Abstract
Abstract. Emergency medical service (EMS) response is extremely critical for pre-hospital lifesaving when disaster events occur. However, disasters increase the difficulty of rescue and may significantly increase the total travel time between dispatch and arrival, thereby increasing the pressure on emergency facilities. Hence, facility location decisions play a crucial role in improving the efficiency of rescue and service capacity. In order to avoid the failure of EMS facilities during disasters and meet the multiple requirements of demand points, we propose a multi-coverage optimal location model for EMS facilities based on the results of disaster impact simulation and prediction. To verify this model, we explicitly simulated the impacts of fluvial flooding events using the 1-D–2-D coupled flood inundation model FloodMap. The simulation results suggested that even low-magnitude fluvial flood events resulted in a decrease in the EMS response area. The integration of the model results with a geographical-information-system (GIS) analysis indicated that the optimization of the EMS locations reduced the delay in emergency responses caused by disasters and significantly increased the number of rescued people and the coverage of demand points.
Highlights
Urban disasters represent a serious and growing challenge
The aforementioned traditional location models ignored the impacts of specific disasters, but we suggest that these impacts must be part of any decision regarding the location of emergency services
We propose a multi-coverage optimal location model, whose output depends on the impact of a disaster and the levels of demand made on the Emergency medical service (EMS)
Summary
Urban disasters represent a serious and growing challenge. Against the backdrop of urbanization, demographic growth, and climate change, the causes of disasters are changing and their impacts are increasing. The focus of the LSCM is to minimize the number of facilities needed to cover all demand points, but it has been shown to lead to an unequal allocation of facilities or a large increase in costs Due to these limitations, the MCLP model was developed to ensure that existing emergency facilities were used to obtain the maximum coverage of the demand points. Apart from causing casualties, a disaster may damage emergency facilities; damage to buildings and roads will lead to traffic congestion and render emergency rescue more difficult than usual To avoid these problems, research has been conducted on choosing the location of emergency service facilities in response to large-scale emergencies. Of urban fluvial floods in the Minhang district of Shanghai, China, to validate this model
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