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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 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
    1912
    PDF: 755
    HTML: 79
  • COVID-19, air quality and space monitoring

    Yves M. Tourre, Mireille Paulin, Gilles Dhonneur, David Attias, Atul Pathak
    06-04-2022
    https://doi.org/10.4081/gh.2022.1052
    1436
    PDF: 392
    HTML: 19
  • Spatial cluster analysis of COVID-19 in Malaysia (Mar-Sep, 2020)

    Sami Ullah, Nurul Hidayah Mohd Nor, Hanita Daud, Nooraini Zainuddin, Muhammad Salim Javed Gandapur, Iftikhar Ali, Alamgir Khalil
    05-05-2021
    https://doi.org/10.4081/gh.2021.961
    3590
    PDF: 1426
    HTML: 75
  • Risk mapping and estimation of COVID-19 transmission in South Sulawesi, Indonesia by a self-identification survey

    Andang Suryana Soma, Andi Alfian Zainuddin, Shanti Riskiyani, Nurhaya Nurdin, Muhammad Firdaus Kasim, Joko Hendarto, Masriadi
    18-03-2022
    https://doi.org/10.4081/gh.2022.1034
    1761
    PDF: 352
    HTML: 37
  • Evaluation and control strategy analysis of influenza cases in Jiujiang City, Jiangxi Province, China from 2018 to 2022

    Zhang Zeng, Huomei Xiong
    09-10-2024
    https://doi.org/10.4081/gh.2024.1294
    678
    PDF: 255
    HTML: 72
  • Geospatial tools for the identification of a malaria corridor in Estado Sucre, a Venezuelan north-eastern state

    Laura Delgado-Petrocelli, Alberto Camardiel, Víctor Hugo Aguilar, Néstor Martinez, Karenia Còrdova, Santiago Ramos
    169-176
    01-05-2011
    https://doi.org/10.4081/gh.2011.168
    2282
    PDF: 811
  • Epidemiological aspects and spatial distribution of human and canine visceral leishmaniasis in an endemic area in northeastern Brazil

    Roseane Campos, Márcio Santos, Gabriel Tunon, Luana Cunha, Lucas Magalhães, Juliana Moraes, Danielle Ramalho, Sanmy Lima, José Antônio Pacheco, Michael Lipscomb, Amélia Ribeiro de Jesus, Roque Pacheco de Almeida
    11-05-2017
    https://doi.org/10.4081/gh.2017.503
    4836
    PDF: 1857
    HTML: 1137
  • Can landscape metrics help determine the Culicoides imicola distribution in Italy?

    Carla Ippoliti, Marius Gilbert, Sabine Vanhuysse, Maria Goffredo, Giuseppe Satta, Eléonore Wolff, Annamaria Conte
    267-277
    01-11-2013
    https://doi.org/10.4081/gh.2013.72
    1639
    PDF: 773
  • Identifying areas of Australia at risk of H5N1 avian influenza infection from exposure to migratory birds: a spatial analysis

    Iain J. East, Samuel Hamilton, Graeme Garner
    203-213
    01-05-2008
    https://doi.org/10.4081/gh.2008.244
    1682
    PDF: 1004
  • 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
    2029
    PDF: 599
    Supplementary Materials: 81
    HTML: 164
  • Space-time cluster analysis of anemia in pregnant women in the province of Khyber Pakhtunkhwa, Pakistan (2014-2020)

    Sami Ullah, SM Aqil Burney, Tariq Rasheed, Shamaila Burney, Mushtaq Ahmad Khan Barakzia
    05-10-2023
    https://doi.org/10.4081/gh.2023.1192
    966
    PDF: 522
    HTML: 19
  • Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns

    Yali Si, Andrew K. Skidmore, Tiejun Wang, Willem F. de Boer, Pravesh Debba, Albert G. Toxopeus, Lin Li, Herbert H.T. Prins
    65-78
    01-11-2009
    https://doi.org/10.4081/gh.2009.211
    5274
    PDF: 1289
  • Spatial patterns of Plasmodium vivax transmission explored by multivariate auto-regressive state-space modelling - A case study in Baoshan Prefecture in southern China

