Spatial difference analysis for accessibility to high level hospitals based on travel time in Shenzhen, China

Measuring the spatial accessibility and capacity of healthcare facilities is an important task to improve the quality of health services and reduce the pressure on them. This research assesses the current spatial accessibility and capacity of two-level of healthcare facilities (comprehensive healthcare centers and hospitals) in the Greater Irbid Municipality using the enhanced two-step floating catchment area (E2SFCA) method. To do this, Network analysis techniques including original-destination matrix (OD), service area, and location-allocation were employed for determining the travel time from residents' points towards every healthcare facility, the service coverage and capacity within travel time zones, and the number of served areas by every healthcare facility. Then, optimum locations for new healthcare facilities that improve the accessibility and capacity rates were determined. The results show that while all areas in the study area are located within a 30-minute drive from the hospital's locations, 18 out of 23 areas are within 15 minutes drive towards the comprehensive health centers. This means that 28.80% of the population needs more than 15 minutes of driving time to access the second level of healthcare services. In addition, the annual average of the actual patient-doctor ratio ranges from 1338 to 2900 patients per doctor in the hospitals, and 2676 to 8524 patients per doctor in the comprehensive healthcare centers, and thus, the health services are inadequate in the study area. Furthermore, the suggested new healthcare facilities in terms of the numbers and optimum location would improve the spatial accessibility and the capacity ratio.

Green space in urban areas is one of the most critical infrastructures for the well-being of residents, and its spatial accessibility configuration is a key indicator of urban planning layout and ecological civilization construction. Using the Gaussian two-step floating catchment area (G2SFCA) method, K-means cluster analysis, and Kriging spatial interpolation, this study examines the spatial characteristics of green space accessibility in the Hongkou District, focusing on the relationship between “green space-community” supply. The findings indicate the following: (1) green space accessibility in Hongkou District decreases as the level of green spaces decreases. Higher levels of accessibility are associated with smaller variations in spatial distribution. (2) The green space accessibility in Hongkou District is affected by the surrounding large green space. Compared to other areas, the community green spaces near Lu Xun Park and Peace Park have higher accessibility. (3) The green space accessibility in Hongkou District is impacted by the mismatch between population density and green spaces. An overlay analysis of accessibility and population density reveals that high accessibility areas have average or low-average population density. Based on the results of the green space accessibility analysis, recommendations are proposed to optimize the green space layout in Hongkou District from the perspective of spatial justice. These suggestions are aimed at promoting the equalization of green space services in Hongkou District, improving the overall level of urban green space services, with a view to improving the quality of urban living environment and creating a green and livable urban area.

Modeling job accessibility using online map data: An extended two-step floating catchment area method with multiple travel modes

Improvement of the equality of geographical allocation of limited health-care resources requires an accurate evaluation of spatial accessibility of the facilities. The adoption of appropriate population distribution measures is one of the leading factors affecting such an evaluation. Using primary health-care institutions in Hainan, China as an example, this study aimed to explore the disparities embedded in spatial accessibility evaluations based on six common measures of population distribution, namely community/ village population (VillagePop), average population distribution (AveragePop), population distribution by night-time light intensity (NighttimelightPop) together with the public population databases LandScan, WorldPop and PoiPop for construction of the weights. The enhanced two-step floating catchment area method, two-way analysis of variance (ANOVA), Dunnett test, root mean square error and the mean absolute error were employed to assess and compare spatial accessibilities based on these different population distribution measures. The spatial accessibility of primary health-care institutions in Hainan was found to vary when plotted using the various population distribution measures mentioned. As indicated by the statistical outcomes of both ANOVA and the Dunnett test, using the spatial accessibility calculated by VillagePop as reference, those calculated by AveragePop and PoiPop were found to be significantly different. In addition, the spatial accessibilities calculated by AveragePop and PoiPop demonstrated higher error rates in the identification of underserved areas compared with the reference. Considering the limitations of public population databases, the adoption of night-time light data is highly recommended for estimating population distribution in the absence of high-resolution data.

Ensuring convenient access to cancer screening, diagnosis, and treatment is essential for mitigating and preventing the disease. Geographical accessibility plays a crucial role in cancer mitigation and healthcare planning, particularly in low-income countries such as Nepal. A spatial perspective is crucial for improving cancer mitigation planning and evidence-based policy formulation. This study examined the spatial accessibility and population coverage at the municipal level in Bagmati province, Nepal. This study utilized spatial data, including LULC, DEM, OSM road networks, population distribution, and location of cancer hospitals, to calculate three different scenarios for reaching these hospitals. Based on that, a raster surface of travel time between residences and cancer hospitals was developed. We incorporated terrain, physical barriers, travel modes, speeds, and topography through various land-cover classes. Accordingly, underserved populations and zonal statistics were assessed using an interactive modeling approach to determine the spatial relationship between population, travel time, and zonal boundaries. The motorized travel scenario exhibited the highest spatial accessibility, followed by the bicycling and walking scenarios. It varied significantly across the three scenarios. The motorized scenario has the highest accessibility, with 72.57% of people covered within a 30-min travel time. Motorized scenario has a maximum people coverage of 96.78% within a 360-min travel time. Kathmandu Valley and Chitawan urban areas showed higher accessibility across all scenarios, attributed to easy road networks. Rural and mountainous regions in the middle hills of the northern and eastern parts have low accessibility, attributed to steep slopes, scattered settlements, and sparse infrastructure. The findings demonstrate significant spatial disparities across various travel scenarios, underscoring the need for spatially informed health planning and policy development. These insights provide a foundation for addressing problems and enhancing cancer care delivery in Nepal using spatial techniques.

