Geospatial Health最新文献

{"title":"Geospatial determinants of diabetes risk in Thailand: socioeconomic and health service factors.","authors":"Withaya Polnakoo, Wongsa Laohasiriwong, Kittipong Sonlorm","doi":"10.4081/gh.2026.1440","DOIUrl":"10.4081/gh.2026.1440","url":null,"abstract":"<p><p>Diabetes prevalence is increasing in Thailand, creating growing demands on the health system. Understanding the spatial distribution of diabetes risk and its association with socioeconomic and healthcare system factors among the diabetes risk population is critical for designing targeted prevention and intervention strategies. We examined the distribution of diabetes risk groups across provinces in Thailand with reference to the spatial association between economic, social and public health service factors based on data from the Ministry of Public Health's Health Data Center (HDC) for the year 2021. The dataset included 22,491,934 individuals across the 76 provinces as well as social, economic and public health services. The methods included Local Indicators of Spatial Association (LISA), Ordinary Least Squares (OLS), Spatial Lag Model (SLM) and Spatial Error Model (SEM). Explanatory variables included average night-time light intensity, average monthly income, hospital-to-population ratio and proportion of the population with health insurance. Major clusters of High-High (HH) diabetes risk were identified by LISA mainly located in the North of Thailand. In all models, the direction and significance of the associations were consistent (p<0.001 for all variables investigated and p<0.01). R2=0.47. The SLM gave the best fit, capturing spatial spill-over effects. Higher night-time light intensity (coefficient = -85.70, p<0.05) and higher monthly income (coefficient = -0.079, p<0.001) were negatively associated with diabetes risk. These inverse relationships implied that greater urbanization and higher socio-economic standing may protect against diabetes risk, possibly through improved access to health infrastructure, improved health education and preventive services. Conversely, the higher hospital-to-population ratios (coefficient = 572.28, p<0.001) and the larger proportions of Civil Servant Medical Benefits Scheme (CSMBS) coverage (coefficient = 226.46, p<0.001) the higher diabetes risk. These counterintuitive findings likely reflect reverse causation, in which provinces with higher disease burden or poor health attract more resources of health care and have increased insurance coverage, a pattern consistent with healthcare service distribution responding to existing health needs rather than preventing occurrence of disease.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148363889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial distribution and predictive risk of perpetuation of non-typhoidal salmonellosis in poultry farms and human communities: meta-analysis of data from Nigeria.","authors":"Abdullahi O Sanni, Annelize Jonker, Olatunji O Johnson, Ezra Gayawan, Aminu Shittu, Olubunmi G Fasanmi, Oluwawemimo A Adebowale, Folorunso O Fasina","doi":"10.4081/gh.2026.1316","DOIUrl":"10.4081/gh.2026.1316","url":null,"abstract":"<p><p>To gain insight into the common pathogenic, bacterial zoonosis represented by Salmonella infections in poultry and humans, we acted to determine salmonellosis prevalence in poultry and humans in Nigeria mapping hotspots. Using multi-sourced data, we conducted a meta-analysis to determine national and sub-national prevalence of salmonellosis in poultry from 2000 until 2020. Bayesian spatial joint modelling was used to map Non-Typhoidal Salmonella (NTS) infections in humans and poultry using climatic and demographic predictor variables. With the overall prevalence in poultry at 31.6%, the highest state-level prevalence rates were seen in Ogun (70.2%), Lagos (61.8%), Zamfara (58.2%) and Bauchi (57.1%). The North-West, South-West and South-South regions of Nigeria have the highest regional-level prevalence in poultry amounting to 38.5%, 36.9% and 33.6%, respectively. Thirteen states have higher than the average national prevalence (31.6%). While we found a negative association between NTS in humans and in poultry, the prevalence of diarrhoea in humans positively predicted salmonellosis in poultry. Not surprisingly, poultry populations positively predicted salmonellosis in other poultry populations. Higher numbers of human cases were predicted in the North, with more poultry cases in the South and in some North-Eastern states. The observed human NTS-poultry salmonellosis correlation is counterfactual to logic and plausibility as high poultry density and contamination in poultry are expected to predict human infection. The outcome pointed to under-reporting linked to self-treatment, under-testing in the public health and veterinary laboratory and lack of uniform primary healthcare services, particularly in under-served areas of Nigeria. Salmonellosis continues to be a serious burden, and provision of better health data is needed.