{"title":"用 Gaidai 多变量风险评估法预测艾滋病毒死亡率","authors":"Oleg Gaidai","doi":"10.1002/iid3.70040","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objectives</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Study design</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>This investigation described the successful application of a novel bio-risk assessment approach, yielding reliable long-term HIV mortality risk assessments.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The suggested risk assessment methodology may be utilized in various public bio and public health clinical applications based on available raw patient survey datasets.</p>\n </section>\n </div>","PeriodicalId":13289,"journal":{"name":"Immunity, Inflammation and Disease","volume":"12 10","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/iid3.70040","citationCount":"0","resultStr":"{\"title\":\"HIV deathrate prediction by Gaidai multivariate risks assessment method\",\"authors\":\"Oleg Gaidai\",\"doi\":\"10.1002/iid3.70040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objectives</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Study design</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>This investigation described the successful application of a novel bio-risk assessment approach, yielding reliable long-term HIV mortality risk assessments.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>The suggested risk assessment methodology may be utilized in various public bio and public health clinical applications based on available raw patient survey datasets.</p>\\n </section>\\n </div>\",\"PeriodicalId\":13289,\"journal\":{\"name\":\"Immunity, Inflammation and Disease\",\"volume\":\"12 10\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/iid3.70040\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Immunity, Inflammation and Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/iid3.70040\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Immunity, Inflammation and Disease","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/iid3.70040","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
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.
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