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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

  1772

  PDF: 1006

  HTML: 171
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  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

  4469

  PDF: 1826

  HTML: 1756
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  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

  2568

  PDF: 1458

  HTML: 2022
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  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

  4273

  PDF: 1894

  APPENDIX 1: 460

  APPENDIX 2: 487

  HTML: 1648
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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

  2871

  PDF: 1235

  Supplementary Materials: 194

  HTML: 112
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  Design and implementation of a spatial database for analysis of wheelchair accessibility

  Peter Nezval, Takeshi Shirabe

  24-03-2025

  https://doi.org/10.4081/gh.2025.1324

  2023

  PDF: 577

  HTML: 106
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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

  6892

  PDF: 2554

  Appendix: 383

  HTML: 340

• Mapping environmental susceptibility to Saint Louis encephalitis virus, based on a decision tree model of remotelysensed data

  Camilo H. Rotela, Lorena I. Spinsanti, Mario A. Lamfri, Marta S. Contigiani, Walter R. Almiròn, Carlos M. Scavuzzo

  85-94

  01-11-2011

  https://doi.org/10.4081/gh.2011.160

  1403

  PDF: 889
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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

  3224

  PDF: 1686

  HTML: 196
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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

  2396

  PDF: 1067

  HTML: 187
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  Spatio-temporal analysis of foot traffic dynamics in Charleston County, South Carolina: before, during, and after COVID-19

  Wish Shao, Abolfazl Mollalo, Navid Hashemi Tonekaboni

  23-06-2025

  https://doi.org/10.4081/gh.2025.1363

  754

  PDF: 408

  HTML: 32
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  Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model

  Adrian M. Tompkins, Nicky McCreesh

  31-03-2016

  https://doi.org/10.4081/gh.2016.408

  3596

  PDF: 1479

  HTML: 1002
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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

  2749

  PDF: 543

  HTML: 63
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  Spatial accessibility to basic public health services in South Sudan

  Peter M. Macharia, Paul O. Ouma, Ezekiel G. Gogo, Robert W. Snow, Abdisalan M. Noor

  11-05-2017

  https://doi.org/10.4081/gh.2017.510

  9026

  PDF: 2836

  APPENDIX: 6782

  HTML: 1160

• Optimizing denominator data estimation through a multimodel approach

  Ward Bryssinckx, Els Ducheyne, Veerle Versteirt, Herwig Leirs, Guy Hendrickx

  573-582

  01-05-2014

  https://doi.org/10.4081/gh.2014.47

  1226

  PDF: 1091

• Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters

  Muhammad Shahzad Sarfraz, Nagesh K. Tripathi, Fazlay S. Faruque, Usama Ijaz Bajwa, Asanobu Kitamoto, Marc Souris

  S685-S697

  01-12-2014

  https://doi.org/10.4081/gh.2014.297

  11032

  PDF: 2808
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  Using object-based image analysis to map commercial poultry operations from high resolution imagery to support animal health outbreaks and events

  Susan Maroney, MaryJane McCool-Eye, Andrew Fox, Christopher Burdett

  10-12-2020

  https://doi.org/10.4081/gh.2020.919

  2721

  PDF: 923

  HTML: 152
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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

  2446

  PDF: 1556

  HTML: 918
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  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

  166

  PDF: 127

  HTML: 7
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  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

  498

  PDF: 241

  Supplementary Materials: 32

  HTML: 7
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  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

  2190

  PDF: 1098

  HTML: 71
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  Impact of climate change on dengue fever: a bibliometric analysis

  Mai Liu, Yin Zhang

  19-02-2025

  https://doi.org/10.4081/gh.2025.1301

  2757

  PDF: 914

  Supplementary Materials: 367

  HTML: 134
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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

  4377

  PDF: 2305

  HTML: 2205
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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

  8404

  PDF: 3522

  HTML: 2705

• 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

  8452

  PDF: 1583

  HTML: 881
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  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

  1623

  PDF: 751

  HTML: 73