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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

  1981

  PDF: 956

  Supplementary Materials: 148

  HTML: 59
• 

  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

  3947

  PDF: 1674

  APPENDIX 1: 438

  APPENDIX 2: 434

  HTML: 1639
• 

  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

  556

  PDF: 236

  Supplementary Materials: 47

  HTML: 30
• 

  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

  5215

  PDF: 2427

  HTML: 1980
• 

  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

  4012

  PDF: 1702

  HTML: 1234
• 

  Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors

  Roghieh Ramezankhani, Nooshin Sajjadi, Roya Nezakati Esmaeilzadeh, Seyed Ali Jozi, Mohammad Reza Shirzadi

  08-11-2017

  https://doi.org/10.4081/gh.2017.578

  2583

  PDF: 967

  HTML: 925

• Methodological framework for assessing malaria risk associated with climate change in Côte d’Ivoire

  Yao Etienne Kouakou, Iba Dieudonné Dely, Madina Doumbia, Aziza Ouattara, Effah Jemima N’da, Koffi Evrard Brou, Yao Anicet Zouzou, Guéladio Cissé, Brama Koné

  28-08-2024

  https://doi.org/10.4081/gh.2024.1285

  1355

  PDF: 609

  HTML: 100
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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

  3787

  PDF: 1414

  HTML: 1132
• 

  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

  5997

  PDF: 2462

  HTML: 3089
• 

  Impact of climate variability on the occurrence of cutaneous leishmaniasis in Khuzestan Province, southwestern Iran

  Farideh Azimi, Sadegh Shirian, Saranaz Jangjoo, Arman Ai, Tahereh Abbasi

  08-05-2017

  https://doi.org/10.4081/gh.2017.478

  2742

  PDF: 1296

  HTML: 1046
• 

  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

  2823

  PDF: 1311

  HTML: 1674
• 

  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

  6067

  PDF: 2194

  Appendix: 576

  HTML: 3271

  Appendix: 229

• Spatial-temporal risk factors in the occurrence of rabies in Mexico

  Reyna Ortega-Sánchez, Isabel Bárcenas-Reyes, Jesús Luna-Cozar, Edith Rojas-Anaya, José Quintín Cuador-Gil, Germinal Jorge Cantó-Alarcón, Nerina Veyna-Salazar, Sara González-Ruiz, Feliciano Milián-Suazo

  30-01-2024

  https://doi.org/10.4081/gh.2024.1245

  4064

  PDF: 1189

  HTML: 918
• 

  Geographical distribution of the association between El Niño South Oscillation and dengue fever in the Americas: a continental analysis using geographical information system-based techniques

  Marcos C. Ferreira

  141-151

  01-11-2014

  https://doi.org/10.4081/gh.2014.12

  3212

  PDF: 1825
• 

  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

  4119

  PDF: 2194

  HTML: 2164
• 

  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

  2629

  PDF: 1216

  APPENDIX: 628

  HTML: 1456
• 

  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

  4402

  PDF: 1779

  Appendix: 519

  HTML: 1579
• 

  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

  1657

  PDF: 880

  HTML: 158
• 

  Landscape, demographic and climatic associations with human West Nile virus occurrence regionally in 2012 in the United States of America

  John P. DeGroote, Ramanathan Sugumaran, Mark Ecker

  153-168

  01-11-2014

  https://doi.org/10.4081/gh.2014.13

  2314

  PDF: 1173
• 

  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

  3194

  PDF: 1480

  HTML: 1031
• 

  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

  4178

  PDF: 1677

  HTML: 2548
• 

  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

  3450

  PDF: 1184

  APPENDIX: 387

  HTML: 844
• 

  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

  712

  PDF: 265

  HTML: 28
• 

  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

  3520

  PDF: 1530

  HTML: 1182
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  Assessment of malaria transmission changes in Africa, due to the climate impact of land use change using Coupled Model Intercomparison Project Phase 5 earth system models

  Adrian M. Tompkins, Luca Caporaso

  31-03-2016

  https://doi.org/10.4081/gh.2016.380

  3760

  PDF: 1727

  HTML: 1270
• 

  Cluster analysis of fasciolosis in dairy cow herds in Munster province of Ireland and detection of major climatic and environmental predictors of the exposure risk

