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  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

  4477

  PDF: 2353

  HTML: 2213
• 

  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

  759

  PDF: 333

  Supplementary materials: 37

  HTML: 13
• 

  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

  6583

  PDF: 2700

  HTML: 3138
• 

  Cancer incidence in Priolo, Sicily: a spatial approach for estimation of industrial air pollution impact

  Lucia Fazzo, Mario Carere, Francesco Tisano, Caterina Bruno, Achille Cernigliaro, Maria Rita Cicero, Pietro Comba, Maria Luisa Contrino, Marco De Santis, Fabrizio Falleni, Vincenzo Ingallinella, Anselmo Madeddu, Ida Marcello, Carlo Regalbuto, Giovanna Sciacca, Maria Eleonora Soggiu, Amerigo Zona

  18-04-2016

  https://doi.org/10.4081/gh.2016.320

  5354

  PDF: 2117

  HTML: 2094
• 

  Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches

  Jonas Franke, Michael Gebreslasie, Ides Bauwens, Julie Deleu, Florian Siegert

  03-06-2015

  https://doi.org/10.4081/gh.2015.335

  4735

  PDF: 1705

  HTML: 1224
• 

  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

  3689

  PDF: 1216

  HTML: 831
• 

  Spatial air pollution modelling for a West-African town

  Sirak Zenebe Gebreab, Danielle Vienneau, Christian Feigenwinter, Hampâté Bâ, Guéladio Cissé, Ming-Yi Tsai

  26-11-2015

  https://doi.org/10.4081/gh.2015.321

  3909

  PDF: 1803

  SUPPL. MATERIAL: 477

  HTML: 1091
• 

  One health review of recent Salmonella dynamics and human health outcomes in the United States

  Geoffrey Kangogo, Lavanya Sankaran, Mitesh Rajpurohit, Kate E. Trout

  11-12-2025

  https://doi.org/10.4081/gh.2025.1416

  911

  PDF: 564

  HTML: 86
• 

  Report-back for geo-referenced environmental data: A case study on personal monitoring of temperature in outdoor workers

  Laura Thompson, Maggie Sugg, Jennifer Runkle

  07-05-2018

  https://doi.org/10.4081/gh.2018.629

  2642

  PDF: 1223

  APPENDIX: 409

  HTML: 93
• 

  Modelling and analyzing spatial clusters of leptospirosis based on satellite-generated measurements of environmental factors in Thailand during 2013-2015

  Amornrat Luenam, Nattapong Puttanapong

  26-11-2020

  https://doi.org/10.4081/gh.2020.856

  3685

  PDF: 1302

  HTML: 75
• 

  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

  3830

  PDF: 1963

  HTML: 2264
• 

  Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes

  Verónica Andreo, Juan Rosa, Karina Ramos, O. Daniel Salomón

  06-05-2022

  https://doi.org/10.4081/gh.2022.1033

  1925

  PDF: 1053

  Appendix: 191

  HTML: 42
• 

  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

  3966

  PDF: 1768

  HTML: 1214
• 

  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

  4147

  PDF: 1598

  HTML: 1150
• 

  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

  1531

  PDF: 942

  HTML: 149
• 

  Urban environmental clustering to assess the spatial dynamics of Aedes aegypti breeding sites

  Guillermo Albrieu-Llinás, Manuel O. Espinosa, Agustín Quaglia, Marcelo Abril, Carlos Marcelo Scavuzzo

  07-05-2018

  https://doi.org/10.4081/gh.2018.654

  3243

  PDF: 1541

  HTML: 202
• 

  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

  4562

  PDF: 1309

  HTML: 1220
• 

  Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany

  Renke Lühken, Jörn Martin Gethmann, Petra Kranz, Pia Steffenhagen, Christoph Staubach, Franz J. Conraths, Ellen Kiel

