A modified optimal control for the mathematical model of dengue virus with vaccination
Issued Date
2023-01-01
Resource Type
eISSN
24736988
Scopus ID
2-s2.0-85172262902
Journal Title
AIMS Mathematics
Volume
8
Issue
11
Start Page
27460
End Page
27487
Rights Holder(s)
SCOPUS
Bibliographic Citation
AIMS Mathematics Vol.8 No.11 (2023) , 27460-27487
Suggested Citation
Pongsumpun P., Lamwong J., Tang I.M., Pongsumpun P. A modified optimal control for the mathematical model of dengue virus with vaccination. AIMS Mathematics Vol.8 No.11 (2023) , 27460-27487. 27487. doi:10.3934/math.20231405 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/90297
Title
A modified optimal control for the mathematical model of dengue virus with vaccination
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
The dengue viruses (of which there are four strains) are the causes of three illnesses of increasing severity; dengue fever (DF), dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). Recently, dengue fever has reached epidemic proportion in several countries. Strategies or preventative methods have to be developed to combat these epidemics. This can be done by development of vaccines or by preventing the transmission of the virus. The latter approach could involve the use of mosquito nets or insecticide spraying. To determine which strategy would work, we test the strategy using mathematical modeling to simulate the effects of the strategy on the dynamics of the transmission. We have chosen the Susceptible-Exposed-Infected-Recovered (SEIR) model and the Susceptible, Exposed-Infected (SEI) model to describe the human and mosquito populations, repectively. We use the Pontryagin’s maximum principle to find the optimal control conditions. A sensitivity analysis revealed that the transmission rate (ɣℎ, ɣv), the birth rate of human population (µℎ), the constant recruitment rate of the vector population (A) and the total human population (Nℎ) are the most influential factors affecting the disease transmission. Numerical simulations show that the optimal controlled infective responses, when implemented, cause the convergence to zero to be faster than that in uncontrolled cases.