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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

  2724

  PDF: 1190

  Supplementary Materials: 188

  HTML: 103
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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

  6321

  PDF: 2601

  HTML: 3127
• 

  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

  3661

  PDF: 1866

  HTML: 2246
• 

  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

  4349

  PDF: 2291

  HTML: 2197
• 

  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

  2364

  PDF: 1787

  HTML: 1144
• 

  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

  3191

  PDF: 1454

  HTML: 1464
• 

  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

  2503

  PDF: 1423

  HTML: 2019
• 

  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

  2288

  PDF: 1302

  HTML: 332
• 

  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

  2313

  PDF: 643

  HTML: 79
• 

  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

  4209

  PDF: 1845

  APPENDIX 1: 455

  APPENDIX 2: 474

  HTML: 1646
• 

  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

  1452

  PDF: 856

  HTML: 53
• 

  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

  3102

  PDF: 1632

  HTML: 190
• 

  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

  3748

  PDF: 1666

  HTML: 1204
• 

  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

  1275

  PDF: 567

  HTML: 20
• 

  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

  4417

  PDF: 1267

  HTML: 1209
• 

  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

  3417

  PDF: 1604

  HTML: 1040
• 

  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

  4365

  PDF: 1826

  HTML: 1238
• 

  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

  2369

  PDF: 1047

  HTML: 180
• 

  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

  3332

  PDF: 1089

  HTML: 1459
• 

  MALAREO: a user-driven project

  Michael T. Gebreslasie, Ides Bauwens

  04-11-2015

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

  2835

  PDF: 1241

  HTML: 994
• 

  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

  2162

  PDF: 1246

  HTML: 1135
• 

  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

  2193

  PDF: 935

  HTML: 91
• 

  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

  3780

  PDF: 2192

  HTML: 1268
• 

  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

  1778

  PDF: 906

  Appendix: 158

  HTML: 37
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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

  2573

  PDF: 505

  HTML: 38

• 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

  2786

  PDF: 856

  HTML: 84
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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

  1746

  PDF: 924

  HTML: 64
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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

  1618

  PDF: 961

  HTML: 55
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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

  146

  PDF: 115

  HTML: 5
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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

  3954

  PDF: 1486

  HTML: 1142
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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

  4359

  PDF: 1807

  HTML: 1752
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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

  3460

  PDF: 1229

  HTML: 69
• 

  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

  1133

  PDF: 534

  HTML: 52

• 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

  2467

  PDF: 1037
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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

  3425

  PDF: 1345

  HTML: 860
• 

  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

  2776

  PDF: 921

  HTML: 743
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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

  1629

  PDF: 722

  HTML: 44
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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

  2042

  PDF: 883

  Supplementary Materials: 152

  HTML: 58
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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

  1151

  PDF: 744

  HTML: 115
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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

  1820

  PDF: 407

  HTML: 100
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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

  1234

  PDF: 606

  HTML: 274
• 

  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

  1641

  PDF: 895

  Supplementary Materials: 138

  HTML: 67
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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

  674

  PDF: 323

  Supplementary Materials: 76

  HTML: 11
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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

  2681

  PDF: 547

  HTML: 53

• 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

  5955

  PDF: 2049
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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

  4857

  PDF: 1990

  HTML: 1087
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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

  1692

  PDF: 1106

  Appendix: 145

  HTML: 206
• 

  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

  3614

  PDF: 1425

  HTML: 1169
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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

  7541

  PDF: 3149

  HTML: 3274
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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

  4532

  PDF: 1306

  HTML: 274
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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

  3221

  PDF: 1138

  HTML: 1225
• 

  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

  1612

  PDF: 563

  HTML: 47
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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

  4327

  PDF: 1944

  HTML: 1370

• 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

  1682

  PDF: 717

  HTML: 114
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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

  2160

  PDF: 943

  HTML: 703
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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

  5356

  PDF: 2635

  HTML: 792
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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

  1748

  PDF: 986

  HTML: 165
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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

  5424

  PDF: 2577

  HTML: 1993
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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

  1390

  PDF: 576

  HTML: 17
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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

  1523

  PDF: 533

  HTML: 38
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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

  1547

  PDF: 772

  HTML: 73
• 

  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

  5323

  PDF: 1980

  HTML: 1026
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  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

  2231

  PDF: 684

  HTML: 89

• 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

  3114

  PDF: 1695
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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

  1802

  PDF: 966

  HTML: 163
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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

  1282

  PDF: 534

  HTML: 86
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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

  3157

  PDF: 1352

  HTML: 1621
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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

  3305

  PDF: 1432

  HTML: 847
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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

  4552

  PDF: 1626

  HTML: 1218
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  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

  4324

  PDF: 1246

  HTML: 909
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  3795

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  4083

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  3036

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  738

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  2214

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  1252

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  529

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  468

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  4553

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  A dynamic, climate-driven model of Rift Valley fever

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  4753

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  4573

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  31-05-2016

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

  4819

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  Nonlinear analysis of factors influencing public health in China based on machine learning

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  https://doi.org/10.4081/gh.2026.1450

  123

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

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  1083

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  Geographic distribution of canine heartworm (Dirofilaria immitis) infection in stray dogs of eastern Romania

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  21-11-2016

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  4640

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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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  3174

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  2259

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  APPENDIX: 632

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  Vector-borne diseases in a warmer world: Will they stay or will they go?

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  2888

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  2153

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  Measuring neighborhood deprivation for childhood health and development - scale implications in rural and urban context

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  Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data

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  3206

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  Spatio-temporal trends and distribution patterns of typhoid disease in Uganda from 2012 to 2017

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  3599

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  1578

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  Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

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  4147

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

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  979

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  2420

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  APPENDIX: 453

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