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  Spatial accessibility to emergency care in Sichuan province in China

  Xuefeng Tang, Yufan Deng, Huazhen Yang, Fan Tian, Youping Li, Jay Pan

  29-12-2020

  https://doi.org/10.4081/gh.2020.891

  2285

  PDF: 900

  HTML: 48
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  Spatial analysis of the regional variation of hypertensive disease mortality and its socio-economic correlates in South Korea

  Seong-Yong Park, Jin-Mi Kwak, Eun-Won Seo, Kwang-Soo Lee

  31-05-2016

  https://doi.org/10.4081/gh.2016.420

  3058

  PDF: 1747

  HTML: 1379
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  Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda

  Gilbert Nduwayezu, Pengxiang Zhao, Clarisse Kagoyire, Lina Eklund, Jean Pierre Bizimana, Petter Pilesjo, Ali Mansourian

  25-05-2023

  https://doi.org/10.4081/gh.2023.1184

  3106

  PDF: 1635

  HTML: 190
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  Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

  Abdulkader Murad, Fazlay Faruque, Ammar Naji, Alok Tiwari, Mansour Helmi, Ammar Dahlan

  16-05-2022

  https://doi.org/10.4081/gh.2022.1072

  2013

  PDF: 1013

  HTML: 156
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  Effects of geographical factors on reference values of the thyroid stimulating hormone in healthy adults in China and its clinical significance

  Xinrui Pang, Miao Ge, Congxia Wang, Jinwei He

  06-05-2022

  https://doi.org/10.4081/gh.2022.1030

  1234

  PDF: 606

  HTML: 274
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  Spatial association of public sports facilities with body mass index in Korea

  Eun Jin Han, Kiyeon Kang, So Young Sohn

  07-05-2018

  https://doi.org/10.4081/gh.2018.542

  2447

  PDF: 1077

  HTML: 106
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  Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach

  Alexander Domnich, Lucia Arata, Daniela Amicizia, Alessio Signori, Roberto Gasparini, Donatella Panatto

  16-11-2016

  https://doi.org/10.4081/gh.2016.457

  3375

  PDF: 1781

  HTML: 1324
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  Air quality classification and its temporal trend in Tehran, Iran, 2002-2012

  Raheleh Saniei, Ali Zangiabadi, Mohammad Sharifikia, Yousef Ghavidel

  31-05-2016

  https://doi.org/10.4081/gh.2016.442

  4819

  PDF: 1480

  HTML: 2583

• Spatial-temporal risk factors in the occurrence of rabies in Mexico

  Reyna Ortega-Sánchez, Isabel Bárcenas-Reyes, Jesús Luna-Cozar, Edith Rojas-Anaya, José Quintín Cuador-Gil, Germinal Jorge Cantó-Alarcón, Nerina Veyna-Salazar, Sara González-Ruiz, Feliciano Milián-Suazo

  30-01-2024

  https://doi.org/10.4081/gh.2024.1245

  4576

  PDF: 1366

  HTML: 1055
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  Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran

  Roghieh Ramezankhani, Nooshin Sajjadi, Roya Nezakati Esmaeilzadeh, Seyed Ali Jozi, Mohammad Reza Shirzadi

  08-05-2018

  https://doi.org/10.4081/gh.2018.664

  1748

  PDF: 986

  HTML: 165

• Spatial analysis of risk factors for transmission of the Barmah Forest virus in Queensland, Australia

  Suchithra Naish, Kerrie Mengersen, Shilu Tong

  289-299

  01-11-2013

  https://doi.org/10.4081/gh.2013.74

  1865

  PDF: 1035
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  A spatiotemporal analysis of the social determinants of health for COVID-19

  Claire Bonzani, Peter Scull, Daisaku Yamamoto

  25-05-2023

  https://doi.org/10.4081/gh.2023.1153

  2024

  PDF: 929

  HTML: 30
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  Spatial autocorrelation and stratified heterogeneity in the evaluation of breast cancer risk inequity and socioeconomic factors analysis in China: Evidence from Nanchang, Jiangxi Province

  Yaqi Wang, Zhiwei Wan

  17-05-2022

  https://doi.org/10.4081/gh.2022.1078

  1804

  PDF: 966

  HTML: 163
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  A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain

  Olga De Cos, Valentín Castillo-Salcines, David Cantarero-Prieto

  18-03-2022

  https://doi.org/10.4081/gh.2022.1067

  1769

  PDF: 596

  HTML: 41
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  Spatiotemporal heterogeneity of SARS-CoV-2 diffusion at the city level using geographically weighted Poisson regression model: The case of Bologna, Italy

  Addisu Jember Zeleke, Rossella Miglio, Pierpaolo Palumbo, Paolo Tubertini, Lorenzo Chiari, Bologna MODELS4COVID Study Group of the University of Bologna and the National Institute for Nuclear Physics (INFN)

  01-12-2022

  https://doi.org/10.4081/gh.2022.1145

  1728

  PDF: 955

  Appendix: 136

  HTML: 77
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  Socioeconomic determinants of pandemics: a spatial methodological approach with evidence from COVID-19 in Nice, France

  Laurent Bailly, Rania Belgaied, Thomas Jobert, Benjamin Montmartin

  15-09-2025

  https://doi.org/10.4081/gh.2025.1383

  740

  PDF: 297

  Supplementary materials: 67

  HTML: 19