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Design/Methodology/Approach: The study relies on publicly available GDP and adult HIV/AIDS prevalence data and combines machine learning with statistical regression models. Findings: Results show that the relationship between nominal GDP and adult HIV/AIDS prevalence is negative and statistically significant, with the Ensemble Boosted Trees model providing the best fit. Practical implications: Modeling approaches support estimation of adult prevalence using GDP signals.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/investigating-the-relationship-between-nominal-gdp-and-adult-hivaids-prevalence-using-machine-learning/290513/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/investigating-the-relationship-between-nominal-gdp-and-adult-hivaids-prevalence-using-machine-learning/290513.png","ImageObject",300,407,{"name":92,"@type":93},"Noah","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-21","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the purpose of the article?","Question",{"text":112,"@type":113},"The article aims to analyze and model the relationship between nominal GDP and adult HIV/AIDS prevalence using machine learning methods.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What data and methods are used in the study?",{"text":117,"@type":113},"The study uses publicly available GDP and adult HIV/AIDS prevalence data and applies machine learning models together with statistical regression approaches.",{"name":119,"@type":110,"acceptedAnswer":120},"What do the findings conclude about the GDP–HIV/AIDS relationship?",{"text":121,"@type":113},"The relationship is negative and statistically significant, and the Ensemble Boosted Trees model shows the best fit based on indicators comparing actual and predicted values.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},290513,1789641903,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":44,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":143,"preview_page_count":4},8796095462418,"https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780","European Research Studies Journal Volume XXVIII, Issue 4, 2025  \npp. 1786-1794  \nInvestigating the Relationship Between Nominal GDP and Adult HIV/AIDS Prevalence Using Machine Learning  \nMethods  \nSubmitted 19/10/25, 1st revision 14/11/25, 2nd revision 26/11/25, accepted 15/12/25  \nAnna Landowska 1, Marek Landowski23  \nAbstract:  \nPurpose: The aim of this article is to analyze and model the relationship between nominal gross domestic product (GDP) and adult HIV/AIDS prevalence by machine learning methods.  \nDesign/Methodology/Approach: The study utilized publicly available GDP and adult HIV/AIDS prevalence data. To achieve the research objective, machine learning and statistical regression models were used.  \nFindings: Using machine learning models and methods, it is possible to model the relationship between nominal GDP and adult HIV/AIDS prevalence. Selected indicators examining the differences between actual and predicted values indicated the best fit for the Ensemble Boosted Trees model. The relationship between nominal GDP and adult HIV/AIDS prevalence is negative and statistically significant.  \nPractical Implications: Possibilities of modeling adult HIV/AIDS prevalence and nominal GDP using machine learning models and methods.  \nOriginality/Value: This article makes a significant contribution to the development of knowledge on the relationship between nominal GDP and adult HIV/AIDS prevalence. Furthermore, it demonstrates the feasibility of using machine learning methods to model this relationship.  \nKeywords: Nominal gross domestic product, HIV/AIDS prevalence, regression models.  \nJEL codes: C1, C3, E44, C8.  \nPaper type: Research article.  \nResearch funding: Co-financed by the Minister of Science under the “Regional Excellence Initiative”.  \n1Ph.D., University of Szczecin, Institute of Spatial Management and Socio-Economic Geography, Poland, e-mail: [anna.landowska@usz.edu.pl](anna.landowska@usz.edu.pl);  \n2D.Sc. Ph.D., Maritime University of Szczecin, Faculty of Computer Science and Telecommunications, Poland, [e-mail:](e-mail: m.landowski@pm.szczecin.pl)[ ](e-mail: m.landowski@pm.szczecin.pl)[m.landowski@pm.szczecin.pl](e-mail: m.landowski@pm.szczecin.pl)  \n3D.Sc. Ph.D., Pomeranian Medical University in Szczecin, Independent Research and Biostatistics Laboratory, Department of Social Medicine, Poland, e-mail:  \n[marek.landowski@pum.edu.pl](marek.landowski@pum.edu.pl)  \n1. Introduction  \nThe article presents research on the relationship between nominal gross domestic product (GDP) and adult HIV/AIDS prevalence. This topic remains relevant due to the continued rise in HIV infections worldwide. Many scientific papers deal with the impact of the HIV/AIDS epidemic on economic factors. In paper (Bidzha et al., 2024), the authors analyze data covering the years 1995–2019 to examine the impact of antiretroviral treatment on the relationship between HIV/AIDS and GDP in South Africa.  \nThey use various econometric approaches (linear and nonlinear) . They also examine the relationship between HIV/AIDS and GDP by gender. The analysis and estimation of the impact of HIV/AIDS on GDP in the WHO African region is presented in paper (Kirigia et al., 2002) . The analysis was carried out using an econometric model and data from 45–46 countries. Article (Levi et al., 2018) compares the results of implementing preventive measures such as the HIV treatment cascade (90-90-90 target) with GDP, corruption, and conflict in selected countries.  \nIn the paper (Essig et al., 2015), the authors analyze African countries based on the impact of the growth of HIV infections on the GDP per capita. They assume that the increase in infections negatively impacts human capital, and consequently, acountry's GDP per capita.  \nThe broader impact of the HIV epidemic was examined in paper (Jones-Smith et al., 2007) . This paper analyzed the impact of the HIV epidemic on global economic development, taking into account data from 2003. In the paper (Amiri et ","cbCainjW3Z5sKAOi","https://ap.wps.com/l/cbCainjW3Z5sKAOi","pdf",447953,"English","# Introduction\n# Data and Methods\n# Results and Model Assessment\n# Summary","[{\"question\":\"What is the purpose of the article?\",\"answer\":\"The article aims to analyze and model the relationship between nominal GDP and adult HIV/AIDS prevalence using machine learning methods.\"},{\"question\":\"What data and methods are used in the study?\",\"answer\":\"The study uses publicly available GDP and adult HIV/AIDS prevalence data and applies machine learning models together with statistical regression approaches.\"},{\"question\":\"What do the findings conclude about the GDP–HIV/AIDS relationship?\",\"answer\":\"The relationship is negative and statistically significant, and the Ensemble Boosted Trees model shows the best fit based on indicators comparing actual and predicted values.\"}]","Investigating the Relationship Between Nominal GDP and Adult HIV/AIDS Prevalence Using Machine Learning | PDF",23]