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  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

  7347

  PDF: 2556

  APPENDIX: 1185

  HTML: 5447
• 

  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

  3731

  PDF: 1913

  HTML: 2259
• 

  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

  4415

  PDF: 2322

  HTML: 2207
• 

  Correlation analysis of air pollutant index levels and dengue cases across five different zones in Selangor, Malaysia

  Loshini Thiruchelvam, Sarat C. Dass, Rafdzah Zaki, Abqariyah Yahya, Vijanth S. Asirvadam

  07-05-2018

  https://doi.org/10.4081/gh.2018.613

  2357

  PDF: 1339

  HTML: 337

• 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

  1963

  PDF: 742

  HTML: 134
• 

  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

  3307

  PDF: 1457

  HTML: 1227
• 

  Examination of infant mortality risk in Turkey with spatio-temporal Bayesian models

  Sade Kılıç Yıldırım, Celal Reha Alpar

  14-11-2025

  https://doi.org/10.4081/gh.2025.1396

  448

  PDF: 221

  HTML: 6
• 

  Environmental and geographical factors influence malaria transmission in KwaZulu-Natal province, South Africa

  Osadolor Ebhuoma, Michael Gebreslasie, Oswaldo Villena, Ali Arab

  09-06-2025

  https://doi.org/10.4081/gh.2025.1370

  1324

  PDF: 853

  HTML: 137
• 

  Estimating small area health-related characteristics of populations: a methodological review

  Azizur Rahman

  08-05-2017

  https://doi.org/10.4081/gh.2017.495

  4408

  PDF: 1990

  HTML: 1374
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  Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

  Joseph Leedale, Adrian M. Tompkins, Cyril Caminade, Anne E. Jones, Grigory Nikulin, Andrew P. Morse

  31-03-2016

  https://doi.org/10.4081/gh.2016.393

  4640

  PDF: 1926

  HTML: 2560
• 

  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

  1449

  PDF: 606

  HTML: 24
• 

  Spatial Bayesian semi-parametric Cox-Leroux modelling of stroke patient hospitalization: aspects on survival

  Aswi Aswi, Bobby Poerwanto, Nurussyariah Hammado, Nurwan Nurwan, Oktaviana Oktaviana, Siti Djawijah, Susanna Cramb

  21-07-2025

  https://doi.org/10.4081/gh.2025.1380

  977

  PDF: 402

  HTML: 38
• 

  The spatial distribution of Schistosoma mansoni infection in four regions of western Côte d'Ivoire

  Rufin K. Assaré, Ying-Si Lai, Ahoua Yapi, Yves-Nathan T. Tian-Bi, Mamadou Ouattara, Patrick K. Yao, Stefanie Knopp, Penelope Vounatsou, Jürg Utzinger, Eliézer K. N'Goran

  03-06-2015

  https://doi.org/10.4081/gh.2015.345

  4496

  PDF: 1874

  HTML: 1241
• 

  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

  1256

  PDF: 660

  HTML: 150
• 

  Combining process-based and correlative models improves predictions of climate change effects on Schistosoma mansoni transmission in eastern Africa

  Anna-Sofie Stensgaard, Mark Booth, Grigory Nikulin, Nicky McCreesh

  31-03-2016

  https://doi.org/10.4081/gh.2016.406

  4243

  PDF: 1616

  HTML: 1068
• 

  Spatial analysis of incidence of cutaneous melanoma in the Friuli Venezia Giulia region in the period 1995-2005

  Lorenzo Cecconi, Anna Busolin, Fabio Barbone, Diego Serraino, Alessandra Chiarugi, Annibale Biggeri, Dolores Catelan

  18-04-2016

  https://doi.org/10.4081/gh.2016.422

  2627

  PDF: 1705

  HTML: 981
• 

  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

  2437

  PDF: 1847

  HTML: 1146
• 

  Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches

  Farah Kristiani, I Gede Nyoman Mindra Jaya, Robyn Irawan, Inanta Maria Priscilia

  02-02-2026

  https://doi.org/10.4081/gh.2026.1461

  611

  PDF: 314

  Supplementary materials: 47

  HTML: 10
• 

  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

  2896

  PDF: 589

  HTML: 73
• 

  Effects of weather and landscape on the equine West Nile virus infection risk in Mississippi, USA

  Guiming Wang

  04-11-2015

  https://doi.org/10.4081/gh.2015.357

  2181

  PDF: 1397

  HTML: 959
• 

  Preferential sampling in veterinary parasitological surveillance

  Lorenzo Cecconi, Annibale Biggeri, Laura Grisotto, Veronica Berrocal, Laura Rinaldi, Vincenzo Musella, Giuseppe Cringoli, Dolores Catelan