  31-05-2016

  https://doi.org/10.4081/gh.2016.405

  3510

  PDF: 1143

  HTML: 1468
• 

  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

  2505

  PDF: 1899

  HTML: 1148
• 

  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

  2704

  PDF: 1249

  HTML: 1138
• 

  Assessing the relationship between environmental factors and malaria vector breeding sites in Swaziland using multi-scale remotely sensed data

  Sabelo Nick Dlamini, Jonas Franke, Penelope Vounatsou

  03-06-2015

  https://doi.org/10.4081/gh.2015.302

  4739

  PDF: 1876

  HTML: 1761
• 

  A dynamic, climate-driven model of Rift Valley fever

  Joseph Leedale, Anne E. Jones, Cyril Caminade, Andrew P. Morse

  31-03-2016

  https://doi.org/10.4081/gh.2016.394

  4950

  PDF: 2139

  Appendix: 597

  HTML: 1600
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  Environmental change and Rift Valley fever in eastern Africa: projecting beyond HEALTHY FUTURES

  David Taylor, Michael Hagenlocher, Anne E. Jones, Stefan Kienberger, Joseph Leedale, Andrew P. Morse

  31-03-2016

  https://doi.org/10.4081/gh.2016.387

  6616

  PDF: 2086

  HTML: 2209
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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

  4788

  PDF: 1956

  HTML: 2563
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  Health, environmental change and adaptive capacity; mapping, examining and anticipating future risks of water-related vector-borne diseases in eastern Africa

  David Taylor, Stefan Kienberger, Jack B. Malone, Adrian M. Tompkins

  18-02-2016

  https://doi.org/10.4081/gh.2016.464

  3732

  PDF: 1691

  HTML: 1122
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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

  3447

  PDF: 1767

  HTML: 216
• 

  Estimating malaria burden in Nigeria: a geostatistical modelling approach

  Nnadozie Onyiri

  04-11-2015

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

  7909

  PDF: 3271

  HTML: 3289
• 

  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

  341

  PDF: 229

  HTML: 11
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  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

  4582

  PDF: 1919

  HTML: 1246
• 

  Lung cancer associated with natural vegetation cover: spatial analysis in the state of Pará, eastern Brazil

  Bruna Rafaela Leite Dias, Laura Maria Vidal Nogueira, Ivaneide Leal Ataíde Rodrigues, Bruna Puty, Maria Liracy Batista de Souza, Gracileide Maia Corrêa, Altem Nascimento Pontes

  12-09-2025

  https://doi.org/10.4081/gh.2025.1399

  792

  PDF: 312

  HTML: 14
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  Modelling homogeneous regions of social vulnerability to malaria in Rwanda

  Jean Pierre Bizimana, Stefan Kienberger, Michael Hagenlocher, Emmanuel Twarabamenye

  31-03-2016

  https://doi.org/10.4081/gh.2016.404

  3949

  PDF: 1932

  HTML: 2264
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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

  2944

  PDF: 1312

  HTML: 1016
• 

  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

  2545

  PDF: 959

  HTML: 87
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  Modelling the domestic poultry population in the United States: A novel approach leveraging remote sensing and synthetic data methods

  Kelly A. Patyk, Mary J. McCool-Eye, David D. South, Christopher L. Burdett, Susan A. Maroney, Andrew Fox, Grace Kuiper, Sheryl Magzamen

  10-12-2020

  https://doi.org/10.4081/gh.2020.913

  4100

  PDF: 1570

  HTML: 201
• 

  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

  860

  PDF: 487

  HTML: 23

• A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment

  Jerry Enoe , Michael Sutherland, Dexter Davis, Bheshem Ramlal, Charisse Griffith-Charles , Keston H. Bhola, Elsai Mati Asefa

  28-03-2024

  https://doi.org/10.4081/gh.2024.1264

  3175

  PDF: 948

  HTML: 122
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  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

  4427

  PDF: 1645

  HTML: 1072
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  Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda

  Felipe J. Colòn-González, Adrian M. Tompkins, Riccardo Biondi, Jean Pierre Bizimana, Didacus Bambaiha Namanya

