Geohealth最新文献

{"title":"Mechanistic Modeling of Aedes aegypti Mosquito Habitats for Climate-Informed Dengue Forecasting","authors":"C. N. Yasanayake,&nbsp;B. F. Zaitchik,&nbsp;A. Gnanadesikan,&nbsp;L. M. Gardner,&nbsp;A. Shet","doi":"10.1029/2025GH001376","DOIUrl":"10.1029/2025GH001376","url":null,"abstract":"<p>The mosquito-borne disease dengue is sensitive to climate, in part because of the influence climate has on breeding habitats of dengue's <i>Aedes</i> mosquito vectors. Dengue risk assessment models currently leverage climate-dengue <i>statistical</i> associations, yet what remain understudied are the <i>mechanistic</i> pathways that yield different statistical relationships in different locations. We hypothesize that elucidating the mechanisms by which spatiotemporal variability in climate influences dengue incidence will improve dengue dynamics predictions across climatically distinct locations and beyond dengue's well-known seasonal cycles. We test this hypothesis by investigating a key pathway in the climate-dengue process chain: climate impacts on <i>Aedes</i> breeding habitats. We have implemented a mechanistic modeling pipeline that simulates climatic influence on habitat water dynamics and thereby on relative population size of the vector. We use this modeling pipeline, driven by meteorological data, to simulate monthly <i>Aedes</i> populations for three climatically distinct cities in Sri Lanka. We find that simulated vector abundance is plausibly associated with climate conditions and that climate drivers of vector abundance vary among locations. Moreover, tercile-tercile comparisons of dengue incidence against model variables indicate that risk assessments based on predicted vector abundance perform similarly to those based on meteorology alone—the signal of weather variability and its relationship to dengue propagates through the modeling pipeline. These results justify future testing of this modeling pipeline within a dengue risk assessment framework, where its process-based structure may be leveraged to guide proactive dengue control efforts in high-risk years and to simulate impacts of future climate conditions on dengue dynamics.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12439285/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082221","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":"Current and Future Projection of Scrub Typhus Risk Related to Land Use Change in China","authors":"Ling Han,&nbsp;Zhaobin Sun,&nbsp;Guwei Zhang,&nbsp;Yunfei Zhang,&nbsp;Hongyu Ren,&nbsp;Zhongqiu Teng,&nbsp;Jianguo Xu,&nbsp;Tian Qin","doi":"10.1029/2024GH001203","DOIUrl":"10.1029/2024GH001203","url":null,"abstract":"<p>The widespread concern surrounding the enhanced spillover risk of infectious diseases due to dramatic global land use changes has sparked significant discussion. However, the specific implications of these changes on scrub typhus, a vector-borne infectious disease facing increasing incidence and substantial expansion, remain unclear. Here, we constructed a comprehensive landscape fragmentation index (LFI), which reflects the interaction between human activities and natural habitats. Then we utilized a generalized additive model (GAM) to estimate the comprehensive and segmented impacts of LFI on scrub typhus incidence in China, grouping the results by year, land use type and fragmentation level. Additionally, we projected changes in such impacts under four shared socioeconomic pathways (SSPs), including SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Key results were: (a) The LFI exhibited a nonlinear positive correlation with scrub typhus incidence. Each 0.1 increase in the LFI was associated with a relative risk of 1.20 (95% CI:1.19–1.21) for scrub typhus. Notably, at higher fragmentation levels, scrub typhus incidence tended to decrease. (b) Forest fragmentation had the most significant impact on scrub typhus, followed by cropland fragmentation, whereas construction land fragmentation was negatively associated. (c) The future areas of elevated scrub typhus risk varied among the SSPs, but they were mainly concentrated at the interface between urban expansion and natural habitats. Our results indicate that human interference with the natural ecosystem is a critical factor for the incidence of scrub typhus. These findings are conducive to promoting ecological protection and the prevention and control of scrub typhus.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024GH001203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057934","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":"Improved High Resolution Heat Exposure Assessment With Personal Weather Stations and Spatiotemporal Bayesian Models","authors":"Eva Marquès,&nbsp;Kyle P. Messier","doi":"10.1029/2025GH001451","DOIUrl":"10.1029/2025GH001451","url":null,"abstract":"<p>Most of the United States (US) population resides in cities, where they are subjected to the urban heat island effect. In this study, we develop a method to estimate hourly air temperatures at <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>0.01</mn>\u0000 <mo>°</mo>\u0000 <mo>×</mo>\u0000 <mn>0.01</mn>\u0000 <mo>°</mo>\u0000 </mrow>\u0000 <annotation> $0.01{}^{circ}times 0.01{}^{circ}$</annotation>\u0000 </semantics></math> resolution, improving exposure assessment of US population when compared to existing gridded products. We use an extensive network of personal weather stations