Geospatial Health最新文献_第6页

Application of geospatial information systems (GIS) for assessment of the distribution of periodontal disease in Makassar City, South Sulawesi Province, Indonesia. 地理空间信息系统在印度尼西亚南苏拉威西省望加锡市牙周病分布评估中的应用。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-11-07 DOI: 10.4081/gh.2023.1240

Fuad Husain Akbar, Nur Amaliyah Riyadh

引用次数: 0

From Snow's map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis. 从斯诺的霍乱传播地图到动态流域边界划定：空间分析中的当前前线。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-26 DOI: 10.4081/gh.2023.1247

Behzad Kiani, Colleen Lau, Robert Bergquist

{"title":"From Snow's map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis.","authors":"Behzad Kiani, Colleen Lau, Robert Bergquist","doi":"10.4081/gh.2023.1247","DOIUrl":"10.4081/gh.2023.1247","url":null,"abstract":"The history of mapping infectious diseases dates back to the 19th century when Dr John Snow utilised spatial analysis to pinpoint the source of the 1854 cholera outbreak in London, a ground-breaking work that laid the foundation for modern epidemiology and disease mapping (Newsom, 2006). As technology advanced, so did mapping techniques. In the late 20th century, geographic information systems (GIS) revolutionized disease mapping by enabling researchers to overlay diverse datasets to visualise and analyse complex spatial patterns (Bergquist & Manda 2019; Hashtarkhani et al., 2021). The COVID-19 pandemic showed that disease mapping is particularly valuable for optimising prevention and control strategies of infectious diseases by prioritising geographical targeting interventions and containment strategies (Mohammadi et al., 2021). Today, with the aid of highresolution satellite imagery, geo-referenced electronic data collection systems, real-time data feeds, and sophisticated modelling algorithms, disease mapping has become a feasible and accessible tool for public health officials in tracking, managing, and mitigating the spread of infectious diseases at global, regional and local scales (Hay et al., 2013). [...].","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71415404","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

A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina. 考虑到阿根廷一个中型城市的环境特征，对心脏代谢疾病及其风险因素进行地理空间分析。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-23 DOI: 10.4081/gh.2023.1212

Micaela Natalia Campero, Carlos Matías Scavuzzo, Veronica Andreo, María Sol Mileo, Micaela Belén Franzois, María Georgina Oberto, Carla Gonzalez Rodriguez, María Daniela Defagó

{"title":"A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina.","authors":"Micaela Natalia Campero, Carlos Matías Scavuzzo, Veronica Andreo, María Sol Mileo, Micaela Belén Franzois, María Georgina Oberto, Carla Gonzalez Rodriguez, María Daniela Defagó","doi":"10.4081/gh.2023.1212","DOIUrl":"10.4081/gh.2023.1212","url":null,"abstract":"New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI: - 0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR= -1.39; 95% CI: -2.62 to -0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49694304","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 comparison of London's three waves of Spanish Flu. 伦敦三波西班牙流感的空间比较。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-19 DOI: 10.4081/gh.2023.1235

Walter Peterson

{"title":"Spatial comparison of London's three waves of Spanish Flu.","authors":"Walter Peterson","doi":"10.4081/gh.2023.1235","DOIUrl":"10.4081/gh.2023.1235","url":null,"abstract":"England and Wales experienced three waves of influenza during the 1918/19 Spanish Flu pandemic. A previous analysis showed that these three waves had fundamentally different spatial and temporal characteristics. This present study compares London's experience of the three waves to discern possible geographic differences on a metropolitan level. Borough mortality data for each wave were normalized and then scaled, with spatial autocorrelation techniques displayed by GIS software and analysed for each wave. Registrar General in England and Wales reporting provided data concerning measures of 'health' and 'wealth' for each metropolitan borough. Spearman's rank correlation determined the correlation of each wave's mortality to each of the other waves including the 'health,' 'wealth' and population density factors. The comparisons showed that there is a spatial difference among the waves. The first two are spatially similar, with both exhibiting 'random' autocorrelation patterns, while the third wave exhibits a 'clustered' pattern. The borough mortality of the first two waves strongly correlated with each other, with both having similar 'health,' 'wealth' and population density factors. However, the third wave's mortality did not correlate with any of the first two and actually behaved in an opposite manner with regard to the 'health,' 'wealth,' and population density factors. These results do not appear in the literature and create new opportunities for research to explain London's mortality during the Spanish Flu pandemic of 1918/19.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49685505","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

Exploring geomasking methods for geoprivacy: a pilot study in an environment with built features. 探索地理隐私的地理测绘方法：在具有建筑特征的环境中进行的试点研究。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-17 DOI: 10.4081/gh.2023.1205

Alok Tiwari, Sohail Ahmad, Emad Qurunflah, Mansour Helmi, Ayad Almaimani, Alaa Alaidroos, Majed Mustafa Hallawani

