HIV deathrate prediction by Gaidai multivariate risks assessment method

Abstract

Abstract Objectives HIV is a contagious disease with reportedly high transmissibility, being spread worldwide, with certain mortality, allegedly presenting a burden to public health worldwide. The main objective of this study was to determine excessive HIV death risks at any time within any region or country of interest. Study design Current study presents a novel multivariate public health system bio‐risk assessment approach that is particularly applicable to environmental multi‐regional, biological, and public health systems, being observed over a representative period of time, yielding reliable long‐term HIV deathrate assessment. Hence, the development of a new bio‐statistical approach, that is, population‐based, multicenter, and medical survey‐based. The expansion of extreme value statistics from the univariate to the bivariate situation meets with numerous challenges. Firstly, the univariate extreme value types theorem cannot be directly extended to the bivariate (2D) case, ‐ not to mention challenges with system dimensionality higher than 2D. Methods Existing bio‐statistical methods that process spatiotemporal clinical observations of multinational bio‐processes often do not have the advantage of efficiently dealing with high regional dimensionalities and complex nonlinear inter‐correlations between different national raw datasets. Hence, this study advocates the direct application of the novel bio‐statistical Gaidai method to a raw unfiltered clinical data set. Results This investigation described the successful application of a novel bio‐risk assessment approach, yielding reliable long‐term HIV mortality risk assessments. Conclusions The suggested risk assessment methodology may be utilized in various public bio and public health clinical applications based on available raw patient survey datasets.

Keywords

• AI
• AIDS
• edidemic outbreak
• HIV
• mathematical biology
• public‐health