Loading [MathJax]/jax/output/SVG/jax.js
Research article

Dynamic analysis of a SIV Filippov system with media coverage and protective measures

  • This study aims to analyze a class of SIV systems considering the transmission rate influenced by media coverage and protective measures, in which the transmission rate is represented by a piecewise-smooth function. Firstly, for the SIV Filippov system, we take the dynamic behaviors of two subsystems into consideration, and obtain the basic reproduction number and the equilibria of the subsystems respectively. Secondly, based on the Filippov convex method, we calculate the sliding domain and the sliding mode equation, and further analyze the global dynamic behaviors of the system, through which we verify that there is no closed orbit in the system. Furthermore, we prove the global asymptotical stability of the disease-free equilibrium, two real equilibria, and the pseudo-equilibrium under certain conditions. The results demonstrate that the threshold value, the protective measures, and the media coverage could affect the number of infected individuals and the final scale of the disease. To prevent the spread of the disease, it is necessary to select an appropriate threshold and take applicable protective measures combined with media coverage. Lastly, we verify the validity of the results by numerical simulations.

    Citation: Shifan Luo, Dongshu Wang, Wenxiu Li. Dynamic analysis of a SIV Filippov system with media coverage and protective measures[J]. AIMS Mathematics, 2022, 7(7): 13469-13492. doi: 10.3934/math.2022745

    Related Papers:

    [1] Aziz Belmiloudi . Time-varying delays in electrophysiological wave propagation along cardiac tissue and minimax control problems associated with uncertain bidomain type models. AIMS Mathematics, 2019, 4(3): 928-983. doi: 10.3934/math.2019.3.928
    [2] Zuliang Lu, Xiankui Wu, Fei Huang, Fei Cai, Chunjuan Hou, Yin Yang . Convergence and quasi-optimality based on an adaptive finite element method for the bilinear optimal control problem. AIMS Mathematics, 2021, 6(9): 9510-9535. doi: 10.3934/math.2021553
    [3] Zahra Pirouzeh, Mohammad Hadi Noori Skandari, Kamele Nassiri Pirbazari, Stanford Shateyi . A pseudo-spectral approach for optimal control problems of variable-order fractional integro-differential equations. AIMS Mathematics, 2024, 9(9): 23692-23710. doi: 10.3934/math.20241151
    [4] Xin Yi, Rong Liu . An age-dependent hybrid system for optimal contraception control of vermin. AIMS Mathematics, 2025, 10(2): 2619-2633. doi: 10.3934/math.2025122
    [5] Yuanyuan Cheng, Yuan Li . A novel event-triggered constrained control for nonlinear discrete-time systems. AIMS Mathematics, 2023, 8(9): 20530-20545. doi: 10.3934/math.20231046
    [6] Woocheol Choi, Young-Pil Choi . A sharp error analysis for the DG method of optimal control problems. AIMS Mathematics, 2022, 7(5): 9117-9155. doi: 10.3934/math.2022506
    [7] Xiang Wu, Yuzhou Hou, Kanjian Zhang . Optimal feedback control for a class of fed-batch fermentation processes using switched dynamical system approach. AIMS Mathematics, 2022, 7(5): 9206-9231. doi: 10.3934/math.2022510
    [8] Tainian Zhang, Zhixue Luo . Optimal harvesting for a periodic competing system with size structure in a polluted environment. AIMS Mathematics, 2022, 7(8): 14696-14717. doi: 10.3934/math.2022808
    [9] Qian Li, Zhenghong Jin, Linyan Qiao, Aichun Du, Gang Liu . Distributed optimization of nonlinear singularly perturbed multi-agent systems via a small-gain approach and sliding mode control. AIMS Mathematics, 2024, 9(8): 20865-20886. doi: 10.3934/math.20241015
    [10] Asaf Khan, Gul Zaman, Roman Ullah, Nawazish Naveed . Optimal control strategies for a heroin epidemic model with age-dependent susceptibility and recovery-age. AIMS Mathematics, 2021, 6(2): 1377-1394. doi: 10.3934/math.2021086
  • This study aims to analyze a class of SIV systems considering the transmission rate influenced by media coverage and protective measures, in which the transmission rate is represented by a piecewise-smooth function. Firstly, for the SIV Filippov system, we take the dynamic behaviors of two subsystems into consideration, and obtain the basic reproduction number and the equilibria of the subsystems respectively. Secondly, based on the Filippov convex method, we calculate the sliding domain and the sliding mode equation, and further analyze the global dynamic behaviors of the system, through which we verify that there is no closed orbit in the system. Furthermore, we prove the global asymptotical stability of the disease-free equilibrium, two real equilibria, and the pseudo-equilibrium under certain conditions. The results demonstrate that the threshold value, the protective measures, and the media coverage could affect the number of infected individuals and the final scale of the disease. To prevent the spread of the disease, it is necessary to select an appropriate threshold and take applicable protective measures combined with media coverage. Lastly, we verify the validity of the results by numerical simulations.



    A century ago, the first metric fixed-point theorem was published by Banach [1]. In fact, before Banach, some famous mathematicians such as Picard and Liouville had used the fixed point approach to solve certain differential equations, more precisely, initial value problems. Inspired by their results, Banach considered it as a separated and independent result in the framework of the nonlinear functional analysis and point-set topology. The statement and the proof of an outstanding work of Banach, also known as contraction mapping principle, can be considered as an art piece: Each contraction, in the setting of a complete metric space, possesses a unique fixed point. Metric fixed point theory has been appreciated and investigated by several researchers. These researchers have different reasons and motivations to study this theory. The most important reason why the researchers find worthful to work and investigate metric fixed point theory is the natural and strong connection of the theoretical result in nonlinear functional analysis with applied sciences. If we look at it with the chronological aspect, we note that the fixed point theory was born as a tool to solve certain differential equations. Banach liberated the theory from being a tool in applied mathematics to an independent work of nonlinear functional analysis. On Picard and Liouville's side, it is a tool to solve the initial value problem. On the other side, from Banach's point of view, the fixed point theory is an independent research topic that has enormous application potential on almost all qualitative sciences, including applied mathematics. Secondly, Banach fixed point theorem not only guarantee the solution (the existence of a fixed point) but also indicate how we reach the mentioned solution (how to find the fixed point). Finally, we need to underline that almost all real world problems can be transferred to a fixed point problem, easily.