  31-03-2016

  https://doi.org/10.4081/gh.2016.379

  6617

  PDF: 2423

  Appendix: 654

  HTML: 3356

  Appendix: 269
• 

  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

  4508

  PDF: 1973

  APPENDIX 1: 472

  APPENDIX 2: 504

  HTML: 1653
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  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

  3594

  PDF: 1674

  HTML: 1049
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  Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

  Manuel O. Espinosa, Francisco Polop, Camilo H. Rotela, Marcelo Abril, Carlos M. Scavuzzo

  21-11-2016

  https://doi.org/10.4081/gh.2016.471

  4299

  PDF: 1676

  APPENDIX: 578

  HTML: 1544
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  Fine scale mapping of malaria infection clusters by using routinely collected health facility data in urban Dar es Salaam, Tanzania

  Yeromin P. Mlacha, Prosper P. Chaki, Alpha D. Malishee, Victoria M. Mwakalinga, Nicodem J. Govella, Alex J. Limwagu, John M. Paliga, Daniel F. Msellemu, Zawadi D. Mageni, Dianne J. Terlouw, Gerry F. Killeen, Stefan Dongus

  11-05-2017

  https://doi.org/10.4081/gh.2017.494

  4913

  PDF: 1801

  HTML: 1302
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  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

  2422

  PDF: 1710

  APPENDIX: 671

  HTML: 1054
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  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

  1340

  PDF: 639

  HTML: 58

• Spatial pattern analysis of the impact of community food environments on foetal macrosomia, preterm births and low birth weight

  Micaela Natalia Campero, Carlos Matías Scavuzzo, Carlos Marcelo Scavuzzo, María Dolores Román

  07-05-2024

  https://doi.org/10.4081/gh.2024.1249

  1281

  PDF: 787

  Supplementary Materials: 168

  HTML: 72
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  Modelling of the distribution of Biomphalaria glabrata and Biomphalaria straminea in the metropolitan region of Recife, Pernambuco, Brazil

  Verônica Santos Barbosa, Ricardo José de Paula Souza e Guimarães, Rodrigo Moraes Loyo, Constança Simões Barbosa

  25-11-2016

  https://doi.org/10.4081/gh.2016.490

  3305

  PDF: 1432

  HTML: 1630
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  Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

  Yazmin Alcala-Canto, Juan Antonio Figueroa-Castillo, Froylán Ibarra-Velarde, Yolanda Vera-Montenegro, María Eugenia Cervantes-Valencia, Abdelfattah Z.M. Salem, Jorge Alfredo Cuéllar-Ordaz

  07-05-2018

  https://doi.org/10.4081/gh.2018.624

  4672

  PDF: 1396

  HTML: 280
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  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

  1034

  PDF: 350

  HTML: 39
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  Is missing geographic positioning system data in accelerometry studies a problem, and is imputation the solution?

  Kristin Meseck, Marta M. Jankowska, Jasper Schipperijn, Loki Natarajan, Suneeta Godbole, Jordan Carlson, Michelle Takemoto, Katie Crist, Jacqueline Kerr

  31-05-2016

  https://doi.org/10.4081/gh.2016.403

  2716

  PDF: 1595

  HTML: 925
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  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

  3173

  PDF: 1465

  HTML: 1686
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  Validation of a spatial liver fluke model under field conditions in Ireland

  Amalia Naranjo Lucena, María Pía Munita Corbalán, Ana María Martínez-Ibeas, Guy McGrath, Riona Sayers, Grace Mulcahy, Annetta Zintl

  07-05-2018

  https://doi.org/10.4081/gh.2018.641

  2494

  PDF: 1109

  HTML: 192
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  Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia

  Amare Sewnet Minale, Kalkidan Alemu

  07-05-2018

  https://doi.org/10.4081/gh.2018.660

  7479

  PDF: 2599

  HTML: 1244
• 

  Zoning the territory of the Republic of Kazakhstan as to the risk of rabies among various categories of animals

