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eISSN 1970-7096 - pISSN 1827-1987

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  • Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old

    André Oliveira, Antònio J.R. Cabral, Jorge M. Mendes, Maria R.O. Martins, Pedro Cabral
    04-11-2015
    https://doi.org/10.4081/gh.2015.365
    3123
    PDF: 1378
    HTML: 1221
  • 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
    1827
    PDF: 880
    HTML: 139
  • 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
    1563
    PDF: 888
    Appendix: 114
    HTML: 70
  • 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
    2548
    PDF: 1399
    HTML: 171
  • 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
    478
    PDF: 140
    Supplementary materials: 41
    HTML: 7
  • Does mobility restriction significantly control infectious disease transmission? Accounting for non-stationarity in the impact of COVID-19 based on Bayesian spatially varying coefficient models

    I Gede Nyoman Mindra Jaya, Anna Chadidjah, Farah Kristiani, Gumgum Darmawan, Jane Christine Princidy
    25-05-2023
    https://doi.org/10.4081/gh.2023.1161
    1214
    PDF: 500
    HTML: 11
  • Geographically weighted regression for modelling the accessibility to the public hospital network in Concepción Metropolitan Area, Chile

    Marcela Martínez Bascuñán, Carolina Rojas Quezada
    22-11-2016
    https://doi.org/10.4081/gh.2016.451
    3678
    PDF: 1724
    HTML: 2157
  • Spatiotemporal analysis of hand, foot and mouth disease data using time-lag geographically-weighted regression

    Zhi-Min Hong, Hu-Hu Wang, Yan-Juan Wang, Wen-Rui Wang
    29-12-2020
    https://doi.org/10.4081/gh.2020.849
    1784
    PDF: 811
    HTML: 25
  • Spatial analysis and modelling of depression relative to social vulnerability index across the United States

    Kiara M. Rivera, Abolfazl Mollalo
    01-09-2022
    https://doi.org/10.4081/gh.2022.1132
    4161
    PDF: 1943
    HTML: 482
  • 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
    3201
    PDF: 1593
    HTML: 1305
  • Spatial distribution and identifying biochemical factors affecting haemoglobin levels among women of reproductive age for each province in Indonesia: A geospatial analysis

    Muhammad Nur Aidi, Fitrah Ernawati, Efriwati Efriwati, Nunung Nurjanah, Rika Rachmawati, Elisa Diana Julianti, Dian Sundari, Fifi Retiaty, Anwar Fitrianto, Khalilah Nurfadilah, Aya Yuriestia Arifin
    30-11-2022
    https://doi.org/10.4081/gh.2022.1118
    1963
    PDF: 954
    HTML: 59
  • Spatial heterogeneity of quality, use and spending on medicare for the elderly

    Felipa de Mello-Sampayo
    07-05-2018
    https://doi.org/10.4081/gh.2018.655
    1976
    PDF: 837
    HTML: 110
  • Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

    Rutendo Birri Makota, Eustasius Musenge
    27-11-2023
    https://doi.org/10.4081/gh.2023.1207
    1388
    PDF: 680
    HTML: 55
  • Neonatal mortality in East Africa and West Africa: a geographic analysis of district-level demographic and health survey data

    Sue C. Grady, April N. Frake, Qiong Zhang, Matlhogonolo Bene, Demetrice R. Jordan, Joshua Vertalka, Thania C. Dossantos, Ameen Kadhim, Judith Namanya, Lisa-Marie Pierre, Yi Fan, Peiling Zhou, Fatoumata B. Barry, Libbey Kutch
    26-05-2017
    https://doi.org/10.4081/gh.2017.501
    9064
    PDF: 4268
    HTML: 2198
  • Associating socio-economic factors with access to public healthcare facilities using geographically weighted regression in the city of Tshwane, South Africa

    Thabiso Moeti, Tholang Mokhele, Solomon Tesfamichael
    20-11-2024
    https://doi.org/10.4081/gh.2024.1288
    1696
    PDF: 510
    HTML: 74
  • 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
    2924
    PDF: 1657
    HTML: 1372
  • Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry

