Optimal control in a malaria model: intervention of fumigation and bed nets
Abstract Malaria is one of the world’s most serious health problems because of the increasing number of cases every year. First, we discuss a deterministic model of epidemic SIR-SI spread of malaria with the intervention of bed nets and fumigation. We found that the malaria-free equilibrium is local...
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doaj-9170305565ad46378edfd6c2f6472c492020-12-06T12:48:47ZengSpringerOpenAdvances in Difference Equations1687-18472019-12-012019112510.1186/s13662-019-2424-6Optimal control in a malaria model: intervention of fumigation and bed netsBevina D. Handari0Febyan Vitra1Radhiya Ahya2Tengku Nadya S.3Dipo Aldila4Department of Mathematics, Universitas IndonesiaDepartment of Mathematics, Universitas IndonesiaDepartment of Mathematics, Universitas IndonesiaDepartment of Mathematics, Universitas IndonesiaDepartment of Mathematics, Universitas IndonesiaAbstract Malaria is one of the world’s most serious health problems because of the increasing number of cases every year. First, we discuss a deterministic model of epidemic SIR-SI spread of malaria with the intervention of bed nets and fumigation. We found that the malaria-free equilibrium is locally asymptotically stable (LAS) when R0<1 $\mathcal{R}_{0} <1$ and unstable otherwise. A malaria endemic equilibrium exists and is LAS when R0>1 $\mathcal{R}_{0} >1$. Sensitivity analysis of R0 $\mathcal{R}_{0} $ shows that the use of bed nets and fumigation can reduce R0 $\mathcal{R}_{0}$. We modify the previous model into a stochastic differential equation model to understand the effect of random environmental factors on the spread of malaria. Numerical simulations show that when R0>1 $\mathcal{R}_{0} >1$, a greater value of noise intensity σ generates a solution that is different from a deterministic solution; when R0<1 $\mathcal{R}_{0} <1$, regardless of the σ value, the solution approaches a deterministic solution. Then the deterministic model was modified into an optimal control model to determine the best strategy in controlling the spread of malaria by using fumigation as the control variable. Numerical simulations show that periodic fumigations cost less than constant intervention and can reduce the number of infected humans. Priority is given to the endemic prevention strategy rather than to the endemic reduction strategy. For more effective intervention, the value of R0 $\mathcal{R}_{0}$ should receive close attention. A potentially endemic ( R0>1 $\mathcal{R}_{0}>1$) environment requires more frequent fumigation than an environment that is not potentially endemic ( R0<1 $\mathcal{R}_{0}<1$). A combination of the use of bed nets and fumigation can reduce the number of infected individuals at minimal cost.https://doi.org/10.1186/s13662-019-2424-6MalariaOptimal control problemFumigationStochastic differential equation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bevina D. Handari Febyan Vitra Radhiya Ahya Tengku Nadya S. Dipo Aldila |
spellingShingle |
Bevina D. Handari Febyan Vitra Radhiya Ahya Tengku Nadya S. Dipo Aldila Optimal control in a malaria model: intervention of fumigation and bed nets Advances in Difference Equations Malaria Optimal control problem Fumigation Stochastic differential equation |
author_facet |
Bevina D. Handari Febyan Vitra Radhiya Ahya Tengku Nadya S. Dipo Aldila |
author_sort |
Bevina D. Handari |
title |
Optimal control in a malaria model: intervention of fumigation and bed nets |
title_short |
Optimal control in a malaria model: intervention of fumigation and bed nets |
title_full |
Optimal control in a malaria model: intervention of fumigation and bed nets |
title_fullStr |
Optimal control in a malaria model: intervention of fumigation and bed nets |
title_full_unstemmed |
Optimal control in a malaria model: intervention of fumigation and bed nets |
title_sort |
optimal control in a malaria model: intervention of fumigation and bed nets |
publisher |
SpringerOpen |
series |
Advances in Difference Equations |
issn |
1687-1847 |
publishDate |
2019-12-01 |
description |
Abstract Malaria is one of the world’s most serious health problems because of the increasing number of cases every year. First, we discuss a deterministic model of epidemic SIR-SI spread of malaria with the intervention of bed nets and fumigation. We found that the malaria-free equilibrium is locally asymptotically stable (LAS) when R0<1 $\mathcal{R}_{0} <1$ and unstable otherwise. A malaria endemic equilibrium exists and is LAS when R0>1 $\mathcal{R}_{0} >1$. Sensitivity analysis of R0 $\mathcal{R}_{0} $ shows that the use of bed nets and fumigation can reduce R0 $\mathcal{R}_{0}$. We modify the previous model into a stochastic differential equation model to understand the effect of random environmental factors on the spread of malaria. Numerical simulations show that when R0>1 $\mathcal{R}_{0} >1$, a greater value of noise intensity σ generates a solution that is different from a deterministic solution; when R0<1 $\mathcal{R}_{0} <1$, regardless of the σ value, the solution approaches a deterministic solution. Then the deterministic model was modified into an optimal control model to determine the best strategy in controlling the spread of malaria by using fumigation as the control variable. Numerical simulations show that periodic fumigations cost less than constant intervention and can reduce the number of infected humans. Priority is given to the endemic prevention strategy rather than to the endemic reduction strategy. For more effective intervention, the value of R0 $\mathcal{R}_{0}$ should receive close attention. A potentially endemic ( R0>1 $\mathcal{R}_{0}>1$) environment requires more frequent fumigation than an environment that is not potentially endemic ( R0<1 $\mathcal{R}_{0}<1$). A combination of the use of bed nets and fumigation can reduce the number of infected individuals at minimal cost. |
topic |
Malaria Optimal control problem Fumigation Stochastic differential equation |
url |
https://doi.org/10.1186/s13662-019-2424-6 |
work_keys_str_mv |
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