Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays

Chou, C.K.; Chiang, Wen-Chu; Chen, Albert Y.

doi:10.1016/j.tre.2021.102591

Cited by 22 publications

(11 citation statements)

References 84 publications

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“…This is because the road traffic conditions of adjacent periods are relatively similar as the Internet vehicle travel time data is at a two-minute interval. Thus, we define a time supplementary value as T time , see (1), where T t −1 and T t +1 are the vehicle travel times corresponding to the two adjacent time periods before and after the missing data point. Since the search for missing data is in chronological order, if the latter data point is also missed, we only use the previous one.…”

Section: Data Imputation Methods Based On Time Series and Road Topologymentioning

confidence: 99%

“…In recent years, with the ongoing urbanization and rapid economic development, the limited road resources are gradually difficult to bear the growing traffic demand. Traffic congestion emerges or has been aggravated in many cities around the world, which negatively affects urban mobility, including the normal daily travel and the emergency operation efficiency [1]. Traffic congestion also exacerbates the problems of travel safety, energy waste, and air pollution [2].…”

Section: Introductionmentioning

confidence: 99%

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Urban road travel time prediction based on gated recurrent unit using internet data

Li,

Hao,

Yang

et al. 2023

IET Intelligent Trans Sys

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Traffic congestion has been aggravated in many cities, which not only negatively affects the traffic efficiency, but also exacerbates the related social problems. Accurate prediction of urban road travel times plays a crucial role in assisting traffic management and alleviating the derived problems caused by traffic congestion. This study aims to propose an innovative Gated Recurrent Unit (GRU)‐based model for vehicle travel time prediction on urban road networks using the Internet vehicle travel time data. The Internet data used in the paper represents the real‐world average vehicle travel times on urban road networks, avoiding the privacy issue and the computational challenge in individual trajectory data. Before presenting the model, a data imputation method based on time series to reconstruct the missing data, and a time‐series data similarity evaluation method for road link classification are developed. The road‐category‐based model helps balance the computational efficiency and the prediction accuracy. Finally, the modelling framework is tested on a road network in Xuhui District, Shanghai. By comparing its performance with different models, it is concluded that the GRU‐based model considering road link categories is more efficient and more accurate in urban road travel time prediction.

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Section: Data Imputation Methods Based On Time Series and Road Topologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Urban road travel time prediction based on gated recurrent unit using internet data

Li,

Hao,

Yang

et al. 2023

IET Intelligent Trans Sys

View full text Add to dashboard Cite

show abstract

“…Disaster ethics have been previously considered by Geale, et al as requiring further development and maturity that considers the scope of practice of responders and ensuring that the rights of the patient, including consent to treatment, are upheld in events resulting in mass-casualty incidents. 42 Prehospital Processes Mass-casualty incident response prehospital processes are undergoing rapid change due to new and emerging technologies. Identification and adaptation of such technology adopted in other industries offers potential enhancement of existing prehospital response processes.…”

Section: Prehospital Life Support and Damage Controlmentioning

confidence: 99%

Sudden-Onset Disaster Mass-Casualty Incident Response: A Modified Delphi Study on Triage, Prehospital Life Support, and Processes

Cuthbertson,

Weinstein,

Franc

et al. 2023

Prehosp. Disaster med.

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The application and provision of prehospital care in disasters and mass-casualty incident response in Europe is currently being explored for opportunities to improve practice. The objective of this translational science study was to align common principles of approach and action and to identify how technology can assist and enhance response. To achieve this objective, the application of a modified Delphi methodology study based on statements derived from key findings of a scoping review was undertaken. This resulted in 18 triage, eight life support and damage control interventions, and 23 process consensus statements. These findings will be utilized in the development of evidence-based prehospital mass-casualty incident response tools and guidelines.

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“…Hu et al ( 37 ) proposed a mixed integer programming model that considers the uncertainty of the number of injured people and integrates the decision of locating shelters and transferring injured people. Chou et al ( 17 ) proposed a patient transportation and assignment model considering the routing of ambulances and operational conditions of hospitals.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust optimization for casualty scheduling considering injury deterioration and point-edge mixed failures in early stage of post-earthquake relief

Zhou

Gong²,

Hu³

2023

Front. Public Health

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ObjectiveScientifically organizing emergency rescue activities to reduce mortality in the early stage of earthquakes.MethodsA robust casualty scheduling problem to reduce the total expected death probability of the casualties is studied by considering scenarios of disrupted medical points and routes. The problem is described as a 0-1 mixed integer nonlinear programming model. An improved particle swarm optimization (PSO) algorithm is introduced to solve the model. A case study of the Lushan earthquake in China is conducted to verify the feasibility and effectiveness of the model and algorithm.ResultsThe results show that the proposed PSO algorithm is superior to the compared genetic algorithm, immune optimization algorithm, and differential evolution algorithm. The optimization results are still robust and reliable even if some medical points fail and routes are disrupted in affected areas when considering point-edge mixed failure scenarios.ConclusionDecision makers can balance casualty treatment and system reliability based on the degree of risk preference considering the uncertainty of casualties, to achieve the optimal casualty scheduling effect.

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Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays

Cited by 22 publications

References 84 publications

Urban road travel time prediction based on gated recurrent unit using internet data

Urban road travel time prediction based on gated recurrent unit using internet data

Sudden-Onset Disaster Mass-Casualty Incident Response: A Modified Delphi Study on Triage, Prehospital Life Support, and Processes

Robust optimization for casualty scheduling considering injury deterioration and point-edge mixed failures in early stage of post-earthquake relief

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