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Geospatial Health

eISSN 1970-7096 - pISSN 1827-1987

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Editor-in-Chief: Robert Bergquist

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  • Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

    Timothy Shields, Jessie Pinchoff, Jailos Lubinda, Harry Hamapumbu, Kelly Searle, Tamaki Kobayashi, Philip E. Thuma, William J. Moss, Frank C. Curriero
    31-05-2016
    https://doi.org/10.4081/gh.2016.410
    2021
    PDF: 876
    HTML: 886
  • 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
    2174
    PDF: 1174
    HTML: 2011
  • 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
    3481
    PDF: 1388
    SUPPL. MATERIAL: 392
    HTML: 1078
  • 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
    4170
    PDF: 1438
    HTML: 1215
  • MALAREO: a user-driven project

    Michael T. Gebreslasie, Ides Bauwens
    04-11-2015
    https://doi.org/10.4081/gh.2015.329
    2621
    PDF: 1038
    HTML: 973
  • 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
    2385
    PDF: 979
    HTML: 1097
  • Satellite imagery technology in public health: analysis of site catchment areas for assessment of poliovirus circulation in Nigeria and Niger

    Marina Takane, Shizu Yabe, Yumiko Tateshita, Yusuke Kobayashi, Akihiko Hino, Kazuo Isono, Hiromasa Okayasu, Ousmane M. Diop, Takeo Tadono
    21-11-2016
    https://doi.org/10.4081/gh.2016.462
    2451
    PDF: 1382
    HTML: 1141
  • Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus

    Vasna Joshua, Kamaraj Pattabi, Yuvaraj Jeyaraman, Prabhdeep Kaur, Tarun Bhatnagar, Suresh Arunachalam, Sabarinathan Ramasamy, Venkateshprabhu Janagaraj, Manoj V Murhekar
    30-11-2022
    https://doi.org/10.4081/gh.2022.1097
    2001
    PDF: 738
    HTML: 110
  • 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
    1484
    PDF: 680
    Appendix: 98
    HTML: 30
  • The influence of urban heat islands and socioeconomic factors on the spatial distribution of Aedes aegypti larval habitats

    Thiago S. de Azevedo, Brian Patrick Bourke, Rafael Piovezan, Maria Anice M. Sallum
    08-05-2018
    https://doi.org/10.4081/gh.2018.623
    2661
    PDF: 1194
    HTML: 498
  • 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
    3657
    PDF: 1256
    APPENDIX: 473
    HTML: 1532
  • There is more to satellite imagery than meets the eye

    Robert Bergquist, John B. Malone
    31-05-2022
    https://doi.org/10.4081/gh.2022.1106
    2262
    PDF: 448
    HTML: 19
  • Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset

    Xiaohui Xu, Hui Hu, Sandie Ha, Daikwon Han
    23-11-2016
    https://doi.org/10.4081/gh.2016.482
    2732
    PDF: 767
    HTML: 812
  • 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
    1567
    PDF: 300
    HTML: 72
  • Geospatial analysis of invasion of the Asian tiger mosquito Aedes albopictus: competition with Aedes japonicus japonicus in its northern limit area in Japan

    Naoko Nihei, Osamu Komagata, Kan-ichiro Mochizuki, Mutsuo Kobayashi
    417-427
    01-05-2014
    https://doi.org/10.4081/gh.2014.30
    2492
    PDF: 1008
  • Urban environmental clustering to assess the spatial dynamics of Aedes aegypti breeding sites

    Guillermo Albrieu-Llinás, Manuel O. Espinosa, Agustín Quaglia, Marcelo Abril, Carlos Marcelo Scavuzzo
    07-05-2018
    https://doi.org/10.4081/gh.2018.654
    2759
    PDF: 1144
    HTML: 185
  • 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
    1607
    PDF: 474
    HTML: 82
  • A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina

    Micaela Natalia Campero, Carlos Matías Scavuzzo, Veronica Andreo, María Sol Mileo, Micaela Belén Franzois, María Georgina Oberto, Carla Gonzalez Rodriguez, María Daniela Defagó
    23-10-2023
    https://doi.org/10.4081/gh.2023.1212
    1156
    PDF: 599
    HTML: 13
  • 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
    2917
    PDF: 988
    HTML: 1194
  • 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
    10416
    PDF: 2463
  • TerraSAR-X high-resolution radar remote sensing: an operational warning system for Rift Valley fever risk

    Cécile Vignolles, Yves M. Tourre, Oscar Mora, Laurent Imanache, Murielle Lafaye
    23-31
    01-11-2010
    https://doi.org/10.4081/gh.2010.184
    1280
    PDF: 778
  • 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
    3122
    PDF: 1173
    HTML: 850
  • 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
    4118
    PDF: 1100
    HTML: 1196
  • Estimating population and livestock density of mobile pastoralists and sedentary settlements in the south-eastern Lake Chad area

    Vreni Jean-Richard, Lisa Crump, Abbani Alhadj Abicho, Ali Abba Abakar, Abdraman Mahamat II, Mahamat Bechir, Sandra Eckert, Matthias Engesser, Esther Schelling, Jakob Zinsstag
    18-05-2015
    https://doi.org/10.4081/gh.2015.307
    3888
    PDF: 1455
    HTML: 1458
  • Visualization of schistosomiasis snail habitats using light unmanned aerial vehicles

    Andrew J. Chamberlin, Isabel J. Jones, Andrea J. Lund, Nicolas Jouanard, Gilles Riveau, Raphaël Ndione, Susanne H. Sokolow, Chelsea L. Wood, Kevin D. Lafferty, Giulio A. De Leo
    08-01-2021
    https://doi.org/10.4081/gh.2020.818
    1408
    HTML: 65
    PDF: 677
  • 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
    2329
    PDF: 729
    HTML: 94
  • Trends in obesity at the national and local level among South Korean adolescents