    Jinxin Zheng, Benyun Shi, Shang Xia, Guojing Yang, Xiao-Nong Zhou
    12-03-2021
    https://doi.org/10.4081/gh.2021.879
    1577
    PDF: 556
    HTML: 21
  • 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
    3685
    PDF: 1249
    HTML: 1130
  • A multifaceted comparison of ArcGIS and MapMarker for automated geocoding

    Sanjaya Kumar, Ming Liu, Syni-An Hwang
    145-151
    01-11-2012
    https://doi.org/10.4081/gh.2012.113
    2253
    PDF: 1025
  • Mapping brucellosis risk in communities in the Republic of Armenia

    Thibaud Porphyre, Ronald Jackson, Carola Sauter-Louis, David Ward, Grigor Baghyan, Edik Stepanyan
    103-118
    01-11-2010
    https://doi.org/10.4081/gh.2010.191
    1745
    PDF: 952
  • Reducing bias in risk indices for COVID-19

    Michał Paweł Michalak, Jack Cordes, Agnieszka Kulawik, Sławomir Sitek, Sławomir Pytel, Elżbieta Zuzańska-Żyśko, Radosław Wieczorek
    14-01-2022
    https://doi.org/10.4081/gh.2022.1013
    2612
    PDF: 258
    Appendix: 325
    HTML: 28
  • Risk areas for hepatitis A, B and C in the municipality of Maringá, Paraná State, Brazil 2007-2010

    Valéria Miranda Avanzi, Udelysses Janete Veltrini Fonzar, Eraldo Schunk Silva, Jorge Juarez Vieira Teixeira, Dennis Armando Bertolini
    08-05-2018
    https://doi.org/10.4081/gh.2018.607
    1800
    PDF: 660
    HTML: 128
  • 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
    4198
    PDF: 1612
    Appendix: 481
    HTML: 1576
  • The use of spatial tools in the study of Schistosoma mansoni and its intermediate host snails in Brazil: a brief review

    Andrea Gazzinelli, Helmut Kloos
    51-58
    01-11-2007
    https://doi.org/10.4081/gh.2007.254
    1908
    PDF: 817
  • 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
    1433
    PDF: 265
    HTML: 49
  • Intestinal schistosomiasis and soil-transmitted helminthiasis in Ugandan schoolchildren: a rapid mapping assessment

    Claire J. Standley, Moses Adriko, Moses Alinaitwe, Francis Kazibwe, Narcis B. Kabatereine, J. Russell Stothard
    39-53
    01-11-2009
    https://doi.org/10.4081/gh.2009.209
    2681
    PDF: 1098
  • Spatio-temporal analysis of tuberculosis incidence in North Aceh District, Indonesia 2019-2021

    Farrah Fahdhienie, Frans Yosep Sitepu
    29-11-2022
    https://doi.org/10.4081/gh.2022.1148
    1813
    PDF: 1137
    HTML: 107
  • 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
    2465
    PDF: 1100
    HTML: 210
  • 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
    2721
    PDF: 757
    HTML: 812
  • Analysis of the El Niño/La Niña-Southern Oscillation variability and malaria in the Estado Sucre, Venezuela

    Laura Delgado-Petrocelli, Karenia Còrdova, Alberto Camardiel, Víctor H. Aguilar, Denise Hernández, Santiago Ramos
    S51-S57
    01-09-2012
    https://doi.org/10.4081/gh.2012.122
    2465
    PDF: 920
  • Mapping displaced populations with reference to social vulnerabilities for post-disaster public health management

    Junaid Ahmad, Anees Ahmad, Mokbul Morshed Ahmad, Nafees Ahmad
    27-11-2017
    https://doi.org/10.4081/gh.2017.576
    3346
    PDF: 1078
    HTML: 1413
  • 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
    2006
    PDF: 865
    HTML: 886
  • The relative risk of spatial cluster occurrence and spatiotemporal evolution of meningococcal disease in Niger, 2002-2008

    Halima B. Maïnassara, Nicolas Molinari, Christophe Dematteï, Pascale Fabbro-Peray
    93-101
    01-11-2010
    https://doi.org/10.4081/gh.2010.190
    1189
    PDF: 788
  • Spatial clustering of colorectal cancer in Malaysia