to capture the intra-urban variability. The uncertainty associated with this crowdsourced data set is addressed through a spatiotemporal Bayesian model implemented with the Integrated Nested Laplace Approximation-Stochastic Partial Differential Equation approach. We evaluate the model on Philadelphia (PA), New York City (NY), Phoenix (AZ), and the Triangle area (NC). These case studies span different climatic zones and urban landscapes. They cover several meteorological events including a deadly heatwave in Phoenix and a snowstorm hitting part of the US in winter 2021. We obtain an overall root mean square error of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>1.06</mn>\u0000 <mo>°</mo>\u0000 <mi>C</mi>\u0000 </mrow>\u0000 <annotation> $1.06{}^{circ}mathrm{C}$</annotation>\u0000 </semantics></math>, demonstrating the versatility of our model, and its applicability across various regions in the US. The high granularity of our model allows for the precise identification of hotspots that were previously undetected with daymet and gridMET products. Using the data generated by our method, we show that neighborhoods with high population concentration are more likely to experience elevated temperatures and prolonged hot nights, thus encouraging the use of our model for further epidemiological investigations on the impact of heat or cold stress on human health.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008001","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":"Forecasting Dengue: Evaluating the Role of Hydroclimate Information in Subseasonal to Seasonal Prediction","authors":"Maxwell R. W. Beal,&nbsp;Jorge Osorio,&nbsp;Karl Ciuoderis,&nbsp;Juan Pablo Hernandez-Ortiz,&nbsp;Paul Block","doi":"10.1029/2024GH001325","DOIUrl":"10.1029/2024GH001325","url":null,"abstract":"<p>Dengue fever is a mosquito-borne viral disease rapidly creating a significant global public health burden, particularly in urban areas of tropical and sub-tropical countries. Hydroclimatic variables, particularly local temperature, precipitation, relative humidity, and large-scale climate teleconnections, can influence the prevalence of dengue by impacting vector population development, viral replication, and human-mosquito interactions. Leveraging predictions of these variables at lead times of weeks to months can facilitate early warning system preparatory actions such as allocating funding, acquisition and preparation of medical supplies, or implementation of vector control strategies. We develop hydroclimate-based statistical forecast models for dengue virus (DENV) at 1-, 3-, and 6- month lead times for four cities across Colombia (Cali, Cúcuta, Medellín, and Leticia) and compare with standard autoregressive models conditioned on dengue case counts. Our results indicate that (a) hydroclimate-based models are particularly skillful at 3- and 6- month lead times when autoregressive models often fail, (b) sea surface temperatures are the most skillful predictor at 3- and 6- month leads and (c) application of hydroclimate models are most beneficial when average DENV incidence is low, autoregressive relationships are weak, but outbreaks may still occur.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 9","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024GH001325","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923772","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":"Physics-Based Spatial Oversampling of TROPOMI NO2 Observations to US Neighborhoods Reveals the Disparities of Air Pollution","authors":"Xiaomeng Jin,&nbsp;Zaina Merchant,&nbsp;Kang Sun","doi":"10.1029/2025GH001423","DOIUrl":"10.1029/2025GH001423","url":null,"abstract":"<p>Satellite observations provide continuous and global coverage observations of air pollutants, widely used to inform health impacts and air pollution disparities. Linking satellite retrievals with socioeconomic or health data involves matching the irregularly shaped satellite observations with administrative units. Here, we develop a physics-based approach to spatially oversample nitrogen dioxide (NO₂) retrievals from TROPOspheric Monitoring Instrument (TROPOMI) directly to United States (US) neighborhoods (i.e., block groups). The physics-based oversampling approach considers each satellite pixel as a sensitivity distribution, meaning that satellite instruments are more sensitive to the neighborhoods at the center than at the edge of the observations. We show that directly oversampling satellite observations to administrative shapes is a more accurate and computationally efficient approach than the commonly used gridding approaches, and it is advantageous for shorter temporal windows. Combining the newly developed NO₂ data set with demographic data, we find widespread racial/ethnic and income-related NO₂ disparities across the US. NO₂ disparities are even more pronounced during the most polluted days, suggesting greater acute health effects for overburdened communities. We expect that the resolution-adaptive, neighborhood-level, and GIS-compatible NO₂ data set would lower barriers of the public to access and interpret satellite observations, facilitating the actionable applications of satellite observations.