ISPRS International Journal of Geo-Information

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16 pages, 5279 KB

Open AccessArticle

Do We Care Enough About Child Maltreatment?—Analyzing Social Media Discourse on Child Maltreatment in the United States

by Xi Gong, Yujian Lu, Rebecca A. Girardet, Hannah M. C. Schreier, Zhenlong Li, Theresa H. Cruz and Yan Lin

ISPRS Int. J. Geo-Inf. 2026, 15(5), 195; https://doi.org/10.3390/ijgi15050195 - 1 May 2026

Abstract

Sentiment expressions related to child maltreatment (CM) in public discourse are influenced by demographic, economic, and cultural factors and individual characteristics. Using 188,429 geotagged CM-related tweets during 2018–2022, we explored public sentiment expression about CM across the contiguous U.S. We applied multiscale geographically [...] Read more.

Sentiment expressions related to child maltreatment (CM) in public discourse are influenced by demographic, economic, and cultural factors and individual characteristics. Using 188,429 geotagged CM-related tweets during 2018–2022, we explored public sentiment expression about CM across the contiguous U.S. We applied multiscale geographically weighted regression (MGWR) to examine how contextual factors relate to the percentage of CM-related tweets with negative sentiment at the county level, revealing the spatial heterogeneity and varying geographic scales of these associations. Counties with higher male-to-female ratios and lower education levels tended to express negative sentiment in CM-related tweets, with consistent patterns observed nationwide. Five factors exhibited spatially varying associations by U.S. region, with higher levels of negative sentiment in the following contexts: a lower percentage of residents living in group quarters or a higher percentage of same-sex couples (Eastern and Central); fewer households lacking broadband access (Central); a higher percentage of single-parent households (New England and Southern Mississippi River); and areas where professionals are mandated to report CM (Great Lakes and Southern Appalachian Mountains). This study provides critical insights for policymakers to adjust policies, educators to design focused interventions, and the public to raise CM awareness. The methodology also provides a valuable framework for investigating public discourse on other social issues. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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17 pages, 752 KB

Open AccessArticle

Unveiling Livelihood Vulnerability and Consumption Declines in U.S. Counties During the COVID-19 Pandemic: A Multilevel Analysis

by Seongbeom Park, Jong Ho Won and Jaekyung Lee

ISPRS Int. J. Geo-Inf. 2026, 15(5), 183; https://doi.org/10.3390/ijgi15050183 - 23 Apr 2026

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Abstract

COVID-19 was a prolonged public-health shock that disrupted mobility, access to services, and household spending. Although the official U.S. poverty rate declined to 11.1%, the Supplemental Poverty Measure rose to 12.9%, suggesting that material hardship persisted unevenly across places. This study asks whether [...] Read more.

COVID-19 was a prolonged public-health shock that disrupted mobility, access to services, and household spending. Although the official U.S. poverty rate declined to 11.1%, the Supplemental Poverty Measure rose to 12.9%, suggesting that material hardship persisted unevenly across places. This study asks whether pre-existing livelihood vulnerability and local epidemic burden translated into geographically concentrated consumption losses during 2020–2022. Because sustained consumption loss can erode households’ health-related spending, tracking where spending declines concentrate helps connect local social and environmental conditions to how communities withstand a health crisis. We analyze consumer expenditure, unlike prior research relying on aggregate retail sales, to capture fine-grained economic strains as a proxy for shock-absorption capacity. A Livelihood Vulnerability Index (LVI) was calculated for each U.S. county using 16 socio-economic variables, and counties were classified as high- or low-risk. A multilevel model then examined how socio-economic and COVID-19 factors at county and census tract levels shaped consumption changes. Higher-risk communities experienced greater consumption reductions. At the census tract level, the non-White ratio, vacancy rate, built year, per capita income, education level, and housing value were significant. At the county level, COVID-19 cases and deaths, crowding, public transportation use, and vehicle availability mattered most. These findings support place-targeted strategies that combine public-health response with socio-environmental interventions to reduce disparities rooted in pre-existing vulnerability. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

20 pages, 3345 KB

Open AccessArticle

The Geography of Water Pipe Use: A Case Study in Tabriz City, Northwestern Iran

by Alireza Mohammadi, Arshad Ahmed, Elahe Pishgar, Munazza Fatima and Robert Bergquist

ISPRS Int. J. Geo-Inf. 2026, 15(4), 169; https://doi.org/10.3390/ijgi15040169 - 13 Apr 2026

Viewed by 426

Abstract

Water pipe smoking, or hookah smoking, is a growing public health concern ingrained in urban leisure cultures. Even though hookah smoking is common, the localized spatial drivers of this activity are still poorly understood. In order to close this gap, this study examined [...] Read more.

Water pipe smoking, or hookah smoking, is a growing public health concern ingrained in urban leisure cultures. Even though hookah smoking is common, the localized spatial drivers of this activity are still poorly understood. In order to close this gap, this study examined the locations of 273 hookah cafés in the Tabriz metropolis in Iran, modeling the distribution of these cafés against eight urban predictors: population density, road networks, and six distinct land use categories, such as commercial, administrative, educational, industrial, religious, and recreational land use. We combined Kernel Density Estimation (KDE) with Local Bivariate Relationships (LBR) using a high-resolution spatial approach. The findings indicate a non-random and spatially clustered pattern, using entropy-based measures of local relationship complexity. With the highest mean entropy value (0.84) and percentage of significant relationships (87.7%), educational land use density was found to be the best predictor. Additionally, there was a robust and consistent correlation with commercial land use density. Relationships with administrative and recreational land uses, on the other hand, showed lower entropy and were weaker and more dispersed. According to this study’s findings, the distribution of hookah cafés is spatially correlated to youth concentration and commercial activity patterns. Entropy analysis reveals substantial neighborhood-level variation in predictor influence, highlighting the value of local spatial analysis for identifying place-specific exposure. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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19 pages, 29486 KB

Open AccessArticle

Mapping Mental Wellbeing and Air Pollution: A Geospatial Data Approach

by Morgan Ecclestone and Thomas Johnson

ISPRS Int. J. Geo-Inf. 2026, 15(4), 142; https://doi.org/10.3390/ijgi15040142 - 25 Mar 2026

Viewed by 587

Abstract

Urban air pollution is increasingly recognised as a determinant of mental wellbeing, yet most existing studies rely on static exposure estimates and lack spatial granularity. This limits understanding of how pollutant-specific patterns influence psychological states in real-world settings. To address this gap, we [...] Read more.

