Geospatial Health最新文献_第2页

Promoting sustainable health equity: accessibility analysis and optimization of tertiary hospital networks in China's metropolitan areas. 促进可持续健康公平：中国大城市三级医院网络可达性分析与优化。

IF 0.9 4区医学

Geospatial Health Pub Date : 2025-07-07 Epub Date: 2025-10-07 DOI: 10.4081/gh.2025.1414

Jiarui Han, Liping Fu, Tong Pei, Tiantian Zhang

{"title":"Promoting sustainable health equity: accessibility analysis and optimization of tertiary hospital networks in China's metropolitan areas.","authors":"Jiarui Han, Liping Fu, Tong Pei, Tiantian Zhang","doi":"10.4081/gh.2025.1414","DOIUrl":"https://doi.org/10.4081/gh.2025.1414","url":null,"abstract":"Healthcare accessibility is vital for sustainable urban development, ensuring timely diagnosis, chronic disease management, and emergency response. However, in many developing countries, the uneven distribution of advanced healthcare services exacerbates health disparities. Taking Tianjin in China as an example, this study aims to evaluate the spatial accessibility of tertiary hospitals and optimize hospital placement to improve healthcare coverage. Using the Gaussian Two-Step Floating Catchment Area (G2SFCA) method, the study integrated high-resolution spatial data on hospital locations, population density, and transportation networks, assessing the accessibility of higher-level healthcare services citywide. The results indicate that central urban districts exhibited high accessibility, where all demand points were within the 1-hour service range. In contrast, suburban districts had an average accessibility of 0.194, and outer suburban districts had the lowest citywide mean of 0.005, with less than 20% of the area covered. Despite its economic significance, Binhai New Area's healthcare accessibility remained inadequate, with a mean score of 0.010. The application of a location-allocation model to optimize the placement of 24 planned new hospitals, prioritizing areas with high population density and low accessibility resulted in an increased population coverage from 73.31% to 95.05%, significantly reducing non-accessible points. This study aligns with the United Nations' Sustainable Development Goals 3 and 11, advocating a hierarchical healthcare system, telemedicine, and improved transportation to minimize time costs and reduce inequities.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240338","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}

引用次数: 0

Advanced analysis of depression tendency in China: an investigation of environmental and social factors based on geographical and temporal weighted regression. 中国抑郁趋势的高级分析：基于地理和时间加权回归的环境和社会因素调查。

IF 1 4区医学

Geospatial Health Pub Date : 2025-07-07 Epub Date: 2025-07-21 DOI: 10.4081/gh.2025.1385

Yanhong Xu, Zhilin Hong, Huimei Lin, Xiaofeng Huang

{"title":"Advanced analysis of depression tendency in China: an investigation of environmental and social factors based on geographical and temporal weighted regression.","authors":"Yanhong Xu, Zhilin Hong, Huimei Lin, Xiaofeng Huang","doi":"10.4081/gh.2025.1385","DOIUrl":"https://doi.org/10.4081/gh.2025.1385","url":null,"abstract":"The spatiotemporal distribution of depressive tendencies across China from 2011 to 2022 was investigated using the Baidu Depression Search Index (BDSI). We examined key influencing natural factors, such as water pollution, air pollution, and deforestation, along with economic indicators, such as gross domestic product per capita, disposable income per capita, and health professionals per 10,000 population. Geographical and Temporal Weighted Regression (GTWR) was applied to capture the spatiotemporal heterogeneity of the BDSI determinants. The results revealed significant regional disparities, with the China's eastern region consistently exhibiting the highest values reflecting heightened mental health concerns, while the western region were found to have the lowest. The BDSI trends followed different trajectories, all of which peaked in 2019 before a sharp decline in 2020. Water pollution transitioned from negative to positive influence in the East, while deforestation exhibited regionally variable effects. Air pollution, peaking in 2019 and 2022, demonstrated the highest impact variability. The economic indicators showed complex regional and temporal patterns underscoring the need for tailored interventions. Together, these findings provided critical insights into the intricate interplay between environmental, economic, and healthcare factors in shaping mental health that highlighted the necessity of region-specific policies to mitigate depressive tendencies and enhance public mental well-being. These research results offer targeted recommendations for regionally adaptive mental health strategies across China.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676679","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}

