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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

  812

  PDF: 341

  Supplementary materials: 82

  HTML: 23
• 

  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

  8483

  PDF: 3532

  HTML: 2707
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  Spatial inequalities in cancer with special reference to lung cancer across Europe and their implications for environmental health policy

  Dimitrios Ntokos

  14-04-2026

  https://doi.org/10.4081/gh.2026.1453

  536

  PDF: 210

  Supplementary materials: 30

  HTML: 8
• 

  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

  5453

  PDF: 2690

  HTML: 806
• 

  A review of spatial technologies with applications for malaria transmission modelling and control in Africa

  Michael T. Gebreslasie

  26-11-2015

  https://doi.org/10.4081/gh.2015.328

  6418

  PDF: 2650

  HTML: 3133
• 

  Optimizing vaccination sites for infectious diseases based on heterogeneous travel modes in multiple scenarios

  Wentao Yang, Fengjie Wang, Yihan You, Zhixiong Fang, Xing Wang, Xiaoming Mei

  24-03-2025

  https://doi.org/10.4081/gh.2025.1362

  1922

  PDF: 444

  HTML: 105
• 

  Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases

  Sarah Isnan, Ahmad Fikri bin Abdullah, Abdul Rashid Shariff, Iskandar Ishak, Sharifah Norkhadijah Syed Ismail, Maheshwara Rao Appanan

  07-04-2025

  https://doi.org/10.4081/gh.2025.1277

  2446

  PDF: 854

  Supplementary materials: 208

  HTML: 113
• 

  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

  2874

  PDF: 582

  HTML: 73
• 

  Local healthcare resources associated with unmet healthcare needs in South Korea: a spatial analysis

  Sang Min Lee, Dong Woo Huh, Young Gyu Kwon

  11-03-2025

  https://doi.org/10.4081/gh.2025.1295

  2277

  PDF: 735

  Supplementary materials: 215

  HTML: 118

• Bayesian spatial Durbin modelling of stunting prevalence across Indonesian districts

  Ferra Yanuar, Yudiantri Asdi, Sandi Sandi, Aidinil Zetra, Fenni Kurnia Mutiya, Ade Suzana Eka Putri

  25-05-2026

  https://doi.org/10.4081/gh.2026.1441

  68

  PDF: 47

  HTML: 3
• 

  Spatial and temporal dynamic analysis of rabies: A review of current methodologies

  Shuaicheng Chen

  30-11-2022

  https://doi.org/10.4081/gh.2022.1139

  2917

  PDF: 2072

  HTML: 413
• 

  Application of geo-spatial technology in schistosomiasis modelling in Africa: a review

  Tawanda Manyangadze, Moses John Chimbari, Michael Gebreslasie, Samson Mukaratirwa

  04-11-2015

  https://doi.org/10.4081/gh.2015.326

  4411

  PDF: 2321

  HTML: 2207
• 

  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

  7335

  PDF: 2554

  APPENDIX: 1185

  HTML: 5446
• 

  Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

  Dustin T. Duncan, Ryan R. Ruff, Basile Chaix, Seann D. Regan, James H. Williams, Joseph Ravenell, Marie A. Bragg, Gbenga Ogedegbe, Brian Elbel

  31-05-2016

  https://doi.org/10.4081/gh.2016.399

  4223

  PDF: 1995

  HTML: 1504
• 

  Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

  Suparat Tappo, Wongsa Laohasiriwong, Nattapong Puttanapong

  29-11-2022

  https://doi.org/10.4081/gh.2022.1091

  1796

  PDF: 1151

  Appendix: 164

  HTML: 217
• 

  Modelling the presence of disease under spatial misalignment using Bayesian latent Gaussian models

  Xavier Barber, David Conesa, Silvia Lladosa, Antonio Lòpez-Quílez

  18-04-2016

  https://doi.org/10.4081/gh.2016.415

  3725

  PDF: 1912

  HTML: 2259
• 

  Spatial analysis of antimicrobial resistance in the environment. A systematic review

  Patrick Spets, Karin Ebert, Patrik Dinnétz

  25-05-2023

  https://doi.org/10.4081/gh.2023.1168

  3124

  PDF: 1171

  Supplementary Materials: 291

  HTML: 73
• 

  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

  2510

  PDF: 1110

  HTML: 112
• 

  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

  1354

  PDF: 461

  HTML: 30
• 

  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

  1905

  PDF: 999

  HTML: 176
• 

  Spatial association and modelling of under-5 mortality in Thailand, 2020

  Suparerk Suerungruang, Kittipong Sornlorm, Wongsa Laohasiriwong, Roshan Kumar Mahato

