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Geospatial Health

eISSN 1970-7096 - pISSN 1827-1987

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Editor-in-Chief: Behzad Kiani

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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
    4517
    PDF: 2089
    HTML: 1382
  • 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
    4554
    PDF: 2394
    HTML: 2225
  • 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
    3735
    PDF: 1242
    HTML: 831
  • 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
    6667
    PDF: 2766
    HTML: 3142
  • 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
    3961
    PDF: 1878
    SUPPL. MATERIAL: 488
    HTML: 1091
  • 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
    3879
    PDF: 2016
    HTML: 2265
  • 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
    4798
    PDF: 1757
    HTML: 1224
  • Improving AfriPop dataset with settlement extents extracted from RapidEye for the border region comprising South-Africa, Swaziland and Mozambique

    Julie Deleu, Jonas Franke, Michael Gebreslasie, Catherine Linard
    04-11-2015
    https://doi.org/10.4081/gh.2015.336
    2731
    PDF: 1296
    HTML: 1138
  • 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
    4610
    PDF: 1345
    HTML: 1221
  • 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
    3537
    PDF: 1172
    HTML: 1468
  • Assessment of malaria transmission changes in Africa, due to the climate impact of land use change using Coupled Model Intercomparison Project Phase 5 earth system models

    Adrian M. Tompkins, Luca Caporaso
    31-03-2016
    https://doi.org/10.4081/gh.2016.380
    4413
    PDF: 1995
    HTML: 1286
  • Modelling homogeneous regions of social vulnerability to malaria in Rwanda

    Jean Pierre Bizimana, Stefan Kienberger, Michael Hagenlocher, Emmanuel Twarabamenye
    31-03-2016
    https://doi.org/10.4081/gh.2016.404
    4012
    PDF: 1980
    HTML: 2264
  • 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
    4841
    PDF: 1999
    HTML: 2564
  • 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
    4021
    PDF: 1817
    HTML: 1218
  • Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases

    Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A. Abdulkareem, Raul Zurita Milla
    11-02-2025
    https://doi.org/10.4081/gh.2025.1326
    2666
    PDF: 770
    Supplementary Materials: 421
    HTML: 224
  • 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
    4181
    PDF: 1636
    HTML: 1151
  • 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
    2538
    PDF: 1965
    HTML: 1149
  • 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
    5021
    PDF: 2201
    Appendix: 614
    HTML: 1602
  • 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
    1614
    PDF: 1032
    HTML: 167
  • 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
    3639
    PDF: 1740
    HTML: 1050
  • 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
    799
    PDF: 499
    Supplementary materials: 80
    HTML: 19
  • Geospatial assessment of primary healthcare centres in Jeddah, Saudi Arabia

    Abdulkader A. Murad, Mohaimin Azmain
    26-02-2026
    https://doi.org/10.4081/gh.2026.1463
    861
    PDF: 458
    HTML: 19
  • Modelling the domestic poultry population in the United States: A novel approach leveraging remote sensing and synthetic data methods

    Kelly A. Patyk, Mary J. McCool-Eye, David D. South, Christopher L. Burdett, Susan A. Maroney, Andrew Fox, Grace Kuiper, Sheryl Magzamen
    10-12-2020
    https://doi.org/10.4081/gh.2020.913
    4173
    PDF: 1634
    HTML: 219
  • 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
    3218
    PDF: 1511
    HTML: 1686
  • 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
    2486
    PDF: 1763
    APPENDIX: 685
    HTML: 1058
  • 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
    2960
    PDF: 1517
    APPENDIX: 761
    HTML: 1514
  • 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
    6674
    PDF: 2476
    Appendix: 666
    HTML: 3373
    Appendix: 281
  • Spatiotemporal heterogeneity of SARS-CoV-2 diffusion at the city level using geographically weighted Poisson regression model: The case of Bologna, Italy

