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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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  • 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
    7605
    PDF: 2639
    APPENDIX: 1217
    HTML: 5552
  • 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
    3873
    PDF: 2010
    HTML: 2265
  • Examination of infant mortality risk in Turkey with spatio-temporal Bayesian models

    Sade Kılıç Yıldırım, Celal Reha Alpar
    14-11-2025
    https://doi.org/10.4081/gh.2025.1396
    630
    PDF: 301
    HTML: 7
  • 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
    2537
    PDF: 1964
    HTML: 1149
  • 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
    4637
    PDF: 1982
    HTML: 1246
  • 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
    2484
    PDF: 1762
    APPENDIX: 685
    HTML: 1058
  • 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
    1606
    PDF: 1023
    HTML: 165
  • 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
    1524
    PDF: 672
    HTML: 47
  • Bayesian spatial Durbin modelling of stunting prevalence across Indonesian districts

    Ferra Yanuar, Yudiantri Asdi, Sandi Sandi, Aidinil Zetra, Fenni Kurnia Mutiya, Ade Suzana Eka Putri
    25-05-2026
    https://doi.org/10.4081/gh.2026.1441
    473
    PDF: 206
    HTML: 11
  • 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
    792
    PDF: 496
    Supplementary materials: 78
    HTML: 19
  • 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
    4544
    PDF: 2389
    HTML: 2225
  • 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
    270
    PDF: 349
    HTML: 3
  • Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States

    Chunhui Liu, Xiaodi Su, Zhaoxuan Dong, Xingyu Liu, Chunxia Qiu
    25-05-2023
    https://doi.org/10.4081/gh.2023.1200
    1905
    PDF: 882
    HTML: 87
  • 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
    1400
    PDF: 693
    HTML: 64
  • 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
    1707
    PDF: 736
    HTML: 44
  • Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis

    François Niragire, Thomas N.O. Achia, Alexandre Lyambabaje, Joseph Ntaganira
    11-05-2017
    https://doi.org/10.4081/gh.2017.450
    3272
    PDF: 1993
    HTML: 1403
  • Bayesian spatial modelling of contraception effects on fertility in Mexican municipalities in 2020

    Gerardo Núñez Medina
    17-05-2022
    https://doi.org/10.4081/gh.2022.1080
    1386
    PDF: 734
    HTML: 170
  • Effects of weather and landscape on the equine West Nile virus infection risk in Mississippi, USA

    Guiming Wang
    04-11-2015
    https://doi.org/10.4081/gh.2015.357
    2235
    PDF: 1455
    HTML: 960
  • 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
    2539
    PDF: 625
    Supplementary 1: 188
    Supplementary 2: 410
    HTML: 181
  • Spatial epidemiology of cancer: a review of data sources, methods and risk factors

    Rita Roquette, Marco Painho, Baltazar Nunes
    08-05-2017
    https://doi.org/10.4081/gh.2017.504
    8688
    PDF: 3647
    HTML: 2723
  • Disease mapping and spatio-temporal analysis: importance of expected-case computation criteria

    Gonzalo Lòpez-Abente, Nuria Aragonés, Javier García-Pérez, Pablo Fernández- Navarro
    27-35
    01-11-2014
    https://doi.org/10.4081/gh.2014.3
    3609
    PDF: 1827
  • Identifying counties vulnerable to diabetes from obesity prevalence in the United States: a spatiotemporal analysis

    Xiao Li, Amanda Staudt, Lung-Chang Chien
    21-11-2016
    https://doi.org/10.4081/gh.2016.439
    2902
    PDF: 1401
    APPENDIX: 507
    HTML: 1192
  • 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
    3177
    PDF: 2384
    HTML: 477
  • Survived infancy but still vulnerable: spatial-temporal trends and risk factors for child mortality in the Agincourt rural sub-district, South Africa, 1992-2007

    Benn Sartorius, Kathleen Kahn, Mark A. Collinson, Penelope Vounatsou, Stephen M. Tollman
    285-295
    01-05-2011
    https://doi.org/10.4081/gh.2011.181
    2593
    PDF: 1365
  • Spatial analysis of congenital heart disease in São Paulo State, Brazil 2012-2022: associations with air pollution, maternal factors and social vulnerability

    Amarílis Bahia Bezerra, Ligia Vizeu Barrozo, Alfredo Pereira de Queiroz
    18-09-2025
    https://doi.org/10.4081/gh.2025.1407
    944
    PDF: 572
    HTML: 28
  • Spatial-temporal analysis of prostate cancer incidence from the Pennsylvania Cancer Registry, 2000-2011

    Ming Wang, Stephen A. Matthews, Khaled Iskandarani, Yimei Li, Zheng Li, Vernon M. Chinchilli, Lijun Zhang
    28-11-2017
    https://doi.org/10.4081/gh.2017.611
    3827
    PDF: 1037
    HTML: 732
  • 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
    3449
    PDF: 736
    HTML: 126
  • Bayesian spatio-temporal modelling of tobacco-related cancer mortality in Switzerland

    Verena Jürgens, Silvia Ess, Harish C. Phuleria, Martin Früh, Matthias Schwenkglenks, Harald Frick, Thomas Cerny, Penelope Vounatsou
    219-236
    01-05-2013
    https://doi.org/10.4081/gh.2013.82
    3658
    PDF: 1577
  • The influence of socioeconomic deprivation, access to healthcare and physical environment on old-age survival in Portugal