  31-08-2023

  https://doi.org/10.4081/gh.2023.1220

  1616

  PDF: 956

  HTML: 53
• 

  The spatiotemporal dynamics and structural covariates of homicide in the Republic of Korea, 2008-2017: A dynamic spatial panel data approach

  Yunho Yeom, Jaehun Choi

  09-05-2022

  https://doi.org/10.4081/gh.2022.1040

  1091

  PDF: 744

  HTML: 40
• 

  The effects of population mobility on Chinese HIV epidemics in spill-over and influx risks perspectives: a spatial epidemiology analysis

  Yazhen Zhang, Hui Jin

  08-09-2025

  https://doi.org/10.4081/gh.2025.1384

  830

  PDF: 429

  Supplementary materials: 81

  HTML: 30
• 

  Spatial autocorrelation patterns and factors associated with regular alcohol consumption behaviour among Thai men

  Naowarat Maneenin, Warangkana Sungsitthisawad, Chanwit Maneenin, Chananya Jirapornkul, Kittipong Sornlorm, Roshan Kumar Mahato, Wongsa Laohasiriwong

  26-09-2025

  https://doi.org/10.4081/gh.2025.1406

  710

  PDF: 391

  HTML: 26
• 

  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

  2149

  PDF: 937

  HTML: 117
• 

  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

  2440

  PDF: 863

  HTML: 81
• 

  Evaluating the utility of companion animal tick surveillance practices for monitoring spread and occurrence of human Lyme disease in West Virginia, 2014-2016

  Brian Hendricks, Miguella Mark-Carew, Jamison Conley

  13-11-2017

  https://doi.org/10.4081/gh.2017.582

  2719

  PDF: 887

  HTML: 757
• 

  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

  491

  PDF: 162

  HTML: 8
• 

  Spatial association between socio-economic health service factors and sepsis mortality in Thailand

  Juree Sansuk, Wongsa Laohasiriwong, Kittipong Sornlorm

  13-09-2023

  https://doi.org/10.4081/gh.2023.1215

  1729

  PDF: 687

  HTML: 49
• 

  Spatial and temporal clustering analysis of pulmonary tuberculosis and its associated risk factors in southwest China

  Jianjiao Wang, Xiaoning Liu, Zhengchao Jing, Jiawai Yang

  25-05-2023

  https://doi.org/10.4081/gh.2023.1169

  1211

  PDF: 879

  HTML: 37
• 

  Spatial access to public hospitals during COVID-19 in Nottinghamshire, UK

  Jishuo Zhang, Meifang Li

  29-11-2022

  https://doi.org/10.4081/gh.2022.1123

  1204

  PDF: 926

  HTML: 90
• 

  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

  1521

  PDF: 713

  Supplementary Materials: 123

  HTML: 21
• 

  Geostatistical modelling of the malaria risk in Mozambique: effect of the spatial resolution when using remotely-sensed imagery

  Federica Giardina, Jonas Franke, Penelope Vounatsou

  26-11-2015

  https://doi.org/10.4081/gh.2015.333

  3818

  PDF: 1731

  HTML: 1212
• 

  Spatial distribution and sociodemographic risk factors of malaria in Nigerian children less than 5 years old

  Chigozie Louisa J. Ugwu, Temesgen Zewotir

  29-12-2020

  https://doi.org/10.4081/gh.2020.819

  3895

  PDF: 1832

  HTML: 779

• Performance of a negative binomial-GLM in spatial scan statistic: a case study of low-birth weights in Pakistan

  Sami Ullah, Mushtaq Ahmad Khan Barakzai, Tianfa Xie

  03-09-2024

  https://doi.org/10.4081/gh.2024.1313

  1394

  PDF: 646

  HTML: 162
• 

  Spatial autocorrelation and heterogenicity of demographic and healthcare factors in the five waves of COVID-19 epidemic in Thailand