Urban air pollution is increasingly recognised as a determinant of mental wellbeing, yet most existing studies rely on static exposure estimates and lack spatial granularity. This limits understanding of how pollutant-specific patterns influence psychological states in real-world settings. To address this gap, we integrate real-time environmental and physiological data from 40 participants using the DigitalExposome dataset, applying multivariate and spatial analysis techniques. Our findings confirm that Particulate Matter (PM_2.5) exerts the strongest negative association with mental wellbeing while extending prior work by establishing a preliminary ranking of other pollutants Particulate Matter (PM₁₀), Particulate Matter (PM₁), Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Ammonia (NH₃). We applied statistical and spatial analysis methods, including heatmaps and Voronoi diagrams, to explore links between pollutants and wellbeing and compare the relative influence of air pollution and noise. This enabled identification of pollutant-specific hotspots and multi-level wellbeing patterns across individual, accumulated, and collective scales. These results demonstrate the value of spatial analysis for environmental health research and support targeted urban interventions, such as green space placement and traffic re-routing, to mitigate mental wellbeing risks. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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19 pages, 4258 KB

Open AccessArticle

Uneven Paths to Health: A Spatial Analysis of Sidewalk Conditions and Healthcare Access for Older Adults

by Nikolaos Stasinos, Kleomenis Kalogeropoulos, Andreas Tsatsaris and Marianna Mantzorou

ISPRS Int. J. Geo-Inf. 2026, 15(3), 137; https://doi.org/10.3390/ijgi15030137 - 23 Mar 2026

Cited by 1 | Viewed by 674

Abstract

As urban populations age, the built environment becomes a vital determinant of health equity. This research evaluates the sidewalk infrastructure, surrounding the Health Center in Egaleo, Greece, in order to quantify its impact on healthcare accessibility for older adults. Using a GIS-based approach [...] Read more.

As urban populations age, the built environment becomes a vital determinant of health equity. This research evaluates the sidewalk infrastructure, surrounding the Health Center in Egaleo, Greece, in order to quantify its impact on healthcare accessibility for older adults. Using a GIS-based approach to simulate realistic navigation, a routing algorithm prioritized the “easiest” path over the shortest distance by transforming accessibility scores into traversal costs. The results revealed a significant disadvantage in healthcare access, with routes to the Health Center scoring lower than the average accessibility of the greater study area. In addition, the negative correlation (r = −0.20, p < 0.001) confirms the pattern of accessibility disparity, where neighborhoods with the highest older adult density consistently face the poorest infrastructure. Eventually, Global Moran’s I of 0.912 confirms strong spatial autocorrelation, Local Indicators of Spatial Association (LISA) identifies “Accessibility Deserts” which comprise a 92.5% absence of crosswalks and an 81.7% rate of obstructions. This study outlines that those who depend most on the sidewalk network are disproportionately affected by inadequate urban planning conditions. By underscoring the necessity to remediate these low-accessibility clusters, public health is improved, ensuring equitable healthcare access and supporting healthy aging. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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34 pages, 21746 KB

Open AccessArticle

Spatial Distribution Evaluation and Optimization of Medical Resource Systems in High-Density Cities: A Case Study of Macau via GIS and Space Syntax Analysis

by Zekai Guo, Liang Zheng, Wei Liu, Qingnian Deng, Jingwei Liang and Yile Chen

ISPRS Int. J. Geo-Inf. 2026, 15(3), 126; https://doi.org/10.3390/ijgi15030126 - 13 Mar 2026

Viewed by 612

Abstract

As a typical example of a high-density city, Macau’s medical resource allocation system, a key component of the city’s complex socio-technical system, suffers from significant spatial imbalances, which restricts the overall effectiveness of the medical service system. Based on the perspective of systems [...] Read more.

As a typical example of a high-density city, Macau’s medical resource allocation system, a key component of the city’s complex socio-technical system, suffers from significant spatial imbalances, which restricts the overall effectiveness of the medical service system. Based on the perspective of systems science theory, regards the allocation of medical resources as a dynamic system with multiple coupled factors. It comprehensively utilizes systems research methods such as POI data mining and space syntax analysis and employs techniques such as kernel density analysis and spatial structure coupling models to systematically evaluate the spatial structure, resource accessibility, and service balance of Macau’s medical service system. It found that (1) the Macau Peninsula has concentrated core medical resources, such as the Conde de São Januário Hospital (CHCSJ) and Kiang Wu Hospital, which form a core subsystem with high service saturation. Excessive concentration of resources has led to high concentration of a certain type of facility. (2) Taipa Island and the Cotai Reclamation Area have created an extended subsystem of medical resources along with urban development. However, the northern area does not have enough facilities, and its internal structure is not balanced. (3) Coloane Island has only basic health stations remaining, forming a marginal subsystem with scarce medical resources, which has a significant hierarchical gap with the core and extended subsystems. This spatial pattern of “saturated Macau peninsula, expanded Taipa Island, and sparse Coloane Island” is essentially a concrete manifestation of the imbalance between the medical resource allocation system and the urban spatial development system. Therefore, based on system optimization theory, it proposes constructing a multi-level, networked spatial system for medical facilities to promote the coordinated operation of various regional medical subsystems and achieve overall functional optimization and a balanced layout for Macau’s medical service system. This research analyzes the imbalance mechanism of high-density urban public service systems using systems science methods, providing not only a scientific basis for the precise optimization of Macau’s medical resource allocation system but also a practical reference for the planning and governance of similar high-density urban public service systems under a systems thinking framework. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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30 pages, 5159 KB

Open AccessArticle

Changes in Individual OpenStreetMap Contributors’ Contribution Behavior Under COVID-19: A Case Study in New York City

by Jin Xu and Guiming Zhang

ISPRS Int. J. Geo-Inf. 2026, 15(3), 121; https://doi.org/10.3390/ijgi15030121 - 12 Mar 2026

Viewed by 378

Abstract

Volunteered Geographic Information (VGI) is geographic data obtained from voluntary contributions of individual contributors on social media and non-social media platforms, where contributors exhibit diverse interests and behavior patterns. While studies have found that the COVID-19 pandemic has influenced VGI contributor behavior on [...] Read more.