  Nikolaos Selemetas, Paul Phelan, Padraig O'Kiely, Theo de Waal

  271-279

  19-03-2015

  https://doi.org/10.4081/gh.2015.349

  2610

  PDF: 1263
• 

  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

  2192

  PDF: 957

  HTML: 130
• 

  Outbreak of acute fasciolosis in sheep farms in a Mediterranean area arising as a possible consequence of climate change

  Antonio Bosco, Laura Rinaldi, Vincenzo Musella, Alessandra Amadesi, Giuseppe Cringoli

  319-324

  19-03-2015

  https://doi.org/10.4081/gh.2015.354

  3051

  PDF: 1627

• Climatic factors associated with amyotrophic lateral sclerosis: a spatial analysis from Taiwan

  Ching-Piao Tsai, Charles Tzu-Chi Lee

  45-52

  01-11-2013

  https://doi.org/10.4081/gh.2013.53

  1624

  PDF: 995

• Effect modification of the association between meteorological variables and mortality by urban climatic conditions in the tropical city of Kaohsiung, Taiwan

  William B. Goggins, Chao Ren, Edward Ng, Chunyuh Yang, Emily Y.Y. Chan

  37-44

  01-11-2013

  https://doi.org/10.4081/gh.2013.52

  2179

  PDF: 1263

• Remote sensing and climate data as a key for understanding fasciolosis transmission in the Andes: review and update of an ongoing interdisciplinary project

  Márius V. Fuentes

  59-70

  01-11-2006

  https://doi.org/10.4081/gh.2006.281

  1656

  PDF: 1006
• 

  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

  3963

  PDF: 1210

  Appendix: 509

  HTML: 1213

• 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

  10544

  PDF: 2589
• 

  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

  2467

  PDF: 1362

  HTML: 155

• Importance of individual analysis of environmental and climatic factors affecting the density of Leishmania vectors living in the same geographical area: the example of Phlebotomus ariasi and P. perniciosus in northeast Spain

  Cristina Ballart, Irene Guerrero, Xavier Castells, Sergio Baròn, Soledad Castillejo, M. Magdalena Alcover, Montserrat Portús, Montserrat Gállego

  389-403

  01-05-2014

  https://doi.org/10.4081/gh.2014.28

  2751

  PDF: 1240
• 

  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

  2873

  PDF: 1201

  HTML: 1609
• 

  Modelling recent and future climatic suitability for fasciolosis in Europe

  Cyril Caminade, Jan van Dijk, Matthew Baylis, Diana Williams

  301-308

  19-03-2015

  https://doi.org/10.4081/gh.2015.352

  4150

  PDF: 1594
• 

  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

  1267

  PDF: 682

  HTML: 25
• 

  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

  6097

  PDF: 2338

  Appendix: 323

  HTML: 281
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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

  2011

  PDF: 848

  HTML: 82
• 

  Spatial analysis and risk mapping of Fasciola hepatica infection in dairy herds in Ireland

  Nikolaos Selemetas, Els Ducheyne, Paul Phelan, Padraig O'Kiely, Guy Hendrickx, Theo de Waal

  281-291

  19-03-2015

  https://doi.org/10.4081/gh.2015.350

  4071

  PDF: 1839
• 

  American cutaneous leishmaniasis cases in the metropolitan region of Manaus, Brazil: association with climate variables over time

  Rodrigo Augusto Ferreira de Souza, Rita Valéria Andreoli, Mary Toshie Kayano, Afrânio Lima Carvalho

  18-05-2015

  https://doi.org/10.4081/gh.2015.314

  2828

  PDF: 1407

  HTML: 810
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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

  3875

  PDF: 1443

  HTML: 1054
• 

  Analytical report of the 2016 dengue outbreak in Córdoba city, Argentina

  Camilo Rotela, Laura Lopez, María Frías Céspedes, Gabriela Barbas, Andrés Lighezzolo, Ximena Porcasi, Mario A. Lanfri, Carlos M. Scavuzzo, David E. Gorla