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146183604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reduction of latency in geospatial analysis of air quality: a classical modelling approach inspired by quantum principles.","authors":"Hooshang Eivazy","doi":"10.4081/gh.2026.1409","DOIUrl":"10.4081/gh.2026.1409","url":null,"abstract":"<p><p>Inspired by conceptual principles from quantum information theory, a novel classical approach to address temporal delays in spatial data analysis is presented. Current geospatial services face latency challenges due to complex processing chains, which motivate an investigation of whether the quantum-inspired paradigm could offer efficiency gains when implemented using classical hardware. A framework is proposed that incorporates three metaphors derived from quantum concepts: i) application of bit-like representation that mimics Qubit superposition to handle data uncertainty probabilistically; ii) use of probabilistic distributions for handling data uncertainty; and iii) creation of efficient data linkages by establishing pre-computed spatial correlations as an analogue to quantum entanglement. This model suggests potential temporal improvements while acknowledging current classical computing limitations. The proof-of-concept was tested on urban air quality monitoring, integrating data from fixed stations and mobile sensors. Simulation results indicated potential latency reduction while maintaining analytical accuracy (mean error <5.2% in controlled tests). Compared to the standard classical methods, the quantum-inspired metaphor showed efficiency improvements in theory when scaled to appropriate problem sizes, with simulated refresh rates of 250 milliseconds. Error analysis support the usefulness of the system for environmental health applications running on existing classical infrastructure. This research contributes: i) a framework for using quantum- inspired metaphors to address temporal challenges in geospatial analysis; ii) a simulation prototype for air quality monitoring; and iii) preliminary evidence of potential advantages from a bio-inspired approach in GIS processing. The technique may prove valuable for time-sensitive applications with today's technology and could inform future designs for potential quantum computing implementations.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148363999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial inequalities in cancer with special reference to lung cancer across Europe and their implications for environmental health policy.","authors":"Dimitrios Ntokos","doi":"10.4081/gh.2026.1453","DOIUrl":"10.4081/gh.2026.1453","url":null,"abstract":"<p><p>This study investigates spatial disparities in cancer and lung-cancer mortality across Europe through an integrative geospatial epidemiological framework. Using age-standardised Eurostat mortality data for 2022 at the NUTS-2 level, we combine Getis-Ord Gi* and Anselin Local Moran's I to detect statistically significant hot/cold spots, while multivariate regressions incorporate environmental and topographic predictors. Results reveal pronounced east-west and urban-rural gradients: persistent high-mortality clusters span Central and Eastern Europe, where historical industrialisation, elevated smoking prevalence, and structural healthcare gaps converge. By contrast, Southern European regions - Portugal, western Spain, and southern Greece - are associated with lower observed mortality levels, plausibly reflecting favourable behavioural profiles, environmental conditions, and healthcare accessibility. Spatial outliers identify territories where localised factors, such as air-pollution peaks or differential diagnostic capacity, modify broader regional patterns. Overall, the findings highlight geography as a structuring context for exposure, vulnerability, and access to care, rather than as a direct causal driver of cancer risk, and demonstrate the value of spatial epidemiology for territorial health governance, environmental monitoring, and urban planning. Policy relevance is twofold. First, the evidence supports region-specific interventions aligned with the Sustainable Development Goals (SDG) - especially SDG 3 (health), SDG 10 (reduced inequalities), and SDG 11 (sustainable cities). Second, the spatial outputs provide a robust empirical basis for informing the health-equity ambitions of Europe's Beating Cancer Plan and the environmental-justice agenda of the European Green Deal. By bridging granular geospatial evidence with EU-wide priorities, the study underscores the need for place-based, equity-oriented frameworks in cancer prevention and control across heterogeneous European landscapes.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147678949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial assessment of primary healthcare centres in Jeddah, Saudi Arabia.","authors":"Abdulkader A Murad, Mohaimin Azmain","doi":"10.4081/gh.2026.1463","DOIUrl":"10.4081/gh.2026.1463","url":null,"abstract":"<p><p>Rapid urban growth has increased concerns about spatial equity in access to Primary Healthcare Facilities (PHCs), particularly in contexts where proximity-based assessments may overestimate effective access by overlooking population demand and service capacity. This study evaluates district-level accessibility and equity of PHCs in Jeddah, Saudi Arabia using a capacity-sensitive Modified Two-Step Floating Catchment Area (M2SFCA) framework incorporating population weighting, distance decay and bed capacity. Network-based service area analysis was used to define catchment thresholds, while origin-destination cost matrices supported accessibility indexing. Spatial patterns were examined using Global Moran's I, and distributional equity was assessed through coefficient of variation, percentile ratio, accessibility shares, Gini coefficient and Lorenz curves. A planning-oriented