  18-04-2016

  https://doi.org/10.4081/gh.2016.412

  2340

  PDF: 1669

  APPENDIX: 652

  HTML: 1051
• 

  Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy

  Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Loshini Thiruchelvam, Nur Balqishanis Zainal Abidin, Ani Shabri, Sarah A'fifah Abdullah Sani

  13-11-2023

  https://doi.org/10.4081/gh.2023.1236

  1742

  PDF: 751

  HTML: 74

• 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

  89

  PDF: 54

  HTML: 3
• 

  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

  3826

  PDF: 1731

  HTML: 1212
• 

  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

  1793

  PDF: 971

  Appendix: 145

  HTML: 82
• 

  A Bayesian spatiotemporal Poisson conditional autoregressive model for dengue haemorrhagic fever in Indonesia integrating satellite-generated environmental data

  Sukarna Sukarna, Hari Wijayanto, Yenni Angraini, Anang Kurnia

  18-07-2025

  https://doi.org/10.4081/gh.2025.1379

  1270

  PDF: 595

  HTML: 56
• 

  Bivariate spatiotemporal disease mapping of cancer of the breast and cervix uteri among Iranian women

  Mehdi Raei, Volker Johann Schmid, Behzad Mahaki

  08-05-2018

  https://doi.org/10.4081/gh.2018.645

  2570

  PDF: 1195

  HTML: 145
• 

  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

  6422

  PDF: 2652

  HTML: 3133
• 

  Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?

  Ulrik B. Pedersen, Dimitrios-Alexios Karagiannis-Voules, Nicholas Midzi, Tkafira Mduluza, Samson Mukaratirwa, Rasmus Fensholt, Birgitte J. Vennervald, Thomas K. Kristensen, Penelope Vounatsou, Anna-Sofie Stensgaard

  08-05-2017

  https://doi.org/10.4081/gh.2017.505

  3520

  PDF: 1637

  HTML: 1047
• 

  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

  562

  PDF: 216

  Supplementary materials: 31

  HTML: 10
• 

  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

  3313

  PDF: 1720

  HTML: 201
• 

  Post-pandemic COVID-19 estimated and forecasted hotspots in the Association of Southeast Asian Nations (ASEAN) countries in connection to vaccination rate

  I Gede Nyoman Mindra Jaya, Yudhie Andriyana, Bertho Tantular

  22-03-2022

  https://doi.org/10.4081/gh.2022.1070

  1600

  PDF: 573

  HTML: 41
• 

  Climate change and species distribution: possible scenarios for thermophilic ticks in Romania

  Cristian DomÈ™a, Attila D. Sándor, Andrei D. Mihalca

  31-05-2016

  https://doi.org/10.4081/gh.2016.421

  3066

  PDF: 1437

  HTML: 1685
• 

  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

  1686

  PDF: 775

  HTML: 76
• 

  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

  3536

  PDF: 1189

  HTML: 828
• 

  Estimating malaria burden in Nigeria: a geostatistical modelling approach

  Nnadozie Onyiri

  04-11-2015

  https://doi.org/10.4081/gh.2015.306

  7688

  PDF: 3199

  HTML: 3284
• 

  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

  2267

  PDF: 980

  HTML: 96
• 

  Spatio-temporal variations and determinants of antenatal care utilization among adolescents in Bulawayo metropolitan area, Zimbabwe: an analysis of routine data, 2019-2024

  Tariroyashe Chivanganye, Maphios Siamuchembu, Alice Gumbo, Lenka Beňová, Peter M. Macharia

  11-12-2025

  https://doi.org/10.4081/gh.2025.1434

  524

  PDF: 443

  HTML: 40
• 

  Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

  Yvonne Walz, Martin Wegmann, Benjamin Leutner, Stefan Dech, Penelope Vounatsou, Eliézer K. N'Goran, Giovanna Raso, Jürg Utzinger

  30-11-2015

  https://doi.org/10.4081/gh.2015.398

  4491

  PDF: 1284

  HTML: 1216
• 

  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

  8495

  PDF: 3538

  HTML: 2708
• 

  Assessing spatial patterns of HIV prevalence and interventions in semi-urban settings in South Africa. Implications for spatially targeted interventions

  Lucy Chimoyi, Zvifadzo Matsena-Zingoni, Salome Charalambous, Edmore Marinda, Samuel Manda, Eustasius Musenge