{"title":"Exploring geomasking methods for geoprivacy: a pilot study in an environment with built features.","authors":"Alok Tiwari, Sohail Ahmad, Emad Qurunflah, Mansour Helmi, Ayad Almaimani, Alaa Alaidroos, Majed Mustafa Hallawani","doi":"10.4081/gh.2023.1205","DOIUrl":"10.4081/gh.2023.1205","url":null,"abstract":"This study discusses the ethical use of geographical information systems (GIS) data with a focus on geomasking for upholding locational privacy. As part of a pilot study in Jeddah City, Saudi Arabia, we used open-source geomasking methods to ensure geoprivacy while examining built environment features that determine the quality of life among individuals with type-II diabetes. We employed the open-source algorithms Maskmy.XYZ and NRand-k for geomasking 329 data points. The results showed no differences between global and city-level spatial patterns, but significant variations were observed with respect to local patterns. These findings indicate the promising potential of the chosen geomasking technologies with respect to ensuring locational privacy but it was noted that further improvements are needed. We recommend developing enhanced algorithms and conducting additional studies to minimize any negative impact of geomasking in spatial analysis with the overall aim of achieving a better understanding of ethical considerations in GIS sciences. In conclusion, application of geomasking is straightforward and can lead to enhanced use for privacy protection in geospatial data analysis.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41241248","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

Assessment of the supply/demand balance of medical resources in Beijing from the perspective of hierarchical diagnosis and treatment. 分级诊疗视角下的北京市医疗资源供需平衡评价。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-13 DOI: 10.4081/gh.2023.1228

Yuehan Jiang, Xinyu Cai, Yanhui Wang, Junwu Dong, Mengqin Yang

{"title":"Assessment of the supply/demand balance of medical resources in Beijing from the perspective of hierarchical diagnosis and treatment.","authors":"Yuehan Jiang, Xinyu Cai, Yanhui Wang, Junwu Dong, Mengqin Yang","doi":"10.4081/gh.2023.1228","DOIUrl":"10.4081/gh.2023.1228","url":null,"abstract":"Considering the United Nations' Sustainable Development Goals (SDGs) and the need for a balanced spatial distribution of urban medical resources capable of perspective of hierarchical diagnosis and treatment, i.e. providing continuous and accessible medical services during potential public health emergencies, we assessed accessibility and service capacity of the three hospital levels in Beijing. Using geographical information systems (GIS) and the two-step floating catchment area method with the street as research unit, we found that there is an over-supply of medical resources in the centre of the city with weaker support in the peripheral areas as manifested by less supply in relation to popular demand of medical services. The spatial distribution of hospitals at all levels and their resources was found to be uneven: 82.4% of the residents can reach a tertiary hospital (a hospital offering advanced specialized medical and health services to multiple regions) within a 15-minute drive; 50.6% can reach a secondary hospital (a hospital offering comprehensive medical and health services to various communities) within a 10-minute drive; and 77.6% can reach a primary hospital (a hospital directly delivering prevention, medical treatment, healthcare, and rehabilitation services to the community of a certain population) within a 15- minute walk. It was noted that the supply/demand balance of medical resources in the tertiary hospitals decreases from the centre to the periphery, while the secondary hospitals show a dual-centre pattern and the primary hospitals a more uneven distribution, with oversupply in the East and the opposite in the Centre. The results of the study provide supplementary decision support for improving the hierarchical diagnosis and treatment system and accelerate the overall deployment of medical resources.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41221138","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

Intra-urban differences underlying leprosy spatial distribution in central Brazil: geospatial techniques as potential tools for surveillance. 巴西中部麻风病空间分布的城市内部差异：作为潜在监测工具的地理空间技术。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-06 DOI: 10.4081/gh.2023.1227

Amanda G Carvalho, Carolina Lorraine H Dias, David J Blok, Eliane Ignotti, João Gabriel G Luz

{"title":"Intra-urban differences underlying leprosy spatial distribution in central Brazil: geospatial techniques as potential tools for surveillance.","authors":"Amanda G Carvalho, Carolina Lorraine H Dias, David J Blok, Eliane Ignotti, João Gabriel G Luz","doi":"10.4081/gh.2023.1227","DOIUrl":"10.4081/gh.2023.1227","url":null,"abstract":"This ecological study identified an aggregation of urban neighbourhoods spatial patterns in the cumulative new case detection rate (NCDR) of leprosy in the municipality of Rondonópolis, central Brazil, as well as intra-urban socioeconomic differences underlying this distribution. Scan statistics of all leprosy cases reported in the area from 2011 to 2017 were used to investigate spatial and spatiotemporal clusters of the disease at the neighbourhood level. The associations between the log of the smoothed NCDR and demographic, socioeconomic, and structural characteristics were explored by comparing multivariate models based on ordinary least squares (OLS) regression, spatial lag, spatial error, and geographically weighted regression (GWR). Leprosy cases were observed in 84.1% of the neighbourhoods of Rondonópolis, where 848 new cases of leprosy were reported corresponding to a cumulative NCDR of 57.9 cases/100,000 inhabitants. Spatial and spatiotemporal high-risk clusters were identified in western and northern neighbourhoods, whereas central and southern areas comprised low-risk areas. The GWR model was selected as the most appropriate modelling strategy (adjusted R²: 0.305; AIC: 242.85). By mapping the GWR coefficients, we identified that low literacy rate and low mean monthly nominal income per household were associated with a high NCDR of leprosy, especially in the neighbourhoods located within high-risk areas. In conclusion, leprosy presented a heterogeneous and peripheral spatial distribution at the neighbourhood level, which seems to have been shaped by intra-urban differences related to deprivation and poor living conditions. This information should be considered by decision-makers while implementing surveillance measures aimed at leprosy control.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71415405","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

