Scholarlink

<p>This work presents a mathematical model for studying the transmission dynamics of HIV (Human Immunodeficiency Virus) and AIDS (Acquired Immune Deficiency Syndrome). The model incorporates both horizontal transmission (adult-to-adult infection through sexual contact or needle sharing) and vertical transmission (mother-to-child infection). This framework also accounts for important HIV/AIDS features like progression to treatment and disease stages. Through rigorous mathematical analysis, we derive key epidemiological indicators including the basic reproduction number (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\mathcal {R}_0\)</EquationSource> </InlineEquation>) and characterize the system’s equilibrium points. We establish conditions for disease persistence or eradication, supported by numerical simulations. Our results demonstrate an approach to model these complex transmission dynamics and highlight the critical role of <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\mathcal {R}_0\)</EquationSource> </InlineEquation> in providing valuable insights for public health control strategies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Mathematical Analysis of a HIV/AIDS Model Considering Vertical Transmission

  • 期刊论文

  • 发表日期：

    2025年9月26日

查看全文
  • Juan Felipe Pacazuca Santiago,
  • Cristian Camilo Espitia Morillo

摘要

This work presents a mathematical model for studying the transmission dynamics of HIV (Human Immunodeficiency Virus) and AIDS (Acquired Immune Deficiency Syndrome). The model incorporates both horizontal transmission (adult-to-adult infection through sexual contact or needle sharing) and vertical transmission (mother-to-child infection). This framework also accounts for important HIV/AIDS features like progression to treatment and disease stages. Through rigorous mathematical analysis, we derive key epidemiological indicators including the basic reproduction number ( \(\mathcal {R}_0\) ) and characterize the system’s equilibrium points. We establish conditions for disease persistence or eradication, supported by numerical simulations. Our results demonstrate an approach to model these complex transmission dynamics and highlight the critical role of \(\mathcal {R}_0\) in providing valuable insights for public health control strategies.