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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

  2991

  PDF: 1274

  Supplementary Materials: 201

  HTML: 126
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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

  3733

  PDF: 1914

  HTML: 2259
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  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

  2441

  PDF: 1847

  HTML: 1146
• 

  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

  6423

  PDF: 2653

  HTML: 3134
• 

  Dynamic risk model for Rift Valley fever outbreaks in Kenya based on climate and disease outbreak data

  David Gikungu, Jacob Wakhungu, Donald Siamba, Edward Neyole, Richard Muita, Bernard Bett

  31-05-2016

  https://doi.org/10.4081/gh.2016.377

  3285

  PDF: 1491

  HTML: 1481
• 

  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

  2603

  PDF: 1478

  HTML: 2023
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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

  4416

  PDF: 2323

  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

  2358

  PDF: 1341

  HTML: 337
• 

  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

  4339

  PDF: 1916

  APPENDIX 1: 464

  APPENDIX 2: 492

  HTML: 1650
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  Elimination of malaria due to Plasmodium vivax in central part of the People's Republic of China: analysis and prediction based on modelling

  Zhao Chen, Liang Shi, Xiao-Nong Zhou, Zhi-Gui Xia, Robert Bergquist, Qing-Wu Jiang

  169-177

  01-11-2014

  https://doi.org/10.4081/gh.2014.14

  3759

  PDF: 1238
• 

  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

  2452

  PDF: 877

  HTML: 81
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  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

  4493

  PDF: 1285

  HTML: 1216
• 

  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

  2418

  PDF: 1078

  HTML: 188
• 

  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

  3382

  PDF: 1118

  HTML: 1464
• 

  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

  3827

  PDF: 1731

  HTML: 1212
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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

  3314

  PDF: 1721

  HTML: 201
• 

  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

  1339

  PDF: 598

  HTML: 25
• 

  MALAREO: a user-driven project

  Michael T. Gebreslasie, Ides Bauwens

  04-11-2015

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

  2894

  PDF: 1277

  HTML: 1013
• 

  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

  2268

  PDF: 980

  HTML: 96
• 

  Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka

  Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

  26-11-2015

  https://doi.org/10.4081/gh.2015.376

  3872

  PDF: 2232

  HTML: 1271
• 

  Spatial analysis and prediction of the flow of patients to public health centres in a middle-sized Spanish city

  Isabel Ramos, Juan J. Cubillas, Francisco R. Feito, Tomas Ureña

  21-11-2016

  https://doi.org/10.4081/gh.2016.452

  2216

  PDF: 1287

  HTML: 1139
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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

  4496

  PDF: 1877

  HTML: 1241
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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

  4040

  PDF: 1529

  HTML: 1147
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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

  3522

  PDF: 1637

  HTML: 1047
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  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: 75
• 

  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

  4509

  PDF: 1844

  HTML: 1758
• 

  Climate impact on malaria in northern Burkina Faso

  Yves M. Tourre, Cécile Vignolles, Christian Viel, Flore Mounier

  27-11-2017

  https://doi.org/10.4081/gh.2017.600

  2843

  PDF: 972

  HTML: 748
• 

  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

  3533

  PDF: 1267

  HTML: 73
• 

  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

  1274

  PDF: 598

  HTML: 56
• 

  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

  2113

  PDF: 914

  Supplementary Materials: 162

  HTML: 63

• 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

  2222

  PDF: 970
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  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

  1856

  PDF: 958

  Appendix: 174

  HTML: 41
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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

  2901

  PDF: 592

  HTML: 73
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  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

  1329

  PDF: 855

  HTML: 137

• 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: 954
• 

  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

  1702

  PDF: 597

  HTML: 52

• Strategy formulation for schistosomiasis japonica control in different environmental settings supported by spatial analysis: a case study from China

  Zhao Chen, Xiao-Nong Zhou, Kun Yang, Xian-Hong Wang, Zhen-Qi Yao, Tian-Ping Wang, Guo-Jing Yang, Ying-Jing Yang, Shi-Qing Zhang, Jian Wang, Tie-Wu Jia, Xiao-Hua Wu

  223-231

  01-05-2007

  https://doi.org/10.4081/gh.2007.270

  1695

  PDF: 989

• 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

  2889

  PDF: 915

  HTML: 92
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  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

  1847

  PDF: 959

  HTML: 70
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  The dog and cat population on Maio Island, Cape Verde: characterisation and prediction based on household survey and remotely sensed imagery

  Ana Carolina Lopes Antunes, Els Ducheyne, Ward Bryssinckx, Sara Vieira, Manuel Malta, Yolanda Vaz, Telmo Nunes, Koen Mintiens

  04-11-2015

  https://doi.org/10.4081/gh.2015.386

  3278

  PDF: 1166

  HTML: 1231
• 

  Estimating malaria burden in Nigeria: a geostatistical modelling approach

  Nnadozie Onyiri

  04-11-2015

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

  7689

  PDF: 3201

  HTML: 3284

• A geospatial risk assessment model for leprosy in Ethiopia based on environmental thermal-hydrological regime analysis

  Azeb Tadesse Argaw, E.J. Shannon, Abraham Assefa, Fekade Silassie Mikru, Berhane Kidane Mariam, John B. Malone

  105-113

  01-11-2006

  https://doi.org/10.4081/gh.2006.285

  2543

  PDF: 1078
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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

  4605

  PDF: 1355

  HTML: 277
• 

  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

  1299

  PDF: 635

  HTML: 292
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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

  5510

  PDF: 2637

  HTML: 1997
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  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

  1601

  PDF: 574

  HTML: 41
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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

  1793

  PDF: 1018

  HTML: 173
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  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