  Ei Sandar U, Wongsa Laohasiriwong, Kittipong Sornlorm

  25-05-2023

  https://doi.org/10.4081/gh.2023.1183

  1745

  PDF: 949

  Supplementary Materials: 151

  HTML: 90
• 

  Accessibility evaluation of urban basic public service facilities for persons with disabilities: a case study of central Beijing

  Ying Sun, Xiangfeng Li, Zhizhe Sun, Weiyang Jia

  02-02-2026

  https://doi.org/10.4081/gh.2026.1460

  652

  PDF: 363

  HTML: 12
• 

  Satellite-based forest monitoring: spatial and temporal forecast of growing index and short-wave infrared band

  Caroline Bayr, Heinz Gallaun, Ulrike Kleb, Birgit Kornberger, Martin Steinegger, Martin Winter

  18-04-2016

  https://doi.org/10.4081/gh.2016.310

  2597

  PDF: 1477

  HTML: 2023
• 

  Optimizing mobile mammography deployment in Oklahoma 2024: a two-step floating catchment area approach

  Janis E. Campbell, Amanda Janitz, Ayesha B. Sambo, Nubwa St. James, Stephanie F. Pharr, Mark P. Doescher

  21-04-2026

  https://doi.org/10.4081/gh.2026.1426

  191

  PDF: 158

  Supplementary materials: 27

  HTML: 4
• 

  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

  1786

  PDF: 971

  Appendix: 145

  HTML: 82
• 

  Impact of the presence of private hospitals on the spatial equality of healthcare accessibility in Beijing, China

  Teqi Dai, Kaifei Guo, Juanjuan Zhao, Wenqing Lu

  29-11-2022

  https://doi.org/10.4081/gh.2022.1157

  2255

  PDF: 1130

  HTML: 105
• 

  Global spreading of Omicron variant of COVID-19

  Pengxin Zhang, Shuhan Yang, Shaoqing Dai, Darren How Jin Aik, Shujuan Yang, Peng Jia

  13-07-2022

  https://doi.org/10.4081/gh.2022.1083

  2044

  PDF: 886

  HTML: 55
• 

  Assessing the spatial accessibility of hospital care in Sichuan Province, China

  Jay Pan, Huiran Liu, Xiuli Wang, Hongmei Xie, Paul L. Delamater

  27-11-2015

  https://doi.org/10.4081/gh.2015.384

  6286

  PDF: 2383

  HTML: 1651
• 

  The future of general practitioner care in Lower Saxony, Germany: an analysis of actual vs target states using a GIS-based floating catchment area method

  Jonas Schoo, Frank Schüssler

  19-02-2025

  https://doi.org/10.4081/gh.2025.1339

  2691

  PDF: 811

  HTML: 110
• 

  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

  2329

  PDF: 709

  HTML: 96
• 

  Geographic distribution and demographic factors associated with use of a long-acting reversible contraceptive (LARC) in Ethiopia

  Mintesnot Tenkir Teni, Travis Loux, Ness Sandoval, Anne Sebert Kuhlmann

  23-01-2025

  https://doi.org/10.4081/gh.2025.1302

  3771

  PDF: 1380

  HTML: 1155
• 

  Identification and analysis of spatial access disparities related to primary healthcare in Batna City, Algeria

  Ahmed Akakba, Belkacem Lahmar

  14-12-2023

  https://doi.org/10.4081/gh.2023.1238

  2091

  PDF: 1148

  HTML: 44
• 

  A 24-year exploratory spatial data analysis of Lyme disease incidence rate in Connecticut, USA

  Abolfazl Mollalo, Jason K. Blackburn, Lillian R. Morris, Gregory E. Glass

  08-11-2017

  https://doi.org/10.4081/gh.2017.588

  3234

  PDF: 1372

  HTML: 1035
• 

  Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

  Timothy Shields, Jessie Pinchoff, Jailos Lubinda, Harry Hamapumbu, Kelly Searle, Tamaki Kobayashi, Philip E. Thuma, William J. Moss, Frank C. Curriero

  31-05-2016

  https://doi.org/10.4081/gh.2016.410

  2318

  PDF: 1137

  HTML: 915
• 

  Spatial dispersal of Aedes albopictus mosquitoes captured by the modified sticky ovitrap in Selangor, Malaysia

  Muhammad Aidil Roslan, Romano Ngui, Muhammad Fathi Marzuki, Indra Vythilingam, Aziz Shafie, Sabri Musa, Wan Yusoff Wan Sulaiman

