Please use this identifier to cite or link to this item: https://repository.seku.ac.ke/handle/123456789/8114
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dc.contributor.authorTilahun, Getachew T.-
dc.contributor.authorMakinde, Oluwole D.-
dc.contributor.authorMalonza, David M.-
dc.date.accessioned2025-07-11T09:04:06Z-
dc.date.available2025-07-11T09:04:06Z-
dc.date.issued2017-06-14-
dc.identifier.citationJournal of biological dynamics, volume 11, (sup2), pp 400-426, 2017en_US
dc.identifier.issn1751-3766-
dc.identifier.urihttps://www.tandfonline.com/doi/pdf/10.1080/17513758.2017.1337245-
dc.identifier.urihttp://repository.seku.ac.ke/xmlui/handle/123456789/8114-
dc.descriptionhttps://doi.org/10.1080/17513758.2017.1337245en_US
dc.description.abstractWe propose and analyse a nonlinear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the asymptotic stability conditions for the disease free and as well as for the endemic equilibria are established. The possibility of bifurcation of the model and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies: namely disease prevention through education, treatment and screening. The cost-effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost-effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphicallyen_US
dc.language.isoenen_US
dc.publisherTaylor and Francisen_US
dc.subjectPneumonia dynamicsen_US
dc.subjectstability analysisen_US
dc.subjectoptimal controlen_US
dc.subjectcost-effectiveness analysisen_US
dc.subjectnumerical simulationen_US
dc.titleModelling and optimal control of pneumonia disease with cost-effective strategiesen_US
dc.typeArticleen_US
Appears in Collections:School of Science and Computing (JA)

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