  06-11-2017

  https://doi.org/10.4081/gh.2017.564

  3236

  PDF: 1258

  HTML: 853

• Mathematical modelling of the impact of climatic conditions in France on Rhipicephalus sanguineus tick activity and density since 1960

  Frédéric Beugnet, Michel Kolasinski, Paul-Antoine Michelangeli, Julien Vienne, Harilaos Loukos

  255-263

  01-05-2011

  https://doi.org/10.4081/gh.2011.178

  2440

  PDF: 1381
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  Estimating malaria burden in Nigeria: a geostatistical modelling approach

  Nnadozie Onyiri

  04-11-2015

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

  7136

  PDF: 2984

  HTML: 3252
• 

  Spatial correlates of COVID-19 first wave across continental Portugal

  Bruno Barbosa, Melissa Silva, César Capinha, Ricardo A.C. Garcia, Jorge Rocha

  23-06-2022

  https://doi.org/10.4081/gh.2022.1073

  1368

  PDF: 457

  HTML: 43
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  Potential for spread of the white-nose fungus (Pseudogymnoascus destructans) in the Americas: use of Maxent and NicheA to assure strict model transference

  Luis E. Escobar, Andrés Lira-Noriega, Gonzalo Medina-Vogel, A. Townsend Peterson

  221-229

  01-11-2014

  https://doi.org/10.4081/gh.2014.19

  7164

  PDF: 3242
• 

  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

  2411

  PDF: 732

  Supplementary Materials: 333

  HTML: 96

• Impact of climate change and man-made irrigation systems on the transmission risk, long-term trend and seasonality of human and animal fascioliasis in Pakistan

  Kiran Afshan, Cesar A. Fortes-Lima, Patricio Artigas, M. Adela Valero, Mazhar Qayyum, Santiago Mas-Coma

  317-334

  01-05-2014

  https://doi.org/10.4081/gh.2014.22

  26504

  PDF: 2174

• Spatial analysis of risk factors for transmission of the Barmah Forest virus in Queensland, Australia

  Suchithra Naish, Kerrie Mengersen, Shilu Tong

  289-299

  01-11-2013

  https://doi.org/10.4081/gh.2013.74

  1748

  PDF: 954
• 

  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

  4042

  PDF: 1693

  HTML: 1742
• 

  Mosquito habitat and dengue risk potential in Kenya: alternative methods to traditional risk mapping techniques

  David F. Attaway, Kathryn H. Jacobsen, Allan Falconer, Germana Manca, Lauren Rosenshein Bennett, Nigel M. Waters

  119-130

  01-11-2014

  https://doi.org/10.4081/gh.2014.10

  3182

  PDF: 1575
• 

  Haemonchus contortus: spatial risk distribution for infection in sheep in Europe

  Laura Rinaldi, Dolores Catelan, Vincenzo Musella, Lorenzo Cecconi, Hubertus Hertzberg, Paul R. Torgerson, Fabien Mavrot, Theo de Waal, Nikolaos Selemetas, Tom Coll, Antonio Bosco, Annibale Biggeri, Giuseppe Cringoli

  325-331

  19-03-2015

  https://doi.org/10.4081/gh.2015.355

  4222

  PDF: 1918
• 

  Sheep and Fasciola hepatica in Europe: the GLOWORM experience

  Laura Rinaldi, Annibale Biggeri, Vincenzo Musella, Theo de Waal, Hubertus Hertzberg, Fabien Mavrot, Paul R. Torgerson, Nikolaos Selemetas, Tom Coll, Antonio Bosco, Laura Grisotto, Giuseppe Cringoli, Dolores Catelan

  309-317

  19-03-2015

  https://doi.org/10.4081/gh.2015.353

  4367

  PDF: 2102
• 

  Spatial epidemiology and meteorological risk factors of COVID-19 in Fars Province, Iran

  Marjan Zare, Ali Semati, Alireza Mirahmadizadeh, Abdulrasool Hemmati, Mostafa Ebrahimi

  08-06-2022

  https://doi.org/10.4081/gh.2022.1065

  898

  PDF: 429

  HTML: 21
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  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