引用次数: 0

Associations between rocky mountain spotted fever and veterinary care access, climatic factors and landscape in the State of Arizona, USA. 美国亚利桑那州落基山斑疹热与兽医护理途径、气候因素和景观之间的关系。

IF 1 4区医学

Geospatial Health Pub Date : 2025-07-07 Epub Date: 2025-07-17 DOI: 10.4081/gh.2025.1390

Yan Lin, Al Ekram Elahee Hridoy, Meifang Li, Zhe Wang, Li Luo, Xiaogang Ma, Zhuoming Liu, Murphy John, Chao Fan, Irene Ruberto, Xi Gong, Xun Shi

{"title":"Associations between rocky mountain spotted fever and veterinary care access, climatic factors and landscape in the State of Arizona, USA.","authors":"Yan Lin, Al Ekram Elahee Hridoy, Meifang Li, Zhe Wang, Li Luo, Xiaogang Ma, Zhuoming Liu, Murphy John, Chao Fan, Irene Ruberto, Xi Gong, Xun Shi","doi":"10.4081/gh.2025.1390","DOIUrl":"https://doi.org/10.4081/gh.2025.1390","url":null,"abstract":"Rocky Mountain Spotted Fever (RMSF) is a potentially fatal tick-borne disease historically prevalent in the eastern and southeastern U.S. Since the early 2000s, there has been a notable rise in RMSF cases in the south-western U.S. Despite the documented role of dogs in tick-borne disease transmission, research on the influence of other factors, such as veterinary care access, climatic conditions and landscape characteristics on RMSF incidence is limited. This study investigated the combined impact of these factors on RMSF using county-level temperature, relative humidity, precipitation, land cover, dog populations and veterinary care access in Arizona from 2006 to 2021. Employing a spatial negative binomial regression model, the study revealed significant associations between veterinary care access, precipitation, relative humidity, shrubland, and RMSF incidence across three models incorporating lagged effects (0-month, 1-month, and 2-month) for climatic variables. A key finding was that counties experiencing higher veterinary care access were more likely to report lower RMSF case counts (incidence rate ratio (IRR): 0.9237). The mean precipitation consistently showed the highest positive IRR (1.8137) across all models, indicating its strong influence. In contrast, relative humidity (IRR: 0.9413) and shrubland presence (IRR: 0.9265) demonstrated significant negative associations with RMSF incidence. These findings underscore the importance of veterinary care access, climatic factors, and land cover in shaping RMSF dynamics, particularly in regions with increasing incidence rates.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661125","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}

引用次数: 0

Spatial Bayesian semi-parametric Cox-Leroux modelling of stroke patient hospitalization: aspects on survival. 脑卒中患者住院的空间贝叶斯半参数Cox-Leroux模型：生存方面。

IF 1 4区医学

Geospatial Health Pub Date : 2025-07-07 Epub Date: 2025-07-21 DOI: 10.4081/gh.2025.1380

Aswi Aswi, Bobby Poerwanto, Nurussyariah Hammado, Nurwan Nurwan, Oktaviana Oktaviana, Siti Djawijah, Susanna Cramb

{"title":"Spatial Bayesian semi-parametric Cox-Leroux modelling of stroke patient hospitalization: aspects on survival.","authors":"Aswi Aswi, Bobby Poerwanto, Nurussyariah Hammado, Nurwan Nurwan, Oktaviana Oktaviana, Siti Djawijah, Susanna Cramb","doi":"10.4081/gh.2025.1380","DOIUrl":"https://doi.org/10.4081/gh.2025.1380","url":null,"abstract":"Survival analysis consists of a set of statistical methods used to analyse data where the outcome variable is the time until an event occurs. When such data are collected across distinct spatial regions, incorporating spatial information into survival models can be beneficial. A common approach is to apply an intrinsic Conditional Autoregressive (CAR) prior to an area-level frailty term to account for spatial correlation between regions. We extend the Bayesian Cox semi-parametric model by incorporating a spatial frailty term using the Leroux CAR prior. The aim was to improve the model's ability to describe stroke hospitalisations at the Stroke Centre Hospital in Makassar, Indonesia with a focus on understanding the geographic distribution of hospitalisations, Length of Stay (LOS) and factors influencing patient outcomes. The dataset was obtained from medical records of stroke patients admitted to this hospital (April 2021-June 2024). Variables included LOS, discharge outcomes, sex, age, stroke type, uric acid levels, hypertension, hypercholesterolemia, and diabetes mellitus. Our findings indicate that diabetes, stroke type and the presence of hypercholesterolemia significantly influence recovery rates in stroke patients. Specifically, patients with diabetes had lower recovery, while those with hypercholesterolemia and ischemic stroke patients had faster recovery compared to those with haemorrhagic strokes.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676680","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}

