Model analysis for an HIV infectious disease using elasticity and sensitivity techniques
The human immunodeficiency virus (HIV) is an infection that mainly impacts CD4+ T cells inside the immune system, causing a gradual decline in immunological function. If untreated, this can lead to acquired immunodeficiency syndrome (AIDS), a disorder in which the body becomes extremely susceptible...
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AIMS Press
2024-07-01
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| Series: | AIMS Bioengineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/bioeng.2024015 |
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| author | Honar J. Hamad Sarbaz H. A. Khoshnaw Muhammad Shahzad |
| author_facet | Honar J. Hamad Sarbaz H. A. Khoshnaw Muhammad Shahzad |
| author_sort | Honar J. Hamad |
| collection | DOAJ |
| description | The human immunodeficiency virus (HIV) is an infection that mainly impacts CD4+ T cells inside the immune system, causing a gradual decline in immunological function. If untreated, this can lead to acquired immunodeficiency syndrome (AIDS), a disorder in which the body becomes extremely susceptible to opportunistic infections due to a severely compromised immune system. This paper presents a rigorous analysis of a mathematical model that describes the dynamics of HIV infectious disease transmission. There are some key outputs of the study presented. First, we derive the basic reproduction number (R0) which determines the threshold for disease persistence. Then, we analyze the stability of the disease-free and endemic equilibria. After that, we perform a sensitivity analysis to identify the key parameters that influence the dynamics of the system. The basic reproduction number (R0) is calculated using the next generation matrix approach. The stability of the disease-free and endemic equilibria is investigated to understand the long-term behavior of the model. A sensitivity analysis is conducted to determine which model parameters have the greatest impact on the spread of HIV. The model includes a class of nonlinear ordinary differential equations, and has both infection-free and endemic infection equilibrium points. The elasticity of R0 related to the model parameters is determined, and the local sensitivities between the model variables and parameters are numerically evaluated using non-normalization, half-normalization, and full-normalization techniques. The numerical results show that there are different sensitivities between model compartments and model parameters. The findings offer valuable insights for designing effective control strategies and optimizing interventions aimed at curbing the spread of HIV. |
| format | Article |
| id | doaj-art-dc30621d87614d438a70778a2ee8b40e |
| institution | Kabale University |
| issn | 2375-1495 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Bioengineering |
| spelling | doaj-art-dc30621d87614d438a70778a2ee8b40e2025-01-24T01:27:30ZengAIMS PressAIMS Bioengineering2375-14952024-07-0111328130010.3934/bioeng.2024015Model analysis for an HIV infectious disease using elasticity and sensitivity techniquesHonar J. Hamad0Sarbaz H. A. Khoshnaw1Muhammad Shahzad2Department of Mathematics, Faculty of Science, Soran University, Soran, Erbil, IRAQDepartment of Mathematics, University of Raparin, Ranya, Sulaimani, IRAQDepartment of Mathematics and Statistics, The University Haripur, Haripur, PakistanThe human immunodeficiency virus (HIV) is an infection that mainly impacts CD4+ T cells inside the immune system, causing a gradual decline in immunological function. If untreated, this can lead to acquired immunodeficiency syndrome (AIDS), a disorder in which the body becomes extremely susceptible to opportunistic infections due to a severely compromised immune system. This paper presents a rigorous analysis of a mathematical model that describes the dynamics of HIV infectious disease transmission. There are some key outputs of the study presented. First, we derive the basic reproduction number (R0) which determines the threshold for disease persistence. Then, we analyze the stability of the disease-free and endemic equilibria. After that, we perform a sensitivity analysis to identify the key parameters that influence the dynamics of the system. The basic reproduction number (R0) is calculated using the next generation matrix approach. The stability of the disease-free and endemic equilibria is investigated to understand the long-term behavior of the model. A sensitivity analysis is conducted to determine which model parameters have the greatest impact on the spread of HIV. The model includes a class of nonlinear ordinary differential equations, and has both infection-free and endemic infection equilibrium points. The elasticity of R0 related to the model parameters is determined, and the local sensitivities between the model variables and parameters are numerically evaluated using non-normalization, half-normalization, and full-normalization techniques. The numerical results show that there are different sensitivities between model compartments and model parameters. The findings offer valuable insights for designing effective control strategies and optimizing interventions aimed at curbing the spread of HIV.https://www.aimspress.com/article/doi/10.3934/bioeng.2024015hiv infectiousmathematical modelingsensitivity analysiscomputational simulationsstability analysisbasic reproduction number |
| spellingShingle | Honar J. Hamad Sarbaz H. A. Khoshnaw Muhammad Shahzad Model analysis for an HIV infectious disease using elasticity and sensitivity techniques AIMS Bioengineering hiv infectious mathematical modeling sensitivity analysis computational simulations stability analysis basic reproduction number |
| title | Model analysis for an HIV infectious disease using elasticity and sensitivity techniques |
| title_full | Model analysis for an HIV infectious disease using elasticity and sensitivity techniques |
| title_fullStr | Model analysis for an HIV infectious disease using elasticity and sensitivity techniques |
| title_full_unstemmed | Model analysis for an HIV infectious disease using elasticity and sensitivity techniques |
| title_short | Model analysis for an HIV infectious disease using elasticity and sensitivity techniques |
| title_sort | model analysis for an hiv infectious disease using elasticity and sensitivity techniques |
| topic | hiv infectious mathematical modeling sensitivity analysis computational simulations stability analysis basic reproduction number |
| url | https://www.aimspress.com/article/doi/10.3934/bioeng.2024015 |
| work_keys_str_mv | AT honarjhamad modelanalysisforanhivinfectiousdiseaseusingelasticityandsensitivitytechniques AT sarbazhakhoshnaw modelanalysisforanhivinfectiousdiseaseusingelasticityandsensitivitytechniques AT muhammadshahzad modelanalysisforanhivinfectiousdiseaseusingelasticityandsensitivitytechniques |