Volunteered Geographic Information (VGI) is geographic data obtained from voluntary contributions of individual contributors on social media and non-social media platforms, where contributors exhibit diverse interests and behavior patterns. While studies have found that the COVID-19 pandemic has influenced VGI contributor behavior on social media platforms (Facebook, X, and Instagram, etc.), less is known about contribution behaviors on non-social media VGI platforms such as OpenStreetMap (OSM). This study investigates how individual OSM contributors’ data contribution behaviors changed after the COVID-19 outbreak, using New York City as a case study. Metrics quantifying temporal, spatial, thematic, participation, and social interaction aspects of contribution behavior were developed to characterize individual-level contribution behaviors in both the pre- and post-COVID periods (2016–2019 and 2020–2023, respectively). Contributors were clustered into three groups based on pre-COVID behavioral patterns (as reflected by the metrics) using the K-Means algorithm. The resulting model was then applied to identify changes in contributors’ cluster memberships in the post-COVID period. Results reveal differences in contribution behaviors between the two time periods. Compared to pre-COVID contributors, post-COVID contributors, on average, showed stronger contribution engagement, including longer lifespans, larger spatial extent of edits, higher contribution volumes, a greater emphasis on modification over creation, and stronger co-editing network interactions. Healthcare amenity-related edits remained a small fraction of total contributions across both periods and all clusters. Contributors participating in data contribution in both time periods generally increased data contribution engagement after the COVID outbreak, characterized by longer lifespans, broader spatial coverage, more balanced creation and modification, and stronger network centrality. These findings highlight changes in individual contribution behavior under COVID-19 and exhibits the value of examining VGI contribution at the individual level. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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16 pages, 2682 KB

Open AccessArticle

Spatial Association Between Frequent Physical Distress (FPD) and Socioeconomic and Health-Related Factors in the United States: Using Multiscale Geographically Weighted Regression (MGWR)

by Hoehun Ha

ISPRS Int. J. Geo-Inf. 2026, 15(3), 118; https://doi.org/10.3390/ijgi15030118 - 12 Mar 2026

Viewed by 527

Abstract

This study explored the spatial relationship between frequent physical distress (FPD) and socioeconomic as well as health-related factors across the contiguous United States. FPD, defined as having 14 or more physically unhealthy days within the past month, serves as an important measure of [...] Read more.

This study explored the spatial relationship between frequent physical distress (FPD) and socioeconomic as well as health-related factors across the contiguous United States. FPD, defined as having 14 or more physically unhealthy days within the past month, serves as an important measure of overall population health. While many studies have examined the causes of mental distress, research on the geographic variation and social context of physical distress remains limited. Using data from 2673 U.S. counties, this study analyzed how socioeconomic conditions and health indicators relate to FPD at both national and regional levels. Ordinary Least Squares (OLS) multivariate regression model was first used to assess general associations, followed by Geographically Weighted Regression (GWR) and Multiscale Geographically Weighted Regression (MGWR) to identify spatially varying and scale-dependent relationships. Comparing the GWR and MGWR results revealed that several predictors of FPD operate at different spatial scales, reflecting local heterogeneity in health outcomes. Counties in the southeastern United States, particularly those with higher levels of socioeconomic disadvantage and poorer health conditions, showed elevated FPD rates. These findings highlight the importance of accounting for spatial context when addressing physical distress and suggest that locally tailored public health strategies may be more effective than uniform national approaches. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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24 pages, 3793 KB

Open AccessArticle

More Effort Is Needed to Mitigate Spatial Inequality in Rural China’s Healthcare Accessibility: Evidence from a High-Resolution, Multi-Scale and Time-Sensitive Assessment

by Ying Gao, Xiaoran Wu, Mingxiao Xu, Yanlei Ye and Na Zhao

ISPRS Int. J. Geo-Inf. 2026, 15(3), 112; https://doi.org/10.3390/ijgi15030112 - 8 Mar 2026

Viewed by 431

Abstract

This study aims to address gaps in understanding healthcare accessibility inequality in rural China, where traditional distance-based assessments and urban-centric biases are insufficient. By integrating real-time travel data from Amap and the two-step floating catchment area (2SFCA) method, we conducted a high-resolution (1 [...] Read more.

This study aims to address gaps in understanding healthcare accessibility inequality in rural China, where traditional distance-based assessments and urban-centric biases are insufficient. By integrating real-time travel data from Amap and the two-step floating catchment area (2SFCA) method, we conducted a high-resolution (1 km grid) analysis across transportation modes, administrative scales, and time-sensitive populations. Results reveal that driving enables more stable, equitable access (characterized by higher supply–demand ratios and lower variability) than public transport, which distorts ratios due to limited coverage. Accessibility disparities are most pronounced at the county scale, with eastern rural counties (e.g., Yangtze River Delta) showing far higher accessibility (log₁₀(A-value) > 5.0) than remote western counties (log₁₀(A-value) < 1.5). High time-sensitive populations (urgent care) face extreme accessibility gaps, with only 15% of counties providing optimal access. In contrast, low time-sensitive groups benefit from extended travel time thresholds, achieving 62% coverage of optimal access. Targeted interventions—investing in rural high-tier hospitals, enhancing transit frequency, and county-specific policies—are needed to advance health equity. The findings of this study provide the first nationwide high-resolution healthcare accessibility map for rural China, improve assessment accuracy via real-time data, and identify county-level gaps—offering data-driven insights for targeted policies to advance health equity and support rural revitalization. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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27 pages, 2254 KB

Open AccessArticle

GeoJed: A Geospatial Grid Model for Data Acquisition and Spatial–Quality Assessment of Healthcare Services in Jeddah

by Saud Althabiti

ISPRS Int. J. Geo-Inf. 2026, 15(3), 99; https://doi.org/10.3390/ijgi15030099 - 27 Feb 2026

Viewed by 657

Abstract

The limited availability of structured and consistent health-facility information poses challenges for assessing service accessibility and quality in rapidly growing cities, particularly in the Middle East. Although digital map platforms provide extensive public data, such information is often fragmented and not directly suitable [...] Read more.

The limited availability of structured and consistent health-facility information poses challenges for assessing service accessibility and quality in rapidly growing cities, particularly in the Middle East. Although digital map platforms provide extensive public data, such information is often fragmented and not directly suitable for systematic spatial analysis. This study presents GeoJed, a framework designed to automate the collection, organisation, and spatial analysis of healthcare facility information from digital map platforms. The framework is demonstrated through a case study in Jeddah, Saudi Arabia, highlighting its applicability for large-scale and reproducible spatial analysis of healthcare services. Using the resulting GeoJedHF dataset, a baseline analysis was conducted to illustrate the analytical value of the collected data, including the construction of an initial Patient Satisfaction Index (PSI) that integrates service availability with user-reported quality indicators derived from a multilingual sentiment model (XLM-RoBERTa). The results reveal clear spatial variations between districts in both facility distribution and perceived service quality. Overall, GeoJed establishes a reusable and extensible process for facility-level spatial data acquisition and analysis, with potential applications in accessibility assessment, urban planning, and service evaluation. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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28 pages, 71993 KB

Open AccessArticle

Spatial and Social Equity in Access to Emergency Service Facilities—An Opportunity–Outcome Perspective

by Chang Liu, Haoran Su, Hong Leng and Wenkai Chen

ISPRS Int. J. Geo-Inf. 2026, 15(3), 95; https://doi.org/10.3390/ijgi15030095 - 25 Feb 2026

Viewed by 682

Abstract

Equity in access to emergency service facilities (ESFs) is essential for ensuring residents’ safety and well-being. Previous studies on equity in access to ESFs have mainly focused on individual facilities or single dimensions, failing to capture the overall fairness of the emergency service [...] Read more.