  29-08-2022

  https://doi.org/10.4081/gh.2022.1084

  2287

  PDF: 596

  Supplementary 1: 152

  Supplementary 2: 355

  HTML: 178
• 

  Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis

  François Niragire, Thomas N.O. Achia, Alexandre Lyambabaje, Joseph Ntaganira

  11-05-2017

  https://doi.org/10.4081/gh.2017.450

  3201

  PDF: 1840

  HTML: 1395
• 

  Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

  Thandi Kapwata, Michael T. Gebreslasie

  16-11-2016

  https://doi.org/10.4081/gh.2016.434

  4336

  PDF: 1914

  APPENDIX 1: 464

  APPENDIX 2: 492

  HTML: 1650
• 

  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

  2103

  PDF: 1041

  HTML: 161
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  Predicting the spatial distribution of Biomphalaria straminea, a potential intermediate host for Schistosoma mansoni, in China

  Mohamed R. Habib, Yun-Hai Guo, Shan Lv, Wen-Biao Gu, Xiao-Heng Li, Xiao-Nong Zhou

  29-11-2016

  https://doi.org/10.4081/gh.2016.453

  4035

  PDF: 1527

  HTML: 1146
• 

  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

  2936

  PDF: 2083

  HTML: 416
• 

  Human infections and co-infections with helminths in a rural population in Guichi, Anhui Province, China

  Yi Hu, Rui Li, Michael P. Ward, Yue Chen, Henry Lynn, Decheng Wang, Gengxin Chen, Zonggui He, Liqian Sun, Chenglong Xiong, Zhijie Zhang, Qingwu Jiang

  04-11-2015

  https://doi.org/10.4081/gh.2015.374

  2500

  PDF: 1310

  HTML: 982
• 

  CutL: an alternative to Kulldorff's scan statistics for cluster detection with a specified cut-off level

  Barbara Więckowska, Justyna Marcinkowska

  06-11-2017

  https://doi.org/10.4081/gh.2017.556

  2464

  PDF: 771

  HTML: 899
• 

  Spatial multilevel modelling male partners’ influence on women’s modern contraceptive use: a study in Angola and Zambia

  Kabeya Clement Mulamba

  12-05-2025

  https://doi.org/10.4081/gh.2025.1340

  1472

  PDF: 308

  HTML: 59
• 

  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

  833

  PDF: 435

  Supplementary materials: 82

  HTML: 30
• 

  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

  3905

  PDF: 1832

  HTML: 779
• 

  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

  1624

  PDF: 957

  HTML: 53
• 

  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

  1654

  PDF: 830

  HTML: 81
• 

  Nonlinear analysis of factors influencing public health in China based on machine learning

  Dehong Sun, Hui Wang

  16-03-2026

  https://doi.org/10.4081/gh.2026.1450

  195

  PDF: 159

  HTML: 9
• 

  Assessment of primary healthcare accessibility and inequality in north-eastern Kazakhstan

  Askhat Shaltynov, Jorge Rocha , Ulzhan Jamedinova, Ayan Myssayev

  13-05-2022

  https://doi.org/10.4081/gh.2022.1046

  3354

  PDF: 1429

  HTML: 347
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  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

  2956

  PDF: 1010

  HTML: 800
• 

  Spatiotemporal transmission and socio-climatic factors related to paediatric tuberculosis in north-western Ethiopia

  Kefyalew Addis Alene, Kerri Viney, Emma S. McBryde, Archie C.A. Clements

  27-11-2017

  https://doi.org/10.4081/gh.2017.575

  3797

  PDF: 1282

  APPENDIX: 451

  HTML: 863

• Spatial risk profiling of Schistosoma japonicum in Eryuan county, Yunnan province, China

  Peter Steinmann, Xiao-Nong Zhou, Barbara Matthys, Yuan-Lin Li, Hong-Jun Li, Shao-Rong Chen, Zhong Yang, Weng Fan, Tie-Wu Jia, Lan-Hua Li, Penelope Vounatsou, Jürg Utzinger

  59-73

  01-11-2007

  https://doi.org/10.4081/gh.2007.255

  2782

  PDF: 953
• 

  Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia

  Hassan M. Khormi, Lalit Kumar

  21-11-2016

  https://doi.org/10.4081/gh.2016.416

  5509

  PDF: 2635

  HTML: 1997
• 

  Dynamic effect of economic growth on the persistence of suicide rates

  Tzu-Yi Yang, Yu-Tai Yang, Ssu-Han Chen, Yu-Ting Lan, Chia-Jui Peng

  25-05-2023

  https://doi.org/10.4081/gh.2023.1201

  995

  PDF: 714

  HTML: 68
• 

  Venomous snakebite risk and its implications in Zacatecas State, Mexico 2007-2017

