Locating automated external defibrillators in urban areas: considering different travel modes
- 1College of Public Administration, Huazhong Agricultural University
- 2Wuhan Emergency Medical Center
Abstract
Introduction: Out-of-hospital cardiac arrest (OHCA) is a time-critical emergency in which rapid access to automated external defibrillators (AEDs) can improve survival. However, most AED location studies assume a single travel mode and often use population alone as a proxy for demand. This study investigates how travel-mode assumptions affect AED accessibility and optimal deployment and develops a risk-informed multimodal spatial optimization framework.
Methods: Using Wuhan, China, as a case study, an age-risk-weighted potential OHCA demand surface was constructed from 17,842 ambulance dispatch records and age-stratified population data across 1,161 1-km grid cells. The existing 3,569 AEDs were treated as fixed facilities. Accessibility was evaluated under driving, cycling, walking, Drive + Walk, and Cycling + Walk scenarios using a 4-min response threshold. Multimodal extensions of the Location Set Covering Problem (LSCP) and Maximal Covering Location Problem (MCLP) were applied to identify full-coverage requirements and priority locations.
Results: Baseline demand-weighted coverage varied substantially by travel mode: 85.07% for driving, 68.27% for cycling, 31.55% for walking, 53.65% for Drive + Walk, and 45.41% for Cycling + Walk. The additional AEDs required for universal coverage ranged from 68 under driving to 521 under walking, with 327 required under Drive + Walk. Under the first-phase MCLP strategy, 65 new AEDs increased Drive + Walk demand-weighted coverage to 73.31%. Sensitivity analysis confirmed that the main findings were robust to alternative mode weights.
Discussion: AED accessibility and optimal deployment are highly sensitive to responder mobility assumptions. Incorporating heterogeneous travel modes and age-specific OHCA risk can support more realistic, spatially targeted, and resource-efficient AED planning.
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BibTeX
@article{luo2026locating,
title = {{Locating automated external defibrillators in urban areas: considering different travel modes}},
author = {Weicong Luo and Jinhao Liu and Yuhan He and Fei Wang},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1936570},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1936570/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Locating automated external defibrillators in urban areas: considering different travel modes
AU - Weicong Luo
AU - Jinhao Liu
AU - Yuhan He
AU - Fei Wang
PY - 2026
DA - 2026/10/14
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1936570
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1936570/full
AB - Introduction: Out-of-hospital cardiac arrest (OHCA) is a time-critical emergency in which rapid access to automated external defibrillators (AEDs) can improve survival. However, most AED location studies assume a single travel mode and often use population alone as a proxy for demand. This study investigates how travel-mode assumptions affect AED accessibility and optimal deployment and develops a risk-informed multimodal spatial optimization framework. Methods: Using Wuhan, China, as a case study, an age-risk-weighted potential OHCA demand surface was constructed from 17,842 ambulance dispatch records and age-stratified population data across 1,161 1-km grid cells. The existing 3,569 AEDs were treated as fixed facilities. Accessibility was evaluated under driving, cycling, walking, Drive + Walk, and Cycling + Walk scenarios using a 4-min response threshold. Multimodal extensions of the Location Set Covering Problem (LSCP) and Maximal Covering Location Problem (MCLP) were applied to identify full-coverage requirements and priority locations. Results: Baseline demand-weighted coverage varied substantially by travel mode: 85.07% for driving, 68.27% for cycling, 31.55% for walking, 53.65% for Drive + Walk, and 45.41% for Cycling + Walk. The additional AEDs required for universal coverage ranged from 68 under driving to 521 under walking, with 327 required under Drive + Walk. Under the first-phase MCLP strategy, 65 new AEDs increased Drive + Walk demand-weighted coverage to 73.31%. Sensitivity analysis confirmed that the main findings were robust to alternative mode weights. Discussion: AED accessibility and optimal deployment are highly sensitive to responder mobility assumptions. Incorporating heterogeneous travel modes and age-specific OHCA risk can support more realistic, spatially targeted, and resource-efficient AED planning.
SN - 2296-2565
ER -