Equity in access to emergency service facilities (ESFs) is essential for ensuring residents’ safety and well-being. Previous studies on equity in access to ESFs have mainly focused on individual facilities or single dimensions, failing to capture the overall fairness of the emergency service system as an integrated entity. This study introduces an integrated opportunity–outcome evaluation framework to examine spatial and social equity in access to ESFs at the community scale, with particular attention to disparities across facility types, spatial levels, and socioeconomic groups. A machine learning-based approach combining XGBoost and SHAP is employed to identify key spatial and non-spatial factors influencing ESF accessibility. The results indicate that: (1) In terms of opportunity equity, spatial accessibility to ESFs varies significantly, with lower accessibility in southwestern Yongdeng County and northern Gaolan County. (2) Regarding outcome equity, a significant spatial mismatch exists between emergency resource distribution and population demand, resulting in polarization between oversupply and insufficiency, with the FSs supply–demand imbalance being the most pronounced. Low-income groups, rural residents, and the elderly face greater difficulty accessing ESFs compared to the general population. Among all variables, average elevation is found to be a decisive factor affecting accessibility. Based on these findings, the study proposes a zoning-based planning strategy for ESFs in Lanzhou. This strategy offers practical guidance for improving future regional ESF planning, enhancing urban emergency response capacity and resilience. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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24 pages, 4378 KB

Open AccessArticle

Assessing Supply Equity of Community Sports and Fitness Facilities: A Case Study of Shijingshan District, Beijing

by Lei Wang, Shan Wu, Wenqi He, Yutao Han and Bo Zhang

ISPRS Int. J. Geo-Inf. 2026, 15(3), 94; https://doi.org/10.3390/ijgi15030094 - 25 Feb 2026

Viewed by 539

Abstract

Developing a more equitable, efficient, and sustainable system of community sports and fitness facilities, while improving the accessibility and popularity of national fitness activities, is crucial to advancing the Healthy China Initiative. However, existing studies have limitations: insufficiently granular classification of community-level facilities, [...] Read more.

Developing a more equitable, efficient, and sustainable system of community sports and fitness facilities, while improving the accessibility and popularity of national fitness activities, is crucial to advancing the Healthy China Initiative. However, existing studies have limitations: insufficiently granular classification of community-level facilities, failure to account for how differences in facility types affect service equity, absence of integrated validation that combines objective quantification and subjective perception, and inattention to group differences. These gaps provide the motivation for this study. This study uses Shijingshan District, Beijing, as a case study, categorizing community sports and fitness facilities into two categories: for-profit commercial facilities and non-profit community sports parks. Employing GIS technology, Z-score standardization, and questionnaire surveys, an evaluation was conducted from three aspects: accessibility, supply–demand dynamics, and group perception. The results show that: (1) Facility accessibility exhibits significant spatial heterogeneity. Commercial facilities are densely clustered in core subdistricts, whereas community sports parks exhibit higher accessibility in the southern and eastern areas than in the northern and western areas, with inadequate coverage in peripheral areas; (2) most facilities are in short supply shortage, and the supply–demand imbalance is particularly pronounced in peripheral areas; and (3) regarding group equity, gender equity is outperforms age equity, and the supply–demand structure aligns closely with gender-specific preferences. This study argues that the spatial mismatch between facility distribution and resident demand, as well as imbalances in the supply of facility types, are the key factors undermining equity. It proposes optimization strategies, including augmenting facility supply in peripheral areas and coordinating the provision of commercial facilities and community sports parks. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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34 pages, 17669 KB

Open AccessArticle

Integrating Health Status Transitions and Service Demands: A Spatial Framework for Elderly Care Service Resource Allocation

by Zhe Wang and Ying Zhou

ISPRS Int. J. Geo-Inf. 2026, 15(2), 83; https://doi.org/10.3390/ijgi15020083 - 15 Feb 2026

Viewed by 622

Abstract

With the deepening of population ageing, the spatial planning of an elderly care service system faces unprecedented challenges. Building an elderly care service network that aligns with the pace of population ageing has become increasingly important and urgent. Based on annual longitudinal data [...] Read more.

With the deepening of population ageing, the spatial planning of an elderly care service system faces unprecedented challenges. Building an elderly care service network that aligns with the pace of population ageing has become increasingly important and urgent. Based on annual longitudinal data on older adults’ health status and care service utilization from Japan’s Long-Term Care Insurance (LTCI) system, this study quantifies the relationship between changes in health status and elderly care service demand using a discrete time homogeneous Markov model and Poisson regression analysis. Subsequently, Geographic Information System (GIS) techniques are applied to conduct spatial analysis of the urban built environment to identify living service centres for older adults. Indicators including distance, supply–demand balance, and service capacity are then integrated through multi-objective clustering optimization to construct a multi-level elderly care service network system, achieving a quantitative linkage between elderly health status and spatial demand-oriented planning. Finally, the proposed integrated framework, which combines health status transitions, service demand estimation, and spatial allocation, is applied to Qinhuai district in Nanjing, China, generating practical policy recommendations that promote the integration of healthy ageing and precision service delivery. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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18 pages, 10625 KB

Open AccessArticle

An Integrated Approach to Evaluating the Spatial Allocation Efficiency of Urban Public Health Surveillance

by Shuzhen Xiao and Bisong Hu

ISPRS Int. J. Geo-Inf. 2026, 15(2), 81; https://doi.org/10.3390/ijgi15020081 - 14 Feb 2026

Viewed by 486

Abstract

Contingency epidemic outbreaks, such as the novel coronavirus (COVID-19) pandemic in 2020, have underscored the vital function of public health emergency response systems within national strategic frameworks. Public health surveillance and early warnings are imperative for safeguarding peoples’ lives, maintaining social stability, and [...] Read more.

