Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment
This paper considers a deterministic model for the dynamics of measles transmission in a population divided into six classes with respect to the disease states: susceptible, vaccinated, exposed, infected, treated, and recovered. First, we investigate the dynamical properties of the SVEITR model such...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | International Journal of Mathematics and Mathematical Sciences |
Online Access: | http://dx.doi.org/10.1155/2020/1561569 |
id |
doaj-fd529b79a0b2436f85880e6d96d47a77 |
---|---|
record_format |
Article |
spelling |
doaj-fd529b79a0b2436f85880e6d96d47a772020-11-25T02:56:41ZengHindawi LimitedInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252020-01-01202010.1155/2020/15615691561569Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and TreatmentJaharuddin0Toni Bakhtiar1Department of Mathematics, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680, IndonesiaThis paper considers a deterministic model for the dynamics of measles transmission in a population divided into six classes with respect to the disease states: susceptible, vaccinated, exposed, infected, treated, and recovered. First, we investigate the dynamical properties of the SVEITR model such as its equilibrium points, their stability, and parameter sensitivity by applying constant controls. Criteria for determining the stability of disease-free and endemic equilibrium points are provided in terms of basic reproduction number. The model is then extended by incorporating vaccination, therapy, and treatment rates as time-dependent control variables representing the level of coverages. Application of Pontryagin’s maximum principle provides the necessary conditions that must be satisfied for the existence of optimal controls aiming at minimization of the number of exposed and infected individuals simultaneously with the control effort. Numerical simulations that were carried out using the backward sweep method and Runge–Kutta scheme suggest that optimal controls under moderate and high scenarios can effectively reduce the cases of measles. In particular, the moderate scenario that utilizes the existing coverage level of 86% for MCV1 and 69% for MCV2 can degrade the cost functional by 47% of the low scenario. Meanwhile, high scenario that takes the 2020 target of 96% as coverage only makes a slight difference in reducing the number of exposed and infected individuals.http://dx.doi.org/10.1155/2020/1561569 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jaharuddin Toni Bakhtiar |
spellingShingle |
Jaharuddin Toni Bakhtiar Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment International Journal of Mathematics and Mathematical Sciences |
author_facet |
Jaharuddin Toni Bakhtiar |
author_sort |
Jaharuddin |
title |
Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment |
title_short |
Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment |
title_full |
Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment |
title_fullStr |
Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment |
title_full_unstemmed |
Control Policy Mix in Measles Transmission Dynamics Using Vaccination, Therapy, and Treatment |
title_sort |
control policy mix in measles transmission dynamics using vaccination, therapy, and treatment |
publisher |
Hindawi Limited |
series |
International Journal of Mathematics and Mathematical Sciences |
issn |
0161-1712 1687-0425 |
publishDate |
2020-01-01 |
description |
This paper considers a deterministic model for the dynamics of measles transmission in a population divided into six classes with respect to the disease states: susceptible, vaccinated, exposed, infected, treated, and recovered. First, we investigate the dynamical properties of the SVEITR model such as its equilibrium points, their stability, and parameter sensitivity by applying constant controls. Criteria for determining the stability of disease-free and endemic equilibrium points are provided in terms of basic reproduction number. The model is then extended by incorporating vaccination, therapy, and treatment rates as time-dependent control variables representing the level of coverages. Application of Pontryagin’s maximum principle provides the necessary conditions that must be satisfied for the existence of optimal controls aiming at minimization of the number of exposed and infected individuals simultaneously with the control effort. Numerical simulations that were carried out using the backward sweep method and Runge–Kutta scheme suggest that optimal controls under moderate and high scenarios can effectively reduce the cases of measles. In particular, the moderate scenario that utilizes the existing coverage level of 86% for MCV1 and 69% for MCV2 can degrade the cost functional by 47% of the low scenario. Meanwhile, high scenario that takes the 2020 target of 96% as coverage only makes a slight difference in reducing the number of exposed and infected individuals. |
url |
http://dx.doi.org/10.1155/2020/1561569 |
work_keys_str_mv |
AT jaharuddin controlpolicymixinmeaslestransmissiondynamicsusingvaccinationtherapyandtreatment AT tonibakhtiar controlpolicymixinmeaslestransmissiondynamicsusingvaccinationtherapyandtreatment |
_version_ |
1715345878826352640 |