Trends and Spatial Patterns of Oral Cancer Mortality in Ecuador, 2001–2016 by Solange Núñez-González, J. Andrés Delgado-Ron, Christopher Gault, Daniel Simancas-Racines

“…The second cluster included 38 cantons, in the years 2014 to 2016. The Global Moran I index for the study period showed a negative spatial autocorrelation (−0.067; p=0.37). …”
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Spatial Analysis of Industrial Green Development and Sustainable Cities in the Yellow River Basin by Ke Liu, Huan Jiang, Qian Zhou

“…The results indicate the following: (1) in general, IGD in YRB shows an upward trend. (2) The Global Moran’s I index of IGD shows a small increase; the distribution of local spatial correlation is basically unchanged. (3) There are obvious regional differences in the influencing factors of IGD. …”
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Analysis of spatial distribution and access to schools in district 20th of Tehran ‎municipality by habibollah Fasihi

“…In order to analyzing the spatial distribution of ‎schools we used spatial analysis models in GIS including the nearest neighboring index; ‎multi-spatial analysis and Moran index. …”
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Spatial patterns of excess mortality in the first year of the COVID19 pandemic in Germany by Thomas Wieland

“…SMRs and COVID-19-related deaths per 100,000 people are tested for spatial dependence by the Moran’s I index. It is, furthermore, tested whether all-cause mortality is associated with COVID-19-related deaths by correlation coefficients. …”
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Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis by Huan Zhou, Shaojian Qu, Xiaoguang Yang, Qinglu Yuan

“…The Jenks natural breaks method, kernel density function, and Moran index are introduced for spatial statistical analysis. …”
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Spatial-Temporal Variation of Population Aging: A Case Study of China’s Liaoning Province by Dunyi Guan, Lei Lei, Zenglin Han

“…Third, Moran’s I index of aging level first increases and then decreases; the values are all positive. …”
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Unraveling the spatial distribution and influencing factors of 'Bengke' traditional houses in Luhuo County, Western Sichuan. by Siwei Yu, Ding Fan, Ma Ge, Zihang Chen

“…Spatial autocorrelation was tested using Moran's Index, with results indicating no significant spatial autocorrelation, suggesting that the distribution mechanisms are complex and influenced by multiple factors. …”
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Data mining and socio-spatial patterns of COVID-19: geo-prevention keys for tackling the pandemic by Olga De Cos Guerra, Valentín Castillo Salcines, David Cantarero Prieto

“…To that end the research is based on data mining methods (3D bins and emerging hot-spots) and exploratory geo-statistical analysis (Global Moran’s Index, Nearest Neighbourhood and Ordinary Least Square analyses, among others). …”
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An Empirical Study on the Agglomeration Characteristics of China’s Construction Industry Based on Spatial Autocorrelation and Spatiotemporal Transition by Likun Zhao, Junsen Tian, Yanqi Liu, Rui Liu

“…Based on the analysis of the spatiotemporal distribution of China’s construction industry agglomeration, this paper analyzes the characteristics and evolution trend of the spatiotemporal agglomeration of construction industry in 31 provinces and cities of China from 2010 to 2019 by using Moran’s index and the spatiotemporal transition measurement model. …”
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The Analysis of Spatial Pattern and Hotspots of Aviation Accident and Ranking the Potential Risk Airports Based on GIS Platform by Yafei Li, Chen Liang

“…This study established the severity index of aviation accident based on aviation accident data, using GIS spatial analysis methods to study the spatial distribution characteristics of aviation accidents. …”
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Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey by Ying LIU, Xinying ZENG, Lin XIAO, Shiwei LIU

“…The regions with the lowest exposure rates were Shanghai city and Beijing city (exposure rates between 0% and 5%), and the region with the highest exposure rate was Jiangxi province (exposure rate between 25% and 30%). Global spatial autocorrelation analysis showed that the spatial distribution of SHS exposure rates in Chinese healthcare facilities in 2022 was positively correlated and spatially clustered (Moran′s I = 0.359, Z = 3.430, P = 0.002), indicating that regions with higher exposure rates were surrounded by regions with similarly high exposure rates. …”
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Measuring social vulnerability in communities and its association with leprosy burden through spatial intelligence in central West Brazil to guide strategic actions by José Francisco Martoreli Júnior, Antônio Carlos Vieira Ramos, Josilene Dália Alves, Thaís Zamboni Berra, Yan Mathias Alves, Reginaldo Bazon Vaz Tavares, Letícia Perticarrara Ferezin, Titilade Kehinde Ayandeyi Teibo, Ricardo Alexandre Arcêncio

