International Journal of Health Geographics最新文献

{"title":"The effect of recurrent mobility on air pollution exposure and mortality burden in Catalonia.","authors":"Alejandro Navarro-Martínez, Meriem Hajji, Jan Mateu Armengol, Albert Soret, Miguel Ponce-de-León, Alfonso Valencia","doi":"10.1186/s12942-025-00410-0","DOIUrl":"10.1186/s12942-025-00410-0","url":null,"abstract":"<p><strong>Background: </strong>Air pollution exposure is a leading health risk mainly due to its detrimental respiratory and cardiovascular effects. Ambient air quality varies greatly across time and space, most anthropogenic pollutants being higher in cities than rural areas. Residents of rural areas who commute to cities for work are also exposed to the air pollution there. Therefore, exposure assessments that neglect population mobility produce biased estimates.</p><p><strong>Methods: </strong>In this study, we quantify the effect of recurrent mobility on long-term air pollution exposure and its attributable mortality for the pollutants NO <math><mmultiscripts><mrow></mrow> <mn>2</mn> <mrow></mrow></mmultiscripts> </math> , O <math><mmultiscripts><mrow></mrow> <mn>3</mn> <mrow></mrow></mmultiscripts> </math> , PM <math><mmultiscripts><mrow></mrow> <mrow><mn>2.5</mn></mrow> <mrow></mrow></mmultiscripts> </math> and PM <math><mmultiscripts><mrow></mrow> <mn>10</mn> <mrow></mrow></mmultiscripts> </math> , for 584 districts of Catalonia (Spain) in 2022. We use anonymized phone-based mobility data to infer the dynamic distribution of the residents of each district among the different areas, considering only recurrent mobility. We also utilise finely-resolved air quality data for the four pollutants from the bias-corrected CALIOPE model, projected over the districts. We integrate dynamic population with the air quality to calculate dynamic exposure estimates, and compute the effect of mobility on long-term exposure with respect to the static estimates. We also calculate the mortality attributable to each pollutant and the effect of mobility.</p><p><strong>Results: </strong>Considering the four pollutants, between 75.9% and 86.3% of the districts present significant effects of mobility on exposure. Rural areas surrounding cities display increased exposures to NO <math><mmultiscripts><mrow></mrow> <mn>2</mn> <mrow></mrow></mmultiscripts> </math> , PM <math><mmultiscripts><mrow></mrow> <mrow><mn>2.5</mn></mrow> <mrow></mrow></mmultiscripts> </math> and PM <math><mmultiscripts><mrow></mrow> <mn>10</mn> <mrow></mrow></mmultiscripts> </math> , and decreased exposures to O <math><mmultiscripts><mrow></mrow> <mn>3</mn> <mrow></mrow></mmultiscripts> </math> . The magnitude of these effects stays under 1 <math><mi>μ</mi></math> g/m <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>3</mn></mmultiscripts> </math> when considering the complete populations, but they increase up to 8.3 <math><mi>μ</mi></math> g/m <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>3</mn></mmultiscripts> </math> of change when we focus on the mobile populations. However, the effects on attributable mortality are negligible.</p><p><strong>Conclusions: </strong>Our work evidences the impact of cities on the air pollution exposure of people living far away from them, made possible by recurrent mobility. Our results show that correcting exposure profiles by mobility might not have","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"19"},"PeriodicalIF":3.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12306083/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144734356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological epidemiology insights into clonorchiosis endemicity in Guangxi, China and Vietnam: a comprehensive machine learning analysis.","authors":"Jin-Xin Zheng, Hui-Hui Zhu, Shang Xia, Men-Bao Qian, Robert Bergquist, Hung Manh Nguyen, Xiao-Nong Zhou","doi":"10.1186/s12942-025-00404-y","DOIUrl":"10.1186/s12942-025-00404-y","url":null,"abstract":"<p><strong>Background: </strong>Clonorchis sinensis, the liver fluke responsible for clonorchiosis, presents a persistent public health burden in Guangxi (Southern China) and Vietnam. Its transmission is influenced by a complex interplay of ecological, climatic, and socio-cultural factors.</p><p><strong>Methods: </strong>We compiled infection occurrence data from systematic literature reviews and national surveys conducted between 2000 and 2018. Environmental and climatic predictors were obtained from long-term raster datasets. Machine learning models, including logistic regression and tree-based ensemble methods, were used to assess associations between predictor variables and C. sinensis presence. Partial dependence plots were employed to refine predictor selection and explore marginal effects.</p><p><strong>Results: </strong>Raw freshwater fish consumption was identified as the most influential predictor. In Guangxi, 54.9% of counties reported raw fish consumption, compared to 31.7% in Vietnam. Logistic regression achieved the highest predictive accuracy (AUC = 0.941). Climatic comparisons showed that Vietnam had a higher annual mean temperature (Bio1: 23.37 °C vs. 20.86 °C), greater temperature seasonality (Bio4: 609.33 vs. 464.92), and higher annual precipitation (Bio12: 1731.64 mm vs. 1607.56 mm) than Guangxi, contributing to spatial differences in endemicity. High-risk zones were concentrated along the China-Vietnam border, suggesting the need for geographically targeted interventions.