HIV Case Management using Agent-Based Modeling Approach Subject to Antiretroviral Therapy and Lifestyle Treatment Plan

HIV Case Management using Agent-Based Modeling Approach Subject to Antiretroviral Therapy and Lifestyle Treatment Plan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article HIV Case Management using Agent-Based Modeling Approach Subject to Antiretroviral Therapy and Lifestyle Treatment Plan Akintayo Emmanuel Akinsunmade, Anthony Azagbaekwue, Friday Gabriel Emunefe, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7642060/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract This study presents a spatially explicit agent-based model that simulates the interactions between T-cells, viruses, and therapeutic agents in HIV case management. The model framework simulates individual biological entities as discrete agents on a two-dimensional grid to investigate the effects of antiretroviral drugs and lifestyle factors. To validate its accuracy, the model was simulated across three distinct clinical stages of HIV infection and a comparative analysis of four intervention scenarios revealed that while drug therapy is essential for immediate viral suppression, the combination of drugs and lifestyle consistently produces favorably outcomes. Most notably, the study found that in the advanced stage of the disease, this combination therapy was capable of completely eliminating the resistant virus population. The findings of this study demonstrate that a holistic approach to HIV case management, integrating both pharmacological and lifestyle interventions, provides a crucial synergistic effect that promotes long-term immune health and is paramount in preventing the emergence of drug resistance. The agent-based model presented here serves as a powerful framework for future exploration of optimal, personalized treatment strategies. Biological sciences/Computational biology and bioinformatics Health sciences/Diseases Biological sciences/Drug discovery Physical sciences/Mathematics and computing Agent Based Modeling HIV Dynamics Mathematical Biology Stochastic Simulation Antiretroviral Therapy Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 02 Dec, 2025 Reviews received at journal 16 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviewers invited by journal 03 Nov, 2025 Editor invited by journal 26 Sep, 2025 Editor assigned by journal 20 Sep, 2025 Submission checks completed at journal 18 Sep, 2025 First submitted to journal 17 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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