    With this motivation, several generalizations and extensions of Banach's fixed point theory have been released by introducing new contractions or by changing the structure of the studied abstract space. Among, we shall mention only a few of them that set up the skeleton of the contraction dealt with it. Historically, the first contraction we shall focus on it is the Meir-Keeler contraction [2]. Roughly speaking, the Meir-Keeler contraction can be considered as a uniform contraction. The second contraction that we dealt with is Jaggi contraction [3]. The interesting part of Jaggi's contraction is the following: Jaggi's contraction is one of the first of its kind that involves some rational expression. The last one is called as an interpolative contraction [4]. In the interpolative contraction the terms are used exponentially instead of standard usage of them.

    In this paper, we shall introduce a new contraction, hybrid Jaggi-Meir-Keeler type contraction, as a unification and generalization of the Meir-Keeler's contraction, the Jaggi's contraction and interpolative contraction in the setting of a complete metric space. We propose certain assumptions to guarantee the existence of a fixed point for such mappings. In addition, we express some example to indicate the validity of the derived results.

    Before going into details, we would like to reach a consensus by explaining the concepts and notations: Throughout the paper, we presume the sets, we deal with, are non-empty. The letter N presents the set of positive integers. Further, we assume that the pair (X,d) is a complete metric space. This notation is required in each of the following theorems, definitions, lemma and so on. We shall use the pair (X,d) everywhere without repeating that it is a complete metric space.

    In what follows we recall the notion of the uniform contraction which is also known as Meir-Keeler contraction:

    Definition 1.1. [2] A mapping f:(X,d)(X,d) is said to be a Meir-Keeler contraction on X, if for every E>0, there exists δ>0 such that

    Ed(x,y)<E+δimpliesd(fx,fy)<E, (1.1)

    for every x,yX.

    Theorem 1.1. [2] Any Meir-Keeler contraction f:(X,d)(X,d) possesses a unique fixed point.

    Very recently, Bisht and Rakočević [5] suggested the following extension of the uniform contraction:

    Theorem 1.2. [5] Suppose a mapping f:(X,d)(X,d) fulfills the following statements:

    (1) for a given E>0 there exists a δ(E)>0 such that

    E<M(x,y)<E+δ(E)impliesd(fx,fy)E;

    (2) d(fx,fy)<M(x,y), whenever M(x,y)>0;

    for any x,yX, where

    M(x,y)=max{d(x,y),αd(x,fx)+(1α)d(y,fy),(1α)d(x,fx)+αd(y,fy),β[d(x,fy)+d(y,fx)]2},

    with 0<α<1,0β<1.Then, f has a unique fixed point uX and fnxu for each xX.

    On the other hand, in 2018, the idea of interpolative contraction was consider to revisit the well-known Kannan's fixed point theorem [6]:

    Definition 1.2. [4] A mapping f:(X,d)(X,d) is said to be an interpolative Kannan type contraction on X if there exist κ[0,1) and γ(0,1) such that

    d(fx,fy)κ[d(x,fx)]γ[d(y,fy)]1γ, (1.2)

    for every x,yXFix(f), where Fix(f)={xX|fx=x}.

    Theorem 1.3. [4] Any interpolative Kannan-contraction mapping f:(X,d)(X,d) possesses a fixed point.

    For more interpolative contractions results, we refer to [7,8,9,10,11] and related references therein.

    Definition 1.3. A mapping f:(X,d)(X,d) is called a Jaggi type hybrid contraction if there is ψΨ so that

    d(fx,fy)ψ(Jsf(x,y)), (1.3)

    for all distinct x,yX where p0 and σi0,i=1,2,3,4, such that σ1+σ2=1 and

    Jsf(x,y)={[σ1(d(x,fx)d(y,fy)d(x,y))s+σ2(d(x,y))s]1/p,ifp>0,x,yX,xy(d(x,fx))σ1(d(y,fy))σ2,ifp=0,x,yXFf(X), (1.4)

    where Ff(X)={zX:fz=z}.

    Theorem 1.4. A continuous mapping f:(X,d)(X,d) possesses a fixed point x if it forms a Jaggi-type hybrid contraction.In particular, for any x0X, the sequence {fnx0} converges to x.

    Definition 1.4. [12] Let α:X×X[0,+) be a mapping, where X. A self-mapping f:(X,d)(X,d) is called triangular α-orbital admissible and denote as fTαX if

    α(x,fx)1impliesα(fx,f2x)1,

    and

    α(x,y)1,andα(y,fy)1,impliesα(x,fy)1

    for all x,yX.

    This concept, was used by many authors, in order to prove variant fixed point results (see, for instance [13,14,15,16,17,18,19] and the corresponding references therein).

    Lemma 1.1. [12] Assume that fTαX. If there exists x0X such that α(x0,fx0)1, then α(xm,xk)1, for all m,nN, where the sequence {xk} is defined by xk+1=xk.

    The following condition is frequently considered to avoid the continuity of the mappings involved.

    (R) if the sequence {xn} in X is such that for each nN,

    α(xn,xn+1)1andlimn+xn=xx,

    then there exists a subsequence {xn(j)} of {xn} such that

    α(xn(j),x)1, for each jN.

    We start this section by introducing the new contraction, namely, hybrid Jaggi-Meir-Keeler type contraction.