location-allocation model evaluated a scenario-based PHC expansion. Results show that although approximately 69% of the urban area lies within nominal PHC catchments, baseline accessibility exhibits noticeable spatial inequities, with near-zero access in several peripheral districts and significant spatial clustering (Moran's I = 0.398). The proposed scenario introducing four PHCs with varied capacity produced systematic improvements in underserved areas. The percentage ratio declined sharply from 81.34 to 9.13, demonstrating substantial disparities between the highest and lowest-access districts. This increased the accessibility share of the bottom 40% of the population, and lowered overall inequality from 0.191 to 0.172 while slightly weakening spatial clustering. The findings demonstrate that capacity-aware accessibility modelling integrated with planning scenarios provides policy-relevant insights for improving spatial equity in PHC provision and is transferable to other rapidly urbanizing urban contexts.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147312783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The contrary Russian flu: London 1890-1892.","authors":"Walter Peterson","doi":"10.4081/gh.2026.1428","DOIUrl":"10.4081/gh.2026.1428","url":null,"abstract":"<p><p>Influenza epidemics tend to impact the poorest populations living in dense, unhealthy conditions more than the wealthier living in healthier, less dense surroundings. This study shows how the relationship between influenza mortality and the wealth of London's population during the Russian Flu pandemic of the early 1890's contradicts this conventional wisdom. This analysis examines London's 1890, 1891 and 1892 epidemic waves statistically and geographically, comparing wave flu mortality to population wealth, density and healthiness metrics. Correlation analysis shows that flu mortality directly correlates with wealth in all three waves; and inversely correlates with both population healthiness and density metrics. Some deficiencies exist in the 130-year-old data that pre- clude applying 21st-century rigor to the data analysis. For example, the causative agent of the flu was unknown at the time causing significant misidentification of causes of deaths. Nevertheless, analysis of the spatial association of flu mortality with population wealth using Lee's L statistic shows areas of both high mortality and high wealth in the wealthy areas east of the City of London, supporting the counterintuitive results of London's experience. This study does not seek to explain the reasons for these unexpected outcomes; however, the results suggest that today's metropolitan and regional planning authorities need to account for unexpected nuances in contingency plans for potential epidemics based upon best practice recommendations from appropriate national authori- ties. These plans need to consider previous local experience and must have a mechanism/process in place to detect and react to observed departures from the 'expected.'</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146222246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Snakebite epidemiology in the State of Mexico, Mexico 2003-2024.","authors":"Aldo Gómez-Benitez, Erika Adriana Reyes-Velázquez, Edgar Oviedo-Hernández, Laura Sonia Arzate-Garay, Justin Lloyd Rheubert, Oswaldo Hernández-Gallegos","doi":"10.4081/gh.2026.1468","DOIUrl":"10.4081/gh.2026.1468","url":null,"abstract":"<p><p>In the State of Mexico, several venomous snakes have low median lethal doses, which therefore pose serious health risks. We anal- ysed the epidemiology of snakebites from 2003 to 2024 and examined their relationship with demographic, socioeconomic, and bio- logical factors. Incidence rates and demographic characteristics were calculated, and Getis-Ord Gi* statistics were used to identify snakebite hotspots. We also applied Non-Metric Multi-Dimensional Scaling (NMDS) to explore associations between hotspot cate- gories and socioeconomic conditions. The potential distribution of 14 venomous snake species was modelled to estimate venomous snake diversity across municipalities. A total of 3,972 cases were reported, with an increasing trend over time. Most bites occurred in summer, affecting mainly males aged 25-44. Hotspot analysis identified 27 municipalities as hotspots, 50 as not significant and 48 as coldspots. Southern municipalities showed higher snakebite incidence. Coldspot areas had higher educational attainment and greater employment in services and tertiary sectors, despite similar snake diversity to hotspots. These findings can guide public health strategies, particularly regarding the allocation of antivenoms in regional hospitals.