Mathematical modeling and optimal control of HPV-related cervical cancer through awareness campaigns and vaccination

Khalid Aldawsari , Fahad Al Basir

Networks and Heterogeneous Media ›› 2026, Vol. 21 ›› Issue (4) : 1146 -1171.

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Networks and Heterogeneous Media ›› 2026, Vol. 21 ›› Issue (4) :1146 -1171. DOI: 10.3934/nhm.2026046
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Mathematical modeling and optimal control of HPV-related cervical cancer through awareness campaigns and vaccination
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Abstract

In this research, we have derived a mathematical model to study the impact of health center-based awareness campaigns on the spread of human papillomavirus (HPV) infection to cervical cancer. In the model, the human population is divided into susceptible, vaccinated, permanently immune, infected with HPV, and recovered. Moreover,awareness level is assumed as a model compartment. The awareness level affects the rates of infection, vaccination, recovery, and disease progression. The basic reproduction number (R0) is calculated using the next-generation matrix method. The equilibrium points are determined, and their stability analysis is conducted. Disease-free equilibrium (DFE) is globally asymptotically stable for R0 < 1. Forward transcritical bifurcation occurs at R0 = 1. Furthermore, optimal control theory is employed using Pontryagin’s maximum principle, with the objective of minimizing infection rates through optimal vaccination at the minimum cost of control. These results are validated by numerical simulations. The results show that effective HPV awareness campaigns can help control the spread of HPV infections, making it easier to manage cervical cancer. This study confirms the importance of awareness-induced behavioral dynamics in modeling spread of HPV for efficient disease management. Awareness campaigns with optimal vaccination can significantly lower HPV transmission and reduce the incidence of cervical cancer.

Keywords

basic reproduction number (R0) / sensitivity analysis / equilibria and stability / forward bifurcation / optimal control approach / numerical simulations

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Khalid Aldawsari, Fahad Al Basir. Mathematical modeling and optimal control of HPV-related cervical cancer through awareness campaigns and vaccination. Networks and Heterogeneous Media, 2026, 21 (4) : 1146-1171 DOI:10.3934/nhm.2026046

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References

[1]

A. A. A. Oyouni, Human papillomavirus in cancer: Infection, disease transmission, and progress in vaccines, J. Infect. Public Health, 16(2023), 626-631. https://doi.org/10.1016/j.jiph.2023.02.014

[2]

L. J. Mbigili, N. Nyerere, A. Iddi, S. Mpeshe, A mathematical analysis of HPV transmission dynamics and cervical cancer progression: The role of screening, prophylactic and therapeutic vaccination strategies,Comput. Methods Programs Biomed. Update, 8(2025), 100219. https://doi.org/10.1016/j.cmpbup.2025.100219

[3]

J. C. Sierra-Rojas, R. Reyes-Carreto, C. Vargas-De-Léon, J. F. Camacho, Modeling and mathematical analysis of the dynamics of HPV in cervical epithelial cells: Transient, acute, latency, and chronic infections, Comput. Math. Methods Med., 2022(2022), 8650071. https://doi.org/10.1155/2022/8650071

[4]

V. Awasthi, D. Kumar, Cervical cancer awareness and HPV vaccination willingness among women and adolescents in Northern India: A socio-demographic analysis, SSR Inst. Int. J. Life Sci., 11(2025), 8380-8388. https://doi.org/10.21276/SSR-IIJLS.2025.11.5.27

[5]

S. Ramakrishnan, S. Partricia, G. Mathan, Overview of high-risk HPV’s 16 and 18 infected cervical cancer: Pathogenesis to prevention, Biomed. Pharmacother., 70(2015), 103-110. https://doi.org/10.1016/j.biopha.2014.12.041

[6]

S. Zhang, H. Xu, L. Zhang, Y. Qiao, Cervical cancer: Epidemiology, risk factors and screening, Chin. J. Cancer Res., 32(2020), 720-728. https://doi.org/10.21147/j.issn.1000-9604.2020.06.05

[7]

H. D. Desta, G. T. Tilahun, T. M. Tolasa, M. G. Geleso, Mathematical model of human papillomavirus (HPV) dynamics with double-dose vaccination and its impact on cervical cancer, Discrete Dyn. Nat. Soc., 2024(2024), 9971859. https://doi.org/10.1155/ddns/9971859