    Consider the mapping f:(X,d)(X,d) and the set of fixed point, Ff(X)={zX:fz=z}. We define the crucial expression Rsf as follows:

    Rsf(x,y)={[β1(d(x,fx)d(y,fy)d(x,y))s+β2(d(x,y))s+β3(d(x,fy)+d(y,fx)4)s]1/s,fors>0,x,yX,xy(d(x,fx))β1(d(y,fy))β2(d(x,fy)+d(y,fx)4)β3,fors=0,x,yX, (2.1)

    where p1 and βi0, i=1,2,3 are such that β1+β2+β3=1.

    Definition 2.1. Assume that fTαX. We say that f:(X,d)(X,d) is an α-hybrid Jaggi-Meir-Keeler type contraction on X, if for all distinct x,yX we have:

    (a1) for given E>0, there exists δ>0 such that

    E<max{d(x,y),Rsf(x,y)}<E+δα(x,y)d(fx,fy)E; (2.2)

    (a2)

    α(x,y)d(fx,fy)<max{d(x,y),Rsf(x,y)}. (2.3)

    Theorem 2.1. Any continuous α-hybrid Jaggi-Meir-Keeler type contraction f:(X,d)(X,d) provide a fixed point if there exists x0X, such that α(x0,fx0)1 and α(x0,f2x0)1.

    Proof. Let x0X be an arbitrary, but fixed point. We form the sequence {xm}, as follows:

    xm=fxm1=fmx0,

    for all mN and assume that d(xm,xm+1)>0, for all nN{0}. Indeed, if for some l0N{0} we have d(xl0,xl0+1)=0, it follows that xl0=xl0+1=fxl0. Therefore, xl0 is a fixed point of the mapping f and the proof is closed.

    Since, by assumption, the mapping f is triangular α-orbital admissible, it follows that

    α(x0,fx0)1α(x1,x2)=α(fx0,f2x0)1...
    α(xn,xn+1)1, (2.4)

    for every nN.

    We shall study two cases; these are s>0 and s=0.

    Case (A). For the case s>0, letting x=xn1 and y=xn=fxn1 in (a2), we get

    d(xn,xn+1)α(xn1,xn)d(fxn1,fxn)<max{d(xn1,xn),Rsf(xn1,xn)}, (2.5)

    where

    Rsf(xn1,xn)=[β1(d(xn1,fxn1)d(xn,fxn)d(xn1,xn))s+β2(d(xn1,xn))s++β3(d(xn1,fxn)+d(xn,fxn1)4)s]1/s=[β1(d(xn1,xn)d(xn,xn+1)d(xn1,xn))s+β2(d(xn1,xn))s++β3(d(xn1,xn+1)+d(xn,xn)4)s]1/s[β1(d(xn,xn+1))s+β2(d(xn1,xn))s++β3(d(xn1,xn)+d(xn,xn+1)4)s]1/s.

    If we can find n0N such that d(xn0,xn0+1)d(xn01,xn0), we have

    Rsf(xn01,xn0)[β1(d(xn0,xn0+1))s+β2(d(xn0,xn0+1))s++β3(d(xn0,xn0+1))s]1/s=d(xn0,xn0+1)(β1+β2+β3)1/s=d(xn0,xn0+1).

    Then, max{d(xn0,xn0+1),Rsf(xn01,xn0)}=d(xn0,xn0+1), and using (2.4), respectively (2.5) we get

    d(xn0,xn0+1)α(xn01,xn0)d(fxn+01,fxn0)<max{d(xn0,xn0+1),Rsf(xn01,xn0)}d(xn0,xn0+1),

    which is a contradiction. Therefore, d(xn,xn+1)<d(xn1,xn) for all nN and (2.5) becomes

    d(xn,xn+1)<d(xn1,xn),

    for all nN. Consequently, there exists b0 such that limn+d(xn1,xn)=b. If b>0, we have

    d(xm,xm+1)b>0,

    for any mN. On the one hand, since (2.2) holds for every given E>0, it is possible to choose E=b and let δ>0 be such that (2.2) is satisfied. On the other hand, since, also, limn+max{d(xn1,xn),Rsf(xn1,xn)}=b, there exists m0N such that

    b<max{d(xm01,xm0),Rsf(xm01,xm0)}<b+δ.

    Thus, by (2.2), together with (2.4) we obtain

    d(xm0,xm0+1)α(xm0,xm0+1)d(fxm01,fxm0)<b,

    which is a contradiction. Therefore,

    limn+d(xn,xn+1)=b=0. (2.6)

    We claim now that {xn} is a Cauchy sequence. Let E>0 be fixed and we can choose that δ=min{δ(E),E,1}. Thus, from (2.6) it follows that there exists j0N such that

    d(xn,xn+1)<δ2, (2.7)

    for all nj0. Now, we consider the set

    A={xl|lj0,d(xl,xj0)<E+δ2}. (2.8)

    We claim that fyA whenever y=xlA. Indeed, in case of l=j0, we have fxl=fxj0=xj0+1, and taking (2.7) into account, we get

    d(xj0,xj0+1)<δ2<E+δ2. (2.9)

    Thus, we will assume that l>j0, and we distinguish two cases, namely:

    Case 1. Suppose that

    E<d(xl,xj0)<E+δ2. (2.10)

    We have

    Rsf(xl,xj0)=[β1(d(xl,fxl)d(xj0,fxj0)d(xl,xj0))s+β2(d(xl,xj0))s+β3(d(xl,fxj0)+d(xj0,fxl)4)s]1/s=[β1(d(xl,xl+1)d(xj0,xj0+1)d(xl,xj0))s+β2(d(xl,xj0))s++β3(d(xl,xj0+1)+d(xj0,xl+1)4)s]1/s[β1(d(xl,xl+1)d(xj0,xj0+1)d(xl,xj0))s+β2(d(xl,xj0))s++β3(d(xl,xj0)+d(xj0,xj0+1)+d(xl,xj0)+d(xl,xl+1)4)s]1/s<[β1(d(xl,xl+1))s+β2(d(xl,xj0))s+β3(2d(xl,xj0)+d(xj0,xj0+1)+d(xl,xl+1)4)s]1/s<[β1(δ2)s+β2(E+δ2)s+β3(E2+δ4+δ4)s]1/s(β1+β2+β3)1/s(E+δ2)E+δ.

