Control Design for Dengue Fever Model with Disturbance

Authors

  • Hanna Hilyati Aulia Department of Economics, IAIN Metro, Lampung 34112, Indonesia
  • Roberd Saragih Department of Mathematics, Institut Teknologi Bandung, Bandung 40132, Indonesia
  • Dewi Handayani Department of Mathematics, Institut Teknologi Bandung, Bandung 40132, Indonesia

DOI:

https://doi.org/10.5614/cbms.2022.5.2.3

Keywords:

dengue model with disturbance, SDRE, vaccination control

Abstract

A mathematical model has become a useful tool to predict and control dengue fever dynamics. In reality, the dynamic of dengue fever transmission can be disturbed by uncertainty measurements, so it is needed to consider the disturbance in the model. Then, dengue fever model with disturbance is constructed by using a gain matrix consisting a covariance matrix and random vector. As dengue vaccine has been challenging to reduce the pandemic, a dengue model with vaccination as control is constructed. The aim is to propose a feedback controller that can reduces the infected human (H2 control problem) and the uncertainty measurements (H? control problem). The control u denotes the proportion of susceptible humans that one decides to vaccinate at time t. A random mass vaccination with wanning immunity is chosen because vaccine still on development process. A Design of mixed H2 - H? control with State-dependent Riccati Equation (SDRE) approach is applied. The SDRE has been an effective method to solve for synthesizing nonlinear feedback controller by transforming the system to an State-dependent coefficient (SDC) form. By comparing the mixed scheme with basic H?, numerical simulation shows that the control application effectively decreases the number of infected humans and reduces the disturbance.

References

Allen, L.J.S., An introduction to stochastic processes with applications to biology 2nd edition, Texas, CRC Press: Taylor and Francis Group, pp. 415-417, 2010.

Cattand, P., Desjeux, P., Guzman, M.G., Jannin, J., Kroeger, A., Medici, A., Musgrove, P., Nathan, M.B., Shaw, A. and Schofield, C.J., Tropical diseases lacking adequate control measures: dengue, leishmaniasis, and African trypanosomiasis, Disease Control Priorities in Developing Countries, pp. 452-466, 2006.

Centers for Disease Control and Prevention (CDC), cdc.gov/vaccines/vpd.dengue/public/index.html (accessed 2th October 2022).

Cimen, T., State-dependent Riccati equation (SDRE) control: a Survey, Proceedings of the 17th World Congress the International Federation of Automatic Control, Seoul, 41(2) pp. 3761-3775, 2008.

Derouich, M., Boutayeb, A., and Twizell, E.H., A model of dengue fever, BioMedical Engineering Online, 2(1), pp. 1-10, 2003.

Doyle, J.H., Glover, K., Khargonekar, P., and Francis, B., State-space solution to standard H2 and H? control problems, IEEE Transactions on Automathic Control, 34, pp. 831-847, 1989.

Hammet, K.D. , Control of nonlinear systems via state feedback state-dependent riccati equation techniques, Disertation, Air University, 1997.

Keeling, M.J. and Rohani, P. , Modeling infectious disease in human and animals, Princeton, Princeton University Press, 2008.

Lahodny, Glenn and Zevika, Mona,The Effects of Fogging and Mosquito Repellent on the Probability of Disease Extinction for Dengue Fever, Commun. Biomath. Sci., 4(1), pp. 1-13, 2021.

Leleury, Z.A., Lesnussa, Y.A., Bension, J.B., and Kakisina, Y.S. , Analisis stabilitas model SIR (susceptible, infected, recovery) pada penyebaran penyakit demam berdarah dengue di Maluku, Jurnal Matematika, 7(2), pp.144-158, 2017.

Mracek, C.P. and Cloutier, J. R., Control design for the nonlinearbenchmark problem via the state-dependent Riccati equation method, International Journal of Robusst and Nonlinear Control, 8(4-5). pp. 401-433, 1998.

Ndanguza, D., Mbalawata, A.S., Nsabimana, J.P., Analysis of SDEs applied to SEIR epidemic models by extended kalman filter method, Applied Mathemastics, 7(17), pp. 2195-2211, 2016.

Newton, E.A. and Reiter, P., A model of the transmission of dengue fever with an evaluation of the impact of ultra-low volume (ULV) insecticide application on dengue epidemics, Am J Trop Med Hyg, 47(6), pp. 709-720, 1992.

Rodrigues, H.S., Monteiro, M.T.T., and Torres, D.F.M., Vaccination models and optimal control strategies to dengue, Mathematical Biosciences, 247, pp. 1-12, 2013.

Thisyakorn, U and Thisyakorn, C., Latesy development and future directions in dengue vaccines, Ther Adv Vaccines, 2(1), pp. 3-9, 2014.

Wang, X., Yaz, E.E., Schneider, S.C., and Yaz, Y.I. , H2 ? H? control of continuous-time nonlinear systems using the statedependent riccati equation approach, System Science and control Engineering, 5(1), pp. 224-231, 2017.

World Health Organization (WHO), https://www.who.int/news-room/fact-sheets/detail/dengue-ans severe-dengue (accessed 10th October 2018) and http://www.searo.who.int/entity/vector-borne-tropical-diseases/data/data-factsheet/en (accessed 1st August 2019)

Yu, Ningbo and Qiu, Li , A mixed H2 ? H? control problem with controller degree constraint, Proceeding of the 45th IEEE Conference on Decision and Control Problem, San Diego, pp. 5365-5370, 2006.

Ndii, Meksianis Z. , A Game Dynamic Modeling Framework to Understand the Influence of Human Choice to Vaccinate or to Reduce Contact with Mosquitoes on Dengue Transmission Dynamics, Commun. Biomath. Sci., 4(1), pp. 65-80 65, 2021.

Downloads

Published

2023-01-03

How to Cite

Hilyati Aulia, H., Saragih, R., & Handayani, D. (2023). Control Design for Dengue Fever Model with Disturbance. Communication in Biomathematical Sciences, 5(2), 137-150. https://doi.org/10.5614/cbms.2022.5.2.3

Issue

Section

Articles