  Sarsenbay K. Abdrakhmanov, Akhmetzhan A. Sultanov, Kanatzhan K. Beisembayev, Fedor I. Korennoy, Dosym B. Кushubaev, Ablaikhan S. Каdyrov

  31-05-2016

  https://doi.org/10.4081/gh.2016.429

  2918

  PDF: 1453

  APPENDIX: 734

  HTML: 1512
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  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

  5583

  PDF: 2690

  HTML: 2000
• 

  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

  1984

  PDF: 507

  HTML: 63
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  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

  2349

  PDF: 1002

  HTML: 100
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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

  1864

  PDF: 1043

  HTML: 175
• 

  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

  2627

  PDF: 1227

  HTML: 147
• 

  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

  712

  PDF: 412

  Supplementary materials: 60

  HTML: 16
• 

  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

  1748

  PDF: 1011

  HTML: 56
• 

  A spatial lag model analysis of lung cancer incidence and satellite-derived data on air pollution in Thailand from 2020 to 2023

  Wasana Silangam, Amornrat Luenam

  14-11-2025

  https://doi.org/10.4081/gh.2025.1424

  837

  PDF: 397

  HTML: 11
• 

  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

  1077

  PDF: 477

  Supplementary materials: 91

  HTML: 20
• 

  Satellite imagery technology in public health: analysis of site catchment areas for assessment of poliovirus circulation in Nigeria and Niger

  Marina Takane, Shizu Yabe, Yumiko Tateshita, Yusuke Kobayashi, Akihiko Hino, Kazuo Isono, Hiromasa Okayasu, Ousmane M. Diop, Takeo Tadono

  21-11-2016

  https://doi.org/10.4081/gh.2016.462

  2831

  PDF: 1597

  HTML: 1173
• 

  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

  3078

  PDF: 2227

  HTML: 448
• 

  Geospatial analysis in the United States reveals the changing roles of temperature on COVID-19 transmission

  Ruiwen Xiong, Xiaolong Li

  20-07-2023

  https://doi.org/10.4081/gh.2023.1213

  1522

  PDF: 833

  HTML: 32
• 

  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

  2222

  PDF: 711

  HTML: 129
• 

  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

  3390

  PDF: 1481

  HTML: 1230
• 

  Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran

  Mohammadreza Rajabi, Ali Mansourian, Petter Pilesjö, Ahad Bazmani

  179-191

  01-11-2014

  https://doi.org/10.4081/gh.2014.15

  7556

  PDF: 1661
• 

  To what extent does climate explain variations in reported malaria cases in early 20th century Uganda?

  Adrian M. Tompkins, Laragh Larsen, Nicky McCreesh, David Taylor

  31-03-2016

  https://doi.org/10.4081/gh.2016.407

  4867

  PDF: 1356

  Appendix: 582

  HTML: 1234
• 

  Impacts of sample ratio and size on the performance of random forest model to predict the potential distribution of snail habitats

  Yuanhua Liu, Jun Zhang, Michael P. Ward, Wei Tu, Lili Yu, Jin Shi, Yi Hu, Fenghua Gao, Zhiguo Cao, Zhijie Zhang

  03-07-2023

  https://doi.org/10.4081/gh.2023.1151

  2172

  PDF: 949

  Supplementary Materials: 172

  HTML: 66
• 

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

  Mina Whyte, Kennedy Mwai Wambui, Eustasius Musenge

  25-11-2024

  https://doi.org/10.4081/gh.2024.1243

  1687

  PDF: 683

  HTML: 117
• 

  Snakebite epidemiology in the State of Mexico, Mexico 2003-2024

  Aldo Gómez-Benitez, Erika Adriana Reyes-Velázquez, Edgar Oviedo-Hernández, Laura Sonia Arzate-Garay, Justin Lloyd Rheubert, Oswaldo Hernández-Gallegos

