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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

  3149

  PDF: 1486

  HTML: 1080
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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

  3029

  PDF: 1198

  HTML: 958
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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

  1926

  PDF: 1061

  Appendix: 193

  HTML: 42
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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

  1866

  PDF: 1045

  HTML: 175
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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

  3129

  PDF: 1588

  HTML: 830
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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

  2220

  PDF: 1087

  HTML: 56

• 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

  7474

  PDF: 2938

• 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

  2376

  PDF: 1115
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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

  1632

  PDF: 750

  Supplementary Materials: 134

  HTML: 24
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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

  3194

  PDF: 1176

  HTML: 79
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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

  1211

  PDF: 627

  HTML: 46
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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

  2205

  PDF: 941

  HTML: 43
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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

  1867

  PDF: 993

  Appendix: 155

  HTML: 84

• 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

  8667

  PDF: 1645

  HTML: 886
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  Urban gentrification and infectious diseases: an interdisciplinary narrative review

  Behzad Kiani, Gabriel Parker, Senobar Naderian, Colleen L. Lau, Benn Sartorius

  07-07-2025

  https://doi.org/10.4081/gh.2025.1388

  1498

  PDF: 640

  HTML: 101
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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

  3832

  PDF: 1968

  HTML: 2265
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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

  4148

  PDF: 1601

  HTML: 1150