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  Impact of climate variability on the occurrence of cutaneous leishmaniasis in Khuzestan Province, southwestern Iran

  Farideh Azimi, Sadegh Shirian, Saranaz Jangjoo, Arman Ai, Tahereh Abbasi

  08-05-2017

  https://doi.org/10.4081/gh.2017.478

  2554

  PDF: 1165

  HTML: 1037
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  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

  2395

  PDF: 841

  HTML: 913
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  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

  1441

  PDF: 656

  Appendix: 90

  HTML: 30
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  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

  1580

  PDF: 732

  HTML: 157
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  American cutaneous leishmaniasis cases in the metropolitan region of Manaus, Brazil: association with climate variables over time

  Rodrigo Augusto Ferreira de Souza, Rita Valéria Andreoli, Mary Toshie Kayano, Afrânio Lima Carvalho

  18-05-2015

  https://doi.org/10.4081/gh.2015.314

  2662

  PDF: 1303

  HTML: 810
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  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

  1770

  PDF: 794

  HTML: 30

• Exploring recent spatial patterns of cutaneous leishmaniasis and their associations with climate in some countries of the Middle East using geographical information systems

  Salahuddin M. Jaber, Jwan H. Ibbini, Nawal S. Hijjawi, Nafn M. Amdar, Mohammed J. Huwail, Khalid Al-Aboud

  143-158

  01-11-2013

  https://doi.org/10.4081/gh.2013.62

  1925

  PDF: 908

• Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics

  Ahmed Seid, Endalamaw Gadisa, Teshome Tsegaw, Adugna Abera, Aklilu Teshome, Abate Mulugeta, Merce Herrero, Daniel Argaw, Alvar Jorge, Asnakew Kebede, Abraham Aseffa

  377-387

  01-05-2014

  https://doi.org/10.4081/gh.2014.27

  5035

  PDF: 2344
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  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

  1051

  PDF: 477

  Supplementary Materials: 41

  HTML: 10
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  Place and health infrastructure in the Gulf Cooperation Council: A systematic scoping review of GIS applications in health

  Dari Alhuwail, Saad AlSharrah, Neil T Coffee, Faisal H Al-Refaei, Mark Daniel

  29-12-2020

  https://doi.org/10.4081/gh.2020.887

  2429

  PDF: 893

  HTML: 37
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  Spatial epidemiology and meteorological risk factors of COVID-19 in Fars Province, Iran

  Marjan Zare, Ali Semati, Alireza Mirahmadizadeh, Abdulrasool Hemmati, Mostafa Ebrahimi

  08-06-2022

  https://doi.org/10.4081/gh.2022.1065

  730

  PDF: 287

  HTML: 18
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  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

  1275

  PDF: 591

  HTML: 22
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  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

  1336

  PDF: 779

  Appendix: 76

  HTML: 68
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  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

  3320

  PDF: 1584

  HTML: 2222

• Mastering geographically weighted regression: key considerations for building a robust model

  Behzad Kiani, Benn Sartorius, Colleen L. Lau, Robert Bergquist

  29-02-2024

  https://doi.org/10.4081/gh.2024.1271

  7651

  PDF: 1234

  HTML: 846
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  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

  3655

  PDF: 1228

  HTML: 1130