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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

  3118

  PDF: 1455

  HTML: 1078
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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

  3001

  PDF: 1176

  HTML: 955
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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

  1880

  PDF: 982

  Appendix: 181

  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

  1804

  PDF: 1028

  HTML: 174
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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

  3081

  PDF: 1558

  HTML: 823
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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

  2196

  PDF: 1060

  HTML: 52

• 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

  7303

  PDF: 2903

• 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

  2328

  PDF: 1097
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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

  1569

  PDF: 722

  Supplementary Materials: 126

  HTML: 22
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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

  3157

  PDF: 1146

  HTML: 77
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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

  1158

  PDF: 603

  HTML: 44
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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

  2148

  PDF: 920

  HTML: 41
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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

  1826

  PDF: 977

  Appendix: 146

  HTML: 83

• 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

  8589

  PDF: 1616

  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

  1465

  PDF: 619

  HTML: 100
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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

  3778

  PDF: 1939

  HTML: 2262
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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

  4068

  PDF: 1568

  HTML: 1148