Introduction.The number of adults aged 65 and older is increasing across the United States, and substance use disorder is an important health concern for this population.Treatment programs specifically designed for older adults can improve recovery outcomes.This study examines spatial access to substance use treatment (SUT) programs tailored for older adults.Methods.Data on SUT facilities were obtained from the 2022 National Directory of Drug and Alcohol Abuse Treatment Facilities.Distances between census tracts and facility locations were measured, and spatial accessibility was assessed using the two-step floating catchment area method to generate a spatial access index (SPAI).Results are displayed as descriptive statistics overall and by rurality, including the number of census tracts, number of affected populations, average distance, and average SPAI.A map also illustrates spatial patterns of access. Results.Of 12,102 identified SUT facilities, 3,614 (29.9%) offered programs for older adults.Among 84,120 census tracts, 4,323 had no such facility within 50 miles, affecting 2,589,240 adults aged 65 and older.On average, the nearest older adult program was 13 miles away (SD = 19), with small rural tracts averaging 34 miles farther than urban tracts (p <0.001).SPAI values further highlighted disparities in rural areas, even after accounting for service demand.Conclusions.Few SUT facilities provide specialized programs for older adults.For millions, particularly in rural areas, distance poses a significant barrier to care.Expanding these programs in underserved areas could improve treatment availability and promote healthier aging.

Background: The global aging population has raised concerns about the fair distribution of elderly care resources. China, as the largest developing country, has made efforts to address population aging challenges. However, equitable distribution of elderly care resources remains a concern. This study analyzed the spatial layout and accessibility of elderly care service facilities (ECSFs) in Xiamen City to improve resource allocation and enhance the elderly care system in China. The findings provide valuable insights for other developing countries and regions seeking to improve their own elderly care resource allocation. Methods: Xiamen City was chosen as the research area due to its unique geographical location and advanced information technology infrastructure. The study examined the spatial distribution, accessibility, and equity of ECSFs. Using Python, point of interest (POI) data were collected and evaluated using the kernel density method and two-step floating catchment area method. Spatial autocorrelation analysis identified areas of aggregation and dispersion in ECSF accessibility. Results: Xiamen currently has 660 ECSFs, including nursing homes, adult day care centers, home care agencies, and rural elderly care homes. The analysis revealed spatial disparities, with ECSFs clustering primarily in the central area of Xiamen Island. Significant differences in accessibility were found among the four types of ECSFs. Spatial autocorrelation analysis identified cold and hot spot areas, indicating variations in accessibility across regions. Conclusion: Xiamen City has made progress in allocating elderly care resources and constructing service facilities. However, equity in resource allocation remains a concern. Areas with limited accessibility were identified, leading to unequal access to elderly care resources and timely physical care. To address these challenges, decision-making departments should consider increasing facilities, improving transportation, enhancing macro planning, and improving facility service quality and accessibility. These measures will optimize ECSF accessibility and promote equitable distribution of elderly care resources.

The global aging trend is becoming increasingly pronounced, and the accessibility and equity of older adult care facilities directly influence the health and quality of life of the older adult population, thus representing a critical issue in public health research and policy-making. Using Lin'an District, Hangzhou as an illustrative case, this research examines urban-rural integrated areas specifically, addressing the persistent challenge of supply-demand mismatches in older adult care facility allocation and seeking to optimize their spatial configuration. A comprehensive analytical framework based on the multi-modal two-step floating catchment area (2SFCA) method was established, integrating the Gini coefficient, Lorenz curve, and local spatial autocorrelation analysis to systematically evaluate the spatial accessibility and equity of older adult care facilities. The results demonstrate significant spatial heterogeneity in facility accessibility, revealing a clear distribution pattern characterized by higher accessibility in the eastern urban core and markedly lower accessibility in western rural regions, thereby highlighting notable supply-demand imbalances between urban and rural contexts. Furthermore, the application of local spatial autocorrelation effectively identified key regions characterized by pronounced inequities, notably rural areas in the west suffering severe resource deficiencies and transitional urban-rural zones where supply-demand conflicts prominently occur. The study further investigates critical factors underlying accessibility and equity disparities, including differences in transportation infrastructure, uneven older adult population distributions, and hierarchical classifications of service facilities. Ultimately, the findings provide valuable empirical insights and policy recommendations applicable to urban-rural integration contexts globally, contributing meaningfully to the advancement of age-friendly societies.

