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Nonlinear pulse vaccination in an SIR epidemic model with resource limitation. (English) Zbl 1420.92067

Summary: Mathematical models can assist in the design and understanding of vaccination strategies when resources are limited. Here we propose and analyse an SIR epidemic model with a nonlinear pulse vaccination to examine how a limited vaccine resource affects the transmission and control of infectious diseases, in particular emerging infectious diseases. The threshold condition for the stability of the disease free steady state is given. Latin hypercube sampling/partial rank correlation coefficient uncertainty and sensitivity analysis techniques were employed to determine the key factors which are most significantly related to the threshold value. Comparing this threshold value with that without resource limitation, our results indicate that if resources become limited pulse vaccination should be carried out more frequently than when sufficient resources are available to eradicate an infectious disease. Once the threshold value exceeds a critical level, both susceptible and infected populations can oscillate periodically. Furthermore, when the pulse vaccination period is chosen as a bifurcation parameter, the SIR model with nonlinear pulse vaccination reveals complex dynamics including period doubling, chaotic solutions, and coexistence of multiple attractors. The implications of our findings with respect to disease control are discussed.

MSC:

92C60 Medical epidemiology
92D30 Epidemiology
34C25 Periodic solutions to ordinary differential equations
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[1] Anderson, R. M.; May, R. M., Population biology of infectious diseases: part I, Nature, 280, 5721, 361-367 (1979)
[2] Hanert, E.; Schumacher, E.; Deleersnijder, E., Front dynamics in fractional-order epidemic models, Journal of Theoretical Biology, 279, 1, 9-16 (2011) · Zbl 1397.92636
[3] Hethcote, H. W., Mathematics of infectious diseases, SIAM Review, 42, 4, 599-653 (2000) · Zbl 0993.92033
[4] Fiore, A. E.; Bridges, C. B.; Cox, N. J., Seasonal influenza vaccines, Current Topics in Microbiology and Immunology, 333, 1, 43-82 (2009)
[5] Chang, Y.; Brewer, N. T.; Rinas, A. C.; Schmitt, K.; Smith, J. S., Evaluating the impact of human papillomavirus vaccines, Vaccine, 27, 32, 4355-4362 (2009)
[6] Liesegang, T. J., Varicella zoster virus vaccines: effective, but concerns linger, Canadian Journal of Ophthalmology, 44, 4, 379-384 (2009)
[7] Agur, Z.; Cojocaru, L.; Mazor, G.; Anderson, R. M.; Danon, Y. L., Pulse mass measles vaccination across age cohorts, Proceedings of the National Academy of Sciences of the United States of America, 90, 24, 11698-11702 (1993)
[8] Stone, L.; Shulgin, B.; Agur, Z., Theoretical examination of the pulse vaccination policy in the SIR epidemic model, Mathematical and Computer Modelling, 31, 4-5, 207-215 (2000) · Zbl 1043.92527
[9] Shulgin, B.; Stone, L.; Agur, Z., Pulse vaccination strategy in the SIR epidemic model, Bulletin of Mathematical Biology, 60, 6, 1123-1148 (1998) · Zbl 0941.92026
[10] D’Onofrio, A., Stability properties of pulse vaccination strategy in SEIR epidemic model, Mathematical Biosciences, 179, 1, 57-72 (2002) · Zbl 0991.92025
[11] Franceschetti, A.; Pugliese, A., Threshold behaviour of a SIR epidemic model with age structure and immigration, Journal of Mathematical Biology, 57, 1, 1-27 (2008) · Zbl 1141.92037
[12] Terry, A. J., Pulse vaccination strategies in a metapopulation SIR model, Mathematical Biosciences and Engineering, 7, 2, 455-477 (2010) · Zbl 1260.92078
[13] Gao, S. J.; Chen, L. S.; Nieto, J. J.; Torres, A., Analysis of a delayed epidemic model with pulse vaccination and saturation incidence, Vaccine, 24, 35-36, 6037-6045 (2006)
[14] Matrajt, L.; Halloran, M. E.; Longini, I. M., Optimal vaccine allocation for the early mitigation of pandemic influenza, PLoS Computational Biology, 9, 3 (2013)
[15] Sullivan, S. P.; Koutsonanos, D. G.; Martin, M. D. P.; Lee, J. W.; Zarnitsyn, V.; Choi, S.; Murthy, N.; Compans, R. W.; Skountzou, I.; Prausnitz, M. R., Dissolving polymer microneedle patches for influenza vaccination, Nature Medicine, 16, 8, 915-920 (2010)