Contingency epidemic outbreaks, such as the novel coronavirus (COVID-19) pandemic in 2020, have underscored the vital function of public health emergency response systems within national strategic frameworks. Public health surveillance and early warnings are imperative for safeguarding peoples’ lives, maintaining social stability, and promoting economic development. Existing studies are inadequate for accurately evaluating the efficiency of an urban public health surveillance system from a comprehensive perspective. In this work, an integrated framework was proposed for the evaluation of the spatial allocation efficiency of urban public health surveillance. This integrated approach incorporates three key aspects, spatial coverage, overlap, and accessibility, enabling a measurable evaluation of the overall spatial allocation efficiency. We utilized the proposed method to investigate the placement efficiency of the nucleic acid testing sites during the epidemic in Nanchang, China. The findings showed that using the integrated evaluation method based on coverage, overlap, and accessibility provides a more accurate reflection of the efficiency of existing site placements. It offers a flexible measurement system for evaluating urban surveillance site allocation strategies. This study introduces a novel perspective for the efficiency assessment of public health surveillance site placements, contributes to the development of public health emergency response systems, and provides a technical foundation for future contingency planning in public health surveillance. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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13 pages, 3979 KB

Open AccessArticle

Decomposing Spatial Accessibility into Demand, Supply, and Traffic Speed: Averaging Chain Substitution Method

by Kyusik Kim and Kyusang Kwon

ISPRS Int. J. Geo-Inf. 2026, 15(1), 44; https://doi.org/10.3390/ijgi15010044 - 18 Jan 2026

Viewed by 475

Abstract

Spatial accessibility to healthcare services is commonly determined by three core components: demand, supply, and traffic speed. Although understanding which factors contribute to accessibility changes can help prioritize interventions to enhance accessibility in underserved areas, limited research has examined the extent of their [...] Read more.

Spatial accessibility to healthcare services is commonly determined by three core components: demand, supply, and traffic speed. Although understanding which factors contribute to accessibility changes can help prioritize interventions to enhance accessibility in underserved areas, limited research has examined the extent of their individual contributions. To better capture the local dynamics that shape healthcare accessibility, this study decomposes spatial accessibility to primary healthcare services using the chain substitution method (CSM), which quantifies the impact of each component by substituting them one by one. By examining how the order of factor substitution affects the relative impact of each factor on spatial accessibility, we analyzed the importance of substitution order in the CSM. This study found that the order of factor substitution plays a significant role in measuring the relative contribution of each factor. To mitigate the effects of substitution order, we proposed an averaging CSM that uses the average value across all possible substitution combinations. Based on the averaging CSM, our findings offer insight for healthcare policymakers and urban planners by clarifying how demand, supply, and traffic speed interact in determining accessibility, ultimately supporting targeted interventions in underserved areas. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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16 pages, 9338 KB

Open AccessArticle

Integrated Revealing GIS Models to Monitor, Understand and Foresee the Spread of Diseases and Support Emergency Response

by Cristiano Pesaresi and Davide Pavia

ISPRS Int. J. Geo-Inf. 2026, 15(1), 32; https://doi.org/10.3390/ijgi15010032 - 8 Jan 2026

Viewed by 952

Abstract

The importance of GIS models to monitor the spread of infectious diseases and support emergency response has been underlined by a large body of literature and strengthened by the COVID-19 pandemic to identify possible solutions able to recognise spatio-temporal clusters and patterns, evaluate [...] Read more.

The importance of GIS models to monitor the spread of infectious diseases and support emergency response has been underlined by a large body of literature and strengthened by the COVID-19 pandemic to identify possible solutions able to recognise spatio-temporal clusters and patterns, evaluate the presence of acceleration factors and define specific actions. In the field of applied research on health geography and geography of safety, this work briefly displays the main aims of the project “Integrated revealing GIS models to monitor, understand and foresee the spread of diseases and support emergency response” and shows some illustrative applications. The basic assumption of the project is to test revealing models regarding key objectives of social utility, and one of its main aims is to elaborate GIS applications able to understand the spread of COVID-19, relating the geocalisations of the cases with specific variables. In order to provide targeted evidence able to better highlight local differences, a number of elaborations derived from (Arc)GIS models and based on data regarding COVID-19 according to sex, age and healthcare facilities in the Rome municipality (Italy) are presented and contextualised as examples, also replicable for precision preparedness. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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26 pages, 1085 KB

Open AccessArticle

Can Urban Information Infrastructure Development Improve Resident Health? Evidence from China Health and Retirement Longitudinal Survey

by Huiling Zhao, Chenyang Yu and Zhanchuang Han

ISPRS Int. J. Geo-Inf. 2025, 14(12), 496; https://doi.org/10.3390/ijgi14120496 - 16 Dec 2025

Viewed by 837

Abstract

Taking the “Broadband China” policy (BCP) as a quasi-natural experiment, this paper utilizes nationwide tracking data from the China Health and Retirement Longitudinal Survey (CHARLS) for 2011, 2013, 2015, and 2018 and employs a Difference-in-Differences (DID) model to evaluate whether and how urban [...] Read more.

Taking the “Broadband China” policy (BCP) as a quasi-natural experiment, this paper utilizes nationwide tracking data from the China Health and Retirement Longitudinal Survey (CHARLS) for 2011, 2013, 2015, and 2018 and employs a Difference-in-Differences (DID) model to evaluate whether and how urban information infrastructure development affects resident health. We identify a clear and significant improvement in health outcomes attributable to BCP. After the implementation of BCP, physical health and mental health increase by 2.5% and 1.7%, respectively. Furthermore, mechanism analysis confirms that BCP enhances resident health primarily by improving information and communication technology (ICT) levels and by promoting local economic development. The positive health effect of BCP is more pronounced in regions with a better medical environment, suggesting the presence of complementary public-service capacity. At the individual level, heterogeneity tests reveal that BCP exerts a stronger positive influence on the physical health of male and rural respondents, while the benefits for older respondents are relatively smaller. At the city level, the health-promoting effect of BCP is stronger in economically less developed regions, and cities with higher administrative status exhibit more substantial health improvements. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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17 pages, 6761 KB

Open AccessArticle

Risk of Hypoxia in Short-Term Residents in Qinghai–Xizang Plateau Based on the Disaster System Theory Model

by Zemin Zhi, Qiang Zhou, Qiong Chen, Fenggui Liu, Yonggui Ma, Ziqian Zhang and Weidong Ma

ISPRS Int. J. Geo-Inf. 2025, 14(12), 489; https://doi.org/10.3390/ijgi14120489 - 10 Dec 2025

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Abstract

Recognized as the world’s “Third Pole”, the Qinghai–Xizang Plateau poses significant challenges to human health due to its harsh environment. With improved transportation and a tourism boom industry bringing over 90 million low-altitude residents to the plateau annually, hypoxia has become a critical [...] Read more.