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144853743","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":"Concentrations and Health Implications of As, Hg, and Cd and Micronutrients in Rice and Emissions of CH4 From Variably Flooded Paddies","authors":"Angelia L. Seyfferth,&nbsp;Matt A. Limmer,&nbsp;Brian P. Jackson,&nbsp;Benjamin R. K. Runkle","doi":"10.1029/2025GH001410","DOIUrl":"10.1029/2025GH001410","url":null,"abstract":"<p>The flooded soil conditions under which rice is typically grown are beneficial for boosting yield and decreasing herbicide inputs but may pose a food safety and environmental health risk. Flooded soils lead to reducing conditions and anaerobic metabolisms of soil microorganisms, which mobilizes arsenic from soil into soil solution, where it can be absorbed by rice roots and transported to grain. These conditions also promote the production and emission of methane (CH₄)—a potent greenhouse gas. To evaluate how water management affects metal(loid) grain concentrations and CH₄ emissions, we conducted a 2-year field study in which rice paddy water was managed under a range of soil redox conditions that spanned from flooded to non-flooded. We observed that growing rice under less flooded conditions decreased CH₄ emissions and concentrations of grain total As, grain inorganic As, grain total Hg, and grain inorganic Hg relative to flooded conditions, with more reductions observed as conditions were drier; grain organic As and Hg (MeHg) species also decreased with drier conditions particularly in Year 1. However, the driest conditions tested led to a 50%–97% increase in grain Cd concentrations that exceeded the CODEX limit and grain yield reductions as high as 25% and 40% in Year 1 and 2, respectively. While concentrations of toxic metal(loid)s could be manipulated by water management, micronutrient concentrations were similar or decreased with drier conditions, potentially increasing grain Cd bioaccessibility to humans. Because practices for rice water management are gaining momentum, more research should monitor grain Cd levels along with micronutrients.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144832659","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":"Integrating Citizen Science and Remote Sensing Data to Identify Key Environmental Factors Influencing H5N1 Avian Influenza Virus Potential Spillover Risk in the Philippines","authors":"John Oliver Sayseng,&nbsp;Ting-Wu Chuang","doi":"10.1029/2025GH001405","DOIUrl":"10.1029/2025GH001405","url":null,"abstract":"<p>Highly pathogenic avian influenza (HPAI) virus presents a serious threat to poultry and public health worldwide, with transmission dynamics shaped by avian migration patterns and environmental conditions. Recent outbreaks in the Philippines highlight the urgent need for effective control measures. While previous studies have shown the importance of waterfowl-to-poultry transmission and farm-to-farm spread, the spillover risk to local avian species remains underexplored. This study aimed to examine H5N1-HPAI outbreaks in poultry in relation to environmental factors and local avian species in the Philippines. We applied a two-step ecological niche modelling approach using maximum entropy algorithms. First, environmental variables from remote sensing images were used to predict the distribution of 10 common avian species based on citizen science data from the eBird platform. Next, these avian distribution data were combined with environmental variables to create a risk map for H5N1-HPAI outbreaks in the Philippines. The H5N1-HPAI risk model demonstrated strong predictive performance, with an AUCROC value of 0.936 ± 0.026. Key factors contributing to predicted H5N1-HPAI risk included precipitation levels, population density, and avian species such as the Eurasian Tree Sparrow and Zebra Dove. The higher risk of spillover for the two local avian species may be due to their shared similar environmental signatures with outbreak poultries. The risk map highlighted Metro Manila and Central Luzon as high-risk regions of H5N1-HPAI. This study identified the main clusters and environmental factors associated with avian influenza outbreaks in poultry in the Philippines. Additionally, the transmission risk may threaten the local avian population.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12329429/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144800593","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":"Contributions of Great Salt Lake Playa- and Industrially Sourced Priority Pollutant Metals in Dust Contribute to Possible Health Hazards in the Communities of Northern Utah","authors":"Annie L. Putman,&nbsp;Molly Blakowski,&nbsp;Destry DiViesti,&nbsp;Diego Fernandez,&nbsp;Morgan McDonnell,&nbsp;Patrick Longley,&nbsp;Daniel K. Jones","doi":"10.1029/2025GH001462","DOIUrl":"10.1029/2025GH001462","url":null,"abstract":"<p>Communities and ecosystems of northern Utah, USA receive particulate pollution from anthropogenic activity and dust emissions from sources including the Great Salt Lake (“the Lake”) playa. In addition to affecting communities, anthropogenic pollution is delivered to the Lake's playa sediments, which are eroded during dust events. Yet, spatial variability in dust flux and composition and their risks to human health are poorly understood. We analyzed dust in 17 passive samplers proximal to the Lake during fall 2022 for dust flux, the dust fraction of particulate matter, ⁸⁷Sr/⁸⁶Sr, and elemental geochemistry. We evaluated spatial patterns of 11 priority pollutant metals and estimated the hypothetical non-cancer dust and soil ingestion health hazard for six age cohorts. We