    Sharifah Saffinas Syed Soffian, Azmawati Mohammed Nawi, Rozita Hod, Khairul Nizam Abdul Maulud, Ahmad Tarmizi Mohd Azmi, Mohd Hazrin Hasim Hashim, Huan-Keat Chan, Muhammad Radzi Abu Hassan
    25-05-2023
    https://doi.org/10.4081/gh.2023.1158
    1275
    PDF: 548
    HTML: 6
  • 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
    3329
    PDF: 1447
    HTML: 1100
  • Spatio-temporal analysis of the progression of Aujeszky's disease virus infection in wild boar of Saxony-Anhalt, Germany

    Nicolai Denzin, Joachim Borgwardt, Conrad Freuling, Thomas Müller
    203-213
    01-11-2013
    https://doi.org/10.4081/gh.2013.67
    1831
    PDF: 885
  • 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
    2239
    PDF: 440
    HTML: 19
  • Modeling spatio-temporal risk changes in the incidence of dengue fever in Saudi Arabia: a geographical information system case study

    Hassan M. Khormi, Lalit Kumar, Ramze A. Elzahrany
    77-84
    01-11-2011
    https://doi.org/10.4081/gh.2011.159
    2580
    PDF: 1190
  • Addressing operational challenges of combatting malaria in a remote forest area of Vietnam using spatial decision support system approaches

    Thang Duc Ngo, Sara E. Canavati, Ha Son Dinh, Thinh Duc Ngo, Duong T. Tran, Nicholas J. Martin, Gerard C. Kelly
    06-11-2019
    https://doi.org/10.4081/gh.2019.770
    1815
    PDF: 725
    APPENDIX: 198
    HTML: 54
  • Developing operational algorithms using linear and non-linear squares estimation in Python® for the identification of Culex pipiens and Culex restuans in a mosquito abatement district (Cook County, Illinois, USA)

    Benjamin G. Jacob, Weidong Gu, Erik X. Caamano, Robert J. Novak
    157-176
    01-05-2009
    https://doi.org/10.4081/gh.2009.218
    1340
    PDF: 796
  • 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
    2302
    PDF: 719
    HTML: 94
  • 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
    1601
    PDF: 753
    HTML: 157
  • Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

    Rutendo Birri Makota, Eustasius Musenge
    27-11-2023
    https://doi.org/10.4081/gh.2023.1207
    1215
    PDF: 544
    HTML: 38
  • Mapping and predicting malaria transmission in the People's Republic of China, using integrated biology-driven and statistical models

    Guo-Jing Yang, Qi Gao, Shui-Sen Zhou, John B. Malone, Jennifer C. McCarroll, Marcel Tanner, Penelope Vounatsou, Robert Bergquist, Jürg Utzinger, Xiao-Nong Zhou
    11-22
    01-11-2010
    https://doi.org/10.4081/gh.2010.183
    2833
    PDF: 1265
  • Development of a web-geographical information system application for plotting tuberculosis cases

    Nur Adibah Mohidem, Malina Osman, Farrah Melissa Muharam, Saliza Mohd Elias, Rafiza Shaharudin, Zailina Hashim
    19-10-2021
    https://doi.org/10.4081/gh.2021.980
    1568
    PDF: 752
    HTML: 157
  • 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
    7520
    PDF: 3015
    HTML: 2647
  • Schistosoma japonicum risk in Jiangsu province, People's Republic of China: identification of a spatio-temporal risk pattern along the Yangtze River

    Kun Yang, Le-Ping Sun, You-Sheng Liang, Feng Wu, Wei Li, Jian-Feng Zhang, Yi-Xin Huang, De-Rong Hang, Song Liang, Robert Bergquist, Xiao-Nong Zhou
    133-142
    01-11-2013
    https://doi.org/10.4081/gh.2013.61
    2430
    PDF: 876
  • A geospatial risk assessment model for leprosy in Ethiopia based on environmental thermal-hydrological regime analysis

    Azeb Tadesse Argaw, E.J. Shannon, Abraham Assefa, Fekade Silassie Mikru, Berhane Kidane Mariam, John B. Malone
    105-113
    01-11-2006
    https://doi.org/10.4081/gh.2006.285
    2174
    PDF: 908
  • Detection of high risk campylobacteriosis clusters at three geographic levels