  1450

  PDF: 606

  HTML: 24

• 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

  3306

  PDF: 1745

• Spatial epidemiology of Toxoplasma gondii infection in goats in Serbia

  Vitomir Djokić, Ivana Klun, Vincenzo Musella, Laura Rinaldi, Giuseppe Cringoli, Smaragda Sotiraki, Olgica Djurković-Djaković

  479-488

  01-05-2014

  https://doi.org/10.4081/gh.2014.37

  2283

  PDF: 1237
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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

  841

  PDF: 438

  Supplementary Materials: 107

  HTML: 18

• Japan's efforts to promote global health using satellite remote sensing data from the Japan Aerospace Exploration Agency for prediction of infectious diseases and air quality

  Tamotsu Igarashi, Akihiko Kuze, Shinichi Sobue, Aya Yamamoto, Kazuhide Yamamoto, Kei Oyoshi, Keiji Imaoka, Toru Fukuda

  S603-S610

  01-12-2014

  https://doi.org/10.4081/gh.2014.299

  2930

  PDF: 1779
• 

  Vulnerability to COVID-19 in Pernambuco, Brazil: A geospatial evaluation supported by multiple-criteria decision aid methodology

  Ciro José Jardim de Figueiredo, Caroline Maria de Miranda Mota, Amanda Gadelha Ferreira Rosa, Arthur Pimentel Gomes de Souza, Simone Maria da Silva Lima

  14-01-2022

  https://doi.org/10.4081/gh.2022.1000

  2746

  PDF: 587

  HTML: 59
• 

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

  Azizur Rahman

  08-05-2017

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

  4410

  PDF: 1993

  HTML: 1374

• A climate distribution model of malaria transmission in Sudan

  Mohammed I. Musa, Shamarina Shohaimi, Nor R. Hashim, Isthrinayagy Krishnarajah

  27-36

  01-11-2012

  https://doi.org/10.4081/gh.2012.102

  2479

  PDF: 1176
• 

  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

  1763

  PDF: 953

  Supplementary Materials: 151

  HTML: 90
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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

  1709

  PDF: 985

  HTML: 65

• 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

  11102

  PDF: 2821
• 

  Haemodialysis services in the northeastern region of Iran

  Behzad Kiani, Nasser Bagheri, Ahmad Tara, Benyamin Hoseini, Mahmoud Tara

  11-05-2017

  https://doi.org/10.4081/gh.2017.561

  4409

  PDF: 1283

  HTML: 913
• 

  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

  3872

  PDF: 1761

  SUPPL. MATERIAL: 467

  HTML: 1089
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  Air quality classification and its temporal trend in Tehran, Iran, 2002-2012

  Raheleh Saniei, Ali Zangiabadi, Mohammad Sharifikia, Yousef Ghavidel

  31-05-2016

  https://doi.org/10.4081/gh.2016.442

  4897

  PDF: 1522

  HTML: 2589
• 

  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

  3479

  PDF: 1384

  HTML: 864
• 

  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

  4843

  PDF: 2090

  Appendix: 590

  HTML: 1597
• 

  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

  196

  PDF: 159

  HTML: 9
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  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

  2542

  PDF: 1592
• 

  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

  614

  PDF: 317

  Supplementary materials: 47

  HTML: 10
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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

  4642

  PDF: 1927

  HTML: 2560

• 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

  4736

  PDF: 1427

  HTML: 1094
• 

  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

  793

  PDF: 430

  HTML: 33
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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

  821

  PDF: 341

  Supplementary materials: 83

  HTML: 25
• 

  Predicting frequency distribution and influence of sociodemographic and behavioral risk factors of Schistosoma mansoni infection and analysis of co-infection with intestinal parasites

  Carla V.V. Rollemberg, Marília M.B.L. Silva, Karla C. Rollemberg, Fábio R. Amorim, Nayanna M.N. Lessa, Marcos D.S. Santos, Acácia M.B. Souza, Enaldo V. Melo, Roque P. Almeida, Ângela M. Silva, Guilherme L. Werneck, Mario A. Santos, José A.P. Almeida, Amélia R. Jesus

  18-05-2015

  https://doi.org/10.4081/gh.2015.303

  4931

  PDF: 2021

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  1145

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  3518

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  3241

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• Developing operational algorithms using linear and non-linear squares estimation in Python® for the identification of Culex pipiens and Culex restuans in a mosquito abatement district (Cook County, Illinois, USA)

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  3166

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  APPENDIX: 497

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• Remote sensing for predicting potential habitats of Oncomelania hupensis in Hongze, Baima and Gaoyou lakes in Jiangsu province, China

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  4751

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  Appendix: 569

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• Susceptibility mapping of visceral leishmaniasis based on fuzzy modelling and group decision-making methods

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  37-50

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• Meteorological, environmental remote sensing and neural network analysis of the epidemiology of malaria transmission in Thailand

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  3390

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  2287

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  Supplementary 1: 152

  Supplementary 2: 355

  HTML: 178
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  6545

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• Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand

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• Integrated disease mapping in a polyparasitic world

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• Indirect field technology for detecting areas object of illegal spills harmful to human health: application of drones, photogrammetry and hydrological models

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  5385

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• Spatial distribution of Biomphalaria spp., the intermediate host snails of Schistosoma mansoni, in Brazil

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  1294

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• Comparison of data-fitting models for schistosomiasis: a case study in Xingzi, China

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  4823

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  Spatial autocorrelation and stratified heterogeneity in the evaluation of breast cancer risk inequity and socioeconomic factors analysis in China: Evidence from Nanchang, Jiangxi Province

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  1914

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  First year with COVID-19: Assessment and prospects

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  3097

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• An operative dengue risk stratification system in Argentina based on geospatial technology

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  3192

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  2938

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