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eISSN 1970-7096 - pISSN 1827-1987

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Editor-in-Chief: Robert Bergquist

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  • 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
    4093
    PDF: 1641
    HTML: 2547
  • 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
    1822
    PDF: 892
    Supplementary Materials: 129
    HTML: 44
  • 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
    4307
    PDF: 1696
    Appendix: 508
    HTML: 1579
  • 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
    3818
    PDF: 1371
    HTML: 1054
  • 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
    2984
    PDF: 1313
    HTML: 1426
  • 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
    3394
    PDF: 1699
    HTML: 2224
  • 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
    2329
    PDF: 1287
    HTML: 144
  • 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
    2144
    PDF: 1608
    HTML: 1139
  • 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
    2052
    PDF: 1150
    HTML: 317
  • 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
    3529
    PDF: 1496
    SUPPL. MATERIAL: 411
    HTML: 1078
  • 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
    1137
    PDF: 445
    HTML: 10
  • 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
    589
    PDF: 146
    HTML: 9
  • 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
    1252
    PDF: 564
    HTML: 23
  • 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
    3129
    PDF: 988
    HTML: 1457
  • 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
    2227
    PDF: 1252
    HTML: 2011
  • 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
    1981
    PDF: 1495
    APPENDIX: 549
    HTML: 1032
  • Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model

    Adrian M. Tompkins, Nicky McCreesh
    31-03-2016
    https://doi.org/10.4081/gh.2016.408
    3342
    PDF: 1293
    HTML: 995
  • 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
    3474
    PDF: 1491
    HTML: 1179
  • 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
    4182
    PDF: 1149
    HTML: 1197
  • 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
    1758
    PDF: 332
    HTML: 73
  • 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
    4060
    PDF: 2158
    HTML: 2156
  • 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
    212
    PDF: 160
    HTML: 0
  • 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
    3887
    PDF: 1152
    Appendix: 493
    HTML: 1211
  • 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
    5913
    PDF: 2422
    HTML: 3076
  • 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
    1983
    PDF: 1087
    HTML: 1118
  • Spatiotemporal analysis of hand, foot and mouth disease data using time-lag geographically-weighted regression

    Zhi-Min Hong, Hu-Hu Wang, Yan-Juan Wang, Wen-Rui Wang
    29-12-2020
    https://doi.org/10.4081/gh.2020.849
    1711
    PDF: 778
    HTML: 25
  • 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
    6116
    PDF: 1832
    HTML: 2151
  • Estimating small area health-related characteristics of populations: a methodological review

    Azizur Rahman
    08-05-2017
    https://doi.org/10.4081/gh.2017.495
    4007
    PDF: 1753
    HTML: 1348
  • 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
    2162
    PDF: 943
    HTML: 127
  • 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
    1372
    PDF: 809
    HTML: 49
  • 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
    2496
    PDF: 820
    HTML: 726
  • 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
    1270
    PDF: 422
    HTML: 42
  • 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
    3755
    PDF: 1366
    HTML: 1132
  • 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
    1967
    PDF: 824
    HTML: 80
  • 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
    3877
    PDF: 1605
    APPENDIX 1: 429
    APPENDIX 2: 420
    HTML: 1639
  • 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
    5157
    PDF: 2367
    HTML: 1980
  • Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach

    Alexander Domnich, Lucia Arata, Daniela Amicizia, Alessio Signori, Roberto Gasparini, Donatella Panatto
    16-11-2016
    https://doi.org/10.4081/gh.2016.457
    3075
    PDF: 1489
    HTML: 1304
  • Associations between seasonal influenza and meteorological parameters in Costa Rica, Honduras and Nicaragua

    Radina P. Soebiyanto, Wilfrido A. Clara, Jorge Jara, Angel Balmaseda, Jenny Lara, Mariel Lopez Moya, Rakhee Palekar, Marc-Alain Widdowson, Eduardo Azziz-Baumgartner, Richard K. Kiang
    04-11-2015
    https://doi.org/10.4081/gh.2015.372
    4242
    PDF: 1399
    HTML: 1161
  • 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
    4201
    PDF: 1105
    HTML: 254
  • 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
    2197
    PDF: 1361
    HTML: 270
  • 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
    2390
    PDF: 415
    HTML: 44
  • 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
    2471
    PDF: 720
    Supplementary Materials: 132
    HTML: 77
  • 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
    1774
    PDF: 722
    Supplementary Materials: 96
    HTML: 37
  • 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
    3937
    PDF: 1657
    HTML: 1231
  • 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
    1064
    PDF: 450
    HTML: 14
  • 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
    1636
    PDF: 826
    HTML: 158
  • 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
    2367
    PDF: 574
    HTML: 76
  • 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
    1521
    PDF: 748
    Appendix: 116
    HTML: 30
  • 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
    1963
    PDF: 490
    Supplementary 1: 102
    Supplementary 2: 253
    HTML: 145
  • 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
    1041
    PDF: 458
    HTML: 225
  • 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
    6862
    PDF: 2359
    APPENDIX: 1106
    HTML: 5154
  • Spatiality in small area estimation: A new structure with a simulation study