    Jennifer Weisent, Barton Rohrbach, John R. Dunn, Agricola Odoi
    65-76
    01-11-2011
    https://doi.org/10.4081/gh.2011.158
    1601
    PDF: 690
  • Virtual globes and geospatial health: the potential of new tools in the management and control of vector-borne diseases

    Anna-Sofie Stensgaard, Christopher F.L. Saarnak, Jürg Utzinger, Penelope Vounatsou, Christopher Simoonga, Gabriel Mushinge, Carsten Rahbek, Flemming Møhlenberg, Thomas K. Kristensen
    127-141
    01-05-2009
    https://doi.org/10.4081/gh.2009.216
    1931
    PDF: 1597
  • Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019–2021

    Farrah Fahdhienie, Frans Yosep Sitepu, Elpiani Br Depari
    03-09-2024
    https://doi.org/10.4081/gh.2024.1318
    1145
    PDF: 458
    HTML: 93
  • Common errors in disease mapping

    Ricardo Ocaña-Riola
    139-154
    01-05-2010
    https://doi.org/10.4081/gh.2010.196
    3192
    PDF: 1038
  • 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
    5824
    PDF: 500
    Supplementary Materials: 148
    HTML: 85
  • A spatial, statistical approach to map the risk of milk contamination by β-hexachlorocyclohexane in dairy farms

    Sabrina Battisti, Antonino Caminiti, Giancarlo Ciotoli, Valentina Panetta, Pasquale Rombolá, Marcello Sala, Alessandro Ubaldi, Paola Scaramozzino
    77-86
    01-11-2013
    https://doi.org/10.4081/gh.2013.56
    1910
    PDF: 988
  • Spatiotemporal patterns of mortality associated with chronic non-communicable diseases and child malnutrition at the municipal level in Mexico

    José Mauricio Galeana-Pizaña, Leslie Verdeja-Vendrell, Lizbeth Ixchel Díaz-Trejo, Carlos Anzaldo, Daniela Figueroa, Aldo Daniel Jiménez-Ortega
    17-05-2022
    https://doi.org/10.4081/gh.2022.1087
    1286
    PDF: 633
    Appendix: 93
    HTML: 55
  • Geographical accessibility to healthcare by point-of–interest data from online maps: a comparative study

    Heng-Qian Huang-fu, Nan Zhang, Li Wang, Hui-Juan Liang, Ben-Song Xian, Xiao-Fang Gan, Yingsi Lai
    20-12-2024
    https://doi.org/10.4081/gh.2024.1322
    832
    PDF: 191
    Supplementary Materials: 50
    HTML: 7
  • Leptospirosis and its spatial and temporal relations with natural disasters in six municipalities of Santa Catarina, Brazil, from 2000 to 2016

    Ana Elisa Pereira Silva, Francisco Chiaravalloti Neto, Gleice Margarete de Souza Conceição
    26-11-2020
    https://doi.org/10.4081/gh.2020.903
    2439
    PDF: 905
    HTML: 52
  • The utility of Google Trends for epidemiological research: Lyme disease as an example

    Ari Seifter, Alison Schwarzwalder, Kate Geis, John Aucott
    135-137
    01-05-2010
    https://doi.org/10.4081/gh.2010.195
    9979
    PDF: 3491
  • Geospatial (s)tools: integration of advanced epidemiological sampling and novel diagnostics

    Giuseppe Cringoli, Laura Rinaldi, Marco Albonico, Robert Bergquist, Jürg Utzinger
    399-404
    01-05-2013
    https://doi.org/10.4081/gh.2013.97
    3907
    PDF: 1467
  • Spatial distribution of triatomines (Reduviidae: Triatominae) in urban areas of the city of Salvador, Bahia, Brazil

    Karine de Souza O. Santana, Maria Emília Bavia, Artur Dias Lima, Isabel Cristina S. Guimarães, Ênio Silva Soares, Marta Mariana Nascimento Silva, Jorge Mendonça, Moara de Santana Martin
    199-203
    01-05-2011
    https://doi.org/10.4081/gh.2011.172
    1941
    PDF: 858
  • 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
    2178
    PDF: 1171
    HTML: 133
  • Spatiotemporal mapping and detection of mortality cluster due to cardiovascular disease with Bayesian hierarchical framework using integrated nested Laplace approximation: A discussion of suitable statistic applications in Kersa, Oromia, Ethiopia

