Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance
Influenza and pneumonia independently lead to high morbidity and mortality annually among the human population globally; however, a glaring fact is that influenza pneumonia coinfection is more vicious and it is a threat to public health. Emergence of antiviral resistance is a major impediment in the...
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Online Access: | http://dx.doi.org/10.1155/2020/5984095 |
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doaj-ee6678bb15fc4a0190b033619bc9ac722020-11-25T03:20:41ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182020-01-01202010.1155/2020/59840955984095Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral ResistanceCaroline W. Kanyiri0Livingstone Luboobi1Mark Kimathi2Department of Mathematics, Pan African University Institute of Basic Sciences, Technology and Innovation, P.O. Box 62000-00200, Nairobi, KenyaInstitute of Mathematical Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, KenyaDepartment of Mathematics, Machakos University, P.O. Box 139-90100, Machakos, KenyaInfluenza and pneumonia independently lead to high morbidity and mortality annually among the human population globally; however, a glaring fact is that influenza pneumonia coinfection is more vicious and it is a threat to public health. Emergence of antiviral resistance is a major impediment in the control of the coinfection. In this paper, a deterministic mathematical model illustrating the transmission dynamics of influenza pneumonia coinfection is formulated having incorporated antiviral resistance. Optimal control theory is then applied to investigate optimal strategies for controlling the coinfection using prevalence reduction and treatment as the system control variables. Pontryagin’s maximum principle is used to characterize the optimal control. The derived optimality system is solved numerically using the Runge–Kutta-based forward-backward sweep method. Simulation results reveal that implementation of prevention measures is sufficient to eradicate influenza pneumonia coinfection from a given population. The prevention measures could be social distancing, vaccination, curbing mutation and reassortment, and curbing interspecies movement of the influenza virus.http://dx.doi.org/10.1155/2020/5984095 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Caroline W. Kanyiri Livingstone Luboobi Mark Kimathi |
spellingShingle |
Caroline W. Kanyiri Livingstone Luboobi Mark Kimathi Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance Computational and Mathematical Methods in Medicine |
author_facet |
Caroline W. Kanyiri Livingstone Luboobi Mark Kimathi |
author_sort |
Caroline W. Kanyiri |
title |
Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance |
title_short |
Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance |
title_full |
Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance |
title_fullStr |
Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance |
title_full_unstemmed |
Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance |
title_sort |
application of optimal control to influenza pneumonia coinfection with antiviral resistance |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2020-01-01 |
description |
Influenza and pneumonia independently lead to high morbidity and mortality annually among the human population globally; however, a glaring fact is that influenza pneumonia coinfection is more vicious and it is a threat to public health. Emergence of antiviral resistance is a major impediment in the control of the coinfection. In this paper, a deterministic mathematical model illustrating the transmission dynamics of influenza pneumonia coinfection is formulated having incorporated antiviral resistance. Optimal control theory is then applied to investigate optimal strategies for controlling the coinfection using prevalence reduction and treatment as the system control variables. Pontryagin’s maximum principle is used to characterize the optimal control. The derived optimality system is solved numerically using the Runge–Kutta-based forward-backward sweep method. Simulation results reveal that implementation of prevention measures is sufficient to eradicate influenza pneumonia coinfection from a given population. The prevention measures could be social distancing, vaccination, curbing mutation and reassortment, and curbing interspecies movement of the influenza virus. |
url |
http://dx.doi.org/10.1155/2020/5984095 |
work_keys_str_mv |
AT carolinewkanyiri applicationofoptimalcontroltoinfluenzapneumoniacoinfectionwithantiviralresistance AT livingstoneluboobi applicationofoptimalcontroltoinfluenzapneumoniacoinfectionwithantiviralresistance AT markkimathi applicationofoptimalcontroltoinfluenzapneumoniacoinfectionwithantiviralresistance |
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