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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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  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
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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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  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
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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
• 

  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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  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
• 

  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
• 

  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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  A geospatial study of the coverage of catheterization laboratory facilities (cath labs) and the travel time required to reach them in East Java, Indonesia

  Andrianto Andrianto, Farizal Rizky Muharram, Chaq El Chaq Zamzam Multazam, Wigaviola Socha, Doni Firman, Ahmad Chusnu Romdhoni, Senitza Anisa Salsabilla

  25-05-2023

  https://doi.org/10.4081/gh.2023.1164

  1514

  PDF: 890

  HTML: 61
• 

  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
• 

  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
• 

  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
• 

  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
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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
• 

  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
• 

  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
• 

  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 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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  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
• 

  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

• 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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  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
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  Spatial pattern of tuberculosis cases in Jos Metropolis, Nigeria in the period 2019-2022

  Augustine Odo Ebonyi, Mary-Jane Ebire Ebonyi, Femi Rufus Tinuola, Isaiah Gwitira

  16-03-2026

  https://doi.org/10.4081/gh.2026.1456

  278

  PDF: 211

  HTML: 12
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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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  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
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  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
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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

  1274

  PDF: 598

  HTML: 56

• 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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  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
• 

  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
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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
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  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
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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
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  Optimizing vaccination sites for infectious diseases based on heterogeneous travel modes in multiple scenarios

  Wentao Yang, Fengjie Wang, Yihan You, Zhixiong Fang, Xing Wang, Xiaoming Mei

  24-03-2025

  https://doi.org/10.4081/gh.2025.1362

  1933

  PDF: 444

  HTML: 105
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  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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  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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  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
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  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

• Mapping and prediction of schistosomiasis in Nigeria using compiled survey data and Bayesian geospatial modelling

  Uwem F. Ekpo, Eveline Hürlimann, Nadine Schur, Akinola. S. Oluwole, Eniola M. Abe, Margaret A. Mafe, Obiageli J. Nebe, Sunday Isiyaku, Francisca Olamiju, Mukaila Kadiri, Temitope O.S. Poopola, Eka I. Braide, Yisa Saka, Chiedu F. Mafiana, Thomas K. Kristensen, Jürg Utzinger, Penelope Vounatsou

  355-366

  01-05-2013

  https://doi.org/10.4081/gh.2013.92

  6134

  PDF: 2112
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  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

  HTML: 1093
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  Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

  Suparat Tappo, Wongsa Laohasiriwong, Nattapong Puttanapong

  29-11-2022

  https://doi.org/10.4081/gh.2022.1091

  1809

  PDF: 1152

  Appendix: 166

  HTML: 217
• 

  Diagnostic approaches to malaria in Zambia, 2009-2014

  Victor M. Mukonka, Emmanuel Chanda, Mulakwa Kamuliwo, Maha A. Elbadry, Pauline K. Wamulume, Mercy Mwanza-Ingwe, Jailos Lubinda, Lindsey A. Laytner, Wenyi Zhang, Gabriel Mushinge, Ubydul Haque

  03-06-2015

  https://doi.org/10.4081/gh.2015.330

  3687

  PDF: 1460

  HTML: 1171
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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

  7689

  PDF: 3201

  HTML: 3284
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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
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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
• 

  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
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  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

• Application of modern spatio-temporal analysis technologies to identify and visualize patterns of rabies emergence among different animal species in Kazakhstan

  Aizada A. Mukhanbetkaliyeva, Anar M. Kabzhanova, Ablaikhan S. Kadyrov, Yersyn Y. Mukhanbetkaliyev, Temirlan G. Bakishev, Aslan A. Bainiyazov, Rakhimtay B. Tleulessov, Fedor I. Korennoy, Andres M. Perez, Sarsenbay K. Abdrakhmanov

  31-07-2024

  https://doi.org/10.4081/gh.2024.1290

  1793

  PDF: 790

  HTML: 116
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  Variability of nutrients intake, lipid profile and cardiovascular mortality among geographical areas in Spain: The DRECE study

  Agustín Gòmez de la Cámara, Eva de Andrés Esteban, Gerard Urrútia Cuchí, Enrique Calderòn Sandubete, Miguel Ángel Rubio Herrera, Miguel Menéndez Orenga, David Lora Pablos

  07-11-2017

  https://doi.org/10.4081/gh.2017.524

  2224

  PDF: 982

  HTML: 712
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  Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

  Carlos Mena, Cesar Sepúlveda, Eduardo Fuentes, Yony Ormazábal, Iván Palomo

  07-05-2018

  https://doi.org/10.4081/gh.2018.587

  5464

  PDF: 2699

  HTML: 806
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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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  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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  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
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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
• 

  Spatial association between COVID-19 incidence rate and nighttime light index

  Amornrat Luenam, Nattapong Puttanapong

  18-03-2022

  https://doi.org/10.4081/gh.2022.1066

  2337

  PDF: 709

  HTML: 96

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

  Ximena Porcasi, Camilo H. Rotela, María V. Introini, Nicolás Frutos, Sofía Lanfri, Gonzalo Peralta, Estefanía A. De Elia, Mario A. Lanfri, Carlos M. Scavuzzo

  S31-S42

  01-09-2012

  https://doi.org/10.4081/gh.2012.120

  3192

  PDF: 1748
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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

  Yaqi Wang, Zhiwei Wan

  17-05-2022

  https://doi.org/10.4081/gh.2022.1078

  1914

  PDF: 1001

  HTML: 177
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  Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

  Rutendo Birri Makota, Eustasius Musenge

  27-11-2023

  https://doi.org/10.4081/gh.2023.1207

  1658

  PDF: 830

  HTML: 81
• 

  Space-time scan statistics of 2007-2013 dengue incidence in Cimahi city, Indonesia

  Pandji Wibawa Dhewantara, Andri Ruliansyah, M. Ezza Azmi Fuadiyah, Endang Puji Astuti, Mutiara Widawati

  27-11-2015

  https://doi.org/10.4081/gh.2015.373

  5385

  PDF: 2021

  HTML: 1036
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  Urban gentrification and infectious diseases: an interdisciplinary narrative review

  Behzad Kiani, Gabriel Parker, Senobar Naderian, Colleen L. Lau, Benn Sartorius

  07-07-2025

  https://doi.org/10.4081/gh.2025.1388

  1420

  PDF: 594

  HTML: 95
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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

  3235

  PDF: 1400

  HTML: 1627
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  Climate and the distribution of vector-borne diseases: what's in store?

  Robert Bergquist

  08-05-2017

  https://doi.org/10.4081/gh.2017.549

  3375

  PDF: 1469

  HTML: 853
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  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

  4628

  PDF: 1660

  HTML: 1222
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  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

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  4823

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  The spatio-temporal distribution of Oncomelania hupensis along Yangtze river in Jiangsu Province, China after implementation of a new, integrated schistosomiasis control strategy

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