Recognized as the world’s “Third Pole”, the Qinghai–Xizang Plateau poses significant challenges to human health due to its harsh environment. With improved transportation and a tourism boom industry bringing over 90 million low-altitude residents to the plateau annually, hypoxia has become a critical concern. This study analyzes oxygen content data (2017–2022) together with environmental variables including elevation, temperature, precipitation, and vegetation cover, using the GeoDetector method to identify key drivers of near-surface oxygen distribution. Within the framework of disaster system theory, we evaluated the risk of hypoxia among short-term residents. Results show that the near-surface oxygen distribution across the plateau is primarily regulated by climatic and topographic factors. Interactions among environmental variables markedly enhance the explanatory power for spatial variation in oxygen content, with the coupled effects of humidity, atmospheric pressure, elevation, and temperature being especially pronounced. A high hypoxia hazard prevails across the plateau, particularly in the high-altitude western, northern, and central regions. The spatial distribution of hypoxia risk is strongly shaped by human activities, with high-risk zones clustering in densely populated towns, transportation corridors, and regions of intensive tourism. This results in a distinctive coexistence of “high hazard–low exposure” and “low hazard–high exposure” patterns. These findings provide scientific insights for tourism planning, health protection, and risk management in plateau regions. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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20 pages, 6042 KB

Open AccessFeature PaperArticle

GeoSpatial Analysis of Health-Oriented Justice in Tartu, Estonia

by Najmeh Mozaffaree Pour

ISPRS Int. J. Geo-Inf. 2025, 14(12), 467; https://doi.org/10.3390/ijgi14120467 - 28 Nov 2025

Cited by 1 | Viewed by 903

Abstract

This study investigates the role of modern small-scale cities in addressing public health challenges through the lens of spatial justice, using the city of Tartu, Estonia, as a case study. Tartu has been recognized for its progressive public health initiatives, including the Tartu [...] Read more.

This study investigates the role of modern small-scale cities in addressing public health challenges through the lens of spatial justice, using the city of Tartu, Estonia, as a case study. Tartu has been recognized for its progressive public health initiatives, including the Tartu Health Care College, Mental Health Centre, Smoke-Free Tartu campaign, Health Trail network, Healthy School Program, and an expanding smart bike-sharing system. By employing Geographic Information Systems (GIS), we map and analyze the spatial distribution and accessibility of health-promoting infrastructure, such as healthcare facilities, green and blue spaces, health trails, and mobility services, across the urban landscape. A population-weighted accessibility assessment indicates that, although Tartu’s central districts (e.g., Kesklinn (HRI: 0.972)) are well-served, peripheral and densely populated districts such as Annelinn (HRI: 0.351) and Ropka (HRI: 0.377) exhibit notable deficits in health-related infrastructure. However, access to green infrastructure and mobility services is more evenly distributed citywide, reflecting a relatively equitable provision of non-clinical health assets. These findings highlight both the strengths and spatial gaps in Tartu’s health-oriented urban design, emphasizing the need for targeted investment in underserved areas. The study contributes to emerging studies on health-justice planning in small-scale urban contexts and demonstrates how spatial analytics can be guided to advance distributional justice in the provision of public health infrastructure. Ultimately, this research indicates the essential role of spatial analysis in guiding inclusive and data-informed health planning in urban environments. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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30 pages, 3314 KB

Open AccessArticle

Spatio-Temporal Variability and Environmental Associations of Emergency Department Demand: A Longitudinal Analysis in Zaragoza, Spain (2011–2024)

by Jorge Blanco Prieto, Marina Ferreras González and Oscar Cosido Cobos

ISPRS Int. J. Geo-Inf. 2025, 14(11), 439; https://doi.org/10.3390/ijgi14110439 - 7 Nov 2025

Viewed by 839

Abstract

Emergency department (ED) overcrowding has become a critical public health issue worldwide, driven by increasing demand and limited healthcare resources. This study analyzes the spatio-temporal variability of ED visits at Royo Villanova Hospital (Zaragoza, Spain) from 2011 to 2024, integrating clinical, demographic, environmental, [...] Read more.

Emergency department (ED) overcrowding has become a critical public health issue worldwide, driven by increasing demand and limited healthcare resources. This study analyzes the spatio-temporal variability of ED visits at Royo Villanova Hospital (Zaragoza, Spain) from 2011 to 2024, integrating clinical, demographic, environmental, and socioeconomic data. Using geospatial tools and machine learning models (XGBoost with SHAP interpretation), we identify key patterns in ED demand across time and space. Results show that the hour of the day is the most influential variable across all diagnoses, while temperature, humidity, and air pollutants (NO₂, SO₂, O₃) significantly affect respiratory and injury-related visits. Spatial analysis reveals persistent high-demand clusters in specific health zones, with proximity to the hospital playing a major role. The COVID-19 pandemic caused structural shifts in demand, particularly in pediatric care. Our findings highlight the need for tailored, diagnosis-specific predictive models and support the use of geospatial and environmental data for proactive ED resource planning. This approach enhances the capacity of health systems to anticipate demand surges and allocate resources efficiently. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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19 pages, 2731 KB

Open AccessArticle

Exploring the Spatial Relationship Between Severe Depression, COVID-19 Case Rates, and Vaccination Rates in US Counties: A Spatial Analysis Across Two Time Periods

by Yuqing Wang and Wencong Cui

ISPRS Int. J. Geo-Inf. 2025, 14(10), 376; https://doi.org/10.3390/ijgi14100376 - 25 Sep 2025

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Abstract

Severe depression is shaped by complex interactions between public health crises and socioeconomic conditions, yet the spatial and temporal dynamics of these factors remain underexplored. This study investigates the impact of COVID-19 case rates, vaccination rates, and socioeconomic factors on severe depression rates [...] Read more.