observed the highest dust fluxes proximal to the Lake's playa. The highest concentrations of and greatest number of metals occurred in and south of Ogden, UT. Sites to the northeast of Farmington Bay had the highest fluxes. Metal concentrations and ⁸⁷Sr/⁸⁶Sr suggest that the dust composition near Bountiful represents contributions from anthropogenic sources, whereas the dust composition to the northeast of Farmington Bay reflects the Lake's playa emissions. Evaluations of potential health hazards from dust ingestion suggest that children between birth and 6 years are vulnerable at higher ingestion rates. Thallium, As, Pb, Co and Cr contributed most to the estimated hazard. Among these, As and sometimes Pb are likely derived from the Lake's playa emissions. Thus, suppression of dust emissions from the Lake's playa may decrease possible health risks for children in northern Utah.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001462","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773498","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":"Short-Term Effects of Meteorological Factors on Severe Fever With Thrombocytopenia Syndrome Incidence in Xinyang, China","authors":"Quanman Hu,&nbsp;Yan Hu,&nbsp;Yanyan Yang,&nbsp;Jundong Chen,&nbsp;Songshan Zhang,&nbsp;Fei Zhao,&nbsp;Saiwei Lu,&nbsp;Li Zhang,&nbsp;Shuaiyin Chen,&nbsp;Guangcai Duan","doi":"10.1029/2025GH001440","DOIUrl":"10.1029/2025GH001440","url":null,"abstract":"<p>Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne zoonotic disease, which are classified by the World Health Organization as a priority disease for research and development in emergency situations due to the high mortality rate. Previous studies indicated that the complex nonlinear and delayed association was observed between meteorological factors and SFTS. However, these did not consider the short-term effect of meteorological factors on the incidence of SFTS. In this study, we used generalized additive models (GAM) and distributed lag nonlinear models (DLNM) to investigate the short-term correlation between meteorological factors and SFTS incidence. From 1 January 2013 to 31 December 2023 a total of 6,601 cases of SFTS were reported in Xinyang. Females constituted the majority with a male-to-female ratio of 0.68 and the average age of cases being approximately at around 61.52 years old. The multivariate GAM analysis revealed that mean temperature exerted the greatest influence on the incidence of SFTS compared to other meteorological factors and interacted with these factors. After accounting for lag period of 0–14 days, the DLNM analysis indicated that specific range of temperature (18–23°C), a certain range atmospheric pressure (1,006–1,017 hPa), extreme high wind speed (&gt;11.6 m/s), and prolonged sunshine duration (&gt;9h) were associated with SFTS, while there was no significant correlation between relative humidity and the incidence of SFTS. This study investigates the non-linear trend and lagged exposure effect of various meteorological factors on short-term SFTS incidence, thereby enhancing our comprehensive understanding of the effect of meteorological factors on SFTS.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 8","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001440","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767462","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":"Comprehensive Spatial Investigation of Tuberculosis Dynamics and Affecting Factors in Şanlıurfa, Türkiye (2016–2023)","authors":"M. Çelik,&nbsp;M. F. Döker,&nbsp;C. Kırlangıçoğlu,&nbsp;Ö. Ünsal,&nbsp;S. Gökçeoğlu,&nbsp;M. R. Ceylan,&nbsp;O. Karabay","doi":"10.1029/2024GH001235","DOIUrl":"10.1029/2024GH001235","url":null,"abstract":"<p>Tuberculosis (TB) remains a critical public health issue, particularly in regions with significant socio-economic disparities. This study provides a comprehensive spatial analysis of TB dynamics in Şanlıurfa, Türkiye, covering the period from 2016 to 2023. Utilizing Geographic Information Systems, epidemiological data, and advanced statistical techniques, the research examines the spatial distribution and temporal trends of TB cases within this region. By integrating patient data with demographic, environmental, and socio-economic variables, the study assesses the complex factors influencing TB incidence and prevalence. The results indicate significant spatial clustering of TB cases, with the highest concentrations in areas characterized by high population density, lower socio-economic status, limited healthcare accessibility, and poor environmental conditions. Temporal trends reveal a gradual decline in TB incidence over the study period; however, certain hotspots persist, underscoring the need for sustained and targeted interventions. Furthermore, the study identifies a correlation between TB prevalence and inadequate living conditions, emphasizing the role of socio-economic improvement in disease control. These findings provide crucial insights for policymakers and public health officials, facilitating the development of more effective, evidence-based TB control strategies tailored to the unique socio-economic and geographical landscape of Şanlıurfa.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"9 7","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024GH001235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144673204","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}