    In this case,

    E<d(xl,xj0)max{d(xl,xj0),Rsf(xl,xj0)}<max{(E+δ2),(E+δ)}=(E+δ),

    which implies by (a1) that

    α(xl,xj0)d(fxl,fxj0)E. (2.11)

    But, taking into account that the mapping f is triangular α-orbital admissible, together with (2.4) we have

    α(xn,xn+1)1 and α(xn+1,fxn+1)1 implies α(xn,xn+2)1,

    and recursively we get that

    α(xn,xl)1, (2.12)

    for all n,lN. Therefore, from (2.11) and (2.12), we have

    d(xl+1,xj0+1)=d(fxl,fxj0)E. (2.13)

    Now, by the triangle inequality together with (2.7)and (2.13) we get

    d(xl+1,xj0)d(xl+1,xj0+1)+d(xj0+1,xj0)<(E+δ2),

    which means that, indeed fxl=xl+1A.

    Case 2. Suppose that

    d(xl,xj0)E. (2.14)

    Thus,

    d(fxl,xj0)d(fxl,fxj0)+d(fxj0,xj0)α(xl,xj0)d(fxl,fxj0)+d(xj0+1,xj0)<max{d(xl,xj0),Rsf(xl,xj0)}+d(xj0+1,xj0), (2.15)

    where

    Rsf(xl,xj0)=[β1(d(xl,xl+1)d(xj0,xj0+1)d(xl,xj0))s+β2(d(xl,xj0))s++β3(d(xl,xj0)+d(xj0,xj0+1)+d(xl,xj0)+d(xl,xl+1)4)s]1/s.

    We must consider two subcases

    (2a). d(xl,xj0)d(xj0,xj0+1). Then,

    Rsf(xl,xj0)[β1(d(xl,xl+1))s+β2(d(xl,xj0))s++β3(2d(xl,xj0)+d(xj0,xj0+1)+d(xl,xl+1)4)s]1/s<[β1(δ2)s+β2(E))s+β3(2E+2δ24))s]1/s<[β1+β2+β3]1/s(E2+δ4).

    But, since δ=min{δ,E,1}, we get

    Rsf(xl,xj0)<3E4,

    and then

    d(fxl,xj0)<max{d(xl,xj0),Rsf(xl,xj0)}+d(xj0+1,xj0)<max{E,3E4}+δ2=(E+δ2),

    which shows that fxlA.

    (2b). d(xl,xj0)<d(xj0,xj0+1). Then,

    d(fxl,xj0)xl+1,xl)+d(xl,xj0)<δ2+δ2<E+δ2.

    Consequently, choosing some m,nN such that m>n>j0, we can write

    d(xm,xn)d(xm,xj0)+d(xj0,xn)<2(E+δ2)<4E,

    which leads us to

    limm,n+d(xm,xn)=0.

    Therefore, {xm} is a Cauchy sequence in a complete metric space. Thus, we can find a point uX such that limm+xm=u. Moreover, since the mapping f is continuous we have

    u=limm+fm+1x0=limm+f(fmx0)=f(limm+fmx0)=fu,

    that is, u is a fixed point of f.

    Case (B). For the case s=0, letting x=xn1 and y=xn=fxn1 in (2.2), we get

    d(xn,xn+1)α(xn1,xn)d(fxn1,fxn)<max{d(xn1,xn),Rf(xn1,xn)}, (2.16)

    where

    Rf(xn1,xn)=[d(xn1,fxn1)]β1[d(xn,fxn)]β2[d(xn1,fxn)+d(xn,fxn14]β3=[d(xn1,xn)]β1[d(xn,xn+1)]β2[d(xn1,xn+1)+d(xn,xn4]β3=[d(xn1,xn)]β1[d(xn,xn+1)]β2[d(xn1,xn+1)+d(xn,xn4]β3[d(xn1,xn)]β1[d(xn,xn+1)]β2[d(xn1,xn)+d(xn,xn+1)4]β3=[d(xn1,xn)]β1[d(xn,xn+1)]β2[d(xn1,xn)+d(xn,xn+1)4]β3

    Thus, by (2.3) and taking (2.4) into account we have

    d(xn,xn+1)α(xn1,xn)d(fxn1,fxn)<max{d(xn1,xn),Rf(xn1,xn)}.

    Now, if there exists n0N such that d(xn0,xn0+1)d(xn01,xn0), we get

    d(xn0,xn0+1)<max{d(xn01,xn0),Rf(xn01,xn0)}max{d(xn01,xn0),d(xn0,xn0+1)}<d(xn0,xn0+1),

    which is a contradiction. Therefore, d(xn,xn+1)<d(xn1,xn) for all nN, that is, the sequence {xn} decreasing and moreover, converges to some b0. Moreover, since

    Rf(xn1,xn)=[d(xn1,xn)]β1[d(xn,xn+1)]β2[d(xn1,xn+1)4]β3,

    we get that

    limn+max{d(xn1,xn),Rf(xn1,xn)}=b.

    If we suppose that b>0, then, 0<b<d(xn1,xn) and we can find δ>0 such that

    b<max{d(xn1,xn),Rf(xn1,xn)}<b+δ.