    Addisu Jember Zeleke, Rossella Miglio, Pierpaolo Palumbo, Paolo Tubertini, Lorenzo Chiari, Bologna MODELS4COVID Study Group of the University of Bologna and the National Institute for Nuclear Physics (INFN)
    01-12-2022
    https://doi.org/10.4081/gh.2022.1145
    1929
    PDF: 1037
    Appendix: 166
    HTML: 85
  • Spatio-temporal analysis of fox rabies cases in Germany 2005-2006

    Matthias Eckardt, Conrad Freuling, Thomas Müller, Thomas Selhorst
    03-06-2015
    https://doi.org/10.4081/gh.2015.313
    2994
    PDF: 1324
    HTML: 1215
  • Geographically weighted regression for modelling the accessibility to the public hospital network in Concepción Metropolitan Area, Chile

    Marcela Martínez Bascuñán, Carolina Rojas Quezada
    22-11-2016
    https://doi.org/10.4081/gh.2016.451
    4097
    PDF: 1979
    HTML: 2218
  • 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
    1969
    PDF: 1118
    Appendix: 215
    HTML: 42
  • 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
    3846
    PDF: 1307
  • 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
    4473
    PDF: 1733
    HTML: 1072
  • Spatial multilevel modelling male partners’ influence on women’s modern contraceptive use: a study in Angola and Zambia

    Kabeya Clement Mulamba
    12-05-2025
    https://doi.org/10.4081/gh.2025.1340
    1582
    PDF: 352
    HTML: 61
  • Bivariate spatiotemporal disease mapping of cancer of the breast and cervix uteri among Iranian women

    Mehdi Raei, Volker Johann Schmid, Behzad Mahaki
    08-05-2018
    https://doi.org/10.4081/gh.2018.645
    2657
    PDF: 1276
    HTML: 149
  • 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
    4550
    PDF: 2036
    APPENDIX 1: 490
    APPENDIX 2: 517
    HTML: 1654
  • 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
    3766
    PDF: 1722
    HTML: 1122
  • 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
    5622
    PDF: 2749
    HTML: 2002
  • 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
    853
    PDF: 445
    Supplementary materials: 54
    HTML: 18
  • 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
    3352
    PDF: 1476
    HTML: 1630
  • Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations

    Peter M. Macharia, Kerry L.M. Wong, Lenka Beňová, Jia Wang, Prestige Tatenda Makanga, Nicolas Ray, Aduragbemi Banke-Thomas
    27-05-2024
    https://doi.org/10.4081/gh.2024.1266
    3456
    PDF: 1124
    Supplementary Materials: 189
    HTML: 256
  • A determination of the spatial concordance between Lyme disease incidence and habitat probability of its primary vector Ixodes scapularis (black-legged tick)

    Samuel F. Atkinson, Sahotra Sarkar, Aldo Aviña, Jim A. Schuermann, Phillip Williamson
    203-212
    01-11-2014
    https://doi.org/10.4081/gh.2014.17
    15451
    PDF: 1433
  • Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa

    Ernest O. Asare, Adrian M. Tompkins, Leonard K. Amekudzi, Volker Ermert, Robert Redl
    31-03-2016
    https://doi.org/10.4081/gh.2016.391
    3212
    PDF: 1784
    HTML: 4972
  • 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
    3592
    PDF: 1876
    HTML: 224
  • Spatio-temporal variations and determinants of antenatal care utilization among adolescents in Bulawayo metropolitan area, Zimbabwe: an analysis of routine data, 2019-2024

    Tariroyashe Chivanganye, Maphios Siamuchembu, Alice Gumbo, Lenka Beňová, Peter M. Macharia
    11-12-2025
    https://doi.org/10.4081/gh.2025.1434
    640
    PDF: 563
    HTML: 58
  • Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old

    André Oliveira, Antònio J.R. Cabral, Jorge M. Mendes, Maria R.O. Martins, Pedro Cabral
    04-11-2015
    https://doi.org/10.4081/gh.2015.365
    3416
    PDF: 1527
    HTML: 1231
  • Spatial risk of hypertension in rural China: modelling the effect of dietary, behavioural and climate factors