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian spatial Durbin modelling of stunting prevalence across Indonesian districts.","authors":"Ferra Yanuar, Yudiantri Asdi, Sandi Sandi, Aidinil Zetra, Fenni Kurnia Mutiya, Ade Suzana Eka Putri","doi":"10.4081/gh.2026.1441","DOIUrl":"10.4081/gh.2026.1441","url":null,"abstract":"<p><p>Stunting remains a significant public health concern in Indonesia, characterized by wide regional disparities and persistent prevalence in rural and underserved communities. This study applies the Bayesian Spatial Durbin Model (BSDM) to analyze the spatial distribution and interregional dynamics of childhood stunting across 31 provinces in Indonesia. District level data on stunting prevalence were obtained from the community-based health survey RISKESDAS survey of 2023, focusing on three programmatically salient covariates: the proportion of households with adequate housing, the proportion of children under five who received complete basic immunization and the proportion of infants aged 0-5 months who were exclusively breastfed. The BSDM quantifies direct and spatial spill-over effects while accounting for spatial autocorrelation and parameter uncertainty. Results indicate that adequate housing and complete immunization are associated with lower stunting prevalence and that exclusive breastfeeding are directionally protective. The study finds that spatially coordinated investments in housing quality, immunization outreach and infant feeding support accelerated stunting reduction.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148018378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonlinear analysis of factors influencing public health in China based on machine learning.","authors":"Dehong Sun, Hui Wang","doi":"10.4081/gh.2026.1450","DOIUrl":"10.4081/gh.2026.1450","url":null,"abstract":"<p><p>Public health is a key component of the United Nations Sustainable Development Goals (SDGs) and is central to the all-round development of individuals. Based on panel data from 31 provinces in China between 2010 and 2023, this article adopts the Population Mortality Rate (PMR) as a measure of public health and employs the Generalized Additive Model (GAM) from machine learning to systematically investigate the nonlinear effects of multidimensional factors-including medical resources, environmental pollution, socioeconomic conditions, and technology-on public health. The results of the study show that China's PMR exhibits an overall upward trend, with a spatially uneven distribution and significant regional disparities, as mortality rates in the central and western regions are generally higher than those in the eastern coastal provinces. All influencing factors show significant associations with the PMR. The effects of all influencing factors on mortality exhibit complex nonlinear characteristics, with their impacts varying considerably across different value ranges. Specifically, the influence of medical resources exhibits critical thresholds, such as the Number of Urban Practicing (assistant) Physicians per 10,000 people (NUPP) reaching its maximum health benefit at approximately 40; while the relationship between environmental indicators and mortality reveals potential complex confounding mechanisms, as evidenced by the negative association observed between Sulphur Dioxide Emissions (SDE) and mortality rates within the observed range; whereas the health benefits of basic resources and developmental factors, such as Per Capita Water Resources (PCWR), stabilize after crossing a specific threshold (20,000 cubic meters per person). Finally, some practical policy recommendations are put forward.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147470344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accessibility evaluation of urban basic public service facilities for persons with disabilities: a case study of central Beijing.","authors":"Ying Sun, Xiangfeng Li, Zhizhe Sun, Weiyang Jia","doi":"10.4081/gh.2026.1460","DOIUrl":"10.4081/gh.2026.1460","url":null,"abstract":"<p><p>In urban planning practice, urban basic public service facilities are essential spatial carriers for advancing social fairness and public wellbeing. Traditional methods of resource allocation that are primarily motivated by supply efficiency are facing new difficulties as China's urban spatial structure shifts from incremental expansion to stock optimization. As fundamental tenets of modern urban planning, equity and justice demand a more inclusive reevaluation of facility allocation, especially with regard to service accessibility and equitable for vulnerable populations. Beijing was chosen as the study region for this investigation, and information on public service facilities for people with disabilities was gathered from 6,080 residential neighborhoods. Accessibility was assessed using an integrated GIS-based analytical framework that combined kernel density analysis, surface-based hotspot detection, network analysis, and inverse distance weighting. This framework was based on the 15-minute living-circle concept and the actual walking speed of people with disabilities. A gap in previous research, which frequently depends on aggregated administrative units and ignores fine-scale spatial inequalities, is filled by the inclusion of surface-based hotspot detection, which enables accurate identification of high-accessibility clusters and peak areas. With high-value clusters concentrated in particular districts and obvious spatial mismatches between facility layouts and anticipated service needs, the results show notable differences in accessibility and facility distribution across service categories. This study suggests methods to increase facility coverage, optimize spatial organization, and improve street-level accessibility in order to overcome unequal facility distribution and insufficient street-network support. The results highlight a change from basic coverage to user-centered service quality and structural adaptability, which supports inclusive urban growth and the sustainable use of land resources.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146108826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}