    Yadollah Mehrabi, Amir Kavousi, Ahmad-Reza Baghestani, Mojtaba Soltani-Kermanshahi
    29-12-2020
    https://doi.org/10.4081/gh.2020.872
    1047
    PDF: 487
    Supplementary materials: 142
    HTML: 11
  • 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
    1274
    PDF: 397
    HTML: 32
  • 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
    3525
    PDF: 2052
    HTML: 1261
  • Estimating malaria burden in Nigeria: a geostatistical modelling approach

    Nnadozie Onyiri
    04-11-2015
    https://doi.org/10.4081/gh.2015.306
    7067
    PDF: 2923
    HTML: 3251
  • Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis

    Maria Camila Lesmes , Alvaro Ávila-Díaz, Erika Santamaría, Carlos Andrés Morales , Horacio Cadena, Patricia Fuya, Nicolas Frutos, Ximena Porcasi, Catalina Marceló-Díaz
    04-06-2025
    https://doi.org/10.4081/gh.2025.1292
    923
    PDF: 243
    HTML: 14
  • Spatial distribution and identifying biochemical factors affecting haemoglobin levels among women of reproductive age for each province in Indonesia: A geospatial analysis

    Muhammad Nur Aidi, Fitrah Ernawati, Efriwati Efriwati, Nunung Nurjanah, Rika Rachmawati, Elisa Diana Julianti, Dian Sundari, Fifi Retiaty, Anwar Fitrianto, Khalilah Nurfadilah, Aya Yuriestia Arifin
    30-11-2022
    https://doi.org/10.4081/gh.2022.1118
    1858
    PDF: 863
    HTML: 57
  • 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
    418
    PDF: 168
    HTML: 12
  • 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
    3975
    PDF: 1100
    HTML: 901
  • 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
    3327
    PDF: 1629
    HTML: 638
  • 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
    3119
    PDF: 1427
    HTML: 1027
  • 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
    3443
    PDF: 1074
  • 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
    1681
    PDF: 537
    HTML: 85
  • 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
    3714
    PDF: 1371
    APPENDIX: 498
    HTML: 1534
  • Spatial associations between chronic kidney disease and socio-economic factors in Thailand

    Juree Sansuk, Kittipong Sornlorm
    30-01-2024
    https://doi.org/10.4081/gh.2024.1246
    6033
    PDF: 823
    HTML: 947
  • 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
    2989
    PDF: 1029
    HTML: 1208
  • 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
    1833
    PDF: 834
  • Cancer incidence in Priolo, Sicily: a spatial approach for estimation of industrial air pollution impact

    Lucia Fazzo, Mario Carere, Francesco Tisano, Caterina Bruno, Achille Cernigliaro, Maria Rita Cicero, Pietro Comba, Maria Luisa Contrino, Marco De Santis, Fabrizio Falleni, Vincenzo Ingallinella, Anselmo Madeddu, Ida Marcello, Carlo Regalbuto, Giovanna Sciacca, Maria Eleonora Soggiu, Amerigo Zona
    18-04-2016
    https://doi.org/10.4081/gh.2016.320
    4839
    PDF: 1834
    HTML: 1968
  • Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

    Suparat Tappo, Wongsa Laohasiriwong, Nattapong Puttanapong
    29-11-2022
    https://doi.org/10.4081/gh.2022.1091
    1360
    PDF: 950
    Appendix: 103
    HTML: 168
  • 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
    1520
    PDF: 767
    HTML: 56
  • 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
    1481
    PDF: 810
    HTML: 119
  • Spatial-temporal risk factors in the occurrence of rabies in Mexico

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Geospatial Health
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Vol. 20 No. 1 (2025)
Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis
Maria Camila Lesmes et al.
4 June 2025
Vol. 20 No. 1 (2025)
The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure
Nima Kianfar et al.
4 June 2025
Vol. 20 No. 1 (2025)
Typhoid fever in Jakarta, Indonesia 2017-2023: spatial clustering and seasonality of hospitalization data to inform better intervention
Mujiyanto Mujiyanto et al.
15 May 2025
Vol. 20 No. 1 (2025)
Spatial autocorrelation pattern of COVID-19 vaccine coverage in Thailand 2021 and 2022
Sarayu Muntaphan et al.
13 May 2025
Vol. 20 No. 1 (2025)
Spatial multilevel modelling male partners’ influence on women’s modern contraceptive use: a study in Angola and Zambia
Kabeya Clement Mulamba
12 May 2025
Vol. 20 No. 1 (2025)
Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring
Jihong Zhang et al.
28 April 2025

Keywords

Geospatial Health

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