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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

  4369

  PDF: 2303

  HTML: 2204
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  Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry

  Gianluca Boo, Stefan Leyk, Sara Irina Fabrikant, Andreas Pospischil, Ramona Graf

  11-05-2017

  https://doi.org/10.4081/gh.2017.539

  3490

  PDF: 1177

  HTML: 827
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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

  6364

  PDF: 2630

  HTML: 3131
• 

  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

  3685

  PDF: 1891

  HTML: 2253
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  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

  3350

  PDF: 1110

  HTML: 1462
• 

  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

  3826

  PDF: 1733

  SUPPL. MATERIAL: 459

  HTML: 1087
• 

  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

  4262

  PDF: 1886

  APPENDIX 1: 459

  APPENDIX 2: 484

  HTML: 1648
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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

  3978

  PDF: 1500

  HTML: 1145
• 

  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

  2391

  PDF: 1065

  HTML: 186
• 

  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

  4448

  PDF: 1276

  HTML: 1213
• 

  Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda

  Felipe J. Colòn-González, Adrian M. Tompkins, Riccardo Biondi, Jean Pierre Bizimana, Didacus Bambaiha Namanya

  31-03-2016

  https://doi.org/10.4081/gh.2016.379

  6429

  PDF: 2350

  Appendix: 638

  HTML: 3331

  Appendix: 252
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  Validation of an interactive map assessing the potential spread of Galba truncatula as intermediate host of Fasciola hepatica in Switzerland

  Rhea Baggenstos, Tobias Dahinden, Paul R. Torgerson, Hansruedi Bär, Christina Rapsch, Gabriela Knubben-Schweizer

  31-05-2016

  https://doi.org/10.4081/gh.2016.418

  2660

  PDF: 1356

  HTML: 1011
• 

  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

  3788

  PDF: 1709

  HTML: 1209
• 

  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

  4594

  PDF: 1905

  HTML: 2559
• 

  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

  530

  PDF: 266

  Supplementary materials: 39

  HTML: 8
• 

  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

  4788

  PDF: 2066

  Appendix: 583

  HTML: 1596
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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

  3459

  PDF: 1621

  HTML: 1046
• 

  Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

  Nicola A. Wardrop, Matthew Geary, Patrick E. Osborne, Peter M. Atkinson

  237-246

  01-11-2014

  https://doi.org/10.4081/gh.2014.397

  2466

  PDF: 1087
• 

  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

  2392

  PDF: 1819

  HTML: 1145
• 

  Climate change and species distribution: possible scenarios for thermophilic ticks in Romania

  Cristian DomÈ™a, Attila D. Sándor, Andrei D. Mihalca

  31-05-2016

  https://doi.org/10.4081/gh.2016.421

  3020

  PDF: 1424

  HTML: 1683
• 

  Zoning the territory of the Republic of Kazakhstan as to the risk of rabies among various categories of animals

  Sarsenbay K. Abdrakhmanov, Akhmetzhan A. Sultanov, Kanatzhan K. Beisembayev, Fedor I. Korennoy, Dosym B. Кushubaev, Ablaikhan S. Каdyrov

  31-05-2016

  https://doi.org/10.4081/gh.2016.429

  2821

  PDF: 1365

  APPENDIX: 709

  HTML: 1506
• 

  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

  1235

  PDF: 789

  HTML: 125
• 

  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

  2284

  PDF: 1649

  APPENDIX: 646

  HTML: 1046
• 

  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

  1815

  PDF: 931

  Appendix: 164

  HTML: 39
• 

  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

  3190

  PDF: 1374

  HTML: 1626
• 

  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

  2708

  PDF: 540

  HTML: 55
• 

  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

  4568

  PDF: 1330

  HTML: 276
• 

  Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

  Manuel O. Espinosa, Francisco Polop, Camilo H. Rotela, Marcelo Abril, Carlos M. Scavuzzo

  21-11-2016

  https://doi.org/10.4081/gh.2016.471

  4144

  PDF: 1607

  APPENDIX: 556

  HTML: 1541
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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

