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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Methodological framework for assessing malaria risk associated with climate change in Côte d’Ivoire

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Examination of multidimensional geographic mobility and sexual behaviour among Black cisgender sexually minoritized men in Chicago

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https://doi.org/10.4081/gh.2024.1273

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Global Mpox spread due to increased air travel

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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

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https://doi.org/10.4081/gh.2025.1277

1047

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Supplementary materials: 118

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CutL: an alternative to Kulldorff's scan statistics for cluster detection with a specified cut-off level

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Public domain small-area cancer incidence data for New York State, 2005-2009

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A geospatial database management system for the collection of medicinal plants

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https://doi.org/10.4081/gh.2021.998

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Province clustering based on the percentage of communicable disease using the BCBimax biclustering algorithm

Muhammad Nur Aidi, Cynthia Wulandari, Sachnaz Desta Oktarina, Taufiqur Rakhim Aditra, Fitrah Ernawati, Efriwati Efriwati, Nunung Nurjanah, Rika Rachmawati, Elisa Diana Julianti, Dian Sundari, Fifi Retiaty, Aya Yuriestia Arifin, Rita Marleta Dewi, Nazarina Nazaruddin, Salimar Salimar, Noviati Fuada, Yekti Widodo, Budi Setyawati, Nuzuliyati Nurhidayati, Sudikno Sudikno, Irlina Raswanti Irawan, Widoretno Widoretno

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Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

Suparat Tappo, Wongsa Laohasiriwong, Nattapong Puttanapong

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Spatial correlates of COVID-19 first wave across continental Portugal

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Spatial comparison of London’s three waves of Spanish flu

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Methodological framework for assessing malaria risk associated with climate change in Côte d’Ivoire

Examination of multidimensional geographic mobility and sexual behaviour among Black cisgender sexually minoritized men in Chicago

Global Mpox spread due to increased air travel

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

CutL: an alternative to Kulldorff's scan statistics for cluster detection with a specified cut-off level

Public domain small-area cancer incidence data for New York State, 2005-2009

A geospatial database management system for the collection of medicinal plants

Province clustering based on the percentage of communicable disease using the BCBimax biclustering algorithm

Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand

Spatial correlates of COVID-19 first wave across continental Portugal

Spatial comparison of London’s three waves of Spanish flu

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