  11-05-2022

  https://doi.org/10.4081/gh.2022.1025

  2034

  PDF: 897

  Annex I-VI: 168

  HTML: 74

• Childhood stunting in Indonesia: assessing the performance of Bayesian spatial conditional autoregressive models

  Aswi Aswi, Septian Rahardiantoro, Anang Kurnia, Bagus Sartono , Dian Handayani, Nurwan Nurwan, Susanna Cramb

  03-10-2024

  https://doi.org/10.4081/gh.2024.1321

  1950

  PDF: 738

  HTML: 133
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  Factors associated with the spatial distribution of leprosy: a systematic review of the published literature

  Nathan Guilherme de Oliveira, Bruna Eduarda Bortolomai, Andréa Cristina Bogado, Ida Maria Foschiani Dias-Baptista

  18-09-2025

  https://doi.org/10.4081/gh.2025.1394

  982

  PDF: 437

  Supplementary materials: 82

  HTML: 18
• 

  Mapping healthcare resources and regional mortality in Europe: a spatial study of current service coverage

  Alicja Olejnik, Agata Żółtaszek

  04-12-2025

  https://doi.org/10.4081/gh.2025.1425

  374

  PDF: 223

  Supplementary materials: 32

  HTML: 26
• 

  Spatial association between the incidence rate of COVID-19 and poverty in the São Paulo municipality, Brazil

  Marcos César Ferreira

  26-11-2020

  https://doi.org/10.4081/gh.2020.921

  7503

  PDF: 1499

  Appendix: 186

  HTML: 34
• 

  Bayesian spatial modelling of contraception effects on fertility in Mexican municipalities in 2020

  Gerardo Núñez Medina

  17-05-2022

  https://doi.org/10.4081/gh.2022.1080

  1252

  PDF: 660

  HTML: 150

• Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina

  Carlos Matías Scavuzzo, Micaela Natalia Campero, Rosana Elizabeth Maidana, María Georgina Oberto, María Victoria Periago, Ximena Porcasi

  28-05-2024

  https://doi.org/10.4081/gh.2024.1279

  2883

  PDF: 905

  HTML: 91
• 

  Geospatial assessment of primary healthcare centres in Jeddah, Saudi Arabia

  Abdulkader A. Murad, Mohaimin Azmain

  26-02-2026

  https://doi.org/10.4081/gh.2026.1463

  548

  PDF: 265

  HTML: 6
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  Spatial pattern of tuberculosis cases in Jos Metropolis, Nigeria in the period 2019-2022

  Augustine Odo Ebonyi, Mary-Jane Ebire Ebonyi, Femi Rufus Tinuola, Isaiah Gwitira

  16-03-2026

  https://doi.org/10.4081/gh.2026.1456

  272

  PDF: 205

  HTML: 12
• 

  Metropolitan urban hotspots of chronic sleep deprivation: evidence from a community health survey in Gyeongbuk Province, South Korea

  Sun-Bi Um, Jung-Sup Um

  04-11-2015

  https://doi.org/10.4081/gh.2015.382

  3200

  PDF: 1485

  HTML: 1027
• 

  Socio-economic and environmental factors are related to acute exacerbation of chronic obstructive pulmonary disease incidence in Thailand

  Phuricha Phacharathonphakul, Kittipong Sornlorm

  29-11-2024

  https://doi.org/10.4081/gh.2024.1300

  2121

  PDF: 661

  HTML: 114
• 

  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

  1832

  PDF: 620

  HTML: 47
• 

  Assessment of the supply/demand balance of medical resources in Beijing from the perspective of hierarchical diagnosis and treatment

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

  13-10-2023

  https://doi.org/10.4081/gh.2023.1228

  1826

  PDF: 1233

  HTML: 202
• 

  Spatiotemporal distribution and geostatistically interpolated mapping of the melioidosis risk in an endemic zone in Thailand

  Jaruwan Wongbutdee, Jutharat Jittimanee, Wacharapong Saengnill

  05-07-2023

  https://doi.org/10.4081/gh.2023.1189

  1839

  PDF: 958

  HTML: 70
• 

  The spatial distribution pattern of human immunodeficiency virus/acquired immune deficiency syndrome in China

