Elsevier

Cities

Volume 117, October 2021, 103314
Cities

Measuring emergency medical service (EMS) accessibility with the effect of city dynamics in a 100-year pluvial flood scenario

https://doi.org/10.1016/j.cities.2021.103314Get rights and content

Highlights

  • E2SFCA method is used to measure EMS accessibility.

  • The effects of city dynamics and extreme flooding are considered.

  • Both regular and irregular uncertain contextual factors can influence EMS accessibility in a highly complex manner.

  • Carefully taking contextual uncertainties into account is essential for all emergency services in other cities of the world.

Abstract

Emergency medical service (EMS) is important for rescuing victims suffering from life-threatening illnesses or accidents, and is highly time-sensitive by nature. Many uncertain contexts in the urban environment can prolong EMS response time and deteriorate its performance. Using the enhanced two-step floating catchment area (E2SFCA) method, this study measures EMS accessibility with the effect of a regular uncertain context (i.e., the city dynamics like time-varying population and traffic) and an irregular uncertain context (i.e., an extreme pluvial flood event which can cause extensive road closures). The results indicate that, in the central urban area of Shanghai, mid-west areas with denser populations have higher accessibility than eastern peripheral areas. Flooding can cause a remarkable decline of accessibility which falls to the lowest point slightly earlier than the time when the worst road connectivity emerges. The night time exhibits better accessibility than especially the peak hours during the daytime. The GWR results reveal that increasing facility richness and road density while decreasing flood-induced road closures have a positive effect on EMS accessibility. The study indicates that both regular and irregular uncertain contextual factors can influence EMS accessibility in a highly complex manner. Carefully taking these uncertainties into account would enable EMS planning in other contexts and regions to face the enormous challenges posed by the changing climate and increasingly complex urban environment.

Introduction

As one of the pivotal public health services, emergency medical service (EMS) plays a vital role in reducing the rate of morbidity and mortality, especially in the cases of accidents, sudden illnesses and urgent situations (e.g., life-threatening trauma, cardiac arrest, strokes, and childbirth) (Aringhieri et al., 2017; Liu et al., 2019). However, many uncertain contexts in the urban environment can prolong EMS response time and deteriorate its performance. Overlooking the contextual effects may lead to problematic evaluation of EMS accessibility and misinformed policy interventions (Hawthorne & Kwan, 2012).

Accessibility is an important indicator for evaluating EMS response performance. As widely used in disciplines like transportation, urban planning and geography, accessibility has a variety of definitions (Geurs & van Wee, 2004; Hansen, 1959; Hu & Downs, 2019; Kwan, 1998; Le Vine et al., 2013). Basically, how accessibility is measured depends on how it is conceptualized. According to Penchansky and Thomas (1981), a multi-faceted concept for health care access involves five dimensions (affordability, acceptability, availability, accommodation, and geographic accessibility), which respectively denote the cost, satisfaction, sufficiency, appropriateness, and travel impedance of (using) health care services. Among them, geographic accessibility (also known as spatial or physical accessibility) attracts considerable attention from health- and transport geography studies, where it is given a broader meaning referring to the availability of and proximity to health care services (Luo & Wang, 2003).

In view of this two-dimensional definition, the two-step floating catchment area (2SFCA) method has gained great popularity in relevant studies because it measures availability and proximity simultaneously by considering demand (e.g., population size), supply (e.g., number of EMS facilities), and the spatial interaction between them (Wang, 2017). As the name implies, 2SFCA evaluates accessibility through two steps. The first is assigning a supply-to-demand ratio to each supply node, and the second is calculating the accessibility of each demand node. The catchment area is a constraint of time or space that determines whether a pair of supply and demand nodes can spatially interact. Currently, there are several types of improvements to the original 2SFCA method (Wang, 2012; Tao and Tao & Cheng, 2016), mainly focusing on the distance decay function (e.g., enhanced 2SFCA) (Luo & Qi, 2009), the delimitation of catchment areas (e.g., dynamic 2SFCA) (McGrail & Humphreys, 2014), the competition among demand nodes or supply nodes (e.g., modified 2SFCA) (Delamater, 2013), the travel means of the demand side (e.g., multi-mode 2SFCA) (Mao & Nekorchuk, 2013), and actual human travel behavior (e.g., E2SFCA-ICA) (Pan et al., 2018).