  3199

  PDF: 1676

  HTML: 194
• 

  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

  4190

  PDF: 1598

  HTML: 1066
• 

  Health, environmental change and adaptive capacity; mapping, examining and anticipating future risks of water-related vector-borne diseases in eastern Africa

  David Taylor, Stefan Kienberger, Jack B. Malone, Adrian M. Tompkins

  18-02-2016

  https://doi.org/10.4081/gh.2016.464

  3596

  PDF: 1649

  HTML: 1116
• 

  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

  5457

  PDF: 2605

  HTML: 1996
• 

  Spatial inequalities in cancer with special reference to lung cancer across Europe and their implications for environmental health policy

  Dimitrios Ntokos

  14-04-2026

  https://doi.org/10.4081/gh.2026.1453

  320

  PDF: 177

  Supplementary materials: 25

  HTML: 8
• 

  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

  754

  PDF: 403

  Supplementary Materials: 97

  HTML: 16
• 

  Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran

  Mohammadreza Rajabi, Ali Mansourian, Petter Pilesjö, Ahad Bazmani

  179-191

  01-11-2014

  https://doi.org/10.4081/gh.2014.15

  7430

  PDF: 1610
• 

  From Snow’s map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis

  Behzad Kiani, Colleen Lau, Robert Bergquist

  26-10-2023

  https://doi.org/10.4081/gh.2023.1247

  2049

  PDF: 874

  HTML: 32
• 

  Spatial Bayesian semi-parametric Cox-Leroux modelling of stroke patient hospitalization: aspects on survival

  Aswi Aswi, Bobby Poerwanto, Nurussyariah Hammado, Nurwan Nurwan, Oktaviana Oktaviana, Siti Djawijah, Susanna Cramb

  21-07-2025

  https://doi.org/10.4081/gh.2025.1380

  941

  PDF: 385

  HTML: 37
• 

  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

  2385

  PDF: 804

  HTML: 79
• 

  Spatial distribution and sociodemographic risk factors of malaria in Nigerian children less than 5 years old

  Chigozie Louisa J. Ugwu, Temesgen Zewotir

  29-12-2020

  https://doi.org/10.4081/gh.2020.819

  3829

  PDF: 1815

  HTML: 759
• 

  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

  1418

  PDF: 587

  HTML: 21
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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

  1200

  PDF: 565

  HTML: 56
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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

  2077

  PDF: 895

  Supplementary Materials: 157

  HTML: 61
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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

  4436

  PDF: 1861

  HTML: 1239
• 

  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

  753

  PDF: 407

  HTML: 30

• Geospatial Health: achievements, innovations, priorities

  Sherif Amer, Ellen-Wien Augustijn, Carmen Anthonj, Nils Tjaden, Justine Blanford, Marc van den Homberg, Laura Rinaldi, Thomas van Rompay, Raúl Zurita Milla

  25-10-2024

  https://doi.org/10.4081/gh.2024.1355

  1928

  PDF: 724

  HTML: 98
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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

  2837

  PDF: 1226

  Supplementary Materials: 194

  HTML: 111
• 

  Venomous snakebite risk and its implications in Zacatecas State, Mexico 2007-2017

  Jesús Lenin Lara-Galván, Manuel Montesino-San Martín, Xabier Herrero Otero, Juan Felipe Martínez-Montoya, José Jesús Sigala-Rodríguez, Ana Márcia Barbosa

  05-11-2025

  https://doi.org/10.4081/gh.2025.1404

  599

  PDF: 316

  Supplementary materials: 83

  HTML: 9

• Environmental and socio-economic risk modelling for Chagas disease in Bolivia

  Paula Mischler, Michael Kearney, Jennifer C. McCarroll, Ronaldo G.C. Scholte, Penelope Vounatsou, John B. Malone

  S59-S66

  01-09-2012

  https://doi.org/10.4081/gh.2012.123

  3955

  PDF: 1384

• 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

  6018

  PDF: 2069

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

  Frédéric Beugnet, Karine Chalvet-Monfray, Harilaos Loukos

  97-113

  01-11-2009

  https://doi.org/10.4081/gh.2009.213

  2937

  PDF: 1246
• 

  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

  1558

  PDF: 556

  HTML: 40
• 

  A spatial lag model analysis of lung cancer incidence and satellite-derived data on air pollution in Thailand from 2020 to 2023

