev VermaDepartment of Humanities and Social Sciences, Indian Institute of Technology Madras (IIT M), Tamil Nadu, Chennai, India.ORCID 0000-0002-4595-900X
Umakant DashDepartment of Humanities and Social Sciences, Indian Institute of Technology Madras (IIT M), Tamil Nadu, Chennai, India.
Indian Institute of Technology Madras · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong distances to facilities, topographical constraints, inadequate service capacity of institutions and insufficient/ rudimentary road & transportation network culminate into unprecedented barriers to access. These barriers gets exacerbated in presence of external factors like conflict and political disruptions. Thus, this study was conducted in rural, remote and fragile region in India measuring geographical accessibility and modelling spatial coverage of public healthcare network.

methodsVector and raster based approaches were used to discern accessibility for various packages of service delivery. Alternative scenarios derived from local experiences were modelled using health facility, population and ancillary data. Based on that, a raster surface of travel time between facilities and population was developed by incorporating terrain, physical barriers, topography and travelling modes and speeds through various land-cover classes. Concomitantly, spatial coverage was modelled to delineate catchment areas. Further, underserved population and zonal statistics were assessed in an interactive modelling approach to ascertain spatial relationship between population, travel time and zonal boundaries. Finally, raster surface of travel time was re-modelled for the conflict situation in villages vulnerable to obstruction of access due to disturbed security scenario.

resultsEuclidean buffers revealed 11% villages without ambulatory & immunization care within 2 km radius. Similarly, for 5 km radius, 11% and 12% villages were bereft of delivery and inpatient care. Travel time accessibility analysis divulged walking scenario exhibiting lowest level of accessibility. Enabling motorized travel improved accessibility measures, with highest degree of accessibility for privately owned vehicle (motorcycle and cars). Differential results were found between packages of services where ambulatory & immunization care was relatively accessible by walking; whereas, delivery and inpatient care had a staggering average of three hours walking time. Even with best scenario, around 2/3rd population remained unserved for all package of services. Moreover, 90% villages in conflict zone grapples with inaccessibility when the scenario of heightened border tensions was considered.

conclusionsOur study demonstrated the application of GIS technique to facilitate evidence backed planning at granular level. Regardless of the scenario, the analysis divulged inaccessibility to delivery and inpatient care to be most pronounced and majority of population to be unserved. It was suggested to have concerted efforts to bolster already existing facilities and adapt systems approach to exploit synergies of inter-sectoral development.

Indexed as

Public HealthGeographic Information SystemsHealth Services AccessibilityHumansIndiaModels, TheoreticalRural PopulationTransportationWalking

Identifiers

PMID33085682
PMCPMC7577445
OpenAlexW3094560380

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.