BackgroundThe patient’s anxiety before seeing a doctor may influence her/his hospital choice behavior through various ways. In order to explore why high level hospitals were overused by patients and why low level hospitals were not fully used by patients in China, this study was set up to test whether and to what extent the patient’s anxiety before seeing a doctor influenced her/his hospital choice behavior in China.MethodsThis study commissioned a large-scale 2009–2010 national resident household survey (N=4,853) in China, and in this survey the Self-Rating Anxiety Scale (SAS) was employed to help patients assess their anxiety before seeing a doctor. Specified ordered probit models were established to analyze the survey dataset.ResultsWhen the patient had high level of anxiety before seeing a doctor, her/his level of anxiety could not only predict that she/he was more likely to choose the high level hospital, but also accurately predict which level of hospital she/he would choose; when the patient had low level of anxiety before seeing a doctor, her/his level of anxiety could only predict that she/he was more likely to choose the low level hospital, but it couldn’t clearly predict which level of hospital she/he would choose.ConclusionThe patient with high level of anxiety had the strong consistent bias when she/he chose a hospital (she/he always preferred the high level hospital), while the patient with low level of anxiety didn’t have such consistent bias.

The Cancer Centers designated by the National Cancer Institute (NCI Centers) and academic medical centers (AMCs) form the “backbone” of the cancer care system in the United States. We conducted a nationwide analysis and generated a high-resolution map detailing spatial variation in the potentially unfulfilled demand for these facilities. A local demand value incorporates spatial access to the facilities and the number of local potential patients. The spatial access was estimated using the two-step floating catchment area method, taking into account both travel time and facility capacity. The travel time was measured using service-area rings created around each facility based on road networks. The facility capacity was measured as the ratio between the bed count of the facility and the number of potential patients in its three-hour catchment. The number of local potential patients was estimated from local demography and standard cancer rates. The demographic information is a combination of LandScan data and U.S. Census data, and the cancer rates are from the Surveillance Epidemiology and End Results. The final demand map shows distinctive patterns in the western and eastern halves of the contiguous United States. The demand in the east is spatially continuous but relatively low, whereas in the west it is sporadic but tends to have high values. We also examined the inherent relationships between several methods for measuring spatial access and found that the differences between them are technical rather than conceptual, which sets a theoretical basis for selecting and adapting those methods.

A commuter-based two-step floating catchment area method for measuring spatial accessibility of daycare centers

Civil administration departments require reliable measures of accessibility so that residential care facility shortage areas can be accurately identified. Building on previous research, this paper proposes an enhanced variable two-step floating catchment area (EV2SFCA) method that determines facility catchment sizes by dynamically summing the population around the facility until the facility-to-population ratio (FPR) is less than the FPR threshold (FPRT). To minimize the errors from the supply and demand catchments being mismatched, this paper proposes that the facility and population catchment areas must both contain the other location in calculating accessibility. A case study evaluating spatial accessibility to residential care facilities in Nanjing demonstrates that the proposed method is effective in accurately determining catchment sizes and identifying details in the variation of spatial accessibility. The proposed method can be easily applied to assess other public healthcare facilities, and can provide guidance to government departments on issues of spatial planning and identification of shortage and excess areas.

As an important component of urban disaster prevention and mitigation systems, the balance and equity of emergency shelter distribution can be measured based on spatial accessibility utilizing the two-step floating catchment area (2SFCA) method. However, there are some issues in previous studies on emergency shelter accessibility evaluated by the 2SFCA method: (1) the high discretization of population distribution data and the travel cost being measured base on Euclidean distance; (2) ignoring the difference between shelter and population catchment sizes. To address these issues, we propose an improved 2SFCA method that computes the shelter and population catchments respectively to evaluate the emergency shelter accessibility in Changchun, China. We compare the proposed improved 2SFCA method to the original 2SFCA method. The results indicate that the catchment size and shelter accessibility calculated by the proposed method are more realistic and objective. The improved 2SFCA method is applicable method for evaluating the shelter accessibility and can provide advice for the planning and management of emergency shelters in the future.

Assessing the spatial accessibility and spatial equity of public libraries' physical locations

Understanding the nature of human movement is important in many fields, such as transportation management, urban planning, and epidemiology. In this study, we focus on travelers who are grouped by their travel modes in the Tokyo Metropolitan Area. Notably, for each group of travelers, the distribution of daily travel time follows a lognormal distribution. For any travel mode, the distributions of normalized travel time for different years (1968–2008) and distances to the city center converge to a curve, although the average travel time and share of travel modes vary. By employing the concept of utility, we developed a disaggregate model wherein an individual maximizes utility from traveling (=benefit - cost) by modifying daily travel time. This model theoretically explained the observed distributions of travel time. The model was further used to demonstrate travel mode choices. The model parameters were estimated using the distribution of travel time, travel mode share, and manageable assumptions. These results provided interesting interpretations of the perceptual utility of the daily travel time of a population. Moreover, the obtained curves of utility versus time are similar to the shapes of the overall benefits assumed in previous studies. Overall benefit is a concept that has been developed and examined since the 1980s, and our study provides a mathematical foundation for this idea.