    Melkamu Dedefo, Henry Mwambi, Sileshi Fanta, Nega Assefa
    12-11-2018
    https://doi.org/10.4081/gh.2018.681
    1866
    PDF: 954
    HTML: 197
  • The acquired immunodeficiency syndrome in the State of Rio de Janeiro, Brazil: a spatio-temporal analysis of cases reported in the period 2001-2010

    André T. J. Alves, Flávio F. Nobre
    437-443
    01-05-2014
    https://doi.org/10.4081/gh.2014.32
    1656
    PDF: 864
  • 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
    1447
    PDF: 1419
  • Spatial analysis of the prevalence of schistosomiasis in an endemic coastal area in north-eastern Brazil

    Allan D. Santos, Jonhnatas Silva, Ana Caroline Lima, Márcio Santos, Shirley Lima, Monalisa Amor, Carlos Santos, Arthur Vasconcelos, Silvio Dolabella, Karina C.G.M. Araújo
    27-11-2017
    https://doi.org/10.4081/gh.2017.570
    2867
    PDF: 762
    HTML: 861
  • 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
    2888
    PDF: 984
    HTML: 1194
  • Contacts between poultry farms, their spatial dimension and their relevance for avian influenza preparedness

    Lena Fiebig, Timo Smieszek, Jennifer Saurina, Jan Hattendorf, Jakob Zinsstag
    79-95
    01-11-2009
    https://doi.org/10.4081/gh.2009.212
    1702
    PDF: 758
  • 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
    4094
    PDF: 1087
    HTML: 1196
  • Spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes

    Aline Beatriz dos Santos Silva, Ana Catarina de Melo Araújo, Amanda Priscila de Santana Cabral Silva, Mirella Bezerra Rodrigues Vilela, Cristine Vieira do Bonfim
    17-05-2022
    https://doi.org/10.4081/gh.2022.1051
    924
    PDF: 403
    Appendix: 87
    HTML: 18
  • A concise, straightforward presentation can be worth more than a thousand words

    Robert Bergquist
    03-11-2017
    https://doi.org/10.4081/gh.2017.637
    2386
    PDF: 642
    HTML: 653
  • Revealing spatio-temporal patterns of rabies spread among various categories of animals in the Republic of Kazakhstan, 2010-2013

    Sarsenbay K. Abdrakhmanov, Kanatzhan K. Beisembayev, Fedor I. Кorennoy, Gulzhan N. Yessembekova, Dosym B. Кushubaev, Ablaikhan S. Кadyrov
    31-05-2016
    https://doi.org/10.4081/gh.2016.455
    2235
    PDF: 1122
    HTML: 1283
  • Spatial and temporal clustering analysis of pulmonary tuberculosis and its associated risk factors in southwest China

    Jianjiao Wang, Xiaoning Liu, Zhengchao Jing, Jiawai Yang
    25-05-2023
    https://doi.org/10.4081/gh.2023.1169
    794
    PDF: 550
    HTML: 19
  • Association of city-level walkability, accessibility to biking and public transportation and socio-economic features with COVID-19 infection in Massachusetts, USA: An ecological study

    Yucheng Wang, Thomas C. Tsai, Dustin T. Duncan, John Ji
    14-01-2022
    https://doi.org/10.4081/gh.2022.1017
    5267
    PDF: 726
    Appendix: 308
    HTML: 37
  • Operational satellite-based temporal modelling of Aedes population in Argentina

    Manuel Espinosa, Eliana Marina Alvarez Di Fino, Marcelo Abril, Mario Lanfri, Maria Victoria Periago, Carlos Marcelo Scavuzzo
    09-11-2018
    https://doi.org/10.4081/gh.2018.734
    1780
    PDF: 978
    HTML: 63
  • 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
    3746
    PDF: 1284
    HTML: 1054
  • 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
    3003
    PDF: 1269
    HTML: 1218
  • Spatial autocorrelation pattern of COVID-19 vaccine coverage in Thailand 2021 and 2022

    Sarayu Muntaphan, Kittipong Sornlorm
    13-05-2025
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Geospatial Health
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Vol. 20 No. 1 (2025)
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Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring
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28 April 2025

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Geospatial Health

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