</p><p><strong>Conclusion: </strong>The findings underscore the combined influence of ecological and behavioral factors on C. sinensis transmission. The predictive modeling framework offers valuable insights for surveillance planning and cross-border disease control, reinforcing the role of ecological epidemiology in guiding parasitic disease prevention strategies.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"18"},"PeriodicalIF":3.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12302698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144734444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GPS tracking methods for spatiotemporal air pollution exposure assessment: comparison and challenges in study implementation.","authors":"Kalliopi Kyriakou, Benjamin Flückiger, Danielle Vienneau, Nicole Probst-Hensch, Ayoung Jeong, Medea Imboden, Aletta Karsies, Oliver Schmitz, Derek Karssenberg, Roel Vermeulen, Gerard Hoek, Kees de Hoogh","doi":"10.1186/s12942-025-00405-x","DOIUrl":"10.1186/s12942-025-00405-x","url":null,"abstract":"<p><strong>Background: </strong>Epidemiological studies investigating long-term health effects of air pollution typically only consider the residential locations of the participants, thereby ignoring the space-time activity patterns that likely influence total exposure. This paper, part of a study in which residential-only and mobility-integrated exposures were compared in two tracking campaigns, reflects on GPS device choice, privacy, and recruitment strategy.</p><p><strong>Methods: </strong>Tracking campaigns were conducted in Switzerland and the Netherlands. Participants completed a baseline questionnaire, carried a GPS device (SODAQ) for 2 weeks, and used a smartphone app for a time activity diary. The app also tracked GPS, albeit less frequently. Tracks were combined with air pollution surfaces to quantify NO₂ and PM_2.5 exposure by activity.</p><p><strong>Results: </strong>In Switzerland, participants were recruited from the COVCO-Basel cohort (33% recruitment rate; 489 of 1,475). In the Netherlands, -random recruitment was unsuccessful (1.4% rate; 41 of 3,000). Targeted recruitment with leaflets and a financial incentive (25 Euro voucher) increased participation to 189. Comparisons between smartphone app and SODAQ device data showed moderate to high correlations (R2 > 0.57) for total NO₂ exposure and NO₂ exposure at home in both study areas. Activity-specific correlations ranged from 0.43 to 0.63. PM_2.5 correlations in Switzerland were moderate to high, but lower in the Netherlands (R² = 0.28-0.58), due to smaller spatial contrast in observed PM_2.5 levels (RMSE < 0.68 µg/m³).</p><p><strong>Conclusions: </strong>Tracking can be effectively conducted using a mobile app or GPS device. The app's low-frequency GPS readings (every 3-4 min) were sufficient for long-term air pollution exposure assessment. For finer-scale readings, a dedicated GPS device is recommended. Tracking campaigns are crucial for studying personal exposure to air pollution but face challenges due to low recruitment rates and strict privacy regulations. Leveraging an existing cohort can improve recruitment, while targeted leaflet distribution with financial incentives can enhance participation in studies without a pre-recruited group.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"17"},"PeriodicalIF":3.0,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12296587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144718936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When buildings become barriers: assessing the impact of building height on the equality of emergency medical services accessibility-a dual-trip study in Wuhan, China.","authors":"Weicong Luo, Yuanyuan Zhu, Zihan Yang, Fei Wang, Yue Wang","doi":"10.1186/s12942-025-00406-w","DOIUrl":"10.1186/s12942-025-00406-w","url":null,"abstract":"<p><strong>Background: </strong>As urbanization accelerates, the height of urban buildings continues to rise, which may influence the provision of Emergency Medical Services (EMS). However, a current limitation is that related studies often neglect the impact of spatial variations in building height on EMS accessibility equality. Most scholars have focused primarily on EMS road travel-either the Departure Road Trip (DRT) or the Transport Trip (TT)-while overlooking the effects of building height on the in-building EMS trip, known as the Patient Access Trip (PAT).</p><p><strong>Methods: </strong>EMS accessibility was measured using a proximity-based method and a Gaussian two-step floating catchment area (G-2SFCA) model under two scenarios: Scenario 1 considered only DRT, whereas Scenario 2 incorporated both DRT and PAT influenced by building heights. DRT travel times were simulated using Baidu Map's Application Programming Interface (API), and PAT times were calculated based on building elevator/stairs characteristics. Accessibility equality was assessed using multi-ring buffer analysis, Lorenz curves, and Gini coefficients.