    Jie Wang, Enwei Zhang, Kun Yang
    23-07-2026
    https://doi.org/10.4081/gh.2026.1498
    267
    PDF: 140
    HTML: 1
  • Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe

    Els Ducheyne, Johannes Charlier, Jozef Vercruysse, Laura Rinaldi, Annibale Biggeri, Janina Demeler, Christina Brandt, Theo de Waal, Nikolaos Selemetas, Johan Höglund, Jaroslaw Kaba, Slawomir J. Kowalczyk, Guy Hendrickx
    261-270
    19-03-2015
    https://doi.org/10.4081/gh.2015.348
    4076
    PDF: 2147
  • 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
    1384
    PDF: 652
    Supplementary Materials: 153
    HTML: 24
  • 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
    2530
    PDF: 1133
    HTML: 193
  • Spatial electromagnetic field intensity modelling of global system for mobile communication base stations in the Istanbul Technical University Ayazaga campus area

    Kubra Boz, Hayri Hakan Denli
    07-05-2018
    https://doi.org/10.4081/gh.2018.527
    1702
    PDF: 1007
    HTML: 146
  • Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data

    Su Yun Kang, Susanna M. Cramb, Nicole M. White, Stephen J. Ball, Kerrie L. Mengersen
    31-05-2016
    https://doi.org/10.4081/gh.2016.428
    7614
    PDF: 2643
    APPENDIX: 1218
    HTML: 5553
  • Bayesian hierarchical spatial models for disease mapping in the presence of missing covariates

    Sami Ullah, Tianfa Xie
    20-08-2026
    https://doi.org/10.4081/gh.2026.1511
    112
    PDF: 57
    Supplementary materials: 14
    HTML: 2
  • Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data

    Soheil Hashtarkhani, Stephen A. Matthews, Ping Yin, Alireza Mohammadi, Shahab Mohammad Ebrahimi, Mahmood Tara, Behzad Kiani
    20-07-2023
    https://doi.org/10.4081/gh.2023.1198
    3828
    PDF: 1332
    Supplementary Materials: 971
    HTML: 194
  • 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
    2278
    PDF: 979
    HTML: 47
  • Intra-urban differences underlying leprosy spatial distribution in central Brazil: geospatial techniques as potential tools for surveillance

    Amanda G. Carvalho, Carolina Lorraine H. Dias, David J. Blok, Eliane Ignotti, João Gabriel G. Luz
    06-10-2023
    https://doi.org/10.4081/gh.2023.1227
    1703
    PDF: 788
    Supplementary Materials: 149
    HTML: 26
  • Identifying areas of Australia at risk for H5N1 avian influenza infection from exposure to nomadic waterfowl moving throughout the Australo-Papuan region

    Iain J. East, Samuel A. Hamilton, Louise A. Sharp, Michael G. Garner
    17-27
    01-11-2008
    https://doi.org/10.4081/gh.2008.228
    1830
    PDF: 1858
  • 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
    7633
    PDF: 1732
  • Modelling spatial distribution of snails transmitting parasitic worms with importance to human and animal health and analysis of distributional changes in relation to climate

    Ulrik B. Pedersen, Nicholas Midzi, Takafira Mduluza, White Soko, Anna-Sofie Stensgaard, Birgitte J. Vennervald, Samson Mukaratirwa, Thomas K. Kristensen
    335-343
    01-05-2014
    https://doi.org/10.4081/gh.2014.23
    4552
    PDF: 2184
  • Spatial patterns and eco-epidemiological systems - part I: multi-scale spatial modelling of the occurrence of Chagas disease insect vectors

    Emmanuel Roux, Annamaria de Fátima Venâncio, Jean-François Girres, Christine A. Romaña
    41-51
    01-11-2011
    https://doi.org/10.4081/gh.2011.156
    1687
    PDF: 1040
  • Performance of a negative binomial-GLM in spatial scan statistic: a case study of low-birth weights in Pakistan

