The Impact of Imperfect Vaccination on Infectious Disease Transmission in an Age-Structured Population

In this paper, we consider the influence of imperfect vaccination on the spread of infectious diseases in an age-structured population. The benefits of vaccination, even if not perfect, generally outweigh the risks of severe diseases. In a mathematical system, we consider the compartment of susceptible s; vaccinated v and infected i individuals with an age structure. The proposed model is globally analyzed by introducing total trajectories and employing a suitable Lyapunov functional. To illustrate our theoretical findings, we include numerical simulations at the end of the paper. AMS subject classification: 35Q92, 37N25, 92D30. REFERENCES [1] Adimy, M., Chekroun, A., & Ferreira, C. P. (2020). Global dynamics of a differential-difference system: a case of Kermack-McKendrick SIR model with age-structured protection phase. Mathematical Biosciences and Engineering, 17(2), 1329-1354.‏ Search in Google Scholar. https://dx.doi.org/10.3934/mbe.2020067 [2] Benchaira, S., Mancer, S., & Necir, A. (2024). A Log-Probability-Weighted-Moments type estimator for the extreme value index in a truncation scheme. International Journal of Applied Mathematics and Simulation, 1(2).‏ Search in Google Scholar. https://doi.org/10.69717/ijams.v1.i2.99 [3] Soufiane, B., & Touaoula, T. M. (2016). Global analysis of an infection age model with a class of nonlinear incidence rates. Journal of Mathematical Analysis and Applications, 434(2), 1211-1239.‏ Search in Google Scholar. https://doi.org/10.1016/j.jmaa.2015.09.066 [4] Boudjema, I., & Touaoula, T. M. (2018). Global stability of an infection and vaccination age-structured model with general nonlinear incidence. J. Nonlinear Funct. Anal, 2018(33), 1-21.‏ Search in Google Scholar. https://doi.org/10.23952/jnfa.2018.33 [5] Bubar, K. M., Reinholt, K., Kissler, S. M., Lipsitch, M., Cobey, S., Grad, Y. H., & Larremore, D. B. (2021). Model-informed COVID-19 vaccine prioritization strategies by age and serostatus. Science, 371(6352), 916-921.‏ Search in Google Scholar. https://doi.org/10.1126/science.abe6959 [6] Buckner, J. H., Chowell, G., & Springborn, M. R. (2020). Optimal dynamic prioritization of scarce COVID-19 vaccines. Medrxiv, 2020-09.‏ Search in Google Scholar. https://doi.org/10.1073/pnas.2025786118 [7] Cai, L., Martcheva, M., & Li, X. Z. (2013). Epidemic models with age of infection, indirect transmission and incomplete treatment. Discrete and Continuous Dynamical Systems Series B, 18, 2239-2265.‏ Search in Google Scholar. View in Academia [8] Cai, L. M., Modnak, C., & Wang, J. (2017). An age-structured model for cholera control with vaccination. Applied Mathematics and Computation, 299, 127-140.‏ Search in Google Scholar. https://doi.org/10.1016/j.amc.2016.11.013 [9] Castillo-Chavez, C., Hethcote, H. W., Andreasen, V., Levin, S. A., & Liu, W. M. (1989). Epidemiological models with age structure, proportionate mixing, and cross-immunity. Journal of mathematical biology, 27, 233-258.‏ Search in Google Scholar. https://doi.org/10.1007/BF00275810 [10] Diekmann, O., & Heesterbeek, J. A. P. (2000). Mathematical epidemiology of infectious diseases: model building, analysis and interpretation (Vol. 5). John Wiley & Sons.‏ Search in Google Scholar. View [11] Halloran, M. E., Haber, M., & Longini Jr, I. M. (1992). Interpretation and estimation of vaccine efficacy under heterogeneity. American Journal of Epidemiology, 136(3), 328-343.‏ Search in Google Scholar. https://doi.org/10.1093/oxfordjournals.aje.a116498 [12] Feng, Z., Feng, Y., & Glasser, J. W. (2020). Influence of demographically-realistic mortality schedules on vaccination strategies in age-structured models. Theoretical population biology, 132, 24-32.