Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases

Sarah Isnan; Ahmad Fikri bin Abdullah; Abdul Rashid Shariff; Iskandar Ishak; Sharifah Norkhadijah Syed Ismail; Maheshwara Rao Appanan; Jihong Zhang; Guohua Yin; Qiuhua Zhang; Juan Fang; Duo Jiang; Chao Yang; Na Sun; Alireza Mohammadi; Bardia Mashhoodi; Ali Shamsoddini; Elahe Pishgar; Robert Bergquist; Wentao Yang; Fengjie Wang; Yihan You; Zhixiong Fang; Xing Wang; Xiaoming Mei; Sang Min Lee; Dong Woo Huh; Young Gyu Kwon; Peter Nezval; Takeshi Shirabe; Jonas Schoo; Frank Schüssler; Mai Liu; Yin Zhang; Enríque Ibarra-Zapata; Darío Gaytán-Hernández; Yolanda Terán-Figueroa; Verónica Gallegos-García; Carmen del Pilar Suárez-Rodríguez; Sergio Zarazúa Guzmán; Omar Parra Rodríguez; Worrayot Darasawang; Wongsa Laohasiriwong; Kittipong Sornlorm; Warangkana Sungsitthisawad; Roshan Kumar Mahato; Mintesnot Tenkir Teni; Travis Loux; Ness Sandoval; Anne Sebert Kuhlmann; Iuria Betco; Ana Isabel Ribeiro; David S. Vale; Luis Encalada-Abarca; Cláudia M. Viana; Jorge Rocha; Adel Al-Huraibi; Sherif Amer; Justine Blanford; Néstor DelaPaz-Ruíz; Ellen-Wien Augustijn; Mahdi Farnaghi; Sheheen A. Abdulkareem; Raul Zurita Milla

doi:10.4081/gh.2025.1277

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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

4834

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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

2605

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Spatial and spatiotemporal dynamics of visceral leishmaniasis in an endemic North-eastern region of Brazil

Ã‚ndria Silveira Almeida, Caíque Jordan Nunes Ribeiro, Camila Caroline Carlini, Rogério Silva Santos, Allan Dantas dos Santos, Débora Santos Tavares, Karina Conceição Gomes Machado de Araújo, Tatiana Rodrigues de Moura, Priscila Lima dos Santos

11-01-2021

https://doi.org/10.4081/gh.2020.885

1623

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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

2436

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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

1468

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Appendix: 94

HTML: 30
Use of soil moisture active passive satellite data and WorldClim 2.0 data to predict the potential distribution of visceral leishmaniasis and its vector Lutzomyia longipalpis in Sao Paulo and Bahia states, Brazil

Moara de Santana Martins Rodgers, Elivelton Fonseca, Prixia del Mar Nieto, John B. Malone, Jeffery C. Luvall, Jennifer C. McCarroll, Ryan Harry Avery, Maria Emilia Bavia, Raul Guimaraes, Xue Wen, Marta Mariana Nascimento Silva, Deborah D.M.T. Carneiro, Luciana Lobato Cardim

08-06-2022

https://doi.org/10.4081/gh.2022.1095

1322

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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

1599

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HTML: 157
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, AfrÃ¢nio Lima Carvalho

18-05-2015

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

2712

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HTML: 810
Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran

Mohammadreza Rajabi, Ali Mansourian, Petter Pilesjö, Ahad Bazmani

179-191

01-11-2014

https://doi.org/10.4081/gh.2014.15

7062

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Temperature-derived potential for the establishment of phlebotomine sandflies and visceral leishmaniasis in Germany

Dominik Fischer, Stephanie M. Thomas, Carl Beierkuhnlein

59-69

01-11-2010

https://doi.org/10.4081/gh.2010.187

2344

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Identification of environmental parameters and risk mapping of visceral leishmaniasis in Ethiopia by using geographical information systems and a statistical approach

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

299-308

01-05-2013

https://doi.org/10.4081/gh.2013.88

3447

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Risk assessment for canine leishmaniasis spreading in the north of Italy

Giulia Morosetti, Gioia Bongiorno, Bernadett Beran, Aldo Scalone, Judith Moser, Marina Gramiccia, Luigi Gradoni, Michele Maroli

115-127

01-11-2009

https://doi.org/10.4081/gh.2009.214

2420

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Ecological study and risk mapping of visceral leishmaniasis in an endemic area of Iran based on a geographical information systems approach

Abdoreza Salahi-Moghaddam, Mehdi Mohebali, Ali Moshfae, Majid Habibi, Zabiholah Zarei

71-77

01-11-2010

https://doi.org/10.4081/gh.2010.188

1869

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Ecological study and risk mapping of leishmaniasis in an endemic area of Brazil based on a geographical information systems approach

Alba Valéria Machado da Silva, Monica de Avelar Figueiredo Mafra Magalhães, Reginaldo Peçanha Brazil, João Carlos Araujo Carreira

33-40

01-11-2011

https://doi.org/10.4081/gh.2011.155

1571

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Susceptibility mapping of visceral leishmaniasis based on fuzzy modelling and group decision-making methods

Mohamadreza Rajabi, Ali Mansourian, Ahad Bazmani

37-50

01-11-2012

https://doi.org/10.4081/gh.2012.103

1542

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Application of spatio-temporal scan statistics for the detection of areas with increased risk for American visceral leishmaniasis in the state of Bahia, Brazil