引用次数: 0

The effects of population mobility on Chinese HIV epidemics in spill-over and influx risks perspectives: a spatial epidemiology analysis. 外溢和流入风险视角下人口流动对中国艾滋病流行的影响：空间流行病学分析

IF 0.9 4区医学

Geospatial Health Pub Date : 2025-07-07 Epub Date: 2025-09-08 DOI: 10.4081/gh.2025.1384

Yazhen Zhang, Hui Jin

{"title":"The effects of population mobility on Chinese HIV epidemics in spill-over and influx risks perspectives: a spatial epidemiology analysis.","authors":"Yazhen Zhang, Hui Jin","doi":"10.4081/gh.2025.1384","DOIUrl":"10.4081/gh.2025.1384","url":null,"abstract":"Investigating the spatial effects of population mobility on Human Immunodeficiency Virus (HIV) epidemics provides valuable insights for effective disease control. Data on the incidence and prevalence of HIV and socioeconomic factors from 2013 to 2022 across 31 provinces in China were collected. The Baidu migration index was employed to construct inter-provincial population migration matrices for spatial lag models to evaluate spatial spill-overs and influx risks associated with HIV epidemics macroscopically. This study also analysed the impacts of socioeconomic variables, conducted robustness tests for validation, and performed subgroup analysis stratified by HIV incidence levels. Significant spatial autocorrelation of HIV morbidity was confirmed by finding a positive Moran's I. The spatial lag model indicated that when a given province had a 1-unit increase in HIV incidence, its average outflow would cause a 0.7068-unit incidence rate increment in other destination provinces, while every unit increase of HIV incidence in other provinces would induce a 0.7013-unit HIV average incidence rise in the original one when it played the role of destination on average. Furthermore, higher population density and lower educational attainment were associated with elevated HIV incidence (p<0.001). The robustness of the findings was verified, and subgroup analysis indicated that reasons besides population mobility should be given priority consideration in regions with higher HIV incidence. The risks of population mobility related to the HIV epidemic were quantified, highlighting the necessity of developing effective and acceptable HIV prevention and control strategies specifically tailored for migrant populations.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145024866","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}

引用次数: 0

Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases. 整合基于病原体的疾病、流动性和废水模型，以研究传染病的传播。

IF 1 4区医学

Geospatial Health Pub Date : 2025-02-11 DOI: 10.4081/gh.2025.1326

Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A Abdulkareem, Raul Zurita Milla

{"title":"Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases.","authors":"Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A Abdulkareem, Raul Zurita Milla","doi":"10.4081/gh.2025.1326","DOIUrl":"10.4081/gh.2025.1326","url":null,"abstract":"Wastewater-based epidemiology was utilized during the COVID-19 outbreak to monitor the circulation of SARS-CoV-2, the virus causing this disease. However, this approach is limited by the need for additional methods to accurately translate virus concentrations in wastewater to disease-positive human counts. Combined modelling of COVID-19 disease cases and the concentration of its causative virus, SARS-CoV-2, in wastewater will necessarily deepen our understanding. However, this requires addressing the technical differences between disease, population mobility and wastewater models. To that end, we developed an integrated Agent-Based Model (ABM) that facilitates analysis in space and time at various temporal resolutions, including disease spread, population mobility and wastewater production, while also being sufficiently generic for different types of infectious diseases or pathogens. The integrated model replicates the epidemic curve for COVID-19 and can estimate the daily infections at the household level, enabling the monitoring of the spatial patterns of infection intensity. Additionally, the model allows monitoring the estimated production of infected wastewater over time and spatially across the sewage and treatment plant. The model addresses differences between resolutions and can potentially support Early Warning Systems (EWS) for future pandemics.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143400935","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}

