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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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

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3685

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Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

Yazmin Alcala-Canto, Juan Antonio Figueroa-Castillo, Froylán Ibarra-Velarde, Yolanda Vera-Montenegro, María Eugenia Cervantes-Valencia, Abdelfattah Z.M. Salem, Jorge Alfredo Cuéllar-Ordaz

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4155

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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

25-11-2016

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2696

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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

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Zoning the territory of the Republic of Kazakhstan as to the risk of rabies among various categories of animals

Sarsenbay K. Abdrakhmanov, Akhmetzhan A. Sultanov, Kanatzhan K. Beisembayev, Fedor I. Korennoy, Dosym B. Ðšushubaev, Ablaikhan S. ÐšÐ°dyrov

31-05-2016

https://doi.org/10.4081/gh.2016.429

2534

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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

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1473

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Appendix: 95

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Analytical report of the 2016 dengue outbreak in CÃ³rdoba city, Argentina

Camilo Rotela, Laura Lopez, María Frías Céspedes, Gabriela Barbas, Andrés Lighezzolo, Ximena Porcasi, Mario A. Lanfri, Carlos M. Scavuzzo, David E. Gorla

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https://doi.org/10.4081/gh.2017.564

3112

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Climate change and species distribution: possible scenarios for thermophilic ticks in Romania

Cristian DomÈ™a, Attila D. Sándor, Andrei D. Mihalca

31-05-2016

https://doi.org/10.4081/gh.2016.421

2700

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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

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Potential for spread of the white-nose fungus (Pseudogymnoascus destructans) in the Americas: use of Maxent and NicheA to assure strict model transference

Luis E. Escobar, Andrés Lira-Noriega, Gonzalo Medina-Vogel, A. Townsend Peterson

221-229

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Application of geo-spatial technology in schistosomiasis modelling in Africa: a review

Tawanda Manyangadze, Moses John Chimbari, Michael Gebreslasie, Samson Mukaratirwa

04-11-2015

https://doi.org/10.4081/gh.2015.326

4003

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Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

Manuel O. Espinosa, Francisco Polop, Camilo H. Rotela, Marcelo Abril, Carlos M. Scavuzzo

21-11-2016

https://doi.org/10.4081/gh.2016.471

3635

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Ecological niche model of Phlebotomus perniciosus, the main vector of canine leishmaniasis in north-eastern Italy

Manuela Signorini, Rudi Cassini, Michele Drigo, Antonio Frangipane di Regalbono, Mario Pietrobelli, Fabrizio Montarsi, Anna-Sofie Stensgaard

193-201

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https://doi.org/10.4081/gh.2014.16

3374

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Impacts of sample ratio and size on the performance of random forest model to predict the potential distribution of snail habitats

Yuanhua Liu, Jun Zhang, Michael P. Ward, Wei Tu, Lili Yu, Jin Shi, Yi Hu, Fenghua Gao, Zhiguo Cao, Zhijie Zhang

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https://doi.org/10.4081/gh.2023.1151

1730

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Supplementary Materials: 69

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Environmental and socio-economic risk modelling for Chagas disease in Bolivia

Paula Mischler, Michael Kearney, Jennifer C. McCarroll, Ronaldo G.C. Scholte, Penelope Vounatsou, John B. Malone

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An update on distribution models for Rhipicephalus microplus in West Africa

Eva M. De Clercq, Agustin Estrada-Peña, Safiou Adehan, Maxime Madder, Sophie O. Vanwambeke

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Spatial-temporal risk factors in the occurrence of rabies in Mexico

Reyna Ortega-Sánchez, Isabel Bárcenas-Reyes, Jesús Luna-Cozar, Edith Rojas-Anaya, José Quintín Cuador-Gil, Germinal Jorge Cantó-Alarcón, Nerina Veyna-Salazar, Sara González-Ruiz, Feliciano Milián-Suazo

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3746

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Influence of landscape factors and management decisions on spatial and temporal patterns of the transmission of chronic wasting disease in white-tailed deer

Marilyn O'Hara Ruiz, Amy C. Kelly, William M. Brown, Jan E. Novakofski, Nohra E. Mateus-Pinilla

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Climate-based risk models for Fasciola hepatica in Colombia

Natalia Valencia-Lòpez, John B. Malone, Catalina Gòmez Carmona, Luz E. Velásquez

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https://doi.org/10.4081/gh.2012.125

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There is more to satellite imagery than meets the eye

Robert Bergquist, John B. Malone

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https://doi.org/10.4081/gh.2022.1106

2239

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Modeling the distribution of Culex tritaeniorhynchus to predict Japanese encephalitis distribution in the Republic of Korea

Penny Masuoka, Terry A. Klein, Heung-Chul Kim, David M. Claborn, Nicole Achee, Richard Andre, Judith Chamberlin, Jennifer Small, Assaf Anyamba, Dong-Kyu Lee, Suk H. Yi, Michael Sardelis, Young-Ran Ju, John Grieco

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Modelling spatial distribution of snails transmitting parasitic worms with importance to human and animal health and analysis of distributional changes in relation to climate

Ulrik B. Pedersen, Nicholas Midzi, Takafira Mduluza, White Soko, Anna-Sofie Stensgaard, Birgitte J. Vennervald, Samson Mukaratirwa, Thomas K. Kristensen

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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

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https://doi.org/10.4081/gh.2025.1319

1433

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Climate and the distribution of vector-borne diseases: what's in store?

Robert Bergquist

08-05-2017

https://doi.org/10.4081/gh.2017.549

3106

PDF: 1162

HTML: 841

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Predicting the spatial distribution of Biomphalaria straminea, a potential intermediate host for Schistosoma mansoni, in China

Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

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

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

Zoning the territory of the Republic of Kazakhstan as to the risk of rabies among various categories of animals

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

Analytical report of the 2016 dengue outbreak in CÃ³rdoba city, Argentina

Climate change and species distribution: possible scenarios for thermophilic ticks in Romania

Combining process-based and correlative models improves predictions of climate change effects on Schistosoma mansoni transmission in eastern Africa

Potential for spread of the white-nose fungus (Pseudogymnoascus destructans) in the Americas: use of Maxent and NicheA to assure strict model transference

Application of geo-spatial technology in schistosomiasis modelling in Africa: a review

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

Ecological niche model of Phlebotomus perniciosus, the main vector of canine leishmaniasis in north-eastern Italy

Impacts of sample ratio and size on the performance of random forest model to predict the potential distribution of snail habitats

Environmental and socio-economic risk modelling for Chagas disease in Bolivia

An update on distribution models for Rhipicephalus microplus in West Africa

Spatial-temporal risk factors in the occurrence of rabies in Mexico

Influence of landscape factors and management decisions on spatial and temporal patterns of the transmission of chronic wasting disease in white-tailed deer

Climate-based risk models for Fasciola hepatica in Colombia

There is more to satellite imagery than meets the eye

Modeling the distribution of Culex tritaeniorhynchus to predict Japanese encephalitis distribution in the Republic of Korea

Modelling spatial distribution of snails transmitting parasitic worms with importance to human and animal health and analysis of distributional changes in relation to climate

Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning

Climate and the distribution of vector-borne diseases: what's in store?

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