[8]

M. Al-Arydah, Mathematical modeling and optimal control for COVID-19 with population behavior, Math. Methods Appl. Sci., 46(2023), 19184-19198. https://doi.org/10.1002/mma.9619

[9]

M. Adams, B. Jasani, A. Fiander, Human papilloma virus (HPV) prophylactic vaccination: Challenges for public health and implications for screening, Vaccine, 25(2007), 3007-3013. https://doi.org/10.1016/j.vaccine.2007.01.016

[10]

M. Tobaiqy, K. MacLure, A systematic review of human papillomavirus vaccination challenges and strategies to enhance uptake, Vaccines, 12(2024), 746. https://doi.org/10.3390/vaccines12070746

[11]

Medical experts join forces in Kolkata to tackle HPV-associated cancers, The Statesman, 2025. Available from: https://bengalinfo.com/newsdetail.php?newsid=391131.

[12]

Serum Institute of India hosts Conquer HPV & Cancer Conclave 2025 in Kolkata, Voice of Kolkata, 2025. Available from: https://voiceofkolkata.com/ serum-institute-of-india-hosts-conquer-hpv-cancer-conclave-2025-in-kolkata/.

[13]

K. N. Kaur, F. Niazi, D. Nandi, N. Taneja, Gender-neutral HPV vaccine in India; Requisite for a healthy community: A review, Cancer Control, 31(2024), 10732748241285184. https://doi.org/10.1177/10732748241285184

[14]

M. Singh, R. P. Jha, N. Shri, K. Bhattacharyya, P. Patel, D. Dhamnetiya, Secular trends in incidence and mortality of cervical cancer in India and its states, 1990-2019: Data from the Global Burden of Disease 2019 Study, BMC Cancer, 22(2022), 149. https://doi.org/10.1186/s12885-022-09232-w

[15]

S. Patra, H. Shand, S. Ghosal, S. Ghorai, HPV and male cancer: Pathogenesis, prevention and impact, J. Oman Med. Assoc., 2(2025), 4. https://doi.org/10.3390/joma2010004

[16]

F. A. Basir, K. B. Blyuss, A. A. Raezah, B. Rahman, H. J. Alsakaji, Mathematical modelling of the role of Langerhans cells in the dynamics of HPV infection, Sci. Rep., 15(2025), 17505. https://doi.org/10.1038/s41598-025-02608-5

[17]

M. Arunkumar, P. K. Rajan, K. Murugesan, Mathematical analysis of an optimal control problem for mitigating HPV transmission and cervical cancer progression through educational campaigns, Iran. J. Sci., 49(2025), 1309-1325. https://doi.org/10.1007/s40995-025-01804-2

[18]

E. R. Myers, D. C. McCrory, K. Nanda, L. Bastian, D. B. Matchar, Mathematical model for the natural history of human papillomavirus infection and cervical carcinogenesis, Am. J. Epidemiol., 151(2000), 1158-1171. https://doi.org/10.1093/oxfordjournals.aje.a010166

[19]

W. Wang, S. Sawleshwarkar, M. Piraveenan, Computational approaches of modelling human papillomavirus transmission and prevention strategies: A systematic review, J. Biol. Dyn., 19(2025), 2436376. https://doi.org/10.1080/17513758.2024.2436376

[20]

Y. He, H. Ni, W. Kuang, L. Fu, S. Yi, W. Zha, et al., Advances in HPV-associated cervical cancer dynamic modelling for prevention and control evaluation, China CDC Wkly., 7(2025), 225. https://doi.org/10.46234/ccdcw2025.035

[21]

A. A. Alsaleh, A. B. Gumel, Dynamics analysis of a vaccination model for HPV transmission, J. Biol. Syst., 22(2014), 555-599. https://doi.org/10.1142/S0218339014500211

[22]

P. K. Tiwari, R. K. Rai, S. Khajanchi, R. K. Gupta, A. K. Misra, Dynamics of coronavirus pandemic: Effects of community awareness and global information campaigns, Eur. Phys. J. Plus, 136(2021), 994. https://doi.org/10.1140/epjp/s13360-021-01997-6

[23]

