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Mathematical analysis of HPV and gonorrhea co-infection model with optimal control strategies for effective intervention.

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Title: Mathematical analysis of HPV and gonorrhea co-infection model with optimal control strategies for effective intervention.
Authors: Arunkumar, M.1,2 (AUTHOR) arunkumarmak001@gmail.com, Jose, Sayooj Aby1,3,4 (AUTHOR) sayooj@snu.ac.kr, Murugesan, K.1 (AUTHOR) murugu@nitt.edu, Jirawattanapanit, Anuwat5 (AUTHOR) anuwat.j@pkru.ac.th
Source: Mathematics & Computers in Simulation. Nov2026, Vol. 249, p1076-1113. 38p.
Subjects: Human papillomavirus, Gonorrhea, Vaccination, Public health, Infectious disease transmission, Mixed infections, Optimal control theory, Mathematical models
Geographic Terms: United States
Abstract: Human papillomavirus (HPV) and gonorrhea are sexually transmitted infections that pose significant challenges to global public health. This study introduces a novel mathematical model with eleven compartments to capture the dynamics between HPV and gonorrhea co-infection. We explore the basic analytical properties such as nonnegativity and boundedness of the solutions, stability analysis of disease-equilibrium point, existence of endemic equilibrium points for the co-infection model. The basic reproduction number is derived using next generation matrix method. Also, the model is calibrated and validated using real-world gonorrhea infection data from 2012 to 2022, collected in the United States to ensure its accuracy and relevance to current epidemiological trends. Sensitivity analysis is carried out to identify key parameters that influence the basic reproduction number. The findings reveal that reducing contact rates, increasing gonorrhea treatment rates, enhancing HPV vaccine efficacy, and accelerating HPV vaccination efforts substantially lower the disease transmission. Additionally, the effective contact rates of HPV and gonorrhea have been projected until 2062, providing valuable insights into the significance of reducing these infections. To further curb the transmission of these infections, three time-dependent control variables such as promoting safe sex practices, implementing a time-varying HPV vaccination rate and enhancing gonorrhea treatment are incorporated into the model. We then define an optimal control problem to minimize the total number of infected individuals and examine the existence of optimal control along with the necessary conditions for the optimality system. Numerical simulations are carried out to illustrate the practical implications of the model and the effectiveness of the proposed control strategies. The obtained results suggest that the simultaneous implementation of all control measures can significantly lower both single and co-infection rates, leading to improved public health outcomes. • A deterministic model is proposed to study the co-infection of HPV and gonorrhea. • Stability of the disease-free equilibrium point is thoroughly analyzed. • The model is validated using reported gonorrhea cases from the United States. • An optimal control problem is formulated to reduce the overall infected population. • Combined control strategies are the most effective in reducing co-infection. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Human papillomavirus (HPV) and gonorrhea are sexually transmitted infections that pose significant challenges to global public health. This study introduces a novel mathematical model with eleven compartments to capture the dynamics between HPV and gonorrhea co-infection. We explore the basic analytical properties such as nonnegativity and boundedness of the solutions, stability analysis of disease-equilibrium point, existence of endemic equilibrium points for the co-infection model. The basic reproduction number is derived using next generation matrix method. Also, the model is calibrated and validated using real-world gonorrhea infection data from 2012 to 2022, collected in the United States to ensure its accuracy and relevance to current epidemiological trends. Sensitivity analysis is carried out to identify key parameters that influence the basic reproduction number. The findings reveal that reducing contact rates, increasing gonorrhea treatment rates, enhancing HPV vaccine efficacy, and accelerating HPV vaccination efforts substantially lower the disease transmission. Additionally, the effective contact rates of HPV and gonorrhea have been projected until 2062, providing valuable insights into the significance of reducing these infections. To further curb the transmission of these infections, three time-dependent control variables such as promoting safe sex practices, implementing a time-varying HPV vaccination rate and enhancing gonorrhea treatment are incorporated into the model. We then define an optimal control problem to minimize the total number of infected individuals and examine the existence of optimal control along with the necessary conditions for the optimality system. Numerical simulations are carried out to illustrate the practical implications of the model and the effectiveness of the proposed control strategies. The obtained results suggest that the simultaneous implementation of all control measures can significantly lower both single and co-infection rates, leading to improved public health outcomes. • A deterministic model is proposed to study the co-infection of HPV and gonorrhea. • Stability of the disease-free equilibrium point is thoroughly analyzed. • The model is validated using reported gonorrhea cases from the United States. • An optimal control problem is formulated to reduce the overall infected population. • Combined control strategies are the most effective in reducing co-infection. [ABSTRACT FROM AUTHOR]
ISSN:03784754
DOI:10.1016/j.matcom.2026.06.027