‏ Search in Google Scholar. https://doi.org/10.1016/j.tpb.2020.01.005 [13] Galazka, A. M., Robertson, S. E., & Oblapenko, G. P. (1995). Resurgence of diphtheria. European journal of epidemiology, 11, 95-105.‏ Search in Google Scholar. https://doi.org/10.1007/BF01719954 [14] Grenfell, B. T., & Anderson, R. M. (1989). Pertussis in England and Wales: an investigation of transmission dynamics and control by mass vaccination. Proceedings of the Royal Society of London. B. Biological Sciences, 236(1284), 213-252.‏ Search in Google Scholar. https://doi.org/10.1098/rspb.1989.0022 [15] Hathout, F. Z., Touaoula, T. M., & Djilali, S. (2022). Mathematical analysis of a triple age dependent epidemiological model with including a protection strategy. Discrete & Continuous Dynamical Systems-Series B, 27(12).‏ Search in Google Scholar. https://doi.org/10.3934/dcdsb.2022048 [16] Hethcote, H. W. (2000). The mathematics of infectious diseases. SIAM review, 42(4), 599-653.‏ Search in Google Scholar. https://doi.org/10.1137/S0036144500371907 [17] Janaszek, W., Gay, N. J., & Gut, W. (2003). Measles vaccine efficacy during an epidemic in 1998 in the highly vaccinated population of Poland. Vaccine, 21(5-6), 473-478.‏ Search in Google Scholar. https://doi.org/10.1016/S0264-410X(02)00482-6 [18] Kanaan, M. N., & Farrington, C. P. (2002). Estimation of waning vaccine efficacy. Journal of the American Statistical Association, 97(458), 389-397.‏ Search in Google Scholar. https://doi.org/10.1198/016214502760046943 [19] Magal, P., & Thieme, H. R. (2004). Eventual compactness for semiflows generated by nonlinear age-structured models. Commun. Pure Appl. Anal, 3(4), 695-727.‏ Search in Google Scholar. View [20] Magal, P., & Zhao, X. Q. (2005). Global attractors and steady states for uniformly persistent dynamical systems. SIAM journal on mathematical analysis, 37(1), 251-275.‏ Search in Google Scholar. https://doi.org/10.1137/S0036141003439173 [21] Magpantay, F. M., Riolo, M. A., De Celles, M. D., King, A. A., & Rohani, P. (2014). Epidemiological consequences of imperfect vaccines for immunizing infections. SIAM Journal on Applied Mathematics, 74(6), 1810-1830.‏ Search in Google Scholar. https://doi.org/10.1137/140956695 [22] McLean, A. R., & Blower, S. M. (1993). Imperfect vaccines and herd immunity to HIV. Proceedings of the Royal Society of London. Series B: Biological Sciences, 253(1336), 9-13.‏ Search in Google Scholar. https://doi.org/10.1098/rspb.1993.0075 [23] Mossong, J., Nokes, D. J., Edmunds, W. J., Cox, M. J., Ratnam, S., & Muller, C. P. (1999). Modeling the impact of subclinical measles transmission in vaccinated populations with waning immunity. American journal of epidemiology, 150(11), 1238-1249.‏ Search in Google Scholar. https://doi.org/10.1093/oxfordjournals.aje.a009951 [24] Scherer, A., & McLean, A. (2002). Mathematical models of vaccination. British medical bulletin, 62(1), 187-199.‏ Search in Google Scholar. https://doi.org/10.1093/bmb/62.1.187 [25] Shim, E., & Galvani, A. P. (2012). Distinguishing vaccine efficacy and effectiveness. Vaccine, 30(47), 6700-6705.‏ Search in Google Scholar. https://doi.org/10.1016/j.vaccine.2012.08.045 [26] Smith, H. L., & Thieme, H. R. (2011). Dynamical systems and population persistence (Vol. 118). American Mathematical Soc..‏ Search in Google Scholar. View a book [27] Smith, H., & Zhao, X. Q. (2001). Robust persistence for semidynamical systems. Nonlinear Analysis, Theory, Methods and Applications, 47(9), 6169-6179.‏ Search in Google Scholar. https://doi.org/10.1016/S0362-546X(01)00678-2 [28] Webb, G. F. (1985). Theory of nonlinear age-dependent population dynamics. CRC Press.‏ Search in Google Scholar. View a book Communicated Editor: Boumediène Abdellaoui Manuscript received Mar 09, 2024; revised Jan 05, 2025; accepted Jan 19, 2025; published Feb,28 2025.