  Wasana Silangam, Amornrat Luenam

  14-11-2025

  https://doi.org/10.4081/gh.2025.1424

  630

  PDF: 341

  HTML: 7
• 

  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

  1762

  PDF: 997

  HTML: 170
• 

  Using object-based image analysis to map commercial poultry operations from high resolution imagery to support animal health outbreaks and events

  Susan Maroney, MaryJane McCool-Eye, Andrew Fox, Christopher Burdett

  10-12-2020

  https://doi.org/10.4081/gh.2020.919

  2713

  PDF: 921

  HTML: 152
• 

  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

  2849

  PDF: 1949

  HTML: 398
• 

  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

  2803

  PDF: 942

  HTML: 747
• 

  Prehistoric human migrations: a prospective subject for modelling using geographical information systems

  Robert Bergquist

  25-05-2023

  https://doi.org/10.4081/gh.2023.1210

  1471

  PDF: 534

  HTML: 56
• 

  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

  4460

  PDF: 1826

  HTML: 1756
• 

  Snakebite epidemiology in the State of Mexico, Mexico 2003-2024

  Aldo Gómez-Benitez, Erika Adriana Reyes-Velázquez, Edgar Oviedo-Hernández, Laura Sonia Arzate-Garay, Justin Lloyd Rheubert, Oswaldo Hernández-Gallegos

  09-04-2026

  https://doi.org/10.4081/gh.2026.1468

  455

  PDF: 234

  Supplementary Materials: 32

  HTML: 7
• 

  A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations

  Ernest O. Asare, Adrian M. Tompkins, Leonard K. Amekudzi, Volker Ermert

  31-03-2016

  https://doi.org/10.4081/gh.2016.390

  2862

  PDF: 1199

  HTML: 1142
• 

  Estimating malaria burden in Nigeria: a geostatistical modelling approach

  Nnadozie Onyiri

  04-11-2015

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

  7602

  PDF: 3174

  HTML: 3278

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

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

  97-110

  01-11-2013

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

  4100

  PDF: 2135
• 

  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

  3446

  PDF: 1370

  HTML: 863

• Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches

  Romano Ngui, Aziz Shafie, Kek H. Chua, Mohd S. Mistam, Hesham M. Al-Mekhlafi, Wan W. W. Sulaiman, Rohela Mahmud, Yvonne A. L. Lim

  365-376

  01-05-2014

  https://doi.org/10.4081/gh.2014.26

  4498

  PDF: 1360

• Satellite imaging and vector-borne diseases: the approach of the French National Space Agency (CNES)

  Fabienne Marechal, Nathalie Ribeiro, Murielle Lafaye, Antonio Güell

  1-5

  01-11-2008

  https://doi.org/10.4081/gh.2008.226

  2488

  PDF: 1248
• 

  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

  3339

  PDF: 1449

  HTML: 851
• 

  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

  1271

  PDF: 577

  HTML: 57
• 

  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

  2227

  PDF: 966

  HTML: 94
• 

  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

  1253

  PDF: 623

  HTML: 285
• 

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

  Robert Bergquist, Anna-Sofie Stensgaard, Laura Rinaldi

  07-05-2018

  https://doi.org/10.4081/gh.2018.699

  2944

  PDF: 1303

  HTML: 225

• Bayesian modelling of geostatistical malaria risk data

  L. Gosoniu, P. Vounatsou, N. Sogoba, T. Smith

  127-139

  01-11-2006

  https://doi.org/10.4081/gh.2006.287

  9887

  PDF: 1768

• Study of the variation of schistosomiasis risk in Lake Poyang in the People's Republic of China using multiple space-borne sensors for monitoring and modelling

  Kuo-Hsin Tseng, Song Liang, Motomu Ibaraki, Hyongki Lee, C. K. Shum

  353-364

  01-05-2014

  https://doi.org/10.4081/gh.2014.25

  1776

  PDF: 1108

• 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

  2816

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