With continuous improvements, the 2SFCA method has been shown to be capable of yielding increasingly reliable and accurate measurement of health care accessibility; but in the context of EMS, new difficulties arise. Unlike non-emergency problems, EMS response is highly time-sensitive. Higher response time may seriously reduce the survivability of victims to be rescued (Amorim et al., 2019). Measuring EMS accessibility, in particular, should incorporate the uncertainties that may cause fluctuations in response times. However, most empirical studies to date conceptualize accessibility in static terms and ignore the variations in demand, supply, and travel impedance over time and space, and thus suffer from the uncertain geographic context problem (UGCoP) (Kwan, 2012, Kwan, 2018). Solutions for this problem should be based on a good understanding of what the uncertainties are or where they stem from. The primary purpose of this study is to answer the following question: How do the typical uncertain contextual factors in urban areas (e.g., the time-varying population and traffic, an extreme pluvial flood which can cause extensive road closures), influence EMS accessibility? Carefully taking these uncertainties into account can help improve the measurement of accessibility in complex spatial and temporal contexts and provide more credible policy and practical recommendations for emergency management to meet greater challenges against a backdrop of the changing climate with more uncertainties.

Section snippets

Literature review

Herein, we reviewed two types of uncertain contexts, which have been discussed in a limited number of studies, encountered by the measurement of EMS accessibility.

The first type of uncertain context is regular uncertain context, namely the daily changes of traffic and demand due to millions of individuals' mobility, which can simply be referred to as city dynamics. Variations in EMS demand have been noted very early (Cusimano et al., 2010; Fransen et al., 2015; Jamtsho et al., 2015), but the

Data and methods

A brief workflow is illustrated in Fig. 1. Slightly different from the chronological order of the workflow, the following subsections first give an introduction to the study area and the EMS system in it, and then successively describe the detailed methods of (1) measuring accessibility using E2SFCA, (2) depicting the daily changes of the population and traffic (the regular context), and (3) defining flood-induced road closures (the irregular context).

Results

Altogether, we evaluated the EMS accessibility under 36 scenarios based on different combinations of the 4 temporal scenarios (2:00, 9:00, 14:00, and 18:00) and 9 flood condition scenarios. The latter refers to 1 normal scenario (NS) without flooding and 8 flood scenarios corresponding to 8 stages of the flooding. Meanwhile, for each flood scenario, we calculated the mean of 8 accessibility values (i.e., FS-mean) as the final assessment to be compared with the normal scenario. Since the

Discussion on the factors that influence accessibility

This section examines whether there are statistically significant associations between EMS accessibility and the factors we are concerned about. In view of the significant spatial heterogeneity in the accessibility patterns (the values of Moran's I range from 0.5411 to 0.7972), geographically weighted regression (GWR) analysis is used. Altogether, six latent factors are selected as independent variables, including 1) population, 2) facility richness, 3) fastest-nearest ratio, 4) real-time

Conclusion

This paper showed that, with a case study in Shanghai, some regular (e.g., dynamic population and traffic) and irregular (e.g., extreme flooding) contextual factors in urban areas can significantly influence the measurement of EMS accessibility. By integrating fine-grained time-varying demand and travel cost in the E2SFCA method, we address the limitations of past studies that assumed static population and traffic and thus ignored the effect of uncertain contexts on EMS accessibility. This

CRediT authorship contribution statement

Mengya Li designed the initial method, performed the data processing and analysis, interpreted the results and wrote the first draft of the manuscript. Mei-Po Kwan performed the reviewing and editing and contributed to the further development of the methods and interpretations. Mengya Li and Mei-Po Kwan together performed the revision according to the comments provided by the editor and the reviewers. Jie Chen performed the estimation of population based on mobile signaling data. Jie Yin and

Declaration of competing interest

The authors declare no competing financial interests.

Acknowledgments

This research is supported by the National Natural Science Foundation of China (41971199, 42001182, 41871164), the Major Program of National Fund of Philosophy and Social Science of China (18ZDA105), the China Postdoctoral Science Foundation (2019M661424). In addition, Mei-Po Kwan was supported by grants from the Hong Kong Research Grants Council (General Research Fund Grant no. 14605920; Collaborative Research Fund Grant no. C4023-20GF) and a grant from the Research Committee on Research

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