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International Journal of Applied Mathematics and Simulation
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2025-01-22
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https://doi.org/10.69717/ijams.v2.i1.104
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Vaccine Coverage and Hesitancy
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article

The Impact of Imperfect Vaccination on Infectious Disease Transmission in an Age-Structured Population

Tarik Mohammed Touaoula, Fatima Zohra Hathout
International Journal of Applied Mathematics and Simulation
Vaccine Coverage and Hesitancy
article

The Impact of Imperfect Vaccination on Infectious Disease Transmission in an Age-Structured Population

Tarik Mohammed Touaoula, Fatima Zohra Hathout
article en

Abstract

In this paper, we consider the influence of imperfect vaccination on the spread of infectious diseases in an age-structured population. The benefits of vaccination, even if not perfect, generally outweigh the risks of severe diseases. In a mathematical system, we consider the compartment of susceptible s; vaccinated v and infected i individuals with an age structure. The proposed model is globally analyzed by introducing total trajectories and employing a suitable Lyapunov functional. To illustrate our theoretical findings, we include numerical simulations at the end of the paper. AMS subject classification: 35Q92, 37N25, 92D30. REFERENCES [1] Adimy, M., Chekroun, A., & Ferreira, C. P. (2020). Global dynamics of a differential-difference system: a case of Kermack-McKendrick SIR model with age-structured protection phase. Mathematical Biosciences and Engineering, 17(2), 1329-1354.‏ Search in Google Scholar. https://dx.doi.org/10.3934/mbe.2020067 [2] Benchaira, S., Mancer, S., & Necir, A. (2024). A Log-Probability-Weighted-Moments type estimator for the extreme value index in a truncation scheme. International Journal of Applied Mathematics and Simulation, 1(2).‏ Search in Google Scholar. https://doi.org/10.69717/ijams.v1.i2.99 [3] Soufiane, B., & Touaoula, T. M. (2016). Global analysis of an infection age model with a class of nonlinear incidence rates. Journal of Mathematical Analysis and Applications, 434(2), 1211-1239.‏ Search in Google Scholar. https://doi.org/10.1016/j.jmaa.2015.09.066 [4] Boudjema, I., & Touaoula, T. M. (2018). Global stability of an infection and vaccination age-structured model with general nonlinear incidence. J. Nonlinear Funct. Anal, 2018(33), 1-21.‏ Search in Google Scholar. https://doi.org/10.23952/jnfa.2018.33 [5] Bubar, K. M., Reinholt, K., Kissler, S. M., Lipsitch, M., Cobey, S., Grad, Y. H., & Larremore, D. B. (2021). Model-informed COVID-19 vaccine prioritization strategies by age and serostatus. Science, 371(6352), 916-921.‏ Search in Google Scholar. https://doi.org/10.1126/science.abe6959 [6] Buckner, J. H., Chowell, G., & Springborn, M. R. (2020). Optimal dynamic prioritization of scarce COVID-19 vaccines. Medrxiv, 2020-09.‏ Search in Google Scholar. https://doi.org/10.1073/pnas.2025786118 [7] Cai, L., Martcheva, M., & Li, X. Z. (2013). Epidemic models with age of infection, indirect transmission and incomplete treatment. Discrete and Continuous Dynamical Systems Series B, 18, 2239-2265.‏ Search in Google Scholar. View in Academia [8] Cai, L. M., Modnak, C., & Wang, J. (2017). An age-structured model for cholera control with vaccination. Applied Mathematics and Computation, 299, 127-140.‏ Search in Google Scholar. https://doi.org/10.1016/j.amc.2016.11.013 [9] Castillo-Chavez, C., Hethcote, H. W., Andreasen, V., Levin, S. A., & Liu, W. M. (1989). Epidemiological models with age structure, proportionate mixing, and cross-immunity. Journal of mathematical biology, 27, 233-258.‏ Search in Google Scholar. https://doi.org/10.1007/BF00275810 [10] Diekmann, O., & Heesterbeek, J. A. P. (2000). Mathematical epidemiology of infectious diseases: model building, analysis and interpretation (Vol. 5). John Wiley & Sons.‏ Search in Google Scholar. View [11] Halloran, M. E., Haber, M., & Longini Jr, I. M. (1992). Interpretation and estimation of vaccine efficacy under heterogeneity. American Journal of Epidemiology, 136(3), 328-343.