    In this way, taking E=b, we get

    b=E<max{d(xn1,xn),Rf(xn1,xn)}<E+δ,

    which implies (by (a1)) that

    d(xn1,xn)α(xn1,xn)d(fxn1,fxn))E=b,

    which is a contradiction. We thus proved that

    limmd(xn1,xn)=0. (2.17)

    We claim now, that the sequence {xn} is Cauchy. Firstly, we remark that, since d(xn1,xn)=0, there exists j0N, such that

    d(xn1,xn)<δ2, (2.18)

    for any nj0, where δ=min{δ,E,1}. Reasoning by induction, we will prove that the following relation

    d(xj0,xj0+m)<E+δ2 (2.19)

    holds, for any mN. Indeed, in case of m=1,

    d(xj0,xj0+1)<δ2<E+δ2,

    so, (2.19) is true. Now, supposing that (2.19) holds for some l, we shall show that it holds for l+1. We have

    Rf(xj0,xj0+l)=(d(xj0,fxj0))β1(xj0+l,fxj0+l)s(d(xj0,fxj0+l)+d(xj0+l,fxj0)4)β3=(d(xj0,xj0+1))β1(xj0+l,xj0+l+1)s(d(xj0,xj0+l+1)+d(xj0+l,xj0+1)4)β3(d(xj0,xj0+1))β1(d(xj0+l,xj0+l+1))s(d(xj0,xj0+l)+d(xj0+l,xj0+l+1)+d(xj0+l,xj0)+d(xj0,xj0+1)4)β3<(δ2)β1+β2((E2+δ4)+δ4)β3(E+δ2). (2.20)

    As in the Case (A), if d(xj0,xj0+l)>E, by (a2), and keeping in mind the above inequalities, we get

    E<d(xj0,xj0+l)max{d(xj0,xj0+l),Rf(xj0,xj0+l)}<max{δ2,(E+δ2)}=E+δ implies α(xj0,xj0+l)d(fxj0,fxj0+l)E.

    But, since using (2.12), it follows that

    d(xj0+1,xj0+l+1)=d(fxj0,fxj0+l)E,

    and then, by (b3) we get

    d(xj0,xj0+l+1)d(xj0,xj0+1)+d(xj0+1,xj0+l+1)<δ2+E<E+δ2.

    Therefore, (2.19) holds for (l+1). In the opposite situation, if d(xj0,xj0+l)E, again by the triangle inequality, we obtain

    d(xj0,xj0+l+1)d(xj0,xj0+1)+d(xj0+1,xj0+l+1)d(xj0,xj0+1)+α(xj0,xj0+l)d(fxj0,fxj0+l)<δ2+max{d(xj0,xj0+l),Rf(xj0,xl)}<δ2+max{E,E2+δ4}=δ2+E.

    Consequently, the induction is completed. Therefore, {xm} is a Cauchy sequence in a complete metric space. Thus, there exists uX such that fu=u.

    In the above Theorem, the continuity condition of the mapping f can be replace by the continuity of f2.

    Theorem 2.2. Suppose that f:(X,d)(X,d) forms an α-hybrid Jaggi-Meir-Keeler type contraction such that f2 is continuous.Then, f has a fixed point, provided that there exists x0X, such that α(x0,fx0)1.

    Proof. Let x0X such that α(x0,fx0)1 and the sequence {xn}, where xn=fxn1, for any nN. Thus, from Theorem 2.3 we know that this is a convergent sequence. Letting u=limn+xn, we claim that u=fu.

    Since the mapping f2 is supposed to be continuous,

    f2u=limn+f2xn=u.

    Assuming on the contrary, that ufu, we have

    Rsf(u,fu)={[β1(d(u,fu)d(fu,f2u)d(u,fu))s+β2(d(u,fu))s+β3(d(u,f2u)+d(fu,fu)4)s]1/s,fors>0(d(u,fu))β1(d(fu,f2u))β2(d(u,f2u)+d(fu,fu)4)β3,fors=0[16pt]={[β1(d(u,fu)d(fu,u)d(u,fu))s+β2(d(u,fu))s+β3(d(u,u)+d(fu,fu)4)s]1/s,fors>0(d(u,fu))β1(d(fu,u))β2(d(u,u)+d(fu,fu)4)β3,fors=0[16pt]={[β1(d(fu,u))s+β2(d(u,fu))s]1/s,fors>00,fors=0={[β1+β2]1/sd(u,fu)),fors>00,fors=0

    Example 2.1. Let X=[0,+), d:X×X[0,+), d(x,y)=|xy|, and the mapping f:XX, where

    f={12,ifx[0,1]16,ifx>1.

    We can easily observe that f is discontinuous at the point x=1, but f2 is a continuous mapping. Let also the function α:X×X[0,+),

    α(x,y)={x2+y2+1,ifx,y[0,1]ln(x+y)+1,ifx,y(1,+)1,ifx=56,y=760, otherwise ,

    and we choose β1=14,β2=12,β1=14 and s=2. The mapping f is triangular α-orbital admissible and satisfies (a2) in Definition 2.1 for any x,y[0,1], respectively for x,y(1,+). Taking into account the definition of the function α, we have more to check the case x=56, y=76. We have

    Rf(56,76)=[14(d(56,f56)d(76,f76)d(56,76))2+12(d(56,76))2+14(d(56,f76)+d(76,f56)4)2]1/2=14+1219+19=13.

    Therefore,

    α(56,76)d(f56,f76)=d(f56,f76)=d(12,16)=13<13=max{d(56,76),Rf(56,76)}.

    Moreover, since the mapping f satisfies condition (a1) for

    δ(E)={1E,forE<11,forE1,

    it follows that the assumptions of Theorem 2.3 are satisfied, and u=12 ia a fixed point of the mapping f.

    Theorem 2.3. If to the hypotheses of Theorem we add the following assumption

    α(u,v)1for anyu,vFf(X),

    then the mapping f admits an unique fixed point.

    Proof. Let uX be a fixed point of f. Supposing on the contrary, that we can find vX such that fu=uv=fv, we have

    (i) For s>0,

    Rsf=[β1(d(u,fu)d(v,fv)d(u,v))s+β2(d(u,v))s+β3(d(u,fv)+d(v,fu)4)s]1/s=[β2(d(u,v))s+β3(d(u,v)2)s]1/s(β2+β3)1/sd(u,v)d(u,v).

    Thus, taking x=u and y=v in (2.3) we get

    d(u,v)α(u,v)d(fu,fv)<max{d(u,v),Rf(u,v)}=d(u,v),

    which is a contradiction.

