Search

Search Results

• 

  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

  3189

  PDF: 1315

  Supplementary Materials: 203

  HTML: 133
• 

  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

  3779

  PDF: 1939

  HTML: 2262
• 

  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

  2460

  PDF: 1871

  HTML: 1148
• 

  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

  6528

  PDF: 2674

  HTML: 3135
• 

  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

  3326

  PDF: 1517

  HTML: 1484
• 

  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

  2667

  PDF: 1493

  HTML: 2025
• 

  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

  4440

  PDF: 2339

  HTML: 2209
• 

  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

  2378

  PDF: 1348

  HTML: 340
• 

  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

  4451

  PDF: 1937

  APPENDIX 1: 468

  APPENDIX 2: 498

  HTML: 1651
• 

  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

  3780

  PDF: 1257
• 

  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

  2502

  PDF: 929

  HTML: 83
• 

  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

  4522

  PDF: 1298

  HTML: 1217
• 

  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

  3462

  PDF: 1130

  HTML: 1466
• 

  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

  3926

  PDF: 1753

  HTML: 1214
• 

  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

  3397

  PDF: 1745

  HTML: 207
• 

  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

  2440

  PDF: 1091

  HTML: 190
• 

  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

  1373

  PDF: 605

  HTML: 27
• 

  MALAREO: a user-driven project

  Michael T. Gebreslasie, Ides Bauwens

  04-11-2015

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

  2911

  PDF: 1296

  HTML: 1015
• 

  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

  2303

  PDF: 989

  HTML: 98
• 

  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

  3946

  PDF: 2248

  HTML: 1272
• 

  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

  2233

  PDF: 1292

  HTML: 1140
• 

  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

  4536

  PDF: 1899

  HTML: 1245
• 

  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

  4105

  PDF: 1571

  HTML: 1149
• 

  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

  3550

  PDF: 1653

  HTML: 1048
• 

  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

  1849

  PDF: 767

  HTML: 77
• 

  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

  4545

  PDF: 1856

  HTML: 1760
• 

  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

  2873

  PDF: 987

  HTML: 749
• 

  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

  3588

  PDF: 1280

  HTML: 75
• 

  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

  1309

  PDF: 617

  HTML: 58
• 

  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

  2128

  PDF: 929

  Supplementary Materials: 165

  HTML: 64

• 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

  2290

  PDF: 985
• 

  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

  1880

  PDF: 982

  Appendix: 181

  HTML: 42
• 

  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

  3050

  PDF: 632

  HTML: 89
• 

  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

  1452

  PDF: 899

  HTML: 147

• 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

  2872

  PDF: 971
• 

  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

  1764

  PDF: 619

  HTML: 54

• 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

  1715

  PDF: 1001

• 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

  2951

  PDF: 941

  HTML: 93
• 

  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

  1884

  PDF: 974

  HTML: 71
• 

  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

  3303

  PDF: 1180

  HTML: 1232
• 

  Estimating malaria burden in Nigeria: a geostatistical modelling approach

  Nnadozie Onyiri

  04-11-2015

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

  7854

  PDF: 3229

  HTML: 3287

• 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

  2574

  PDF: 1092
• 

  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

  4622

  PDF: 1373

  HTML: 278
• 

  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

  1320

  PDF: 654

  HTML: 296
• 

  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

  5538

  PDF: 2659

  HTML: 2000
• 

  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

  1621

  PDF: 599

  HTML: 42
• 

  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

  1805

  PDF: 1029

  HTML: 174
• 

  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

  1469

  PDF: 624

  HTML: 26

• 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

  3420

  PDF: 1769

• 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

  2543

  PDF: 1252
• 

  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

