Dual-constrained healthcare emergency facility location model under flood scenarios: A case study in the Maozhou River basin, Shenzhen, China

Extreme rainfall-induced flooding significantly impacts healthcare emergency services. Current research on optimizing the deployment of healthcare emergency facilities under flooding scenarios remains limited, particularly in terms of considering both the population coverage and spatial coverage. Based on the simulation of urban flooding, this study proposes a dual-constrained emergency facility location optimization model that balances both the newly added service population and newly service scope, and its effectiveness is validated in the Maozhou River Basin in Shenzhen. The results indicate that urban flooding in the study area is caused by insufficient drainage capacity and low-lying topography, with the former being the dominant contributing factor. Additionally, rainfall events exceeding a 78 mm/h(10-year threshold) alter the shortest access routes to healthcare emergency services for over 50 % of the population.Compared with the decrease in traffic speed, impassable roads due to flooding exert a greater effect on healthcare emergency services. Lastly, optimization outcomes under three flooding scenarios demonstrate the applicability of our model, accurately determining the location of high priority healthcare emergency facilities. Non-inundated populations now achieve assured 15-min healthcare emergency response. This study provides a scientific foundation for urban emergency departments to plan resource allocation, reducing risks from healthcare delays in non-inundated areas.

Publication Details

Journal
Progress in Disaster Science
Published
2025-10-01
DOI
https://doi.org/10.1016/j.pdisas.2025.100473
Citations
1
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.81
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article

Dual-constrained healthcare emergency facility location model under flood scenarios: A case study in the Maozhou River basin, Shenzhen, China

1 citations
Progress in Disaster Science
Genomics and Phylogenetic Studies
0.81
article

Dual-constrained healthcare emergency facility location model under flood scenarios: A case study in the Maozhou River basin, Shenzhen, China

article en
1 citations

Abstract

Extreme rainfall-induced flooding significantly impacts healthcare emergency services. Current research on optimizing the deployment of healthcare emergency facilities under flooding scenarios remains limited, particularly in terms of considering both the population coverage and spatial coverage. Based on the simulation of urban flooding, this study proposes a dual-constrained emergency facility location optimization model that balances both the newly added service population and newly service scope, and its effectiveness is validated in the Maozhou River Basin in Shenzhen. The results indicate that urban flooding in the study area is caused by insufficient drainage capacity and low-lying topography, with the former being the dominant contributing factor. Additionally, rainfall events exceeding a 78 mm/h(10-year threshold) alter the shortest access routes to healthcare emergency services for over 50 % of the population.Compared with the decrease in traffic speed, impassable roads due to flooding exert a greater effect on healthcare emergency services. Lastly, optimization outcomes under three flooding scenarios demonstrate the applicability of our model, accurately determining the location of high priority healthcare emergency facilities. Non-inundated populations now achieve assured 15-min healthcare emergency response. This study provides a scientific foundation for urban emergency departments to plan resource allocation, reducing risks from healthcare delays in non-inundated areas.

Progress in Disaster ScienceVol. 28
Sustainable cities and communities
Openalex Percentile: Top 20%
Genomics and Phylogenetic Studies
0.81
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Dual-constrained healthcare emergency facility location model under flood scenarios: A case study in the Maozhou River basin, Shenzhen, China · Progress in Disaster Science (2025) | TGRS Research Map | TGRS