  3446

  PDF: 1742

  HTML: 2225
• 

  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

  1564

  PDF: 812

  HTML: 62
• 

  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

  6843

  PDF: 2323

  HTML: 1162
• 

  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

  1823

  PDF: 762

  Supplementary Materials: 107

  HTML: 44
• 

  The basic reproduction quotient (Q0) as a potential spatial predictor of the seasonality of ovine haemonchosis

  Muhammad-Bashir Bolajoko, Hannah Rose, Vincenzo Musella, Antonio Bosco, Laura Rinaldi, Jan van Dijk, Giuseppe Cringoli, Eric R. Morgan

  333-350

  19-03-2015

  https://doi.org/10.4081/gh.2015.356

  2252

  PDF: 1408
• 

  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

  4275

  PDF: 1176

  HTML: 260

• Exploring recent spatial patterns of cutaneous leishmaniasis and their associations with climate in some countries of the Middle East using geographical information systems

  Salahuddin M. Jaber, Jwan H. Ibbini, Nawal S. Hijjawi, Nafn M. Amdar, Mohammed J. Huwail, Khalid Al-Aboud

  143-158

  01-11-2013

  https://doi.org/10.4081/gh.2013.62

  2041

  PDF: 993
• 

  A post-pandemic analysis of air pollution over small-sized urban areas in southern Thailand following the COVID-19 lockdown

  Dimitris Stratoulias, Beomgeun Jang, Narissara Nuthammachot

  07-07-2025

  https://doi.org/10.4081/gh.2025.1354

  638

  PDF: 241

  Supplementary Materials: 54

  HTML: 36
• 

  Effects of geographical factors on reference values of the thyroid stimulating hormone in healthy adults in China and its clinical significance

  Xinrui Pang, Miao Ge, Congxia Wang, Jinwei He

  06-05-2022

  https://doi.org/10.4081/gh.2022.1030

  1083

  PDF: 499

  HTML: 232

• Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis

  Prixia Nieto, John B. Malone, Maria E. Bavia

  115-126

  01-11-2006

  https://doi.org/10.4081/gh.2006.286

  1889

  PDF: 854

• Climate change and the potential global distribution of Aedes aegypti: spatial modelling using geographical information system and CLIMEX

  Hassan M. Khormi, Lalit Kumar

  405-415

  01-05-2014

  https://doi.org/10.4081/gh.2014.29

  9280

  PDF: 4608

• Redefining climate regions in the United States of America using satellite remote sensing and machine learning for public health applications

  Alexander Liss, Magaly Koch, Elena N. Naumova

  S467-S659

  01-12-2014

  https://doi.org/10.4081/gh.2014.294

  3095

  PDF: 1300

• Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models

  Ronaldo G. C. Scholte, Nadine Schur, Maria E. Bavia, Edgar M. Carvalho, Frédérique Chammartin, Jürg Utzinger, Penelope Vounatsou

  97-110

  01-11-2013

  https://doi.org/10.4081/gh.2013.58

  3634

  PDF: 1955
• 

  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

  2040

  PDF: 1540

  APPENDIX: 563

  HTML: 1033

• Modeling freshwater snail habitat suitability and areas of potential snail-borne disease transmission in Uganda

  A.S. Stensgaard, A. Jørgensen, N.B. Kabatereine, C. Rahbek, T.K. Kristensen

  93-104

  01-11-2006

  https://doi.org/10.4081/gh.2006.284

  2933

  PDF: 1577
• 

  The spatial distribution of interleukin-4 (IL-4) reference values in China based on a back propagation (BP) neural network

  Zhao Rong Huang, Miao Ge, Xin Rui Pang, Pu Song, Congxia Wang

  13-09-2023

  https://doi.org/10.4081/gh.2023.1197

  1124

  PDF: 486

  HTML: 14
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  Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning

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  APPENDIX: 285

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• Spatial analysis of migrating Apis mellifera colonies in Salvador, Bahia, Brazil

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• FleaTickRisk: a meteorological model developed to monitor and predict the activity and density of three tick species and the cat flea in Europe

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