用 Gaidai 多变量风险评估法预测艾滋病毒死亡率

IF 3.1 4区 医学 Q3 IMMUNOLOGY Immunity, Inflammation and Disease Pub Date : 2024-10-16 DOI:10.1002/iid3.70040
Oleg Gaidai
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引用次数: 0

摘要

目的 艾滋病毒是一种传染性疾病,据报道具有很高的传播性,在全球范围内传播,并有一定的 死亡率,据称给全世界的公共卫生造成了负担。本研究的主要目的是确定在任何相关地区或国家的任何时间,艾滋病毒的死亡风险是否过高。 研究设计 当前的研究提出了一种新型的多变量公共卫生系统生物风险评估方法,该方法特别适用于多地区、生物和公共卫生系统环境,可在具有代表性的时间段内进行观察,从而得出可靠的长期艾滋病毒死亡率评估结果。因此,需要开发一种新的生物统计方法,即基于人群、多中心和医疗调查的方法。将极值统计从单变量扩展到双变量会遇到许多挑战。首先,单变量极值类型定理无法直接扩展到二维(2D)情况,更不用说系统维度高于 2D 的挑战了。 处理跨国生物过程时空临床观测数据的现有生物统计方法往往不具备高效处理高区域维度和不同国家原始数据集之间复杂非线性相互关系的优势。因此,本研究主张将新型生物统计 Gaidai 方法直接应用于未经过滤的原始临床数据集。 结果 这项调查描述了一种新型生物风险评估方法的成功应用,产生了可靠的艾滋病长期死亡风险评估结果。 结论 基于现有的原始患者调查数据集,建议的风险评估方法可用于各种公共生物和公共卫生临床应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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HIV deathrate prediction by Gaidai multivariate risks assessment method

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.

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来源期刊
Immunity, Inflammation and Disease
Immunity, Inflammation and Disease Medicine-Immunology and Allergy
CiteScore
3.60
自引率
0.00%
发文量
146
审稿时长
8 weeks
期刊介绍: Immunity, Inflammation and Disease is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research across the broad field of immunology. Immunity, Inflammation and Disease gives rapid consideration to papers in all areas of clinical and basic research. The journal is indexed in Medline and the Science Citation Index Expanded (part of Web of Science), among others. It welcomes original work that enhances the understanding of immunology in areas including: • cellular and molecular immunology • clinical immunology • allergy • immunochemistry • immunogenetics • immune signalling • immune development • imaging • mathematical modelling • autoimmunity • transplantation immunology • cancer immunology
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