</p><p><strong>Results: </strong>According to the empirical study in Wuhan, China, first, the spatial variations in building height was evident across the city. The building heights in city centre and sub-centres are generally taller compared to those in suburban areas. Second, the variations in building height can obviously affect EMS accessibility. However, the impact of building height on EMS accessibility varies across different regions. The effect is particularly pronounced in sub-centres located around 14 km from the city centre, whereas it is relatively limited in suburban areas. Third, the incorporation of spatial disparities in building height into EMS accessibility modeling reveals increased inequality in EMS provision across the city.</p><p><strong>Conclusion: </strong>Spatial disparities in building heights across a city significantly influence EMS accessibility inequality. Given the widespread differences in building heights worldwide, this study provides valuable findings for healthcare policymakers to improve EMS systems.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"16"},"PeriodicalIF":3.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281799/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impacts of various green space types on the adiposity of undergraduate students: a nationwide quasi-experimental study.","authors":"Jing Wen, Yi Lu, Xiangfen Cui, Weina Kong, Kai Shentu, Haoran Yang","doi":"10.1186/s12942-025-00402-0","DOIUrl":"10.1186/s12942-025-00402-0","url":null,"abstract":"<p><p>Green spaces provide diverse health benefits, and provision of green spaces is often linked to lower incidences of adiposity. Undergraduates, who are at a transitional stage of development, represent a critical population for obesity prevention. However, recent studies suggest that the health effects of green space may vary by type. Furthermore, inferring any causal relationship between green spaces and adiposity using a cross-sectional research design remains challenging. To address these issues, this study utilized a large, representative sample of 21,990 undergraduates from 89 universities across 29 provinces in China, and employed a quasi-experimental approach to explore the impacts of specific green space types on body mass index (BMI). Propensity score matching was used to make the students who were influenced by green spaces comparable to those who were not. A difference-in-differences model was applied to estimate the causal effects of three types of green spaces (trees, bushes, and grass) on BMI. To further explore the underlying mechanisms, we examined two potential mediators: energy expenditure (physical activity) and energy intake (unhealthy food consumption). The results revealed that trees had a negative impact on BMI, whereas bushes and grass had no significant effect. Physical activity serves as a significant mediator linking tree exposure to adiposity changes, while unhealthy food intake showed no statistically significant mediation effect. In the stratified analysis, trees had significantly negative effects only on males. These findings highlight the importance of distinguishing green space types and provide causal evidence linking tree exposure to reduced BMI among undergraduates.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"15"},"PeriodicalIF":3.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12273302/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The development and validation of Spatial Methodology Appraisal of Research Tool (SMART): a concept mapping study.","authors":"Sarah M Wood, Anna Wong Shee, Laura Alston, Kevin Mc Namara, Alex Donaldson, Neil T Coffee, Vincent L Versace","doi":"10.1186/s12942-025-00401-1","DOIUrl":"10.1186/s12942-025-00401-1","url":null,"abstract":"<p><p>This study developed and validated the Spatial Methodology Appraisal of Research Tool (SMART) using group concept mapping with discipline experts. The 16-item tool comprises four domains: (1) methods preliminaries, (2) data quality, (3) spatial data problems, and (4) spatial analysis methods. Validity testing demonstrated excellent content validity and expert agreement. Future studies will assess its usability and reliability to ensure consistent results. Its application in spatial epidemiology and health geography will enable more rigorous and transparent evidence synthesis. This contribution represents a significant step forward in improving the standards of quality appraisal in spatial research.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"14"},"PeriodicalIF":3.0,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144192380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the impact of building footprint dataset choice for health programme planning: a case study of indoor residual spraying (IRS) in Zambia.","authors":"Heather R Chamberlain, Derek Pollard, Anna Winters, Silvia Renn, Olena Borkovska, Chisenga Abel Musuka, Garikai Membele, Attila N Lazar, Andrew J Tatem","doi":"10.1186/s12942-025-00398-7","DOIUrl":"10.1186/s12942-025-00398-7","url":null,"abstract":"<p><strong>Background: </strong>The increasing availability globally of building footprint datasets has brought new opportunities to support a geographic approach to health programme planning. This is particularly acute in settings with high disease burdens but limited geospatial data available to support targeted planning. The comparability of building footprint datasets has recently started to be explored, but the impact of utilising a particular dataset in analyses to support decision making for health programme planning has not been studied. In this study, we quantify the impact of utilising four different building footprint datasets in analyses to support health programme planning, with an example of malaria vector control initiatives in Zambia.