Severe depression is shaped by complex interactions between public health crises and socioeconomic conditions, yet the spatial and temporal dynamics of these factors remain underexplored. This study investigates the impact of COVID-19 case rates, vaccination rates, and socioeconomic factors on severe depression rates across 1470 counties in the contiguous USA in 2021 and 2022. We combined Ordinary Least Squares (OLS) regression with Multiscale Geographically Weighted Regression (MGWR) to capture both global associations and local geographic variability. Results show that higher COVID-19 case rates in 2021 were associated with increased rates of severe depression in 2022, while higher vaccination rates during the same period were associated with decreased rates of severe depression. However, these associations weakened when using 2022 data, suggesting a temporal lag in the impact on mental health. MGWR analyses revealed regional disparities: COVID-19 case rates had a stronger impact in the Midwest, while vaccination benefits were more pronounced on the West Coast. Additional factors, such as unemployment, limited sunlight exposure, and the availability of mental health resources, also influenced outcomes. These findings underscore the importance of temporally and geographically nuanced approaches to public mental health interventions and support the need for region-specific strategies to address mental health disparities in the wake of public health crises. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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25 pages, 11023 KB

Open AccessArticle

Spatio-Temporal Mapping of Violence Against Women: An Urban Geographic Analysis Based on 911 Emergency Reports in Monterrey

by Onel Pérez-Fernández, Octavio Quintero Ávila, Carolina Barros and Gregorio Rosario Michel

ISPRS Int. J. Geo-Inf. 2025, 14(10), 367; https://doi.org/10.3390/ijgi14100367 - 23 Sep 2025

Cited by 3 | Viewed by 3258

Abstract

In Latin American cities, violence against women (VAW) remains critical for public health, well-being, and safety. This phenomenon is influenced by social, political, and environmental drivers. VAW is not randomly distributed; built environments—geography, ambient population, and street networks—influence criminal through spatial dependence across [...] Read more.

In Latin American cities, violence against women (VAW) remains critical for public health, well-being, and safety. This phenomenon is influenced by social, political, and environmental drivers. VAW is not randomly distributed; built environments—geography, ambient population, and street networks—influence criminal through spatial dependence across multiple scales. Despite growing interest in the spatial distribution of crime, few studies have explicitly explored the spatiotemporal dimensions of VAW in Monterrey. This study explores spatio-temporal patterns of VAW in Monterrey, Mexico, based on the analysis of 27,036 georeferenced and verified emergency reports from the 911 system (2019–2022). The study applies kernel density estimation (KDE), the Getis–Ord G_i* statistics, the Local Moran I index, and space–time cube analysis to identify spatial and temporal clusters of VAW. The results show concentrations of incidents during nighttime and weekends, particularly in northern and eastern sectors in Monterrey. The analysis reveals clusters in areas of high socioeconomic vulnerability. VAW in Monterrey follows predictable and cyclical patterns. These insights contribute to the design of tailored public policies and actions to improve women’s health, well-being, and safety in critical zones and timeframes. The findings also enhance international understanding of gender-based spatial violence patterns in the rapidly urbanizing contexts of the Global South. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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27 pages, 13052 KB

Open AccessArticle

A Multi-Scale Geographically Weighted Regression Approach to Understanding Community-Built Environment Determinants of Cardiovascular Disease: Evidence from Nanning, China

by Shuguang Deng, Shuyan Zhu, Xueying Chen, Jinlong Liang and Rui Zheng

ISPRS Int. J. Geo-Inf. 2025, 14(9), 362; https://doi.org/10.3390/ijgi14090362 - 18 Sep 2025

Cited by 2 | Viewed by 3255

Abstract

Clarifying how the community-scale built environment shapes the spatial heterogeneity of cardiovascular disease (CVD) prevalence is essential for precision urban health interventions. We integrated CVD prevalence data from the Guangxi Zhuang Autonomous Region Hospital (2020–2022) with 14 built-environment indicators across 77 communities in [...] Read more.

Clarifying how the community-scale built environment shapes the spatial heterogeneity of cardiovascular disease (CVD) prevalence is essential for precision urban health interventions. We integrated CVD prevalence data from the Guangxi Zhuang Autonomous Region Hospital (2020–2022) with 14 built-environment indicators across 77 communities in Xixiangtang District, Nanning, and compared ordinary least squares (OLS), geographically weighted regression (GWR), and multiscale geographically weighted regression (MGWR). MGWR provided the best model fit (adjusted R² increased by 0.136 and 0.056, respectively; lowest AICc and residual sum of squares) and revealed significant scale-dependent effects. Distance to metro stations, road network density, and the number of transport facilities exhibited pronounced local-scale heterogeneity, while population density, building density, healthy/unhealthy food outlets, facility POI density, and public transport accessibility predominantly exerted global-scale effects. High-risk clusters of CVD were identified in mixed-use, high-density urban communities lacking rapid transit access. The findings highlight the need for place-specific, multi-scale planning measures, such as transit-oriented development and balanced food environments, to reduce the CVD burden and advance precision healthy-city development. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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17 pages, 6488 KB

Open AccessEditor’s ChoiceArticle

A Spatial Analysis of the Association Between Urban Heat and Coronary Heart Disease

by Kyle Lucas, Ben Dewitt, Donald J. Biddle and Charlie H. Zhang

ISPRS Int. J. Geo-Inf. 2025, 14(9), 344; https://doi.org/10.3390/ijgi14090344 - 7 Sep 2025

Cited by 1 | Viewed by 1961

Abstract

Heart disease remains the leading cause of death in both the United States and globally. Urban heat is increasingly recognized as a significant public health challenge, particularly in its connection to cardiovascular conditions. This study, conducted in Jefferson County, Kentucky, examines the distribution [...] Read more.

Heart disease remains the leading cause of death in both the United States and globally. Urban heat is increasingly recognized as a significant public health challenge, particularly in its connection to cardiovascular conditions. This study, conducted in Jefferson County, Kentucky, examines the distribution of coronary heart disease rates and develops an urban heat risk index to examine underlying socioeconomic and environmental factors. We applied bivariate spatial association (Lee’s L), Global Moran’s I, and multiple linear regression methods to examine the relationships between key variables and assess model significance. Global Moran’s I revealed clustered distributions of both coronary heart disease rates and land surface temperature across census tracts. Bivariate spatial analysis identified clusters of high heart disease rates and temperatures within the West End, while clusters of contiguous suburban tracts exhibited lower heart disease rates and temperatures. Regression analyses yielded significant results for both the ordinary least squares (OLS) model and the spatial regression model; however, the spatial error model explained a greater proportion of the variation in coronary heart disease rates across tracts compared to the OLS model. This study offers new insights into spatial disparities in coronary heart disease rates and their associations with environmental risk factors including urban heat, underscoring the challenges faced by many urban communities. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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24 pages, 3580 KB

Open AccessArticle

Delineating Urban High–Risk Zones of Disease Transmission: Applying Tensor Decomposition to Trajectory Big Data

by Tianhua Lu and Wenjia Zhang

ISPRS Int. J. Geo-Inf. 2025, 14(8), 285; https://doi.org/10.3390/ijgi14080285 - 23 Jul 2025

Cited by 1 | Viewed by 1465

Abstract

Risk zone delineation and mobility behavior control constitute critical measures in pandemic containment. Numerous studies utilize static demographic data or dynamic mobility data to calculate the high–risk zones present in cities; however, these studies fail to concurrently consider activity and mobility patterns of [...] Read more.

