Leptospirosis is a global zoonosis and environmental health problem because of its strong association with environmental factors. Although spatiotemporal statistics can estimate area-specific risk indicators, very few spatiotemporal analyses are done at ...
Javier Cortes-Ramirez +5 more
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Geographical systems are inherently hierarchical, involving potential cross-scale interactions, as well as spatial dependencies and heterogeneities at each level of the geographic hierarchy.
Dongyang Yang, Guanpeng Dong
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The coalescence of Human Immunodeficiency Virus (HIV), Tuberculosis (TB), and substance abuse in South Africa presents a multifaceted public health challenge.
Emmanuel Fundisi, Moses Asori
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Integrating spatial data science and bayesian INLA modeling for waste generation assessment in Bali
Solid waste management remains a pressing environmental concern in rapidly developing regions such as Bali, where population growth and tourism expansion intensify waste generation pressures.
Vijaya Isnaniawardhani +8 more
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Spatial variability and uncertainty associated with soil volumetric moisture content (SVMC) is crucial in moisture prediction accuracy, this paper sets out to address this point of SVMC by developing data-driven model.
Yujian Yang, Xueqin Tong
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Bayesian design and analysis of two-arm cluster randomised trials using assurance: Extension to binary outcomes and comparison of Markov chain Monte Carlo and Integrated Nested Laplace Approximations. [PDF]
Aloufi A +4 more
europepmc +1 more source
Spatiotemporal modeling of Under-Five Pneumonia (U-5P) risk in Ghana using Integrated Nested Laplace Approximations, 2018-2022. [PDF]
Asori M, Musah A, Ahiadorme M, Nakua E.
europepmc +1 more source
Bayesian spatio-temporal modeling of COVID-19 incidence in Algerian provinces using integrated nested Laplace approximations. [PDF]
Asri A.
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Parametric Bayesian modelling of tuberculosis mortality determinants and facility level heterogeneity effect using Gamma and Gaussian shared frailty techniques. [PDF]
Tamuzi JL +12 more
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KGR-SKATER: Spatially clustered kernel graph regression for counting processes. [PDF]
Wu J, Peters GW, Franks A.
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