</p><p><strong>Methods: </strong>Using the example of planning indoor residual spraying (IRS) campaigns in Zambia, we identify priority locations for deployment of this intervention based on criteria related to the area, proximity and counts of building footprints per settlement. We apply the same criteria to four different building footprint datasets and quantify the count and geographic variability in the priority settlements that are identified.</p><p><strong>Results: </strong>We show that nationally the count of potential priority settlements for IRS varies by over 230% with different building footprint datasets, considering a minimum threshold of 25 sprayable buildings per settlement. Differences are most pronounced for rural settlements, indicating that the choice of dataset may bias the selection to include or exclude settlements, and consequently population groups, in some areas.</p><p><strong>Conclusions: </strong>The results of this study show that the choice of building footprint dataset can have a considerable impact on the potential settlements identified for IRS, in terms of (i) their location and count, and (ii) the count of building footprints within priority settlements. The choice of dataset potentially has substantial implications for campaign planning, implementation and coverage assessment. Given the magnitude of the differences observed, further work should more broadly assess the sensitivity of health programme planning metrics to different building footprint datasets, and across a range of geographic contexts and health campaign types.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"13"},"PeriodicalIF":3.0,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12103797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MaskMyPy: python tools for performing and analyzing geographic masks.","authors":"David Swanlund, Nadine Schuurman","doi":"10.1186/s12942-025-00399-6","DOIUrl":"10.1186/s12942-025-00399-6","url":null,"abstract":"<p><strong>Background: </strong>Geographic masking is an important but under-utilized technique for protecting and disseminating sensitive geospatial health data. Geographic masks work by displacing static point locations such that the people those locations describe cannot be identified, while at the same time preserving important spatial patterns for analysis. Unfortunately, there is a lack of available tooling surrounding geographic masks which we believe creates an unnecessary barrier towards the adoption of these techniques. As such, this article presents a set of tools for performing, evaluating, and developing geographic masks, called MaskMyPy.</p><p><strong>Results: </strong>MaskMyPy is an open-source Python package that includes functions for performing geographic masks, including donut, street, location swapping, and Voronoi masks. It also includes a range of tools for evaluating the results of these masks, both with regard to privacy and information loss. Finally, it includes a special class called the 'Atlas' that aims to dramatically streamline mask execution and evaluation. We conducted a short case study to illustrate the power of MaskMyPy in geographic masking research, and in doing so showed that mask performance can range widely due solely to randomization. As such, we recommend that masking researchers test their masks repeatedly across a variety of test datasets.</p><p><strong>Conclusion: </strong>MaskMyPy makes it easy to apply a variety of geographic masks to a set of sensitive points and then measure which mask provided the most privacy while suffering the least information loss. We believe this style of tooling is important to not only make geographic masks accessible to non-experts, but to enable expert users to better interrogate the masks they develop, and in doing so drive the geographic masking discipline forward.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"12"},"PeriodicalIF":3.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12065331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying pharmacy gaps: a spatiotemporal study of multimodal accessibility throughout the day.","authors":"Cláudia M Viana, Luis Encalada-Abarca, Jorge Rocha, David S Vale","doi":"10.1186/s12942-025-00396-9","DOIUrl":"10.1186/s12942-025-00396-9","url":null,"abstract":"<p><strong>Background: </strong>Accessibility to community pharmacies is crucial for ensuring timely access to medications and essential health services. While accessibility to community pharmacies is critical, disparities driven by temporal and spatial factors persist, resulting in inequities in healthcare access. This study aims to comprehensively assess spatiotemporal and multimodal accessibility to community pharmacies in Lisbon, highlighting the influence of transport modes and time of day on accessibility disparities.</p><p><strong>Data and methods: </strong>The study employed a methodology that considered five daily time slots and two modes of transport-walking and public transport-to evaluate accessibility to community pharmacies. Data was sourced from road and pedestrian networks, Google API, and GTFS data. Descriptive statistics and spatial analysis were utilized to assess travel time and accessibility disparities across different regions of Lisbon. The analysis focused on both the percentage of residents able to access pharmacies within 10 min and the total number of pharmacies accessible.