    (ii) For s=0,

    d(u,v)α(u,v)d(fu,fv)<max{d(u,v),Rf(u,v)}=max{d(u,v),(d(u,fu))β1(d(v,fv))β2(d(u,fv)+d(v,fu)4)β3}=d(u,v),

    which is a contradiction.

    Consequently, if there exists a fixed point of the mapping f, under the assumptions of the theorem, this is unique.

    Example 2.2. Let the set X=[1,+), d:X×X[0,+), d(x,y)=|xy|, and the mapping f:XX, where

    fx={x2+1,ifx[1,0)1,ifx[0,1]1x,ifx>1.

    Let also α:X×X[0,+) defined as follows

    α(x,y)={34,ifx,y[1,0)x2+y2+1,ifx,y[0,1]1,ifx[1,0),y[0,1]0, otherwise .

    It is easy to check that, with these chooses, f is a continuous triangular α-orbital admissible mapping and also, it follows that the mapping f satisfies the conditions (a2) from Definition (2.1). Moreover, f satisfies the condition (a1), considering δ(E)=1E in case of E<1 and δ(E)=1 for E1. Consequently, f satisfies the conditions of Theorem 2.3 and has a unique fixed point, u=0.

    In particular, for the case s=0, the continuity assumption of the mapping f can be replace by the condition (R).

    Theorem 2.4. We presume thatf:(X,d)(X,d)TαX and fulfills

    (ai) for given E>0, there exists δ>0 such that

    E<O(x,y)<E+δimpliesα(x,y)d(fx,fy)E, (2.21)

    with

    O(x,y)=max{d(x,y),(d(x,fx))β1(d(y,fy))β2(d(x,fy)+d(y,fx)4)β3},

    for all x,yX, where βi0, i=1,2,3 so that β1+β2+β3=1;

    (aii)

    α(x,y)d(fx,fy)<O(x,y). (2.22)

    The mapping f has a unique fixed point provided that:

    (α1) there exists x0X such that α(x0,fx0)1;

    (α3) α(u,v)1 for any u,vFf(X);

    (α2) if the sequence {xn} in X is such that for each nN

    α(xn,xn+1)1andlimn+xn=xX,

    then there exists a subsequence {xn(j)} of {xn} such that

    α(xn(j),x)1,for eachjN.

    Proof. Let x0X such that α(x0,fx0)1. Then, we know (following the proof of Theorem 2.3) that the sequence {xn}, with xn=fnx0 is convergent; let u=limn+xn. On the other hand, from (α2), we can find a subsequence {xn(j)} of {xn} such that

    α(xn(j),u)1, for each jN.

    Since we can suppose that d(xn(j)+1,fu)>0, from (aii) we have

    d((xn(j)+1,fu))α(xn(j),u)d(fxn(j),fu)<O(x,y)=max{d(xn(j),u),(d(xn(j),fxn(j)))β1(d(u,fu))β2(d(xn(j),fu)+d(u,fxn(j))4)β3}=max{d(xn(j),u),(d(xn(j),xn(j)+1))β1(d(u,fu))β2(d(xn(j),fu)+d(u,xn(j)+1)4)β3}.

    Letting n+ in the above inequality, we get d(u,fu)=0. Thus, fu=u.

    To proof the uniqueness, we consider that we can find another fixed point of f. From (aii), we have

    d(u,v)=d(fu,fv)α(u,v)d(fu,fv)<O(u,v)=d(u,v)<d(u,v),

    which is a contradiction. Therefore, u=v.

    Considering α(x,y)=1 in the above theorems, we can easily obtain the following result.

    Definition 2.2. A mapping f:(X,d)(X,d) is called hybrid Jaggi-Meir-Keeler type contraction on X if for all distinct x,yX we have:

    (a1) for given E>0, there exists δ>0 such that

    E<max{d(x,y),Rsf(x,y)}<E+δd(fx,fy)E; (2.23)

    (a2) whenever Rf(x,y)>0,

    d(fx,fy)<max{d(x,y),Rsf(x,y)}. (2.24)

    Corollary 2.1. Any hybrid Jaggi-Meir-Keeler type contraction f:(X,d)(X,d) possesses a unique fixed point provided that f is continuous or f2 is continuous.

    The authors declare that they have no conflicts of interest.