引用次数: 0

Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad. 绘制乍得西部梅奥-凯比省的牲畜系统、牛和山羊疾病地图。

IF 1 4区医学

Geospatial Health Pub Date : 2025-02-03 DOI: 10.4081/gh.2025.1365

Kella Douzouné, Joseph Oloukoi, Ismaila Toko Imorou, Toure Gorgui Ba, Derrick Chefor Ymele Demeveng

{"title":"Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad.","authors":"Kella Douzouné, Joseph Oloukoi, Ismaila Toko Imorou, Toure Gorgui Ba, Derrick Chefor Ymele Demeveng","doi":"10.4081/gh.2025.1365","DOIUrl":"10.4081/gh.2025.1365","url":null,"abstract":"This study aimed to compile an inventory of the main diseases affecting these species in Mayo-Kebbi Ouest Province in Chad. A survey was conducted between 6 May and 7 August 2024 using a cascade data collection method identifying 310 farmers and 19 veterinarians with an average of 10 to 12 years of experience in advising and supporting livestock practices The data collected included socio-professional characteristics of participants, livestock practices, and geospatial information. These data were managed in Excel and analysed with R. The analysis involved descriptive and inferential statistical techniques including binary logistic regression resulting in maps illustrating disease hotspots and livestock systems. Thematic maps, tables and charts with a 5% significance threshold visualised risk areas and associated livestock practices. The results show a predominance of male farmers (91.9%) from 20 different ethnic groups. The livestock systems identified include data on farming divided into extensive (14.8%), mixed (0.3%) and semi-intensive farming (84.8%). On average, farms have 41 cattle and 25 goats. Animal diseases were found to cause 29.5% reduction in herd productivity. Transhumance (p=0.000356) and animal disease incidence (p=0.03) were observed as significant risk factors associated with the abandonment of livestock farming. The main diseases recorded in cattle include contagious bovine pleuropneumonia (11.3%), bovine tuberculosis (2.5%), foot-and-mouth disease (45.0%), bluetongue (1.7%) and disease with symptoms reminiscent of rinderpest (2.5%). For goats, notable diseases include brucellosis (3.8%), lumpy skin disease (19.2%), goat plague (7.9%) and Rift Valley fever (6.3%). These findings confirm the importance of a geospatial epidemiological surveillance tool for monitoring animal diseases in this region.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143124265","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}

引用次数: 0

Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand. 泰国社会经济和卫生服务因素与抗生素自我用药的空间关联

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-27 DOI: 10.4081/gh.2025.1329

Worrayot Darasawang, Wongsa Laohasiriwong, Kittipong Sornlorm, Warangkana Sungsitthisawad, Roshan Kumar Mahato

{"title":"Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand.","authors":"Worrayot Darasawang, Wongsa Laohasiriwong, Kittipong Sornlorm, Warangkana Sungsitthisawad, Roshan Kumar Mahato","doi":"10.4081/gh.2025.1329","DOIUrl":"10.4081/gh.2025.1329","url":null,"abstract":"Antibiotic Self-Medication (ASM) is a major contributing factor to Antimicrobial Resistance (AMR) that can lead to both mortality and long-term hospitalizations. High provincial ASM proportions associated with mortality due to AMR have been observed in Thailand but there is a lack of studies on geographic factors contributing to ASM. The present study aimed to quantify the distribution of ASM in Thailand and its correlated factors. Socioeconomic and health services factors were included in the spatial analysis. Moran's I was performed to identify global autocorrelation with the significance level set at p=0.05 and spatial regression were applied to identify the factors associated with ASM, the proportion of which is predominant in the north-eastern, central and eastern regions with Phitsanulok Province reporting the highest proportion of Thailand's 77 provinces. Autocorrelation between Night-Time Light (NTL) and the proportion of ASM was observed to be statistically significant at p=0.030. The Spatial Lag Model (SLM) and the Spatial Error Model (SEM) were used with the latter providing both the lowest R2 and Akaike Information Criterion (AIC). It was demonstrated that the proportion of alcohol consumption significantly increased the proportion of ASM. The annual number of outpatient department visits and the average NTL decreased the proportion of ASM by 1.5% and 0.4%, respectively. Average monthly household expenditures also decreased the ASM proportion. Policies to control alcohol consumption while promoting healthcare visits are essential strategies to mitigate the burden of AMR in Thailand.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048825","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}

