2013
DOI: 10.4236/am.2013.412229
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Deterministic and Stochastic Schistosomiasis Models with General Incidence

Abstract: In this paper, deterministic and stochastic models for schistosomiasis involving four sub-populations are developed. Conditions are given under which system exhibits thresholds behavior. The disease-free equilibrium is globally asymptotically stable if and the unique endemic equilibrium is globally asymptotically stable when . The populations are computationally simulated under various conditions. Comparisons are made between the deterministic and the stochastic model.

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Cited by 3 publications
(4 citation statements)
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“…Under a given condition, the model (1) admits a random endemic equilibrium exponentially p-stable (p ≥ 2) and globally stable. The introduction of a treatment control function in model (1) gives an optimal control problem governed by model (22). The Projection Gradient method permits to determine numerically the optimal control as well as the cost function corresponding to this problem.…”
Section: Discussionmentioning
confidence: 99%
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“…Under a given condition, the model (1) admits a random endemic equilibrium exponentially p-stable (p ≥ 2) and globally stable. The introduction of a treatment control function in model (1) gives an optimal control problem governed by model (22). The Projection Gradient method permits to determine numerically the optimal control as well as the cost function corresponding to this problem.…”
Section: Discussionmentioning
confidence: 99%
“…The Projection Gradient Method applied to the stochastic model of TB with control, consist therefore in considering the system (30) of two equations (22) and (28) in order to solve it numerically,…”
Section: B Gradient Projection Methodsmentioning
confidence: 99%
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