“…For the spatial correlation between vulnerability and leprosy, Global and local bivariate Moran’s index was used. …”
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Evaluation of Spatial and Temporal Performance of Deep Learning Models for Travel Demand Forecasting: Application to Bike-Sharing Demand Forecasting by Jaehyung Lee, Jinhee Kim

“…These results can be used to enhance the model by introducing the spatial correlation index into the loss function or by incorporating additional features for handling spatial correlations.…”
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Global assessment of leukemia care quality: insights from the quality of care index (QCI) from 1990 to 2021Research in context by Yuzhe Pan, Qian Liu, Nan Zhang, Shuang Peng, Xinqi Li, Fuling Zhou

“…LMM analysis identified sex, age, year, SDI region, and leukemia subtype as significant QCI determinants. Spatial autocorrelation analysis confirmed positive autocorrelation within SDI regions (Global Moran’s I = 0.87, p < 2e-16). …”
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Barriers to healthcare access among female youths in Mozambique: a mixed-effects and spatial analysis using DHS 2022/23 data by Habtu Kifle Negash, Hiwot Tezera Endale, Hailu Aragie, Winta Tesfaye, Mihret Getnet, Tseganesh Asefa, Yibeltal Yismaw Gela, Alebachew Ferede Zegeye

“…Barriers were assessed based on finances, distance, permission, and safety, with independent variables like age, education, wealth index, marital status, and community factors. Analyses included multilevel logistic regression and spatial methods (Global Moran’s I, SaTScan) using Stata 17 and ArcGIS 10.7 to identify barriers and clusters. …”
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Análise de dependência espacial da taxa de mortalidade por Covid-19 nos municípios brasileiros by Vítor Hugo Campelo Pereira, Glairton Cardoso Rocha, Marco Túlio Mendonça Diniz, Marcos Antonio Cavalcante de Oliveira Júnior

“…A methodology was based on the selection of spatial autocorrelation based on the Global Index Moran and the Local Moran Index (LISA) in its univariate and bivariate forms. …”
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Spatiotemporal analysis of mosquito-borne infections and mosquito vectors in mainland Portugal by Sandra Moutinho, Jorge Rocha, Alberto Gomes, Bernardo Gomes, Ana Isabel Ribeiro

“…While the mosquitoes in question do not currently transmit these diseases, they have the potential to do so if there is a significant increase in pathogen circulation. A spatial cluster analysis was performed using the univariate Local Moran Index, the Bivariate Moran Local Index and the Mann-Kendall method. …”
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Condicionantes climáticos e socioeconômicos na espacialização da dengue em período epidêmico e pós-epidêmico na cidade de Fortaleza-CE by Gledson Bezerra Magalhães, Maria Elisa Zanella, Ana Paula Santana, Ricardo Almendra

“…For this, were used Kernel maps and geostatistical procedures (Pearson correlation, Cronbach's alpha coefficient, global and local Moran index). Climatologic, epidemiologic and socioeconomic data were collected. …”
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Geospatial mapping to assess the distribution and determinants of zero dose vaccination status hot spots among children in Ethiopia using EDHS 2019: Spatial and geographical weight... by Muluken Chanie Agimas, Meron Asmamaw, Melese Kebede Hailu, Tigabu Kidie, Habtamu Wagnew Abuhay, Getaneh Awoke Yismaw, Nebiyu Mekonnen Derseh

“…Spatial and geographically weighted regression was used to map the distribution and determinants of zero-dose vaccination status in Ethiopia. …”
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Spatial-temporal pattern and driving mechanism of urban land use eco-efficiency in mountainous counties based on multi-source data: a case study of Zhejiang province, China by Li Fan, Lindong Ma, Lindong Ma, Zhongwei Huang

“…The degree of efficiency differences between counties gradually converged. (2) The ULUEE at the county level exhibited a significant spatial positive correlation, with Moran’s I index increasing from 0.3219 to 0.3715. …”
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