K. Zhang, Y. Ji, Q. Pan, Y. Wei, Y. Ye, H. Liu, Sensitivity analysis and optimal treatment control for a mathematical model of Human Papillomavirus infection, AIMS Math., 5(2020), 172-190. https://doi.org/10.3934/math.2020172

[24]

E. Krokidi, A. P. Rao, E. Ambrosino, P. P. M. Thomas, The impact of health education interventions on HPV vaccination uptake, awareness, and acceptance among people under 30 years old in India: A literature review with systematic search, Front. Reprod. Health, 5(2023), 1151179. https://doi.org/10.3389/frph.2023.1151179

[25]

K. K. Ramavath, R. Olyai, Knowledge and awareness of HPV infection and vaccination among urban adolescents in India: A cross-sectional study, J. Obstet. Gynaecol. India, 63(2013), 399-404. https://doi.org/10.1007/s13224-013-0413-3

[26]

G. O. Agaba, Y. N. Kyrychko, K. B. Blyuss, Mathematical model for the impact of awareness on the dynamics of infectious diseases, Math. Biosci., 286(2017), 22-30. https://doi.org/10.1016/j.mbs.2017.01.009

[27]

J. Lankoande, W. O. Sawadogo, A. Kiemtoré, Mathematical modeling and numerical simulation of the dynamics of human papillomavirus (HPV) and cervical cancer in Burkina Faso, Asia Pac. J. Math., 12(2025), 1-20. https://doi.org/10.28924/APJM/12-8

[28]

J. M. Mutwiwa, S. B. Apima, Mathematical analysis of HPV and cervical cancer model in the presence of protection, Asian Res. J. Math., 19(2023), 1-11. https://doi.org/10.9734/arjom/2023/v19i8683

[29]

H. Ren, R. Xu, J. Zhang, HPV transmission and optimal control of cervical cancer in China, Sci. Rep., 15(2025), 21354. https://doi.org/10.1038/s41598-025-05514-y

[30]

T. Malik, M. Imran, R. Jayaraman, Optimal control with multiple human papillomavirus vaccines, J. Theor. Biol., 393(2016), 179-193. https://doi.org/10.1016/j.jtbi.2016.01.004

[31]

O. Forrest, M. Al-Arydah, Optimal control strategies for infectious diseases with consideration of behavioral dynamics, Math. Methods Appl. Sci., 48(2025), 1362-1380. https://doi.org/10.1002/mma.10388

[32]

F. Al Basir, S. Ray, E. Venturino, Role of media coverage and delay in controlling infectious diseases: A mathematical model, Appl. Math. Comput., 337(2018), 372-385. https://doi.org/10.1016/j.amc.2018.05.042

[33]

E. J. Dasbach, E. H. Elbasha, R. P. Insinga, Mathematical models for predicting the epidemiologic and economic impact of vaccination against human papillomavirus infection and disease, Epidemiol. Rev., 28(2006), 88-100. https://doi.org/10.1093/epirev/mxj006

[34]

A. Korobeinikov, Lyapunov functions and global properties for SEIR and SEIS epidemic models, Math. Med. Biol., 21(2004), 75-83. https://doi.org/10.1093/imammb/21.2.75

[35]

G. H. Li, Y. X. Zhang, Dynamic behaviors of a modified SIR model in epidemic diseases using nonlinear incidence and recovery rates, PLoS One, 12(2017), e0175789. https://doi.org/10.1371/journal.pone.0175789

[36]

J. P. La Salle, The Stability of Dynamical Systems , SIAM, 1976. https://doi.org/10.1137/1.9781611970432

[37]

J. Wu, R. Dhingra, M. Gambhir, J. V. Remais, Sensitivity analysis of infectious disease models: Methods, advances and their application, J. R. Soc. Interface, 10(2013), 20121018. https://doi.org/10.1098/rsif.2012.1018

[38]

K. Dietz, The estimation of the basic reproduction number for infectious diseases, Stat. Methods Med. Res., 2(1993), 23-41. https://doi.org/10.1177/096228029300200103

[39]

C. Castillo-Chavez, B. Song, Dynamical models of tuberculosis and their applications, Math. Biosci. Eng., 1(2004), 361-404. https://doi.org/10.3934/mbe.2004.1.361

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