  09-04-2026

  https://doi.org/10.4081/gh.2026.1468

  951

  PDF: 342

  Supplementary Materials: 183

  HTML: 26
• 

  Public domain small-area cancer incidence data for New York State, 2005-2009

  Francis P. Boscoe, Thomas O. Talbot, Martin Kulldorff

  18-04-2016

  https://doi.org/10.4081/gh.2016.304

  2246

  PDF: 1273

  HTML: 869
• 

  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

  3334

  PDF: 1228

  Supplementary Materials: 333

  HTML: 78
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  Local landscape effects on population dynamics of Ixodes ricinus

  Naveed Asghar, Mona Petersson, Magnus Johansson, Patrik Dinnetz

  21-11-2016

  https://doi.org/10.4081/gh.2016.487

  3502

  PDF: 1628

  HTML: 842
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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

  1864

  PDF: 991

  Appendix: 152

  HTML: 84
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  A determination of the spatial concordance between Lyme disease incidence and habitat probability of its primary vector Ixodes scapularis (black-legged tick)

  Samuel F. Atkinson, Sahotra Sarkar, Aldo Aviña, Jim A. Schuermann, Phillip Williamson

  203-212

  01-11-2014

  https://doi.org/10.4081/gh.2014.17

  15415

  PDF: 1298
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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

  3028

  PDF: 1053

  HTML: 808

• Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics

  Ahmed Seid, Endalamaw Gadisa, Teshome Tsegaw, Adugna Abera, Aklilu Teshome, Abate Mulugeta, Merce Herrero, Daniel Argaw, Alvar Jorge, Asnakew Kebede, Abraham Aseffa

  377-387

  01-05-2014

  https://doi.org/10.4081/gh.2014.27

  7468

  PDF: 2931
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  Associations between rocky mountain spotted fever and veterinary care access, climatic factors and landscape in the State of Arizona, USA

  Yan Lin, Al Ekram Elahee Hridoy , Meifang Li, Zhe Wang, Li Luo, Xiaogang Ma, Zhuoming Liu, Murphy John, Chao Fan, Irene Ruberto, Xi Gong, Xun Shi

  17-07-2025

  https://doi.org/10.4081/gh.2025.1390

  1131

  PDF: 953

  Supplementary Materials: 121

  HTML: 114
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  Comparison of GPS imputation methods in environmental health research

  Sungsoon Hwang, Kashica Webber-Ritchey, Elizabeth Moxley

  29-08-2022

  https://doi.org/10.4081/gh.2022.1081

  2427

  PDF: 1138

  HTML: 42

• Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations

  Peter M. Macharia, Kerry L.M. Wong, Lenka Beňová, Jia Wang, Prestige Tatenda Makanga, Nicolas Ray, Aduragbemi Banke-Thomas

  27-05-2024

  https://doi.org/10.4081/gh.2024.1266

  3292

  PDF: 1024

  Supplementary Materials: 172

  HTML: 251
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  From Snow’s map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis

  Behzad Kiani, Colleen Lau, Robert Bergquist

  26-10-2023

  https://doi.org/10.4081/gh.2023.1247

  2202

  PDF: 939

  HTML: 43
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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

  7555

  PDF: 2586

  APPENDIX: 1194

  HTML: 5486
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  Comparing conditional autoregressive models for Bayesian spatial mapping of dengue cases in Indonesia

  Ferra Yanuar, Yudiantri Asdi, Aidinil Zetra, Sofiana Wudlu, Fenni Kurnia Mutiya, Rahmawita Rahmawita

  18-06-2026

  https://doi.org/10.4081/gh.2026.1443

  185

  PDF: 280

  HTML: 2
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  Validation of an interactive map assessing the potential spread of Galba truncatula as intermediate host of Fasciola hepatica in Switzerland

  Rhea Baggenstos, Tobias Dahinden, Paul R. Torgerson, Hansruedi Bär, Christina Rapsch, Gabriela Knubben-Schweizer