‏ Search in Google Scholar. https://doi.org/10.1093/oxfordjournals.aje.a116498 [12] Feng, Z., Feng, Y., & Glasser, J. W. (2020). Influence of demographically-realistic mortality schedules on vaccination strategies in age-structured models. Theoretical population biology, 132, 24-32.‏ Search in Google Scholar. https://doi.org/10.1016/j.tpb.2020.01.005 [13] Galazka, A. M., Robertson, S. E., & Oblapenko, G. P. (1995). Resurgence of diphtheria. European journal of epidemiology, 11, 95-105.‏ Search in Google Scholar. https://doi.org/10.1007/BF01719954 [14] Grenfell, B. T., & Anderson, R. M. (1989). Pertussis in England and Wales: an investigation of transmission dynamics and control by mass vaccination. Proceedings of the Royal Society of London. B. Biological Sciences, 236(1284), 213-252.‏ Search in Google Scholar. https://doi.org/10.1098/rspb.1989.0022 [15] Hathout, F. Z., Touaoula, T. M., & Djilali, S. (2022). Mathematical analysis of a triple age dependent epidemiological model with including a protection strategy. Discrete & Continuous Dynamical Systems-Series B, 27(12).‏ Search in Google Scholar. https://doi.org/10.3934/dcdsb.2022048 [16] Hethcote, H. W. (2000). The mathematics of infectious diseases. SIAM review, 42(4), 599-653.‏ Search in Google Scholar. https://doi.org/10.1137/S0036144500371907 [17] Janaszek, W., Gay, N. J., & Gut, W. (2003). Measles vaccine efficacy during an epidemic in 1998 in the highly vaccinated population of Poland. Vaccine, 21(5-6), 473-478.‏ Search in Google Scholar. https://doi.org/10.1016/S0264-410X(02)00482-6 [18] Kanaan, M. N., & Farrington, C. P. (2002). Estimation of waning vaccine efficacy. Journal of the American Statistical Association, 97(458), 389-397.‏ Search in Google Scholar. https://doi.org/10.1198/016214502760046943 [19] Magal, P., & Thieme, H. R. (2004). Eventual compactness for semiflows generated by nonlinear age-structured models. Commun. Pure Appl. Anal, 3(4), 695-727.‏ Search in Google Scholar. View [20] Magal, P., & Zhao, X. Q. (2005). Global attractors and steady states for uniformly persistent dynamical systems. SIAM journal on mathematical analysis, 37(1), 251-275.‏ Search in Google Scholar. https://doi.org/10.1137/S0036141003439173 [21] Magpantay, F. M., Riolo, M. A., De Celles, M. D., King, A. A., & Rohani, P. (2014). Epidemiological consequences of imperfect vaccines for immunizing infections. SIAM Journal on Applied Mathematics, 74(6), 1810-1830.‏ Search in Google Scholar. https://doi.org/10.1137/140956695 [22] McLean, A. R., & Blower, S. M. (1993). Imperfect vaccines and herd immunity to HIV. Proceedings of the Royal Society of London. Series B: Biological Sciences, 253(1336), 9-13.‏ Search in Google Scholar. https://doi.org/10.1098/rspb.1993.0075 [23] Mossong, J., Nokes, D. J., Edmunds, W. J., Cox, M. J., Ratnam, S., & Muller, C. P. (1999). Modeling the impact of subclinical measles transmission in vaccinated populations with waning immunity. American journal of epidemiology, 150(11), 1238-1249.‏ Search in Google Scholar. https://doi.org/10.1093/oxfordjournals.aje.a009951 [24] Scherer, A., & McLean, A. (2002). Mathematical models of vaccination. British medical bulletin, 62(1), 187-199.‏ Search in Google Scholar. https://doi.org/10.1093/bmb/62.1.187 [25] Shim, E., & Galvani, A. P. (2012). Distinguishing vaccine efficacy and effectiveness. Vaccine, 30(47), 6700-6705.‏ Search in Google Scholar. https://doi.org/10.1016/j.vaccine.2012.08.045 [26] Smith, H. L., & Thieme, H. R. (2011). Dynamical systems and population persistence (Vol. 118). American Mathematical Soc..‏ Search in Google Scholar. View a book [27] Smith, H., & Zhao, X. Q. (2001). Robust persistence for semidynamical systems. Nonlinear Analysis, Theory, Methods and Applications, 47(9), 6169-6179.‏ Search in Google Scholar. https://doi.org/10.1016/S0362-546X(01)00678-2 [28] Webb, G. F. (1985). Theory of nonlinear age-dependent population dynamics. CRC Press.‏ Search in Google Scholar. View a book Communicated Editor: Boumediène Abdellaoui Manuscript received Mar 09, 2024; revised Jan 05, 2025; accepted Jan 19, 2025; published Feb,28 2025.

International Journal of Applied Mathematics and SimulationVol. 2(1)
University of Abou Bekr Belkaïd (DZ), Higher School of Applied Sciences (SI), École Supérieure en Sciences Appliquées de Tlemcen (DZ)
Openalex Percentile: Top 99%
Vaccine Coverage and Hesitancy
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