  Ying Wang, Yongli Yang, Xuezhong Shi, Saicai Mao, Nian Shi, Xiaoqing Hui

  31-05-2016

  https://doi.org/10.4081/gh.2016.414

  4274

  PDF: 1856

  HTML: 2265
• 

  Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling

  Laura Grisotto, Dario Consonni, Lorenzo Cecconi, Dolores Catelan, Corrado Lagazio, Pier Alberto Bertazzi, Michela Baccini, Annibale Biggeri

  18-04-2016

  https://doi.org/10.4081/gh.2016.426

  2432

  PDF: 1842

  HTML: 1146

• 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

  2799

  PDF: 797

  HTML: 101
• 

  Spatial prediction of the risk of exposure to Echinococcus spp. among schoolchildren and dogs in Ningxia Hui Autonomous Region, People's Republic of China

  Angela M. Cadavid Restrepo, Yu Rong Yang, Donald P. McManus, Darren J. Gray, Tamsin S. Barnes, Gail M. Williams, Ricardo J. Soares Magalhães, Archie C.A. Clements

  07-05-2018

  https://doi.org/10.4081/gh.2018.644

  2259

  PDF: 976

  HTML: 96
• 

  Prevalence of hypertension in Thailand: Hotspot clustering detected by spatial analysis

  Wongsa Laohasiriwong, Nattapong Puttanapong, Atthawit Singsalasang

  07-05-2018

  https://doi.org/10.4081/gh.2018.608

  4325

  PDF: 2053

  HTML: 582
• 

  Spatio-temporal analysis of leptospirosis in Brazil and its relationship with flooding

  Alice Nardoni Marteli, Laurindo Antonio Guasselli , Décio Diament , Gabriele Ozório Wink , Vitor Vieira Vasconcelos

  29-11-2022

  https://doi.org/10.4081/gh.2022.1128

  2816

  PDF: 1709

  HTML: 219

• Spatial associations between chronic kidney disease and socio-economic factors in Thailand

  Juree Sansuk, Kittipong Sornlorm

  30-01-2024

  https://doi.org/10.4081/gh.2024.1246

  6488

  PDF: 1107

  HTML: 1131
• 

  Evaluation by accessibility index differences of the cross-border potential for general inpatient care in the Ems-Dollart Region, a Dutch-German cross-border area

  Sebastian Specht, Helge Schnack, Andreas Hein

  08-08-2025

  https://doi.org/10.4081/gh.2025.1381

  1318

  PDF: 357

  HTML: 53
• 

  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

  2032

  PDF: 929

  HTML: 33
• 

  Improving AfriPop dataset with settlement extents extracted from RapidEye for the border region comprising South-Africa, Swaziland and Mozambique

  Julie Deleu, Jonas Franke, Michael Gebreslasie, Catherine Linard

  04-11-2015

  https://doi.org/10.4081/gh.2015.336

  2665

  PDF: 1217

  HTML: 1134
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  Unravelling the dual burden in regional context: how child malnutrition and socioeconomic gradients shape early childhood development

  Muhammad Usman

  05-02-2026

  https://doi.org/10.4081/gh.2026.1455

  520

  PDF: 354

  HTML: 12
• 

  Differences in spatial patterns of long-term care depending on severity in Hokkaido, Japan

  Kazuki Ohashi, Kensuke Fujiwara, Takumi Tanikawa, Kyohei Bando, Tomohiro Aoki, Katsuhiko Ogasawara

  16-05-2022

  https://doi.org/10.4081/gh.2022.1077

  1615

  PDF: 758

  HTML: 37
• 

  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

  3296

  PDF: 1715

  HTML: 200
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  Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus

  Vasna Joshua, Kamaraj Pattabi, Yuvaraj Jeyaraman, Prabhdeep Kaur, Tarun Bhatnagar, Suresh Arunachalam, Sabarinathan Ramasamy, Venkateshprabhu Janagaraj, Manoj V Murhekar

  30-11-2022

  https://doi.org/10.4081/gh.2022.1097

  2326

  PDF: 945

  HTML: 124
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  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

  1376

  PDF: 688

  HTML: 351
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  MALAREO: a user-driven project

  Michael T. Gebreslasie, Ides Bauwens

  04-11-2015

  https://doi.org/10.4081/gh.2015.329

  2888

  PDF: 1274

  HTML: 1013
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  Evaluation of spatial cluster detection methods for dengue fever in the state of Paraiba, Brazil

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