    [1] G. Zaman, Y. H. Kang, I. H. Jung, Stability analysis and optimal vaccination of an SIR epidemic model, Biosystems, 93 (2008), 240â€"249. http://dx.doi.org/10.1016/j.biosystems.2008.05.004 doi: 10.1016/j.biosystems.2008.05.004
    [2] I. Cooper, A. Mondal, C. G. Antonopoulos, A SIR model assumption for the spread of COVID-19 in different communities, Chaos Soliton. Fract., 139 (2020), 110057. http://dx.doi.org/10.1016/j.chaos.2020.110057 doi: 10.1016/j.chaos.2020.110057
    [3] L. J. S Allen, Some discrete-time SI, SIR, and SIS epidemic models, Math. Biosci., 124 (1994), 83â€"105. http://dx.doi.org/10.1016/0025-5564(94)90025-6 doi: 10.1016/0025-5564(94)90025-6
    [4] Y. Enatsu, Y. Nakata, Y. Muroya, Global stability for a class of discrete SIR epidemic models, Math. Biosci. Eng., 7 (2010), 347â€"361. http://dx.doi.org/10.3934/mbe.2010.7.347 doi: 10.3934/mbe.2010.7.347
    [5] B. Shulgin, L. Stone, Z. Agur, Pulse vaccination strategy in the SIR epidemic model, Bull. Math. Biol., 60 (1998), 1123â€"1148. http://dx.doi.org/10.1006/s0092-8240(98)90005-2 doi: 10.1006/s0092-8240(98)90005-2
    [6] L. Stone, B. Shulgin, Z. Agur, Theoretical examination of the pulse vaccination policy in the SIR epidemic model, Math. Comput. Model., 31 (2000), 207â€"215. http://dx.doi.org/10.1016/S0895-7177(00)00040-6 doi: 10.1016/S0895-7177(00)00040-6
    [7] T. Zhao, Y. Xiao, Non-smooth plant disease models with economic thresholds, Math. Biosci., 241 (2013), 34â€"48. http://dx.doi.org/10.1016/j.mbs.2012.09.005 doi: 10.1016/j.mbs.2012.09.005
    [8] Z. Guo, L. Huang, X. Zou, Impact of discontinuous treatments on disease dynamics in an SIR epidemic model, Math. Biosci. Eng., 9 (2012), 97â€"110. http://dx.doi.org/10.3934/mbe.2012.9.97 doi: 10.3934/mbe.2012.9.97
    [9] Z. Guo, X. Zou, Impact of discontinuous harvesting on fishery dynamics in a stock-effort fishing model, Commun. Nonlinear Sci., 20 (2015), 594â€"603. http://dx.doi.org/10.1016/j.cnsns.2014.06.014 doi: 10.1016/j.cnsns.2014.06.014
    [10] L. Huang, H. Ma, J. Wang, C. Huang, Global dynamics of a Filippov plant disease model with an economic threshold of infected-susceptible ratio, J. Appl. Anal. Comput., 10 (2020), 2263â€"2277. http://dx.doi.org/10.11948/20190409 doi: 10.11948/20190409
    [11] W. Li, L. Huang, J. Wang, Global dynamics of Filippov-type plant disease models with an interaction ratio threshold, Math. Meth. Appl. Sci., 43 (2020), 6995â€"7008. http://dx.doi.org/10.1002/mma.6450 doi: 10.1002/mma.6450
    [12] Y. K. Xie, Z. Wang, A ratio-dependent impulsive control of an SIQS epidemic model with non-linear incidence, Appl. Math. Comput., 423 (2022), 127018. https://doi.org/10.1016/j.amc.2022.127018 doi: 10.1016/j.amc.2022.127018
    [13] Y. K. Xie, Z. Wang, Transmission dynamics, global stability and control strategies of a modified SIS epidemic model on complex networks with an infective medium, Math. Comput. Simul., 188 (2021), 23â€"34. https://doi.org/10.1016/j.matcom.2021.03.029 doi: 10.1016/j.matcom.2021.03.029
    [14] W. O. Kermack, A. G. McKendrick, A contribution to the mathematical theory of epidemics, P. Roy. Soc. A, 115 (1927), 700â€"721. http://dx.doi.org/10.1007/bf02464423 doi: 10.1007/bf02464423
    [15] W. O. Kermack, A. G. McKendrick, Contributions to the mathematical theory of epidemics â…¡.â€"-The problem of endemicity, P. Roy. Soc. A, 138 (1932), 55â€"83. http://dx.doi.org/10.1016/s0092-8240(05)80041-2 doi: 10.1016/s0092-8240(05)80041-2
    [16] W. O. Kermack, A. G. McKendrick, Contributions to the mathematical theory of epidemics â…¢.â€"-Further studies of the problem of endemicity, P. Roy. Soc. A, 141 (1933), 94â€"122. http://dx.doi.org/10.2307/96207 doi: 10.2307/96207
    [17] B Shulgin, L. W. Stone, Z. Agur, Pulse vaccination strategy in the SIR epidemic model, Bull. Math. Biol., 60 (1998), 1123â€"1148. http://dx.doi.org/10.1016/S0092-8240(98)90005-2 doi: 10.1016/S0092-8240(98)90005-2
    [18] A. B. Gumel, S. M. Moghadas, A qualitative study of a vaccination model with non-linear incidence, Appl. Math. Comput., 143 (2003), 409â€"419. http://dx.doi.org/10.1016/S0096-3003(02)00372-7 doi: 10.1016/S0096-3003(02)00372-7
    [19] S. Tang, J. Liang, Y. Xiao, R. A. Cheke, Sliding bifurcations of Filippov two stage pest control models with economic thresholds, SIAM J. Appl. Math., 72 (2012), 1061â€"1080. http://dx.doi.org/10.1137/110847020 doi: 10.1137/110847020
    [20] Y. Zhang, Y. Xiao, Global dynamics for a Filippov epidemic system with imperfect vaccination, Nonlinear Anal. Hybrid Syst., 38 (2020), 100932. http://dx.doi.org/10.1016/j.nahs.2020.100932 doi: 10.1016/j.nahs.2020.100932
    [21] A. P. Lemos-Paio, C. J. Silva, D. F. M. Torres, An epidemic model for cholera with optimal control treatment, J. Comput. Appl. Math., 318 (2017), 168â€"180. http://dx.doi.org/10.1016/j.cam.2016.11.002 doi: 10.1016/j.cam.2016.11.002
    [22] M. J. Jeger, L. V. Madden, F. V. D. Bosch, The effect of transmission route on plant virus epidemic development and disease control, J. Theor. Biol., 258 (2009), 198â€"207. http://dx.doi.org/10.1016/j.jtbi.2009.01.012 doi: 10.1016/j.jtbi.2009.01.012