</p><p><strong>Results: </strong>ndings reveal significant temporal variations in accessibility, with public transport consistently improving access compared to walking. Accessibility peaks in the evening (6-7 PM), when 83.3% of residential buildings are within a 10-min walking distance of a pharmacy, and 92.7% are reachable by public transport. In contrast, early morning hours (4-5 AM) show the lowest accessibility, with only 8.9% of buildings accessible by walking and 16.1% by public transport. During the daytime (8-9 AM), notable disparities emerge across the city: public transport enhances access in the southwest, northwest, and central areas, while limited pharmacy opening hours constrain accessibility in the north and southeast, where only 108 of 258 pharmacies are operational. Finally, travel time to pharmacy services for city residents highlight significant spatial and temporal disparities in pharmacy accessibility, emphasizing the role of transport modes and service hours in shaping urban healthcare access.</p><p><strong>Conclusions: </strong>This study underscores the importance of addressing both temporal and spatial factors to ensure equitable accessibility to community pharmacies. The findings suggest the need for targeted policies to improve public transport services during off-peak hours and to extend pharmacy operating hours. Future research should focus on comparative studies across different urban contexts and incorporate more granular data to better understand accessibility to urban services.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"11"},"PeriodicalIF":3.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12051350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementing large language model and retrieval augmented generation to extract geographic locations of illicit transnational kidney trade.","authors":"Zifu Wang, Meng-Hao Li, Patrick Baxter, Olzhas Zhorayev, Jiaxin Wei, Valerie Kovacs, Qiuhan Zhao, Chaowei Yang, Naoru Koizumi","doi":"10.1186/s12942-025-00397-8","DOIUrl":"10.1186/s12942-025-00397-8","url":null,"abstract":"<p><strong>Background: </strong>Illicit kidney trade networks, operating globally, involve intricate interactions among various players, most notably buyers, sellers, brokers, and surgeons. A comprehensive understanding of these trade networks is, however, hindered by the lack of systematically amassed data for analysis. Further, extracting the geographic locations of buyers, sellers, brokers, transplant surgeons, and medical facilities in all relevant publications often involves extensive, time-consuming, manual labelling that is very costly. Although current techniques such as Named Entity Recognition (NER) tools can potentially automate the process, they are limited to identifying country names and often fail to associate the roles (i.e., offering buyer, seller, broker and/or surgery) that each country played.</p><p><strong>Methods: </strong>This study employed state-of-the-art technologies, including Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-Trained Transformers (GPT) model Llama3.3 from Meta in developing a kidney trade country database. We first extracted news articles reporting illicit kidney trade from the LexisNexis database (2000-2022). BERT and Llama3.3 with chain-of-thought prompt tuning strategies were then applied to the materials to determine the relevance of articles to the illegal kidney trade and to identify the roles those different countries played in kidney trade cases over the past 23 years. The specific country classes recorded in the final kidney trade database included: a) countries of origin for kidney sellers; b) countries of origin of kidney buyers; c) countries performing illegal transplant surgeries; and d) countries of origin of organ trafficking brokers.</p><p><strong>Results: </strong>The BERT classification model achieved an accuracy of 88.75%, ensuring that only relevant articles were analyzed. Additionally, the Llama3.3-70B model with chain-of-thought prompt tuning strategies extracted location-based roles with an accuracy of 86.30% for sellers, 88.89% for buyers, 93.33% for brokers, and 95.93% for surgeries, supporting these observed patterns. We observed in the final database that the kidney trade networks change and evolve dynamically where the primary role played by each country (as a host of either sellers, buyers or surgeries) change over time. About half of the top 10 countries playing each role gets replaced by other countries within a decade. The final database also demonstrated that developing countries were more likely to be a host of kidney sellers while that played by developed countries was a host of kidney buyers.</p><p><strong>Conclusion: </strong>The current study developed a geospatial database describing transnational kidney trade country networks over the past two decades. The new approach for geographic location extraction that is more precise compared to conventional NER and machine learning methods.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":"24 1","pages":"10"},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12039186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}