    Gianluca Boo, Stefan Leyk, Sara Irina Fabrikant, Andreas Pospischil, Ramona Graf
    11-05-2017
    https://doi.org/10.4081/gh.2017.539
    3342
    PDF: 1108
    HTML: 819
  • Estimating small area health-related characteristics of populations: a methodological review

    Azizur Rahman
    08-05-2017
    https://doi.org/10.4081/gh.2017.495
    4140
    PDF: 1831
    HTML: 1366
  • Spatial analysis of the relationship between out-of-pocket expenditure and socioeconomic status in South Korea

    Young-Gyu Kwon, Man-Kyu Choi
    25-05-2023
    https://doi.org/10.4081/gh.2023.1175
    1244
    PDF: 683
    HTML: 39
  • Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach

    Mokhalad A. Majeed, Helmi Z. M. Shafri, Aimrun Wayayok, Zed Zulkafli
    25-05-2023
    https://doi.org/10.4081/gh.2023.1176
    2097
    PDF: 985
    Supplementary Materials: 161
    HTML: 72
  • Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning

    Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist
    26-03-2025
    https://doi.org/10.4081/gh.2025.1319
    1944
    PDF: 390
    HTML: 73
  • Physical inactivity displays a mediator role in the association of diabetes and poverty: A spatiotemporal analysis

    Lung-Chang Chien, Xiao Li, Amanda Staudt
    03-11-2017
    https://doi.org/10.4081/gh.2017.528
    2692
    PDF: 924
    HTML: 761
  • Intra-urban differences underlying leprosy spatial distribution in central Brazil: geospatial techniques as potential tools for surveillance

    Amanda G. Carvalho, Carolina Lorraine H. Dias, David J. Blok, Eliane Ignotti, João Gabriel G. Luz
    06-10-2023
    https://doi.org/10.4081/gh.2023.1227
    1248
    PDF: 608
    Supplementary Materials: 87
    HTML: 15
  • Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis

    Maria Camila Lesmes , Alvaro Ávila-Díaz, Erika Santamaría, Carlos Andrés Morales , Horacio Cadena, Patricia Fuya, Nicolas Frutos, Ximena Porcasi, Catalina Marceló-Díaz
    04-06-2025
    https://doi.org/10.4081/gh.2025.1292
    1345
    PDF: 318
    HTML: 32
  • 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
    1746
    PDF: 847
    HTML: 23
  • Geospatial epidemiology of coronary artery disease treated with percutaneous coronary intervention in Crete, Greece

    Evangelos Melidoniotis, Kleomenis Kalogeropoulos, Andreas Tsatsaris, Michail Zografakis-Sfakianakis, George Lazopoulos, Nikolaos Tzanakis, Ioannis Anastasiou, Emmanouil Skalidis
    16-05-2024
    https://doi.org/10.4081/gh.2024.1251
    2248
    PDF: 542
    HTML: 50
  • Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data

    Su Yun Kang, Susanna M. Cramb, Nicole M. White, Stephen J. Ball, Kerrie L. Mengersen
    31-05-2016
    https://doi.org/10.4081/gh.2016.428
    6958
    PDF: 2415
    APPENDIX: 1133
    HTML: 5223
  • Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China

    Dan Li, Dawei Gao, Masaaki Yamada, Chuangbin Chen, Liuchun Xiang, Haisong Nie
    28-05-2024
    https://doi.org/10.4081/gh.2024.1255
    2427
    PDF: 652
    HTML: 64
  • Mastering geographically weighted regression: key considerations for building a robust model

    Behzad Kiani, Benn Sartorius, Colleen L. Lau, Robert Bergquist
    29-02-2024
    https://doi.org/10.4081/gh.2024.1271
    8006
    PDF: 1442
    HTML: 856
  • Vulnerability to COVID-19 in Pernambuco, Brazil: A geospatial evaluation supported by multiple-criteria decision aid methodology