Risk zone delineation and mobility behavior control constitute critical measures in pandemic containment. Numerous studies utilize static demographic data or dynamic mobility data to calculate the high–risk zones present in cities; however, these studies fail to concurrently consider activity and mobility patterns of populations in both space and time, which results in many studies only being able to employ static geostatistical analytical methods, neglecting the transmission risks associated with human mobility. This study utilized the mobile phone signaling data of Shenzhen residents from 2019 to 2020 and developed a CP tensor decomposition algorithm to decompose the long-sequence spatiotemporal trajectory data to detect high risk zones in terms of detecting overlapped community structures. Tensor decomposition algorithms revealed community structures in 2020 and the overlapping regions among these communities. Based on the overlap in spatial distribution and the similarity in temporal rhythms of these communities, we identified regions with spatiotemporal co-location as high–risk zones. Furthermore, we calculated the degree of population mixing in these areas to indicate the level of risk. These areas could potentially lead to rapid virus spread across communities. The research findings address the shortcomings of currently used static geographic statistical methods in delineating risk zones, and emphasize the critical importance of integrating spatial and temporal dimensions within behavioral big data analytics. Future research should consider utilizing non-aggregated individual trajectories to construct tensors, enabling the inclusion of individual and environmental attributes. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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31 pages, 2250 KB

Open AccessArticle

Spatial and Temporal Correlations of COVID-19 Mortality in Europe with Atmospheric Cloudiness and Solar Radiation

by Adrian Iftime, Secil Omer, Victor-Andrei Burcea, Octavian Călinescu and Ramona-Madalina Babeș

ISPRS Int. J. Geo-Inf. 2025, 14(8), 283; https://doi.org/10.3390/ijgi14080283 - 22 Jul 2025

Cited by 1 | Viewed by 955

Abstract

Previous studies reported the links between the COVID-19 incidence and weather factors, but few investigated their impact and timing on mortality, at a continental scale. We systematically investigated the temporal relationship of COVID-19 mortality in the European countries in the 1st year of [...] Read more.

Previous studies reported the links between the COVID-19 incidence and weather factors, but few investigated their impact and timing on mortality, at a continental scale. We systematically investigated the temporal relationship of COVID-19 mortality in the European countries in the 1st year of pandemic (March–December 2020) with (i) solar insolation (W/

m^{2}

) at the ground level and (ii) objective sky cloudiness (as decimal cloud fraction), both derived from satellite measurements. We checked the correlations of these factors within a sliding window of two months for the whole period. Linear-mixed effect modeling revealed that overall, for the European countries (adjusted for latitude), COVID-19 mortality was substantially negatively correlated with solar insolation in the previous month (std. beta −0.69). Separately, mortality was significantly correlated with the cloudiness in both the previous month (std. beta +0.14) and the respective month (std. beta +0.32). This time gap of ∼1 month between the COVID-19 mortality and correlated weather factors was previously unreported. The long-term monitoring of these factors might be important for epidemiological policy decisions especially in the initial period of potential future pandemics when effective medical treatment might not yet be available. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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18 pages, 16726 KB

Open AccessArticle

Spatial Accessibility to Healthcare Facilities: GIS-Based Public–Private Comparative Analysis Using Floating Catchment Methods

by Onel Pérez-Fernández and Gregorio Rosario Michel

ISPRS Int. J. Geo-Inf. 2025, 14(7), 253; https://doi.org/10.3390/ijgi14070253 - 29 Jun 2025

Cited by 8 | Viewed by 8020

Abstract

Healthcare accessibility is among the most critical challenges affecting millions, reflecting profound geospatial disparities in Latin America. This study aims to evaluate healthcare service geospatial accessibility patterns, comparing the geospatial coverage between public and private healthcare facilities in Santiago district, Panama. We first [...] Read more.

Healthcare accessibility is among the most critical challenges affecting millions, reflecting profound geospatial disparities in Latin America. This study aims to evaluate healthcare service geospatial accessibility patterns, comparing the geospatial coverage between public and private healthcare facilities in Santiago district, Panama. We first apply the Two-Step Floating Catchment Area (2SFCA) method and its extended variant (E2SFCA) to calculate geospatial accessibility indexes at public and private healthcare facilities. We then use Getis–Ord Gi* and Local Moran geospatial statistical analysis to identify significant clusters of high and low accessibility. The results reveal that public healthcare facilities still offer higher geospatial coverage than private healthcare facilities, with higher geospatial accessibility in the central zone and lower geospatial accessibility in the south zone of Santiago. These findings highlighted the location of new healthcare facilities in zones with lower geospatial accessibility coverage. This study provides reproducible methodological tools for other geographical contexts. It also contributes to improving decision-making and formulating public policies to reduce spatial disparities in healthcare services in Panama and other Caribbean and Latin American countries. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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38 pages, 1179 KB

Open AccessSystematic Review

Reproducible GIS-Based Evidence for Public Health and Urban Security: A Systematic Mapping and Review

by Washington Ramírez Montalvan, Ibeth Manzano Gallardo, Verónica Defaz Toapanta, Edison Espinosa Gallardo and Lucas Garcés Guayta

ISPRS Int. J. Geo-Inf. 2026, 15(1), 4; https://doi.org/10.3390/ijgi15010004 - 19 Dec 2025

Cited by 1 | Viewed by 1905

Abstract

Geographic Information Systems (GIS) are increasingly applied to public health and urban security challenges, yet current evidence remains fragmented across methods, disciplines, and regions. This study integrates Systematic Mapping (SM) and Systematic Review (SR) within a unified PICOS–SPICE framework to consolidate existing GIS-based [...] Read more.

Geographic Information Systems (GIS) are increasingly applied to public health and urban security challenges, yet current evidence remains fragmented across methods, disciplines, and regions. This study integrates Systematic Mapping (SM) and Systematic Review (SR) within a unified PICOS–SPICE framework to consolidate existing GIS-based research. From an initial corpus of 7106 records, 65 studies met all methodological and reproducibility criteria. Scientific production shows consistent growth, peaking in 2023, with research concentrated in Asia and North America and limited representation from Africa and South America. Methodologically, the literature is dominated by accessibility assessments and spatial autocorrelation, while advanced analytical models—such as Bayesian inference and machine learning—remain scarce. GIS workflows rely mainly on ArcGIS and QGIS, complemented by open-source tools, including R, Python, and SaTScan. The fused SM + SR pipeline provides a transparent and replicable structure that highlights current strengths in spatial resolution and analytical versatility while revealing persistent gaps in data openness, reproducibility, and global equity. These findings offer a consolidated evidence base to guide future GIS research and support informed decision-making in public health and urban security. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T (2nd Edition))

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