View in EDS

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

Saved in:
Bibliographic Details
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]
Copyright of Mathematics & Computers in Simulation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 195144675
AccessLevel: 6
PubType: Periodical
PubTypeId: serialPeriodical
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Mathematical analysis of HPV and gonorrhea co-infection model with optimal control strategies for effective intervention.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Arunkumar%2C+M%2E%22">Arunkumar, M.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> arunkumarmak001@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Jose%2C+Sayooj+Aby%22">Jose, Sayooj Aby</searchLink><relatesTo>1,3,4</relatesTo> (AUTHOR)<i> sayooj@snu.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Murugesan%2C+K%2E%22">Murugesan, K.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> murugu@nitt.edu</i><br /><searchLink fieldCode="AR" term="%22Jirawattanapanit%2C+Anuwat%22">Jirawattanapanit, Anuwat</searchLink><relatesTo>5</relatesTo> (AUTHOR)<i> anuwat.j@pkru.ac.th</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Mathematics+%26+Computers+in+Simulation%22">Mathematics & Computers in Simulation</searchLink>. Nov2026, Vol. 249, p1076-1113. 38p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Human+papillomavirus%22">Human papillomavirus</searchLink><br /><searchLink fieldCode="DE" term="%22Gonorrhea%22">Gonorrhea</searchLink><br /><searchLink fieldCode="DE" term="%22Vaccination%22">Vaccination</searchLink><br /><searchLink fieldCode="DE" term="%22Public+health%22">Public health</searchLink><br /><searchLink fieldCode="DE" term="%22Infectious+disease+transmission%22">Infectious disease transmission</searchLink><br /><searchLink fieldCode="DE" term="%22Mixed+infections%22">Mixed infections</searchLink><br /><searchLink fieldCode="DE" term="%22Optimal+control+theory%22">Optimal control theory</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Mathematics & Computers in Simulation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=195144675
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.matcom.2026.06.027
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 38
        StartPage: 1076
    Subjects:
      – SubjectFull: Human papillomavirus
        Type: general
      – SubjectFull: Gonorrhea
        Type: general
      – SubjectFull: Vaccination
        Type: general
      – SubjectFull: Public health
        Type: general
      – SubjectFull: Infectious disease transmission
        Type: general
      – SubjectFull: Mixed infections
        Type: general
      – SubjectFull: Optimal control theory
        Type: general
      – SubjectFull: Mathematical models
        Type: general
      – SubjectFull: United States
        Type: general
    Titles:
      – TitleFull: Mathematical analysis of HPV and gonorrhea co-infection model with optimal control strategies for effective intervention.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Arunkumar, M.
      – PersonEntity:
          Name:
            NameFull: Jose, Sayooj Aby
      – PersonEntity:
          Name:
            NameFull: Murugesan, K.
      – PersonEntity:
          Name:
            NameFull: Jirawattanapanit, Anuwat
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: Nov2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 03784754
          Numbering:
            – Type: volume
              Value: 249
          Titles:
            – TitleFull: Mathematics & Computers in Simulation
              Type: main
ResultId 1