Evidence map›Paper›PMID 42344262›Full record

ArticleFrontiers in public health2026

Measuring and optimizing spatial accessibility to emergency medical services with a focus on age-based spatial variations in EMS risk.

Weicong Luo, Xinxin Chen, Luyan Zhao, Lijie He

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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

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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

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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

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5 · Who and what money

Authors and funding

4 authors.

Weicong LuoCollege of Public Administration, Huazhong Agricultural University, Wuhan, China.
Xinxin ChenCollege of Public Administration, Huazhong Agricultural University, Wuhan, China.
Luyan ZhaoCollege of Public Administration, Huazhong Agricultural University, Wuhan, China.
Lijie HeCollege of Public Administration, Huazhong Agricultural University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Emergency Medical Services (EMS) play a crucial role in safeguarding public health, yet their efficiency is highly dependent on spatial accessibility and optimal facility location. Existing research often evaluates EMS spatial accessibility using total population counts, overlooking the heterogeneity of EMS risk across space and age groups. This study aims to improve EMS accessibility measurement and spatial optimization by integrating spatial and demographic variations in EMS risk. Method: An integrated framework combining a modified two-step floating catchment area (2SFCA) model and two spatial optimization models-the Maximum Covering Location Problem (MCLP) and the P-median model-were developed. The improved models incorporate spatial and age-based EMS risk derived from 2024 EMS records in Wuhan, China. Comparative analyses were conducted between traditional and risk-integrated models to examine differences in accessibility and optimal station layouts. Results: Findings reveal significant age-related and spatial variations in EMS risk, with older adults populations showing markedly higher risks, and high-risk areas concentrated in central and near-suburban districts. Compared to traditional 2SFCA results, the improved model produced significantly different accessibility distributions, particularly in peri-urban areas. In optimization analyses, risk-integrated MCLP and P-median models located new EMS stations closer to near-urban areas, whereas traditional models favored peripheral suburbs. Conclusion: Incorporating spatial and demographic variations in EMS risk substantially enhances the accuracy of accessibility measurement and optimization outcomes. The results underscore the importance of prioritizing high-risk older adults populations, strengthening EMS capacity in urban cores, and improving coverage in underserved suburbs. This framework offers a transferable tool for developing more efficient and equitable EMS systems in rapidly urbanizing and aging regions.

Indexed as

Emergency Medical ServicesHealth Services AccessibilityAdolescentAdultAgedAge FactorsChildChild, PreschoolChinaFemaleHumansMaleMiddle AgedSpatial AnalysisYoung Adultaccessibilityage groupsEMS riskGISspatial optimization

Identifiers

PMID42344262
PMCPMC13286794

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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.