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Ali Traore

Author Information

Full Name: Ali Traore

Current Address: Laboratoire De Math ´Ematiques ET Informatique, Universit ´E Joseph Ki-zerbo, 03 BP 7021 Ouagadougou 03, Burkina Faso.

Email: traoreali.univ@yahoo.fr

ORCID: 0000-0001-6647-7985

Open AccessArticle

A Theoretical Assessment of the Effects of Hospital Resources on a Host-vector Disease

Rosaire Ouedraogo, Ali Traore* and Hamadoum Dicko

Annals of Communications in Mathematics 2025,

8 (1),

150-162

DOI: https://doi.org/10.62072/acm.2025.080112

AbstractThis paper provides a mathematical analysis of a host vectors disease model with the influence of available hospital resources. We derive the basic reproduction number Rh 0 of the model. We prove the existence of a unique disease-free equilibrium, which is stable when the basic reproduction number Rh 0 is less than 1, indicating that the disease can be eradicated under these conditions. However, when Rh 0 exceeds 1, the system exhibits multiple endemic equilibria, leading to the possible persistence of the disease into the population. The study also reveals the existence of bifurcations, indicating qualitative changes in the system’s dynamics depending on certain critical parameter values. A sensitivity analysis of the parameters is carried out to assess the most influential parameters in managing the epidemic.
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Open AccessArticle

Asymptotic Behavior of a Vector-host Disease Model with Piecewise-smooth Treatment

Ali Traore*, Issoufou Zore and Boureima Ouedraogo

Annals of Communications in Mathematics 2026,

9(1),

2

DOI: https://doi.org/10.62072/acm.2026.09002

ABSTRACT. In this paper, we analyze a vector-host epidemic model with a piecewise-smooth treatment rate. The use of piecewise-smooth treatment depicts the limited medical resource situation in the community. The treatment increases linearly with infective population until the treatment capacity is reached, after which constant treatment (i.e., maximum treatment) is applied. The analysis indicates that there exists a critical value \( I_{h0}^c = \frac{b_h}{\mu_h} \) for the infective human population level \( I_{h0} \) at which the health care system reaches its capacity. We derive that when \( I_{h0} \geq I_{h0}^c \), the dynamics of the model is completely determined by the basic reproduction number \( R_0 \). When \( I_{h0} < I_{h0}^c \), the model exhibits multiple endemic equilibria.
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