We develop in this paper a Susceptible Exposed Infectious Hospitalized and Recovered (SEIHR), spread model. In the model studied, we introduce a recruitment constant, to take into account the fact ...that newborns can transmit disease. The disease-free and endemic equilibrium points are computed and analyzed. The basic reproduction number
is acquired, when
≤ 1, the disease dies out and persists in the community whenever
> 1. From numerical simulation, we illustrate our theoretical analysis.
In this paper, we propose to study a class of discrete schistosomiasis models with general incidence function. This model is derived from a continuous schistosomiasis model (in Appl. Math. ...4:1682-1693,
2003
) by using the backward Euler discretization method with step size
h
=
1
. We visit some basic properties of this discrete model and we study the stabilities of the equilibria by constructing some appropriate Lyapunov functional for the endemic equilibrium.
We prove the existence of weak solutions for an anisotropic homoclinic discrete nonlinear system. Suitable Hilbert spaces and norms are constructed. The proof of the main result is based on a ...minimization method. We also extend the problem by using generalized penality and source functions.
In this article, we prove the existence and uniqueness of solutions for a family of discrete boundary value problems for data
f
which belongs to a discrete Hilbert space
W
.
2010 Mathematics Subject ...Classification:
47A75; 35B38; 35P30; 34L05; 34L30.
In this article, we prove the existence of heteroclinic solutions for a family of anisotropic difference equations. The proof of the main result is based on a minimization method, a change of ...variables and a discrete Holder type inequality.
In this paper, we prove the existence of weak heteroclinic solutions for a family of anisotropic difference equations under competition phenomena between parameters.
In this article, we are working on an SEIR-SI type model for dengue disease in order to better observe the dynamics of infection in human beings. We calculate the basic reproduction number
R
0
and ...determine the equilibrium points. We then show the existence of global stability in each of the different states depending on the value of
R
0
. Moreover, to support the theoretical work, we present numerical simulations obtained using Python. We also study the sensitivity of the parameters included in the expression of
R
0
with the aim of identifying the most influential parameters in the dynamics of dengue disease spread. Finally, we introduce two functions u and v, respectively indicating the treatment of the infected people and any prevention system minimizing contact between humans and the disease causing vectors. We present the curves of the controlled system after calculating the optimal pair of controls capable of reducing the dynamics of the disease spread, still using Python.
One of the first environmental crises to attract interest in development initiatives and aid was the great drought of the 1970s in the Sahel. This study investigates the extent of damage caused by ...natural disasters from one of the most widely used databases—EM-DAT—with a sample size of 16 Sahelian countries over the period 1960–2020. These countries have been divided into three regions: Western Africa Sahel (WAS), Central Africa Sahel (CAS), and Eastern Africa Sahel (EAS). The analyses encompass four categories of natural hazards, namely, biological, climatological, hydrological, and meteorological. We used descriptive and test statistics to summarize the natural disaster records. Through this approach, we explore tendencies to identify the most frequently reported natural hazards; we examine their spatial distribution and evaluate their impacts in terms of socioeconomic damage and causalities. During the study period, a total of 1000 events were recorded in the database. The Western Africa Sahel (WAS) region had the highest number of disasters, with 476 events, followed by the Eastern Africa Sahel (EAS) region with 369 events. The most common hazards in the Sahel were hydrological (41.8%), mainly floods, and biological (39.5%) hazards. Approximately 300 million people in the Sahel were affected by natural hazards, with 59.17% in EAS, 36.48% in WAS, and 4.35% in CAS. Although droughts occurred less frequently (14%), they had a significant impact on the population, affecting 84% of those affected by natural hazards. In general, EAS experiences a higher impact from natural hazards, potentially influenced by the pastoral lifestyle of its population. However, WAS is also very vulnerable to natural hazards especially epidemics and nowadays floods. The uncontrolled urbanization in the area may contribute to this vulnerability.
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