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  Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda

  Gilbert Nduwayezu, Pengxiang Zhao, Clarisse Kagoyire, Lina Eklund, Jean Pierre Bizimana, Petter Pilesjo, Ali Mansourian

  25-05-2023

  https://doi.org/10.4081/gh.2023.1184

  3449

  PDF: 1770

  HTML: 218
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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

  1864

  PDF: 991

  Appendix: 153

  HTML: 84
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  Spatio-temporal outbreaks of campylobacteriosis and the role of fresh-milk vending machines in the Czech Republic: A methodological study

  Lukáš Marek, Vít Pászto

  08-11-2017

  https://doi.org/10.4081/gh.2017.572

  2897

  PDF: 848

  HTML: 852
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  Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches

  Farah Kristiani, I Gede Nyoman Mindra Jaya, Robyn Irawan, Inanta Maria Priscilia

  02-02-2026

  https://doi.org/10.4081/gh.2026.1461

  719

  PDF: 414

  Supplementary materials: 61

  HTML: 16
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  The spatial distribution of interleukin-4 (IL-4) reference values in China based on a back propagation (BP) neural network

  Zhao Rong Huang, Miao Ge, Xin Rui Pang, Pu Song, Congxia Wang

  13-09-2023

  https://doi.org/10.4081/gh.2023.1197

  1411

  PDF: 624

  HTML: 27