    Ana Isabel Ribeiro, Elias Teixeira Krainski, Marilia Sá Carvalho, Maria de Fátima de Pina
    07-11-2017
    https://doi.org/10.4081/gh.2017.581
    3852
    PDF: 1489
    HTML: 881
  • Dying in their prime: determinants and space-time risk of adult mortality in rural South Africa

    Benn Sartorius, Kathleen Kahn, Mark A. Collinson, Kurt Sartorius, Stephen M. Tollman
    237-249
    01-05-2013
    https://doi.org/10.4081/gh.2013.83
    2348
    PDF: 1270
  • A statistical approach to rank multiple priorities in Environmental Epidemiology: an example from high-risk areas in Sardinia, Italy

    Dolores Catelan, Annibale Biggeri
    81-89
    01-11-2008
    https://doi.org/10.4081/gh.2008.234
    1611
    PDF: 885
  • 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
    1057
    PDF: 438
    Supplementary materials: 150
    HTML: 12
  • The spatial distribution of Anopheles gambiae sensu stricto and An. arabiensis (Diptera: Culicidae) in Mali

    N. Sogoba, P. Vounatsou, M.M. Bagayoko, S. Doumbia, G. Dolo, L. Gosoniu, S.F. Traore, Y.T. Toure, T. Smith
    213-222
    01-05-2007
    https://doi.org/10.4081/gh.2007.269
    3100
    PDF: 1105
  • 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
    4120
    PDF: 1913
    HTML: 798
  • 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
    1372
    PDF: 637
    Supplementary Materials: 153
    HTML: 21
  • 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
    2317
    PDF: 1041
    HTML: 717
  • 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
    835
    PDF: 437
    Supplementary materials: 53
    HTML: 18
  • 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
    2886
    PDF: 1026
    HTML: 173
  • New insights into the application of geographical information systems and remote sensing in veterinary parasitology

    Laura Rinaldi, Vincenzo Musella, Annibale Biggeri, Giuseppe Cringoli
    33-47
    01-11-2006
    https://doi.org/10.4081/gh.2006.279
    4097
    PDF: 1810
  • Spatio-temporal outbreaks of campylobacteriosis and the role of fresh-milk vending machines in the Czech Republic: A methodological study

    Lukáš Marek, Vít Pászto
    08-11-2017
    https://doi.org/10.4081/gh.2017.572
    2917
    PDF: 872
    HTML: 852
  • Spatial analysis of the relationship between early childhood mortality and malaria endemicity in Malawi

    Lawrence N. Kazembe, Christopher C. Appleton, Immo Kleinschmidt
    41-50
    01-11-2007
    https://doi.org/10.4081/gh.2007.253
    3206
    PDF: 1657
  • 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
    4607
    PDF: 1344
    HTML: 1221
  • Spatial association and modelling of under-5 mortality in Thailand, 2020

    Suparerk Suerungruang, Kittipong Sornlorm, Wongsa Laohasiriwong, Roshan Kumar Mahato
    31-08-2023
    https://doi.org/10.4081/gh.2023.1220
    1794
    PDF: 1054
    HTML: 60
  • 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: 2034
    APPENDIX 1: 490
    APPENDIX 2: 517
    HTML: 1654
  • Hyperendemicity, heterogeneity and spatial overlap of leprosy and cutaneous leishmaniasis in the southern Amazon region of Brazil

    Amanda Gabriela de Carvalho, João Gabriel Guimarães Luz, João Victor Leite Dias, Anuj Tiwari, Peter Steinmann, Eliane Ignotti
    29-12-2020
    https://doi.org/10.4081/gh.2020.892
    2248
    PDF: 1119
    HTML: 56
  • Dynamic effect of economic growth on the persistence of suicide rates

    Tzu-Yi Yang, Yu-Tai Yang, Ssu-Han Chen, Yu-Ting Lan, Chia-Jui Peng
    25-05-2023
    https://doi.org/10.4081/gh.2023.1201
    1114
    PDF: 819
    HTML: 83
  • Geospatial assessment of dengue fever risk and spatial patterns in Phayao Province, Thailand

    Phaisarn Jeefoo, Watcharaporn Preedapirom Jeefoo, Sakorn Mekruksavanich, Kanchana Nakhapakorn
    23-07-2026
    https://doi.org/10.4081/gh.2026.1497
    215
    PDF: 180
    HTML: 3
  • 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
    1694
    PDF: 783
    Supplementary Materials: 149
    HTML: 26
  • Geographic distribution and demographic factors associated with use of a long-acting reversible contraceptive (LARC) in Ethiopia

    Mintesnot Tenkir Teni, Travis Loux, Ness Sandoval, Anne Sebert Kuhlmann
    23-01-2025
    https://doi.org/10.4081/gh.2025.1302
    3924
    PDF: 1443
    HTML: 1158
  • Space-time epidemiology and effect of meteorological parameters on influenza-like illness in Phitsanulok, a northern province in Thailand

    Prakash Madhav Nimbalkar, Nitin Kumar Tripathi
    21-11-2016
    https://doi.org/10.4081/gh.2016.447
    2564
    PDF: 1477
    HTML: 1161
  • 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
    414
    PDF: 322
    HTML: 15
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vhealths

vHealth Section

Geospatial Health
opens the new vHealth section. Discover vHealth

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

Keywords

Geospatial Health

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pISSN: 1827-1987
eISSN: 1970-7096

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