  31-05-2016

  https://doi.org/10.4081/gh.2016.418

  2741

  PDF: 1392

  HTML: 1022
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  Habitat suitability map of Ixodes ricinus tick in France using multi-criteria analysis

  Isabelle Lebert, Séverine Bord, Christine Saint-Andrieux, Eva Cassar, Patrick Gasqui, Frédéric Beugnet, Karine Chalvet-Monfray, Sophie O. Vanwambeke, Gwenaël Vourc’h, Magalie René-Martellet

  17-05-2022

  https://doi.org/10.4081/gh.2022.1058

  7415

  PDF: 2624

  Appendix: 409

  HTML: 392
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  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

  8600

  PDF: 3591

  HTML: 2719
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  Use of soil moisture active passive satellite data and WorldClim 2.0 data to predict the potential distribution of visceral leishmaniasis and its vector Lutzomyia longipalpis in Sao Paulo and Bahia states, Brazil

  Moara de Santana Martins Rodgers, Elivelton Fonseca, Prixia del Mar Nieto, John B. Malone, Jeffery C. Luvall, Jennifer C. McCarroll, Ryan Harry Avery, Maria Emilia Bavia, Raul Guimaraes, Xue Wen, Marta Mariana Nascimento Silva, Deborah D.M.T. Carneiro, Luciana Lobato Cardim

  08-06-2022

  https://doi.org/10.4081/gh.2022.1095

  1776

  PDF: 1035

  HTML: 66
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  Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa

  Ernest O. Asare, Adrian M. Tompkins, Leonard K. Amekudzi, Volker Ermert, Robert Redl

  31-03-2016

  https://doi.org/10.4081/gh.2016.391

  3179

  PDF: 1746

  HTML: 4944
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  Spatial distribution and predictive risk of perpetuation of non-typhoidal salmonellosis in poultry farms and human communities: meta-analysis of data from Nigeria

  Abdullahi O. Sanni , Annelize Jonker, Olatunji O. Johnson , Ezra Gayawan , Aminu Shittu , Olubunmi G. Fasanmi , Oluwawemimo A. Adebowale , Folorunso O. Fasina

  12-02-2026

  https://doi.org/10.4081/gh.2026.1316

  1293

  PDF: 529

  Supplementary Materials: 130

  HTML: 19
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  Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe

  Els Ducheyne, Johannes Charlier, Jozef Vercruysse, Laura Rinaldi, Annibale Biggeri, Janina Demeler, Christina Brandt, Theo de Waal, Nikolaos Selemetas, Johan Höglund, Jaroslaw Kaba, Slawomir J. Kowalczyk, Guy Hendrickx

  261-270

  19-03-2015

  https://doi.org/10.4081/gh.2015.348

  4034

  PDF: 2085
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  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

  1627

  PDF: 747

  Supplementary Materials: 132

  HTML: 24
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  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

  3242

  PDF: 666

  HTML: 93
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  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

  3327

  PDF: 1535

  Supplementary Materials: 212

  HTML: 135

• Geospatial tools for the identification of a malaria corridor in Estado Sucre, a Venezuelan north-eastern state

  Laura Delgado-Petrocelli, Alberto Camardiel, Víctor Hugo Aguilar, Néstor Martinez, Karenia Còrdova, Santiago Ramos

  169-176

  01-05-2011

  https://doi.org/10.4081/gh.2011.168

  2596

  PDF: 1036
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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

  869

  PDF: 377

  Supplementary materials: 92

  HTML: 28
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  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

  692

  PDF: 229

  HTML: 11
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  Spatial electromagnetic field intensity modelling of global system for mobile communication base stations in the Istanbul Technical University Ayazaga campus area

  Kubra Boz, Hayri Hakan Denli

  07-05-2018

  https://doi.org/10.4081/gh.2018.527

  1674

  PDF: 962

  HTML: 144
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  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

  4054

  PDF: 1869

  HTML: 794