    Kyungsoo Han, Sejin Park, Jürgen Symanzik, Sookhee Choi, Jeongyong Ahn
    31-05-2016
    https://doi.org/10.4081/gh.2016.381
    2599
    PDF: 1153
    HTML: 1216
  • Mapping environmental susceptibility to Saint Louis encephalitis virus, based on a decision tree model of remotelysensed data

    Camilo H. Rotela, Lorena I. Spinsanti, Mario A. Lamfri, Marta S. Contigiani, Walter R. Almiròn, Carlos M. Scavuzzo
    85-94
    01-11-2011
    https://doi.org/10.4081/gh.2011.160
    1226
    PDF: 727
  • Environmental determinants of Opisthorchis viverrini prevalence in northeast Thailand

    Yi-Chen Wang, Chen-Chieh Feng, Paiboon Sithithaworn
    111-123
    01-11-2013
    https://doi.org/10.4081/gh.2013.59
    2133
    PDF: 1067
  • Spatial patterns and eco-epidemiological systems - part II: characterising spatial patterns of the occurrence of the insect vectors of Chagas disease based on remote sensing and field data

    Emmanuel Roux, Annamaria de Fátima Venâncio, Jean-François Girres, Christine A. Romaña
    53-64
    01-11-2011
    https://doi.org/10.4081/gh.2011.157
    1303
    PDF: 733
  • Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space

    Benjamin G. Jacob, Fiorella Krapp, Mario Ponce, Eduardo Gotuzzo, Daniel A. Griffith, Robert J. Novak
    201-217
    01-05-2010
    https://doi.org/10.4081/gh.2010.201
    1558
    PDF: 886
  • 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
    3436
    PDF: 1418
    HTML: 1177
  • Investigation of landscape risk factors for the recent spread of varroa mite (Varroa destructor) in European honeybee (Apis mellifera) colonies in New South Wales, Australia

    Emily Phaboutdy, Michael Ward
    04-07-2024
    https://doi.org/10.4081/gh.2024.1282
    1564
    PDF: 466
    HTML: 13
  • Prevalence of hypertension in Thailand: Hotspot clustering detected by spatial analysis

    Wongsa Laohasiriwong, Nattapong Puttanapong, Atthawit Singsalasang
    07-05-2018
    https://doi.org/10.4081/gh.2018.608
    3647
    PDF: 1739
    HTML: 575
  • Geospatial tools and data for health service delivery: opportunities and challenges across the disaster management cycle

    Fleur Hierink, Nima Yaghmaei, Mirjam I. Bakker, Nicolas Ray, Marc van den Homberg
    29-10-2024
    https://doi.org/10.4081/gh.2024.1284
    5845
    PDF: 512
    Supplementary Materials: 152
    HTML: 86
  • Geographic clustering of elderly people with above-norm anthropometric measurements and blood chemistry

    Carlos Mena, Eduardo Fuentes, Yony Ormazábal, Iván Palomo
    11-05-2017
    https://doi.org/10.4081/gh.2017.523
    2717
    PDF: 1111
    HTML: 883
  • Changes in geographic clustering of post-traumatic stress disorder and post-traumatic growth seven years after an earthquake in Cauquenes, Chile

    Marcelo Leiva-Bianchi, Carlos Mena, Yony Ormazábal, Carlos Serrano, Pedro Rojas
    26-11-2020
    https://doi.org/10.4081/gh.2020.886
    2161
    PDF: 703
    HTML: 6
  • Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

    Dustin T. Duncan, Ryan R. Ruff, Basile Chaix, Seann D. Regan, James H. Williams, Joseph Ravenell, Marie A. Bragg, Gbenga Ogedegbe, Brian Elbel
    31-05-2016
    https://doi.org/10.4081/gh.2016.399
    3866
    PDF: 1778
    HTML: 1478
  • 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
    2200
    PDF: 1180
    HTML: 136
  • Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors

    Roghieh Ramezankhani, Nooshin Sajjadi, Roya Nezakati Esmaeilzadeh, Seyed Ali Jozi, Mohammad Reza Shirzadi
    08-11-2017
    https://doi.org/10.4081/gh.2017.578
    2463
    PDF: 877
    HTML: 915
  • 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
    3772
    PDF: 1295
    HTML: 1054
  • Spatiotemporal evolution characteristics and attribution analysis of hepatitis A in mainland China

    Xiaodi Su, Chunxia Qiu, Chunhui Liu
    03-12-2024
    https://doi.org/10.4081/gh.2024.1323
    915
    PDF: 241
    HTML: 4
  • 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
    1426
    PDF: 743
    HTML: 115
  • Mapping, cluster detection and evaluation of risk factors of ovine toxoplasmosis in Southern Italy

    Roberto Condoleo, Vincenzo Musella, Maria Paola Maurelli, Antonio Bosco, Giuseppe Cringoli, Laura Rinaldi
    31-05-2016
    https://doi.org/10.4081/gh.2016.432
    2447
    PDF: 1120
    HTML: 1219
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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
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The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure
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Typhoid fever in Jakarta, Indonesia 2017-2023: spatial clustering and seasonality of hospitalization data to inform better intervention
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Spatial autocorrelation pattern of COVID-19 vaccine coverage in Thailand 2021 and 2022
Sarayu Muntaphan et al.
13 May 2025
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Spatial multilevel modelling male partners’ influence on women’s modern contraceptive use: a study in Angola and Zambia
Kabeya Clement Mulamba
12 May 2025
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Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring
Jihong Zhang et al.
28 April 2025

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Geospatial Health

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pISSN: 1827-1987
eISSN: 1970-7096

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