[16] Science Daily Web, Vaccine-delivery patch with dissolving microneedles eliminates “sharps”, boosts protection
[17] Reynolds-Hogland, M. J.; Hogland, J. S.; Mitchell, M. S., Evaluating intercepts from demographic models to understand resource limitation and resource thresholds, Ecological Modelling, 211, 3-4, 424-432 (2008)
[18] Chow, L.; Fan, M.; Feng, Z. L., Dynamics of a multigroup epidemiological model with group-targeted vaccination strategies, Journal of Theoretical Biology, 291, 1, 56-64 (2011) · Zbl 1397.92626
[19] Zhou, L. H.; Fan, M., Dynamics of an SIR epidemic model with limited medical resources revisited, Nonlinear Analysis: Real World Applications, 13, 1, 312-324 (2012) · Zbl 1238.37041
[20] Lakshmikantham, V.; Bainov, D. D.; Simeonov, P. S., Theory of Impulsive Differential Equations (1989), Singapore: World Scientific, Singapore · Zbl 0719.34002
[21] Blower, S. M.; Dowlatabadi, H., Sensitivity and uncertainty analysis of complex-models of disease transmission? An HIV model, as an example, International Statistical Review, 62, 2, 229-243 (1994) · Zbl 0825.62860
[22] Marino, S.; Hogue, I. B.; Ray, C. J.; Kirschner, D. E., A methodology for performing global uncertainty and sensitivity analysis in systems biology, Journal of Theoretical Biology, 254, 1, 178-196 (2008) · Zbl 1400.92013
[23] Tang, S. Y.; Liang, J. H.; Tan, Y. S.; Cheke, R. A., Threshold conditions for integrated pest management models with pesticides that have residual effects, Journal of Mathematical Biology, 66, 1-2, 1-35 (2013) · Zbl 1402.92369
[24] Brauer, F.; Castillo-Chavez, C., Mathematical Models in Population Biology and Epidemiology (2000), New York, NY, USA: Springer, New York, NY, USA · Zbl 1302.92001
[25] Diekmann, O.; Heesterbeek, J. A. P., Mathematical Epidemiology of Infectious Diseases (2000), Chichester, UK: John Wiley & Sons, Chichester, UK · Zbl 0997.92505
[26] Murray, J. D., Mathematical Biology (1989), Berlin, Germany: Springer, Berlin, Germany · Zbl 0682.92001
[27] Anderson, R.; May, R., Infectious Diseases of Humans, Dynamics and Control (1995), Oxford, UK: Oxford University Press, Oxford, UK
[28] Hethcote, M.; Gross, L.; Hallam, T. G.; Levin, S. A., Three basic epidemiological models, Applied Mathematical Ecology, 119-144 (1989), Berlin, Germany: Springer, Berlin, Germany
[29] Hill, A. V., The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves, The Journal of Physiology, 40, 4, 4-7 (1910)
[30] Cull, P., Local and global stability for population models, Biological Cybernetics, 54, 3, 141-149 (1986) · Zbl 0607.92018
[31] Web, W. H. O., Global health observatory data repository
[32] McKay, M. D.; Beckman, R. J.; Conover, W. J., Comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21, 2, 239-245 (1979) · Zbl 0415.62011
[33] Schaffer, W. M.; Olsen, L. F.; Truty, G. L.; Fulmer, S. L.; Graser, D. J.; Markus, M.; Muller, S.; Nicolis, G., Periodic and chaotic dynamics in childhood epidemics, From Chemical to Biological Organization (1988), Berlin, Germany: Springer, Berlin, Germany · Zbl 0665.92014
[34] Lakmeche, A.; Arino, O., Bifurcation of non trivial periodic solutions of impulsive differential equations arising chemotherapeutic treatment, Dynamics of Continuous, Discrete and Impulsive Systems B, 7, 2, 265-287 (2000) · Zbl 1011.34031
[35] Tang, S. Y.; Chen, L. S., Multiple attractors in stage-structured population models with birth pulses, Bulletin of Mathematical Biology, 65, 3, 479-495 (2003) · Zbl 1334.92371
[36] Tang, S. Y.; Xiao, Y. N.; Cheke, R. A., Multiple attractors of host-parasitoid models with integrated pest management strategies: eradication, persistence and outbreak, Theoretical Population Biology, 73, 2, 181-197 (2008) · Zbl 1208.92093
[37] Olsen, L. F.; Schaffer, W. M., Chaos versus noisy periodicity: alternative hypotheses for childhood epidemics, Science, 249, 4968, 499-504 (1990)
[38] Sugihara, G.; May, R. M., Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series, Nature, 344, 6268, 734-741 (1990)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.