Modeling gonorrhea and HIV coinfection with predictive analytics for disability and mortality risks

In this article, a model is developed to depict the dynamics of gonorrhea and human immunodeficiency virus coinfection with disability and mortality risks. Estimating the parameter values and validating the model are done using real-world data on cases of gonorrhea. The properties of solutions, such as boundedness and positivity, uniqueness and existence are investigated. The basic reproduction number is calculated using the next-generation matrix. The stability of Gonorrhea-Free and Present Equilibrium states is also analyzed. The Lyapunov function is used to verify global stability at the Gonorrhea-Free Equilibrium, while the graph-theoretic approach is employed to analyze global stability at the Gonorrhea-Present Equilibrium. Sensitivity indices are calculated to identify the significant parameters transmitting the disease. The Adams Bashforth predictor-corrector scheme is used to simulate the behavior of all classes individually and in combination with the different classes, considering the effect of fractional order ϕ. The relation between various parameters and the basic reproduction number is analyzed and portrayed. The limitations on the values of the parameters to ensure the basic reproduction number is below one are also discussed. This model incorporates aspects that cause disabilities and mortality from both gonorrhea and HIV and estimates the contribution of both to the long-term neurological and reproductive disabilities. The simulation results demonstrate how the course of disabilities is altered when these aspects are modified. This work highlights the importance of early diagnosis and disability prevention efforts.

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Publication Details

Journal
Scientific Reports
Published
2025-09-26
DOI
https://doi.org/10.1038/s41598-025-16601-5
Citations
2
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
3.76

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article

Modeling gonorrhea and HIV coinfection with predictive analytics for disability and mortality risks

Basim M. Makhdoum, Aziz Ullah Awan, Jeevan Kafle, Kamel Guedri et al.
2 citations
Scientific Reports
Mathematical and Theoretical Epidemiology and Ecology Models
3.76
article

Modeling gonorrhea and HIV coinfection with predictive analytics for disability and mortality risks

Basim M. Makhdoum, Aziz Ullah Awan, Jeevan Kafle, Kamel Guedri, Hatoon A. Niyazi, Yasir Ramzan
article en
2 citations

Abstract

In this article, a model is developed to depict the dynamics of gonorrhea and human immunodeficiency virus coinfection with disability and mortality risks. Estimating the parameter values and validating the model are done using real-world data on cases of gonorrhea. The properties of solutions, such as boundedness and positivity, uniqueness and existence are investigated. The basic reproduction number is calculated using the next-generation matrix. The stability of Gonorrhea-Free and Present Equilibrium states is also analyzed. The Lyapunov function is used to verify global stability at the Gonorrhea-Free Equilibrium, while the graph-theoretic approach is employed to analyze global stability at the Gonorrhea-Present Equilibrium. Sensitivity indices are calculated to identify the significant parameters transmitting the disease. The Adams Bashforth predictor-corrector scheme is used to simulate the behavior of all classes individually and in combination with the different classes, considering the effect of fractional order ϕ. The relation between various parameters and the basic reproduction number is analyzed and portrayed. The limitations on the values of the parameters to ensure the basic reproduction number is below one are also discussed. This model incorporates aspects that cause disabilities and mortality from both gonorrhea and HIV and estimates the contribution of both to the long-term neurological and reproductive disabilities. The simulation results demonstrate how the course of disabilities is altered when these aspects are modified. This work highlights the importance of early diagnosis and disability prevention efforts.

Scientific ReportsVol. 15(1)
Khazar University (AZ), Shanghai University (CN), University of the Punjab (PK), King Abdulaziz University (SA), Nepal Development Research Institute (NP), King Salman Center for Disability Research (SA), King Abdulaziz Hospital (SA), University of Business and Technology (SA), Kathmandu University (NP)
King Salman Center for Disability Research
Openalex Percentile: Top 6%
Mathematical and Theoretical Epidemiology and Ecology Models
3.76
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