Deborah D.M.T. Carneiro, Maria E. Bavia, Washington J.S.F. Rocha, Antônio C.Q. Tavares, Luciana L. Cardim, Biruk Alemayehu

113-126

01-11-2007

https://doi.org/10.4081/gh.2007.260

1345

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Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis

Prixia Nieto, John B. Malone, Maria E. Bavia

115-126

01-11-2006

https://doi.org/10.4081/gh.2006.286

1754

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Incidence of visceral leishmaniasis in the Vaishali district of Bihar, India: spatial patterns and role of inland water bodies

Gouri Sankar Bhunia, Shreekant Kesari, Nandini Chatterjee, Dilip Kumar Pal, Vijay Kumar, Alok Ranjan, Pradeep Das

205-215

01-05-2011

https://doi.org/10.4081/gh.2011.173

1572

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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

1090

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Supplementary Materials: 43

HTML: 10
Influence of topography on the endemicity of Kala-azar: a study based on remote sensing and geographical information system

Gouri S. Bhunia, Shreekant Kesari, Algarsamy Jeyaram, Vijay Kumar, Pradeep Das

155-165

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https://doi.org/10.4081/gh.2010.197

2082

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The spatial distribution of injuries in need of surgical intervention in Nepal

Shailvi Gupta, Thomas A. Groen, Barclay T. Stewart, Sunil Shrestha, David A. Spiegel, Benedict C. Nwomeh, Reinou S. Groen, Adam L. Kushner

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https://doi.org/10.4081/gh.2016.359

3304

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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

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https://doi.org/10.4081/gh.2016.415

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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

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2439

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Modelling of the distribution of Biomphalaria glabrata and Biomphalaria straminea in the metropolitan region of Recife, Pernambuco, Brazil

Verônica Santos Barbosa, Ricardo José de Paula Souza e Guimarães, Rodrigo Moraes Loyo, Constança SimÃµes Barbosa

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https://doi.org/10.4081/gh.2016.490

2695

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Monitoring techniques in the capture and adoption of dogs and cats

Jason Onell Ardila Galvis, Oswaldo Santos Baquero, Ricardo Augusto Dias, Fernando Ferreira, Evelyn Nestori Chiozzotto, José Henrique Hildebrand Grisi-Filho

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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

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Predicting frequency distribution and influence of sociodemographic and behavioral risk factors of Schistosoma mansoni infection and analysis of co-infection with intestinal parasites

Carla V.V. Rollemberg, Marília M.B.L. Silva, Karla C. Rollemberg, Fábio R. Amorim, Nayanna M.N. Lessa, Marcos D.S. Santos, Acácia M.B. Souza, Enaldo V. Melo, Roque P. Almeida, Ã‚ngela M. Silva, Guilherme L. Werneck, Mario A. Santos, José A.P. Almeida, Amélia R. Jesus

18-05-2015

https://doi.org/10.4081/gh.2015.303

4519

PDF: 1778

HTML: 1077

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Epidemiological aspects and spatial distribution of human and canine visceral leishmaniasis in an endemic area in northeastern Brazil

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

Spatial and spatiotemporal dynamics of visceral leishmaniasis in an endemic North-eastern region of Brazil

Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors

Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes

Use of soil moisture active passive satellite data and WorldClim 2.0 data to predict the potential distribution of visceral leishmaniasis and its vector Lutzomyia longipalpis in Sao Paulo and Bahia states, Brazil

Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran

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

Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran

Temperature-derived potential for the establishment of phlebotomine sandflies and visceral leishmaniasis in Germany

Identification of environmental parameters and risk mapping of visceral leishmaniasis in Ethiopia by using geographical information systems and a statistical approach

Risk assessment for canine leishmaniasis spreading in the north of Italy

Ecological study and risk mapping of visceral leishmaniasis in an endemic area of Iran based on a geographical information systems approach

Ecological study and risk mapping of leishmaniasis in an endemic area of Brazil based on a geographical information systems approach

Susceptibility mapping of visceral leishmaniasis based on fuzzy modelling and group decision-making methods

Application of spatio-temporal scan statistics for the detection of areas with increased risk for American visceral leishmaniasis in the state of Bahia, Brazil

Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis

Incidence of visceral leishmaniasis in the Vaishali district of Bihar, India: spatial patterns and role of inland water bodies

Intra-urban differences underlying leprosy spatial distribution in central Brazil: geospatial techniques as potential tools for surveillance

Influence of topography on the endemicity of Kala-azar: a study based on remote sensing and geographical information system

The spatial distribution of injuries in need of surgical intervention in Nepal

Modelling the presence of disease under spatial misalignment using Bayesian latent Gaussian models

Leptospirosis and its spatial and temporal relations with natural disasters in six municipalities of Santa Catarina, Brazil, from 2000 to 2016

Modelling of the distribution of Biomphalaria glabrata and Biomphalaria straminea in the metropolitan region of Recife, Pernambuco, Brazil

Monitoring techniques in the capture and adoption of dogs and cats

There is more to satellite imagery than meets the eye

Predicting frequency distribution and influence of sociodemographic and behavioral risk factors of Schistosoma mansoni infection and analysis of co-infection with intestinal parasites

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