引用次数: 0

Socio-spatial vulnerability index of type 2 diabetes mellitus in Mexico in 2020. 2020年墨西哥2型糖尿病社会空间脆弱性指数

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-27 DOI: 10.4081/gh.2025.1348

Enríque Ibarra-Zapata, Darío Gaytán-Hernández, Yolanda Terán-Figueroa, Verónica Gallegos-García, Carmen Del Pilar Suárez-Rodríguez, Sergio Zarazúa Guzmán, Omar Parra Rodríguez

{"title":"Socio-spatial vulnerability index of type 2 diabetes mellitus in Mexico in 2020.","authors":"Enríque Ibarra-Zapata, Darío Gaytán-Hernández, Yolanda Terán-Figueroa, Verónica Gallegos-García, Carmen Del Pilar Suárez-Rodríguez, Sergio Zarazúa Guzmán, Omar Parra Rodríguez","doi":"10.4081/gh.2025.1348","DOIUrl":"10.4081/gh.2025.1348","url":null,"abstract":"This study aimed to estimate a socio-spatial vulnerability index for type 2 diabetes mellitus (T2DM) at the municipal level in Mexico for 2020. It incorporated factors such as poverty, social backwardness, marginalization index, and human development index. This retrospective ecological study analyzed 317,011 incident cases of T2DM in 2020. Utilizing multi-criteria decision analysis, weighted values were assigned to each vulnerability criterion. A multiple linear regression model was developed, complemented by cluster and outlier analyses using Moran I's and the high-low clustering method. A clustered spatial autocorrelation of high values was found across 17.65% of Mexico, which was statistically significant (p < 0.001). Conversely, 37.78% of the territory showed a pattern of low values without significant evidence of groupings. The analysis revealed 117 nodes of very high vulnerability forming six focal areas, 172 nodes with high vulnerability across five areas, 168 nodes with medium vulnerability in two areas, 112 nodes with low vulnerability across 16 areas, and 152 nodes with very low vulnerability in 24 focal areas. This method proves to be robust and offers a technical-scientific basis for guiding T2DM prevention strategies and actions using a spatial/epidemiological approach. It is recommended that future strategies take into account factors such as poverty, social backwardness, marginalization index, and human development index to be effective.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048822","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}

引用次数: 0

Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring. 基于时空监测的covid -19相关社区环境风险差异分析

IF 1 4区医学

Geospatial Health Pub Date : 2025-01-23 Epub Date: 2025-04-28 DOI: 10.4081/gh.2025.1286

Jihong Zhang, Guohua Yin, Qiuhua Zhang, Juan Fang, Duo Jiang, Chao Yang, Na Sun

{"title":"Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring.","authors":"Jihong Zhang, Guohua Yin, Qiuhua Zhang, Juan Fang, Duo Jiang, Chao Yang, Na Sun","doi":"10.4081/gh.2025.1286","DOIUrl":"https://doi.org/10.4081/gh.2025.1286","url":null,"abstract":"The geo-inequality of COVID-19 risk has attracted a great deal of research attention. In this study, the spatial correlation between community environment and the incidence of COVID-19 cases in 30 Chinese cities is discussed. The spread of the disease is analyzed based on timing and spatial monitoring at the km2-grid level, with the use of publicly available data relating to housing prices, Gross Deomestic Product (GDP), medical facilities, consumer sites, public green spaces, and industrial sites. The results indicate substantial geographical variations in the distribution of COVID-19 communities in all 30 cities. Significant global bivariate spatial dependence was observed between the disease and housing prices (Moran's I =0.099, p<0.01, z=488.6), medical facilities (Moran's I = 0.349, p<0.01, z=1675.0), consumer sites (Moran's I =0.369, p<0.01, z=1843.4), green space (Moran's I =0.205, p<0.01, z=1037.8), and industrial sites (Moran's I =0.234, p<0.01, z=1178.6). The risk of COVID-19 under the influence of GDP is further examined for cities with per capita GDPs from high to low ranging from 1.69 to 4.62 (1.69~3.74~4.62, 95% CI). These findings provide greater detail on the interplay between the infectious disease and community environments.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144007918","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}

引用次数: 0