Space-time cluster analysis of anemia in pregnant women in the province of Khyber Pakhtunkhwa, Pakistan (2014-2020). 巴基斯坦开伯尔-普赫图赫瓦省孕妇贫血的时空聚类分析（2014-2020）。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-05 DOI: 10.4081/gh.2023.1192

Sami Ullah, Sm Aqil Burney, Tariq Rasheed, Shamaila Burney, Mushtaq Ahmad Khan Barakzia

引用次数: 0

An investigation of geographical clusters of leptospirosis during the outbreak in Pangandaran, West Java, Indonesia. 印度尼西亚西爪哇省Pangandaran爆发期间钩端螺旋体病地理集群的调查。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-10-05 DOI: 10.4081/gh.2023.1221

Mutiara Widawati, Pandji Wibawa Dhewantara, Raras Anasi, Tri Wahono, Rina Marina, Intan Pandu Pertiwi, Agus Ari Wibowo, Andri Ruliansyah, Muhammad Umar Riandi, Dyah Widiastuti, Endang Puji Astuti

{"title":"An investigation of geographical clusters of leptospirosis during the outbreak in Pangandaran, West Java, Indonesia.","authors":"Mutiara Widawati, Pandji Wibawa Dhewantara, Raras Anasi, Tri Wahono, Rina Marina, Intan Pandu Pertiwi, Agus Ari Wibowo, Andri Ruliansyah, Muhammad Umar Riandi, Dyah Widiastuti, Endang Puji Astuti","doi":"10.4081/gh.2023.1221","DOIUrl":"10.4081/gh.2023.1221","url":null,"abstract":"Leptospirosis is neglected in many tropical developing countries, including Indonesia. Our research on this zoonotic disease aimed to investigate epidemiological features and spatial clustering of recent leptospirosis outbreaks in Pangandaran, West Java. The study analysed data on leptospirosis notifications between September 2022 and May 2023. Global Moran I and local indicator for spatial association (LISA) were applied. Comparative analysis was performed to characterise the identified hotspots of leptospirosis relative to its neighbourhoods. A total of 172 reported leptospirosis in 40 villages from 9 sub-districts in Pangandaran District were analysed. Of these, 132 cases (76.7%) were male. The median age was 49 years (interquartile range [IQR]: 34-59 years). Severe outcomes including renal failure, lung failure, and hepatic necrosis were reported in up to 5% of the cases. A total of 30 patients died, resulting in the case fatality rate (CFR) of 17.4%. Moran's I analysis showed significant spatial autocorrelation (I=0.293; p=0.002) and LISA results identified 7 High-High clusters (hotspots) in the Southwest, with the total population at risk at 26,184 people. The hotspots had more cases among older individuals (median age: 51, IQR: 36-61 years; p<0.001), more farmers (79%, p=0.001) and more evidence of the presence of rats (p=0.02). A comprehensive One Health intervention should be targeted towards these high-risk areas to control the transmission of leptospirosis. More empirical evidence is needed to understand the role of climate, animals and sociodemographic characteristics on the transmission of leptospirosis in the area studied.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41142913","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

On the geographic access to healthcare, beyond proximity. 在地理上获得医疗保健，超越邻近。

IF 1.7 4区医学

Geospatial Health Pub Date : 2023-09-28 DOI: 10.4081/gh.2023.1199

Songyuan Deng, Kevin Bennett

{"title":"On the geographic access to healthcare, beyond proximity.","authors":"Songyuan Deng, Kevin Bennett","doi":"10.4081/gh.2023.1199","DOIUrl":"10.4081/gh.2023.1199","url":null,"abstract":"This study examined the incongruence of travel distance between the nearest provider and the provider that pregnant woman actually chose to visit. Using a dataset of South Carolina claims including rural and urban areas for the period 2014-2018 based on live births of 27,290 pregnant women, we compared the travel distance and travel time for two providers of health: the nearest facility and the main one for the area in question. The number of the former type was counted for every case. The mean travel distance/time to the nearest provider was 3.2 miles (5.2 km) and 5.0 minutes, while that to the main (predominant) provider was 23.0 miles (37.0 km) and 31.7 minutes. Only 21.6% of pregnant women chose one of the closest facilities as their provider. The mean travel distance and time to the nearest provider for women in rural areas were more than twice that for urban women but only 1.2 times for the main provider. Rural women had one third fewer providers situated closer than the main in comparison to number available for urban women. Thus, we conclude that proximity is not the only factor associated with access to healthcare. While evaluating geographic access, the number of available health providers within the mean travel distance or time would be a better indicator of proximate access.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"18 2","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41153442","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