  1014

  PDF: 484

  Supplementary Materials: 115

  HTML: 19

• 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

  2971

  PDF: 1800
• 

  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

  2767

  PDF: 599

  HTML: 60
• 

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

  Azizur Rahman

  08-05-2017

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

  4432

  PDF: 2011

  HTML: 1376

• 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

  2539

  PDF: 1184
• 

  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

  1805

  PDF: 969

  Supplementary Materials: 155

  HTML: 94
• 

  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

  1733

  PDF: 1008

  HTML: 66

• 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

  11146

  PDF: 2841
• 

  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

  4426

  PDF: 1299

  HTML: 914
• 

  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

  3887

  PDF: 1783

  SUPPL. MATERIAL: 473

  HTML: 1090
• 

  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

  244

  PDF: 201

  HTML: 11
• 

  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

  2561

  PDF: 1610
• 

  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

  669

  PDF: 357

  Supplementary materials: 54

  HTML: 14
• 

  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

  4723

  PDF: 1937

  HTML: 2561

• 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

  4829

  PDF: 1452

  HTML: 1105
• 

  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

  824

  PDF: 439

  HTML: 34
• 

  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

  4925

  PDF: 1540

  HTML: 2592
• 

  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

  3524

  PDF: 1402

  HTML: 865
• 

  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

  4898

  PDF: 2115

  Appendix: 594

  HTML: 1598
• 

  Stunting spatial pattern in Rwanda: An examination of the demographic, socio-economic and environmental determinants

  Vestine Uwiringiyimana, Antonie Veldkamp, Sherif Amer

  06-11-2019

  https://doi.org/10.4081/gh.2019.820

  3575

  PDF: 1811

  HTML: 132
• 

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

  Jian He, Wei Li, Robert Bergquist, Jian-Feng Zhang, Liang Shi, Song Zhao, Feng Wu, Kun Yang

  29-11-2016

  https://doi.org/10.4081/gh.2016.480

  3278

  PDF: 1047

  HTML: 913

• 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)

  Benjamin G. Jacob, Weidong Gu, Erik X. Caamano, Robert J. Novak

  157-176

  01-05-2009

  https://doi.org/10.4081/gh.2009.218

  1656

  PDF: 1045

• 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

  1842

  PDF: 803

  HTML: 117

• Identification of environmental parameters and risk mapping of visceral leishmaniasis in Ethiopia by using geographical information systems and a statistical approach

  Teshome Tsegaw, Endalamaw Gadisa, Ahmed Seid, Adugna Abera, Aklilu Teshome, Abate Mulugeta, Merce Herrero, Daniel Argaw, Alvar Jorge, Abraham Aseffa

  299-308

  01-05-2013

  https://doi.org/10.4081/gh.2013.88

  4207

  PDF: 2095
• 

  Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa

  Abiodun Morakinyo Adeola, Joel Ondego Botai, Jane Mukarugwiza Olwoch, Hannes C.J. de W. Rautenbach, Omolola Mayowa Adisa, Christiaan de Jager, Christina M. Botai, Mabuza Aaron

  14-05-2019

  https://doi.org/10.4081/gh.2019.676

  3216

  PDF: 1673

  APPENDIX: 507

  HTML: 316

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

  Guo-Jing Yang, Penelope Vounatsou, Marcel Tanner, Xiao-Nong Zhou, Jürg Utzinger

  85-92

  01-11-2006

  https://doi.org/10.4081/gh.2006.283

  2661

  PDF: 1208
• 

  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

  3118

  PDF: 1455

  HTML: 1078
• 

  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

  4791

  PDF: 1339

  Appendix: 571

  HTML: 1233

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

  Mohamadreza Rajabi, Ali Mansourian, Ahad Bazmani

  37-50

  01-11-2012

  https://doi.org/10.4081/gh.2012.103

  1810

  PDF: 1071

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

  Richard Kiang, Farida Adimi, Valerii Soika, Joseph Nigro, Pratap Singhasivanon, Jeeraphat Sirichaisinthop, Somjai Leemingsawat, Chamnarn Apiwathnasorn, Sornchai Looareesuwan

  71-84

  01-11-2006

  https://doi.org/10.4081/gh.2006.282

  3507

  PDF: 1835

• Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics

  Ahmed Seid, Endalamaw Gadisa, Teshome Tsegaw, Adugna Abera, Aklilu Teshome, Abate Mulugeta, Merce Herrero, Daniel Argaw, Alvar Jorge, Asnakew Kebede, Abraham Aseffa

  377-387

  01-05-2014

  https://doi.org/10.4081/gh.2014.27

  7305

  PDF: 2905
• 

  Assessing spatial patterns of HIV prevalence and interventions in semi-urban settings in South Africa. Implications for spatially targeted interventions

  Lucy Chimoyi, Zvifadzo Matsena-Zingoni, Salome Charalambous, Edmore Marinda, Samuel Manda, Eustasius Musenge