  Jesús Lenin Lara-Galván, Manuel Montesino-San Martín, Xabier Herrero Otero, Juan Felipe Martínez-Montoya, José Jesús Sigala-Rodríguez, Ana Márcia Barbosa

  05-11-2025

  https://doi.org/10.4081/gh.2025.1404

  649

  PDF: 331

  Supplementary materials: 91

  HTML: 10
• 

  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

  2286

  PDF: 744

  Supplementary materials: 216

  HTML: 118

• Mapping and predicting malaria transmission in the People's Republic of China, using integrated biology-driven and statistical models

  Guo-Jing Yang, Qi Gao, Shui-Sen Zhou, John B. Malone, Jennifer C. McCarroll, Marcel Tanner, Penelope Vounatsou, Robert Bergquist, Jürg Utzinger, Xiao-Nong Zhou

  11-22

  01-11-2010

  https://doi.org/10.4081/gh.2010.183

  3354

  PDF: 1719
• 

  The influence of socioeconomic deprivation, access to healthcare and physical environment on old-age survival in Portugal

  Ana Isabel Ribeiro, Elias Teixeira Krainski, Marilia Sá Carvalho, Maria de Fátima de Pina

  07-11-2017

  https://doi.org/10.4081/gh.2017.581

  3765

  PDF: 1378

  HTML: 878

• Sensitivity analysis of the relationship between disease occurrence and distance from a putative source of pollution

  Emanuela Dreassi, Corrado Lagazio, Milena M. Maule, Corrado Magnani, Annibale Biggeri

  263-271

  01-05-2008

  https://doi.org/10.4081/gh.2008.249

  1427

  PDF: 778
• 

  Identifying counties vulnerable to diabetes from obesity prevalence in the United States: a spatiotemporal analysis

  Xiao Li, Amanda Staudt, Lung-Chang Chien

  21-11-2016

  https://doi.org/10.4081/gh.2016.439

  2796

  PDF: 1326

  APPENDIX: 485

  HTML: 1155
• 

  Spatial-temporal analysis of prostate cancer incidence from the Pennsylvania Cancer Registry, 2000-2011

  Ming Wang, Stephen A. Matthews, Khaled Iskandarani, Yimei Li, Zheng Li, Vernon M. Chinchilli, Lijun Zhang

  28-11-2017

  https://doi.org/10.4081/gh.2017.611

  3763

  PDF: 973

  HTML: 730
• 

  The spatial distribution of injuries in need of surgical intervention in Nepal

  Shailvi Gupta, Thomas A. Groen, Barclay T. Stewart, Sunil Shrestha, David A. Spiegel, Benedict C. Nwomeh, Reinou S. Groen, Adam L. Kushner

  31-05-2016

  https://doi.org/10.4081/gh.2016.359

  3639

  PDF: 1310

  HTML: 1112
• 

  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

  512

  PDF: 165

  HTML: 8

• 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

  6497

  PDF: 1108

  HTML: 1132

• A Bayesian kriging model for estimating residential exposure to air pollution of children living in a high-risk area in Italy

  Ana M. Vicedo-Cabrera, Annibale Biggeri, Laura Grisotto, Fabio Barbone, Dolores Catelan

  87-95

  01-11-2013

  https://doi.org/10.4081/gh.2013.57

  2727

  PDF: 1425

• Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist

  Giovanna Raso, Penelope Vounatsou, Donald P. McManus, Jürg Utzinger

  85-96

  01-11-2007

  https://doi.org/10.4081/gh.2007.257

  2696

  PDF: 923

• 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

  1404

  PDF: 651

  HTML: 163
• 

  Point process methods in epidemiology: application to the analysis of human immunodeficiency virus/acquired immunodeficiency syndrome mortality in urban areas

  Jose Antonio Quesada, Inmaculada Melchor, Andreu Nolasco

  26-05-2017

  https://doi.org/10.4081/gh.2017.506

  1865

  PDF: 1004

  HTML: 1066
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  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

  2040

  PDF: 931

  HTML: 33
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  Spatial analysis of congenital heart disease in São Paulo State, Brazil 2012-2022: associations with air pollution, maternal factors and social vulnerability

  Amarílis Bahia Bezerra, Ligia Vizeu Barrozo, Alfredo Pereira de Queiroz

  18-09-2025

  https://doi.org/10.4081/gh.2025.1407

  774

  PDF: 436

  HTML: 20
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  Nigeria’s malaria prevalence in 2015: a geospatial, exploratory district-level approach

  Mina Whyte, Kennedy Mwai Wambui, Eustasius Musenge

  25-11-2024

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• A descriptive and model-based spatial comparison of the standardised mortality ratio and the age-standardised mortality rate

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