    Sami Ullah, Mushtaq Ahmad Khan Barakzai, Tianfa Xie
    03-09-2024
    https://doi.org/10.4081/gh.2024.1313
    1799
    PDF: 708
    HTML: 181
  • Modelling spatial concordance between Rocky Mountain spotted fever disease incidence and habitat probability of its vector Dermacentor variabilis (American dog tick)

    Samuel F. Atkinson, Sahotra Sarkar, Aldo Aviña, Jim A. Schuermann, Phillip Williamson
    91-100
    01-11-2012
    https://doi.org/10.4081/gh.2012.108
    2224
    PDF: 1446
  • Mathematical modelling of the impact of climatic conditions in France on Rhipicephalus sanguineus tick activity and density since 1960

    Frédéric Beugnet, Michel Kolasinski, Paul-Antoine Michelangeli, Julien Vienne, Harilaos Loukos
    255-263
    01-05-2011
    https://doi.org/10.4081/gh.2011.178
    2890
    PDF: 1776
  • A Bayesian spatial ecological analysis of social conditions, infection burden and COVID-19 mortality across mainland Scottish councils 2020-2021

    Zhiyuan Luo, Yancheng Liu, Wenqi Xu
    10-06-2026
    https://doi.org/10.4081/gh.2026.1477
    373
    PDF: 207
    Supplementary Materials: 46
    HTML: 8
  • 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
    1535
    PDF: 674
    HTML: 47
  • Spatial accessibility to basic public health services in South Sudan

    Peter M. Macharia, Paul O. Ouma, Ezekiel G. Gogo, Robert W. Snow, Abdisalan M. Noor
    11-05-2017
    https://doi.org/10.4081/gh.2017.510
    9523
    PDF: 3037
    APPENDIX: 7630
    HTML: 1179
  • Spatial analysis and modelling of depression relative to social vulnerability index across the United States

    Kiara M. Rivera, Abolfazl Mollalo
    01-09-2022
    https://doi.org/10.4081/gh.2022.1132
    5548
    PDF: 2525
    HTML: 619
  • 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
    1413
    PDF: 697
    HTML: 65
  • 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
    2226
    PDF: 1007
    Supplementary Materials: 188
    HTML: 74
  • Human infections and co-infections with helminths in a rural population in Guichi, Anhui Province, China

    Yi Hu, Rui Li, Michael P. Ward, Yue Chen, Henry Lynn, Decheng Wang, Gengxin Chen, Zonggui He, Liqian Sun, Chenglong Xiong, Zhijie Zhang, Qingwu Jiang
    04-11-2015
    https://doi.org/10.4081/gh.2015.374
    2573
    PDF: 1369
    HTML: 988
  • 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
    4953
    PDF: 1387
    Appendix: 606
    HTML: 1234
  • Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

    Abdulkader Murad, Fazlay Faruque, Ammar Naji, Alok Tiwari, Mansour Helmi, Ammar Dahlan
    16-05-2022
    https://doi.org/10.4081/gh.2022.1072
    2330
    PDF: 1162
    HTML: 168
  • Comparing conditional autoregressive models for Bayesian spatial mapping of dengue cases in Indonesia

    Ferra Yanuar, Yudiantri Asdi, Aidinil Zetra, Sofiana Wudlu, Fenni Kurnia Mutiya, Rahmawita Rahmawita
    18-06-2026
    https://doi.org/10.4081/gh.2026.1443
    273
    PDF: 355
    HTML: 3
  • 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
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Geospatial Health
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Vol. 21 No. 2 (2026)
Bayesian hierarchical spatial models for disease mapping in the presence of missing covariates
Sami Ullah et al.
20 August 2026
Vol. 21 No. 2 (2026)
Ten common pitfalls in spatial epidemiology and how to avoid them
Behzad Kiani et al.
1 September 2026
Vol. 21 No. 2 (2026)
Synergistic drivers of Lyme disease emergence in North America: an eco-syndemic review
Michael F. Ojo et al.
4 August 2026

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Geospatial Health

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