  29-08-2022

  https://doi.org/10.4081/gh.2022.1084

  2364

  PDF: 600

  Supplementary 1: 155

  Supplementary 2: 368

  HTML: 180
• 

  Environmental change and Rift Valley fever in eastern Africa: projecting beyond HEALTHY FUTURES

  David Taylor, Michael Hagenlocher, Anne E. Jones, Stefan Kienberger, Joseph Leedale, Andrew P. Morse

  31-03-2016

  https://doi.org/10.4081/gh.2016.387

  6581

  PDF: 2067

  HTML: 2199

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

  Weerapong Thanapongtharm, Thomas P. Van Boeckel, Chandrashekhar Biradar, Xiangming Xiao, Marius Gilbert

  193-201

  01-11-2013

  https://doi.org/10.4081/gh.2013.66

  2011

  PDF: 1229

• Integrated disease mapping in a polyparasitic world

  Simon Brooker, Jürg Utzinger

  141-146

  01-05-2007

  https://doi.org/10.4081/gh.2007.262

  2841

  PDF: 1270
• 

  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

  2371

  PDF: 1693

  APPENDIX: 662

  HTML: 1052

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

  Alessandra Capolupo, Stefania Pindozzi, Collins Okello, Lorenzo Boccia

  S699-S707

  01-12-2014

  https://doi.org/10.4081/gh.2014.298

  4513

  PDF: 2155
• 

  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

  5425

  PDF: 2036

  HTML: 1038

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

  Ronaldo G.C. Scholte, Omar S. Carvalho, John B. Malone, Jürg Utzinger, Penelope Vounatsou

  S95-S101

  01-09-2012

  https://doi.org/10.4081/gh.2012.127

  6157

  PDF: 2406
• 

  Impact of the COVID-19 pandemic on the number of births in Pernambuco Brazil

  Heitor Victor Veiga da Costa, Cristine Vieira do Bonfim, Wilson Fusco, Morvan de Melo Moreira, Fernando Maciano de Paula Neto

  15-06-2022

  https://doi.org/10.4081/gh.2022.1069

  1315

  PDF: 609

  HTML: 59

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

  Yi Hu, Cheng-Long Xiong, Zhi-Jie Zhang, Robert Bergquist, Zeng-Liang Wang, Jie Gao, Rui Li, Bo Tao, Qiu-Lin Jiang, Qingwu Jiang

  125-132

  01-11-2013

  https://doi.org/10.4081/gh.2013.60

  2917

  PDF: 1122
• 

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

  Lavinia Ciucă, Vincenzo Musella, Liviu D. Miron, Maria Paola Maurelli, Giuseppe Cringoli, Antonio Bosco, Laura Rinaldi

  21-11-2016

  https://doi.org/10.4081/gh.2016.499

  4924

  PDF: 1764

  HTML: 2284
• 

  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

  1985

  PDF: 1013

  HTML: 180
• 

  First year with COVID-19: Assessment and prospects

  Robert Bergquist, Behzad Kiani, Samuel Manda

  26-11-2020

  https://doi.org/10.4081/gh.2020.953

  3116

  PDF: 811

  HTML: 29

• 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

  3233

  PDF: 1773
• 

  Spatial and temporal dynamic analysis of rabies: A review of current methodologies

  Shuaicheng Chen

  30-11-2022

  https://doi.org/10.4081/gh.2022.1139

  3018

  PDF: 2176

  HTML: 433
• 

  Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia

  Gary K.K. Low, Panayoti Papapreponis, Ridzuan M. Isa, Seng Chiew Gan, Hui Yee Chee, Kian Keong Te, Nadia M. Hatta

  07-05-2018

  https://doi.org/10.4081/gh.2018.642

  2488

  PDF: 1064

  APPENDIX: 472

  HTML: 127
• 

  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

  2384

  PDF: 717

  HTML: 98
• 

  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

  4377

  PDF: 1626

  HTML: 1069

• A Bayesian kriging model for estimating residential exposure to air pollution of children living in a high-risk area in Italy

  Ana M. Vicedo-Cabrera, Annibale Biggeri, Laura Grisotto, Fabio Barbone, Dolores Catelan

  87-95

  01-11-2013

  https://doi.org/10.4081/gh.2013.57

  2819

  PDF: 1447