    Ciro José Jardim de Figueiredo, Caroline Maria de Miranda Mota, Amanda Gadelha Ferreira Rosa, Arthur Pimentel Gomes de Souza, Simone Maria da Silva Lima
    14-01-2022
    https://doi.org/10.4081/gh.2022.1000
    2516
    PDF: 473
    HTML: 44
  • Advanced analysis of depression tendency in China: an investigation of environmental and social factors based on geographical and temporal weighted regression

    Yanhong Xu, Zhilin Hong, Huimei Lin, Xiaofeng Huang
    21-07-2025
    https://doi.org/10.4081/gh.2025.1385
    544
    PDF: 156
    HTML: 22
  • Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States

    Chunhui Liu, Xiaodi Su, Zhaoxuan Dong, Xingyu Liu, Chunxia Qiu
    25-05-2023
    https://doi.org/10.4081/gh.2023.1200
    1259
    PDF: 636
    HTML: 58
  • Spatial association between COVID-19 incidence rate and nighttime light index

    Amornrat Luenam, Nattapong Puttanapong
    18-03-2022
    https://doi.org/10.4081/gh.2022.1066
    1837
    PDF: 614
    HTML: 86
  • How much incident lung cancer was missed globally in 2012? An ecological country-level study

    Benn Sartorius, Kurt Sartorius
    31-05-2016
    https://doi.org/10.4081/gh.2016.396
    2481
    PDF: 1291
    HTML: 1025
  • Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

    Carlos Mena, Cesar Sepúlveda, Eduardo Fuentes, Yony Ormazábal, Iván Palomo
    07-05-2018
    https://doi.org/10.4081/gh.2018.587
    5058
    PDF: 2454
    HTML: 752
  • Spatial and temporal analysis of the human immunodeficiency virus in an area of social vulnerability in Northeast Brazil

    Géssyca Cavalcante de Melo, Emilia Carolle Azevedo de Oliveira, Iane Brito Leal, Carolina Piedade Morais de Freitas Soares Silva, Roberta Andrade Beltrão, Allan Dantas dos Santos, Renata Karina Reis, Marco Antônio Prado Nunes, Karina Conceição Gomes Machado de Araujo
    26-11-2020
    https://doi.org/10.4081/gh.2020.863
    3018
    PDF: 1052
    HTML: 34
  • Spatial analysis of the AIDS mortality rate among young people in a province of the Brazilian Amazon: An ecological study

    Sara Melissa Lago Sousa, Andrey Oeiras Pedroso , Iaron Leal Seabra , Glenda Roberta Oliveira Naiff Ferreira, Aline Maria Pereira Cruz Ramos , Sandra Helena Isse Polaro, Eliã Pinheiro Botelho
    29-11-2022
    https://doi.org/10.4081/gh.2022.1102
    893
    PDF: 768
    HTML: 15
  • The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure

    Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani
    04-06-2025
    https://doi.org/10.4081/gh.2025.1386
    1621
    PDF: 315
    HTML: 5
  • 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
    2048
    PDF: 832
    HTML: 33
  • Spatiotemporal evolution characteristics and attribution analysis of hepatitis A in mainland China

    Xiaodi Su, Chunxia Qiu, Chunhui Liu
    03-12-2024
    https://doi.org/10.4081/gh.2024.1323
    1143
    PDF: 348
    HTML: 5
  • Use of geographical information systems for delimiting health service areas in China

    Xuechen Xiong, Li Luo
    11-05-2017
    https://doi.org/10.4081/gh.2017.486
    2226
    PDF: 1088
    HTML: 1013
  • The geographic environment and the frequency of falling: a study of mortality outcomes in elderly people in China

    Yi Huang, Chen Li, Xianjing Lu, Yue Wang
    25-05-2023
    https://doi.org/10.4081/gh.2023.1180
    728
    PDF: 491
    HTML: 6
  • When homogeneity meets heterogeneity: the geographically weighted regression with spatial lag approach to prenatal care utilisation

    Carla Shoff, Vivian Yi-Ju Chen, Tse-Chuan Yang
    557-568
    01-05-2014
    https://doi.org/10.4081/gh.2014.45
    2235
    PDF: 1101
  • Spatial variability of mother-to-child human immunodeficiency virus transmission in a province in the Brazilian Rainforest: An ecological study

    Marcus Matheus Quadros Santos, Bianca Alessandra Gomes do Carmo, Taymara Barbosa Rodrigues, Bruna Rafaela Leite Dias, Cleyton Abreu Martins, Glenda Roberta Oliveira Naiff Ferreira, Andressa Tavares Parente, Cíntia Yollete Urbano Pauxis Aben-Atha, Sandra Helena Isse Polaro, Eliã Pinheiro Botelho
    29-11-2022
    https://doi.org/10.4081/gh.2022.1101
    903
    PDF: 802
    HTML: 21
  • 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
    4156
    PDF: 1227
    HTML: 941
  • Temporal and spatial analyses of colorectal cancer incidence in Yogyakarta, Indonesia: a cross-sectional study

    Juan Adrian Wiranata, Herindita Puspitaningtyas, Susanna Hilda Hutajulu, Jajah Fachiroh, Nungki Anggorowati, Guardian Yoki Sanjaya, Lutfan Lazuardi, Patumrat Sripan
    25-05-2023
    https://doi.org/10.4081/gh.2023.1186
    1598
    PDF: 922
    HTML: 46
  • Spatial epidemiology of cancer: a review of data sources, methods and risk factors

    Rita Roquette, Marco Painho, Baltazar Nunes
    08-05-2017
    https://doi.org/10.4081/gh.2017.504
    7862
    PDF: 3260
    HTML: 2667
  • Simulation of the spatial distribution of urban populations based on first-aid call data

    Yinan Zhou, Qin Zhong Zhu, Li Luo
    29-12-2020
    https://doi.org/10.4081/gh.2020.768
    1450
    PDF: 577
    HTML: 19
  • 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
    1602
    PDF: 510
    HTML: 37
  • Urban gentrification and infectious diseases: an interdisciplinary narrative review

    Behzad Kiani, Gabriel Parker, Senobar Naderian, Colleen L. Lau, Benn Sartorius
    07-07-2025
    https://doi.org/10.4081/gh.2025.1388
    806
    PDF: 320
    HTML: 35
  • Hospital distribution in a metropolitan city: assessment by a geographical information system grid modelling approach

    Kwang-Soo Lee, Kyeong-Jun Moon
    537-544
    01-05-2014
    https://doi.org/10.4081/gh.2014.43
    1847
    PDF: 1156
  • A geographically weighted regression approach to investigate air pollution effect on lung cancer: A case study in Portugal

    Diogo Cardoso, Marco Painho, Rita Roquette
    13-05-2019
    https://doi.org/10.4081/gh.2019.701
    3729
    PDF: 1790
    APPENDIX: 408
    HTML: 237
  • Modelling youth pregnancy in continental Portugal through geographically weighted regression

    João David, Pedro Cabral
    14-05-2019
    https://doi.org/10.4081/gh.2019.680
    1769
    PDF: 914
    APPENDIX: 306
    HTML: 123
  • Geospatial modelling to estimate the territory at risk of establishment of influenza type A in Mexico - An ecological study

    Enrique Ibarra-Zapata, Darío Gaytán-Hernández, Verònica Gallegos-García, Claudia Elena González-Acevedo, Thuluz Meza-Menchaca, María Judith Rios-Lugo, Héctor Hernández-Mendoza
    14-05-2021
    https://doi.org/10.4081/gh.2021.956
    1892
    PDF: 572
    HTML: 27
  • Typhoid fever in Jakarta, Indonesia 2017-2023: spatial clustering and seasonality of hospitalization data to inform better intervention

    Mujiyanto Mujiyanto, Basuki Rachmat, Aris Yulianto, Made Agus Nurjana, Wawan Ridwan, Endang Puji Astuti, Doni Lasut, Pandji Wibawa Dhewantara
    15-05-2025
    https://doi.org/10.4081/gh.2025.1372
    1878
    PDF: 654
    HTML: 462
1 - 55 of 55 items

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Geospatial Health
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Vol. 20 No. 2 (2025)
Evaluation of emergency medical service application from a geographical location perspective in Turkey
Özgür Elmas et al.
29 September 2025

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Geospatial Health

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