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Hot-spots of HIV infection in Cameroon: a spatial analysis based on Demographic and Health Surveys data | BMC Infectious Diseases - Vimarsana News

Hot-spots of HIV infection in Cameroon: a spatial analysis based on Demographic and Health Surveys data | BMC Infectious Diseases

The Human Immunodeficiency Virus(HIV) infection prevalence in Cameroon has decreased from $$5.28\%$$ in 2004 to $$2.8\%$$ in 2018. However, this decrease in prevalence does not show disparities especially in terms of spatial or geographical pattern. Efficient control and fight against HIV infection may require targeting hotspot areas. This study aims at presenting a cartography of HIV infection situation in Cameroon using the 2004, 2011 and 2018 Demographic and Health Survey data, and investigating whether there exist spatial patterns of the disease, may help to detect hot-spots. HIV biomarker...

"Spherical Poisson point process intensity function modeling and estima" by Tin Lok James Ng and Andrew Zammit-Mangion - Vimarsana News

"Spherical Poisson point process intensity function modeling and estima" by Tin Lok James Ng and Andrew Zammit-Mangion

Recent years have seen an increased interest in the application of methods and techniques commonly associated with machine learning and artificial intelligence to spatial statistics. Here, in a celebration of the ten-year anniversary of the journal Spatial Statistics, we bring together normalizing flows, commonly used for density function estimation in machine learning, and spherical point processes, a topic of particular interest to the journal's readership, to present a new approach for modeling non-homogeneous Poisson process intensity functions on the sphere. The central idea of this ...

Source: uow.edu.au
"Deep Compositional Spatial Models" by Andrew Zammit-Mangion, Tin Lok James Ng et al. - Vimarsana News

"Deep Compositional Spatial Models" by Andrew Zammit-Mangion, Tin Lok James Ng et al.

Abstract Spatial processes with nonstationary and anisotropic covariance structure are often used when modeling, analyzing, and predicting complex environmental phenomena. Such processes may often be expressed as ones that have stationary and isotropic covariance structure on a warped spatial domain. However, the warping function is generally difficult to fit and not constrained to be injective, often resulting in “space-folding.” Here, we propose modeling an injective warping function through a composition of multiple elemental injective functions in a deep-learning framework. We conside...

Source: uow.edu.au
"A few statistical principles for data science" by Noel Cressie - Vimarsana News

"A few statistical principles for data science" by Noel Cressie

Abstract In any other circumstance, it might make sense to define the extent of the terrain (Data Science) first, and then locate and describe the landmarks (Principles). But this data revolution we are experiencing defies a cadastral survey. Areas are continually being annexed into Data Science. For example, biometrics was traditionally statistics for agriculture in all its forms but now, in Data Science, it means the study of characteristics that can be used to identify an individual. Examples of non-intrusive measurements include height, weight, fingerprints, retina scan, voice, photograph...

Source: uow.edu.au