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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

2323

PDF: 1159

HTML: 168
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

3414

PDF: 1524

HTML: 1231
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

3189

PDF: 1856

HTML: 1385
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

2287

PDF: 1036

HTML: 50
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

4167

PDF: 800

HTML: 103
Diabetes prevalence in the state of Alabama: identifying the risk factors

Kwaku Karikari Manu, Seth Appiah-Opoku

31-03-2026

https://doi.org/10.4081/gh.2026.1465

769

PDF: 286

HTML: 12
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

8764

PDF: 1705

HTML: 891
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

1670

PDF: 901

HTML: 63
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

5522

PDF: 2514

HTML: 618
Geographically weighted regression for modelling the accessibility to the public hospital network in ConcepciÃ³n Metropolitan Area, Chile

Marcela Martínez Bascuñán, Carolina Rojas Quezada

22-11-2016

https://doi.org/10.4081/gh.2016.451

4092

PDF: 1977

HTML: 2216
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

943

PDF: 425

Supplementary materials: 107

HTML: 29
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

3621

PDF: 1941

HTML: 1338
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

2353

PDF: 1222

HTML: 90
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

2154

PDF: 1007

HTML: 43
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

2636

PDF: 791

HTML: 63
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

1810

PDF: 910

HTML: 92
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

3571

PDF: 1867

HTML: 224
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

2216

PDF: 982

HTML: 118
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

1694

PDF: 783

Supplementary Materials: 149

HTML: 26
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

1235

PDF: 1012

HTML: 23
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

3089

PDF: 857

HTML: 118
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

1214

PDF: 1051

HTML: 35
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

1903

PDF: 1036

Appendix: 166

HTML: 85
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

2844

PDF: 668

HTML: 74
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

2846

PDF: 1303
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

2066

PDF: 550

HTML: 66
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

3449

PDF: 736

HTML: 126
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

1707

PDF: 717

HTML: 43
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

5670

PDF: 2825

HTML: 819
Identifying geographical variations in poverty-obesity relationships: empirical evidence from Taiwan

Tzai-Hung Wen, Duan-Rung Chen, Meng-Ju Tsai

257-265

01-05-2010

https://doi.org/10.4081/gh.2010.205

3851

PDF: 1745
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

1999

PDF: 694

HTML: 50
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

1905

PDF: 882

HTML: 87
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

1524

PDF: 672

HTML: 47
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

2238

PDF: 762

HTML: 42
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

1122

PDF: 381

HTML: 39
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

4271

PDF: 2072

APPENDIX: 561

HTML: 322
Exploring geomasking methods for geoprivacy: a pilot study in an environment with built features

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

17-10-2023

https://doi.org/10.4081/gh.2023.1205

1508

PDF: 748

HTML: 362
Oncologic burden in Ukraine: regional inequalities and environmental risk factors

Anatolii Kornus, Olesia Kornus, Yurii Liannoi, Olena Danylchenko, Serhii Lutsenko

14-11-2025

https://doi.org/10.4081/gh.2025.1418

783

PDF: 307

HTML: 18
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

11074

PDF: 4603

HTML: 2248
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

2168

PDF: 1226

HTML: 72
Geographic clustering of elderly people with above-norm anthropometric measurements and blood chemistry

Carlos Mena, Eduardo Fuentes, Yony Ormazábal, Iván Palomo

11-05-2017

https://doi.org/10.4081/gh.2017.523

3023

PDF: 1386

HTML: 895

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