    [23] V. C. C. Cheng, S. C. Wong, V. W. M. Chuang, S. Y. C. So, J. H. K. Chen, S. Sridhar, et al., The role of community-wide wearing of face mask for control of coronavirus disease 2019 (COVID-19) epidemic due to SARS-CoV-2, J. Infect., 81 (2020), 107â€"114. http://dx.doi.org/10.1016/j.jinf.2020.04.024 doi: 10.1016/j.jinf.2020.04.024
    [24] S. E. Eikenberry, M. Mancuso, E. Iboi, T. Phan, K. Eikenberry, Y. Kuang, et al., To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the covid-19 pandemic, Infect. Dis. Model., 5 (2020), 293â€"308. http://dx.doi.org/10.1101/2020.04.06.20055624 doi: 10.1101/2020.04.06.20055624
    [25] C. R. MacIntyre, S. Cauchemez, D. E. Dwyer, H. Seale, P. Cheung, G. Browne, et al., Face mask use and control of respiratory virus transmission in households, Emerg. Infect. Dis., 15 (2009), 233. http://dx.doi.org/10.3201/eid1502.081167 doi: 10.3201/eid1502.081167
    [26] Z. Tai, T. Sun, Media dependencies in a changing media environment: The case of the 2003 SARS epidemic in China, New Media Soc., 9 (2007), 987â€"1009. http://dx.doi.org/10.1177/1461444807082691 doi: 10.1177/1461444807082691
    [27] S. Collinson, J. M. Heffernan, Modelling the effects of media during an influenza epidemic, BMC Public Health, 14 (2014), 1â€"10. http://dx.doi.org/10.1186/1471-2458-14-376 doi: 10.1186/1471-2458-14-376
    [28] R. M. Anderson, R. M. May, Infectious diseases of humans: Dynamics and control, Oxford: Oxford Science Publications, 1992. http://dx.doi.org/10.1126/science.254.5031.591
    [29] J. Cui, Y. Sun, H. Zhu, The impact of media on the spreading and control of infectious disease, J. Dyn. Differ. Equ., 20 (2008), 31â€"53. http://dx.doi.org/10.1007/s10884-007-9075-0 doi: 10.1007/s10884-007-9075-0
    [30] J. Deng, S. Tang, H. Shu, Joint impacts of media, vaccination and treatment on an epidemic Filippov model with application to COVID-19, J. Theor. Biol., 523 (2021), 110698. http://dx.doi.org/10.1016/j.jtbi.2021.110698 doi: 10.1016/j.jtbi.2021.110698
    [31] A. Wang, Y. Xiao, A Filippov system describing media effects on the spread of infectious diseases, Nonlinear Anal. Hybrid Syst., 11 (2014), 84â€"97. http://dx.doi.org/10.1016/j.nahs.2013.06.005 doi: 10.1016/j.nahs.2013.06.005
    [32] J. Wang, F. Zhang, L. Wang, Equilibrium, pseudoequilibrium and sliding-mode heteroclinic orbit in a Filippov-type plant disease model, Nonlinear Anal.-Real, 31 (2016), 308â€"324. http://dx.doi.org/10.1016/j.nonrwa.2016.01.017 doi: 10.1016/j.nonrwa.2016.01.017
    [33] W. Li, L. Huang, J. Wang, Dynamic analysis of discontinuous plant disease models with a non-smooth separation line, Nonlinear Dyn., 99 (2020), 1675â€"1697. http://dx.doi.org/10.1007/s11071-019-05384-w doi: 10.1007/s11071-019-05384-w
    [34] A. F. Filippov, Differential equations with discontinuous right-hand side, Dordrecht: Kluwer Academic, 1988. http://dx.doi.org/10.1016/0022-247X(91)90044-Z
    [35] X. Chen, L. Huang, A Filippov system describing the effect of prey refuge use on a ratio-dependent predator-prey model, J. Math. Anal. Appl., 428 (2015), 817â€"837. http://dx.doi.org/10.1016/j.jmaa.2015.03.045 doi: 10.1016/j.jmaa.2015.03.045
    [36] A. Wang, Y. Xiao, Sliding bifurcation and global dynamics of a Filippov epidemic model with vaccination, Int. J. Bifurcat. Chaos, 23 (2013), 1350144. http://dx.doi.org/10.1142/S0218127413501447 doi: 10.1142/S0218127413501447
    [37] M. di Bernardo, C. J. Budd, A. R. Champneys, P. Kowalczyk, A. B. Nordmark, Bifurcation in nonsmooth dynamical systems, SIAM Rev., 50 (2008), 629â€"701. http://dx.doi.org/10.1137/050625060 doi: 10.1137/050625060
    [38] Y. A. Kuznetsov, S. Rinaldi, A. Gragnani, One parameter bifurcations in planar Filippov systems, Int. J. Bifurcat. Chaos, 13 (2003), 2157â€"2188. http://dx.doi.org/10.1142/S0218127403007874 doi: 10.1142/S0218127403007874
    [39] P. V. D. Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29â€"48. http://dx.doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6
    [40] Z. Ma, Y. Zhou, C. Li, Qualitative and stability methods for ordinary differential equations, Beijing: Science Press, 2015.
    [41] R. M. Corless, G. H. Gonnet, D. E. G. Hare, D. J. Jeffrey, D. E. Kunth, On the Lambert W function, Adv. Comput. Math., 5 (1996), 329â€"359. http://dx.doi.org/10.1007/BF02124750 doi: 10.1007/BF02124750
  • This article has been cited by:

    1. Sana Hadj Amor, Ameni Remadi, Self similarity sets via fixed point theory with lack of convexity, 2023, 37, 0354-5180, 10055, 10.2298/FIL2329055A
    2. Vo Tri, Continuous dependence on parameters of differential inclusion using new techniques of fixed point theory, 2023, 37, 0354-5180, 5469, 10.2298/FIL2316469T
    3. Mohammed Shehu Shagari, Manzuma Mustapha, Hala H. Taha, Sarah Aljohani, Nabil Mlaiki, On Combinational Contractions with Applications, 2025, 24058440, e41905, 10.1016/j.heliyon.2025.e41905
    4. Mohammed Shehu Shagari, Faryad Ali, Monairah Alansari, Akbar Azam, New views on RLC-electric circuit models via combinational contractions, 2025, 2025, 1687-2770, 10.1186/s13661-025-02068-w
    5. Sirajo Yahaya, Mohammed Shagari, Ibrahim Fulatan, Fixed points of bilateral multivalued contractions, 2024, 38, 0354-5180, 2835, 10.2298/FIL2408835Y
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2255) PDF downloads(85) Cited by(3)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog