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In this paper, an SIRS epidemic model using Grunwald–Letnikov fractional-order derivative is formulated with the help of a nonlinear system of fractional differential equations to analyze the effects of fear in the population during the outbreak of deadly infectious diseases. The criteria for the spread or extinction of the disease are derived and discussed on the basis of the basic reproduction number. The condition for the existence of Hopf bifurcation is discussed considering fractional order as a bifurcation parameter. Additionally, using the Grunwald–Letnikov approximation, the simulation is carried out to confirm the validity of analytic results graphically. Using the real data of COVID-19 in India recorded during the second wave from 15 May 2021 to 15 December 2021, we estimate the model parameters and find that the fractional-order model gives the closer forecast of the disease than the classical one. Both the analytical results and numerical simulations presented in this study suggest different policies for controlling or eradicating many infectious diseases. [ABSTRACT FROM AUTHOR]

This paper investigates a nonlocal dispersal epidemic model under the multiple nonlocal distributed delays and nonlinear incidence effects. First, the minimal wave speed c ∗ and the basic reproduction number R 0 are defined, which determine the existence of traveling wave solutions. Second, with the help of the upper and lower solutions, Schauder's fixed point theorem, and limiting techniques, the traveling waves satisfying some asymptotic boundary conditions are discussed. Specifically, when ℛ 0 > 1 , for every speed c > c ∗ there exists a traveling wave solution satisfying the boundary conditions, and there is no such traveling wave solution for any 0 < c < c ∗ when ℛ 0 > 1 or c > 0 when ℛ 0 < 1. Finally, we analyze the effects of nonlocal time delay on the minimum wave speed. [ABSTRACT FROM AUTHOR]

In this paper, a new generalized non-monotonic and saturated incidence rate was introduced into a susceptible-infected-susceptible (SIS) epidemic model to account for inhibitory effect and crowding effect. The dynamic properties of the model were studied by qualitative theory and bifurcation theory. It is shown that when the influence of psychological factors is large, the model has only disease-free equilibrium point, and this disease-free equilibrium point is globally asymptotically stable; when the influence of psychological factors is small, for some parameter conditions, the model has a unique endemic equilibrium point, which is a cusp point of co-dimension two, and for other parameter conditions the model has two endemic equilibrium points, one of which could be weak focus or center. In addition, the results of the model undergoing saddle-node bifurcation, Hopf bifurcation and Bogdanov–Takens bifurcation as the parameters vary were also proved. These results shed light on the impact of psychological behavior of susceptible people on the disease transmission. [ABSTRACT FROM AUTHOR]

In this paper, we develop an epidemic model with a nonlinear function that describes the saturated digital contact tracing. The model is theoretically and numerically analyzed based on its dynamics. The model equilibria points and the basic reproduction number are obtained. However, the proposed model reveals both backward and forward bifurcation, and backward bifurcation occurs when the digital contact tracing saturation parameter is larger than a specific threshold. Real data are used to fit the model and estimate the parameter values. Sensitivity analysis reveals that interventions such as reducing the infection rate, enhancing quarantine efforts, and accelerating vaccination can effectively reduce the basic reproduction number, R 0 . Simulations show that improving tracing accuracy and encouraging greater participation in providing personal track information can effectively reduce the peak of undetected exposed individuals. Moreover, we analyze the expression for the specific threshold and determine that the increasing hospital resources and strengthening patient quarantine can reduce the potential occurrence of backward bifurcation. The analysis and simulations presented in this paper provide valuable suggestions for the prevention and control of the epidemic. [ABSTRACT FROM AUTHOR]

This paper explores a predator–prey system featuring fear and disease within the predator population,utilizing the Rosenzweig–MacArthur model with Holling type-II functional response. The primary focus lies in investigating the impact of a fear factor, wherein the prey's growth rate is hindered due to predator-induced fear. Additionally, the model accounts for the spread of disease among predators,leading to a division between susceptible and infected predator subpopulations. The inclusion of an Allee effect in the susceptible predator further enriches the model. The study involves a thorough examination, encompassing local and global stability analysis as well as Hopf bifurcation analysis around the interior equilibrium point. Numerical simulations underscore a noteworthy observation: an escalation in interaction force propels the system into chaotic dynamics,marked by stable focus, limit cycles and period-doubling phenomena. A noteworthy finding pertains to the influence of the Allee parameter (θ) on chaotic dynamics. As the Allee parameter values increase, the system tends to stable focus through a sequence of chaotic states, period-doubling and limit cycles. Subsequently, the paper introduces the role of another pivotal parameter, the fear factor, into the chaotic dynamics. Intriguingly, chaos transforms into stable focus through diverse nonlinear phenomena, including period-doubling and limit cycles. This nuanced exploration of parameters sheds light on the intricate dynamics governing the predator–prey system, offering a comprehensive understanding of the interplay between fear, disease and ecological factors. So our observation throughout this paper that how chaos behaves here after one by one injection of our new features: fear factor and Allee parameter? [ABSTRACT FROM AUTHOR]

A nonlinear infectious disease model with information-influenced vaccination behavior and contact patterns is proposed in this paper, and the impact of information related to disease prevalence on increasing vaccination coverage and reducing disease incidence during the outbreak is considered. First, we perform the analysis for the existence of equilibria and the stability properties of the proposed model. In particular, the geometric approach is used to obtain the sufficient condition which guarantees the global asymptotic stability of the unique endemic equilibrium E e when the basic reproduction number R 0 > 1. Second, mathematical derivation combined with numerical simulation shows the existence of the double Hopf bifurcation around E e . Third, based on the numerical results, it is shown that the information coverage and the average information delay may lead to more complex dynamical behaviors. Finally, the optimal control problem is established with information-influenced vaccination and treatment as control variables. The corresponding optimal paths are obtained analytically by using Pontryagin's maximum principle, and the applicability and validity of virous intervention strategies for the proposed controls are presented by numerical experiments. [ABSTRACT FROM AUTHOR]

The quarantine strategy plays a crucial role in the prevention and control of infectious disease. In this paper, a two-layer network model coupling the transmission of infectious diseases and the dynamics of human behavior based on game theory is proposed. The basic reproduction number of the infectious disease in our proposed model is obtained by the next-generation matrix method and the stability of the disease-free equilibrium is analyzed. Theoretical results show that the spread of infectious diseases can be controlled when the voluntary quarantined individuals reach a certain proportion. The sensitivities of the parameters are analyzed by simulations, and the results show that increasing propaganda can directly accelerate quarantine, and reducing the relative cost of quarantine has a significant effect on preventing the infectious diseases. Increasing the detection rate will lead to overestimating the proportion of undiagnosed infected individuals, and can also promote individuals to quarantine. [ABSTRACT FROM AUTHOR]

This paper considered a multi-stage sheep brucellosis model with incomplete immunity. First, we established a deterministic model, calculated the basic reproduction number ℛ 0 , set out the conditions for the global stability of the disease-free equilibrium and endemic equilibrium. Second, considering the influence of environmental white noise on brucellosis infection, we further established the stochastic version of the model. By constructing a suitable Lyapunov function, we proved the existence and uniqueness of the global positive solution. Further, we got the sufficient conditions for disease extinction and the existence of ergodic stationary distribution. Finally, we carried out some numerical simulations to verify the theoretical results. [ABSTRACT FROM AUTHOR]

Recent evidences show that individuals who recovered from COVID-19 can be reinfected. However, this phenomenon has rarely been studied using mathematical models. In this paper, we propose an SEIRE epidemic model to describe the spread of the epidemic with reinfection. We obtain the important thresholds R 0 (the basic reproduction number) and R c (a threshold less than one). Our investigations show that when R 0 > 1 , the system has an endemic equilibrium, which is globally asymptotically stable. When R c < R 0 < 1 , the epidemic system exhibits bistable dynamics. That is, the system has backward bifurcation and the disease cannot be eradicated. In order to eradicate the disease, we must ensure that the basic reproduction number R 0 is less than R c . The basic reinfection number is obtained to measure the reinfection force, which turns out to be a new tipping point for disease dynamics. We also give definition of robustness, a new concept to measure the difficulty of completely eliminating the disease for a bistable epidemic system. Numerical simulations are carried out to verify the conclusions. [ABSTRACT FROM AUTHOR]

In this paper, an attempt has been made to explore a new delayed epidemiological model assuming that the disease is transmitted among the susceptible population and possessing nonlinear incidence function along with a saturated treatment rate. Due attention is paid to the positivity and boundedness of the solutions and the bifurcation of the dynamical system as well. Basic reproduction number is being calculated, and considering the latent period as a bifurcation parameter, it has been examined that a Hopf-bifurcation occurs near the endemic equilibrium point while the parameter attains critical values. We have also discussed the stability and direction of Hopf-bifurcation near the endemic equilibrium point, the global stability analysis and the optimal control theory. We conclude that the system reveals chaotic dynamics through a specific time-delay value. Numerical simulations are being performed in order to explain the accuracy and effectiveness of the acquired theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a reaction–diffusion SEI epidemic model with nonlinear incidence rate is proposed. The well-posedness of solutions is studied, including the existence of positive and unique classical solution and the existence and the ultimate boundedness of global solutions. The basic reproduction numbers are given in both heterogeneous and homogeneous environments. For spatially heterogeneous environment, by the comparison principle of the diffusion system, the infection-free steady state is proved to be globally asymptotically stable if R 0 < 1 , if R 0 > 1 , the system will be persistent and admit at least one positive steady state. For spatially homogenous environment, by constructing a Lyapunov function, the infection-free steady state is proved to be globally asymptotically stable if R 0 < 1 , and then the unique positive steady state is achieved and is proved to be globally asymptotically stable if R 0 > 1. Finally, two examples are given via numerical simulations, and then some control strategies are also presented by the sensitive analysis. [ABSTRACT FROM AUTHOR]

Considering the prevailing situations, the mathematical modeling and dynamics of novel coronavirus (2019-nCoV) particularly in India are studied in this paper. The goal of this work is to create an effective SEIRS model to study about the epidemic. Four different SEIRS models are considered and solved in this paper using an efficient homotopy perturbation method. A clear picture of disease spreading can be obtained from the solutions derived using this method. We parametrized the model by considering the number of infection cases from 1 April 2020 to 30 June 2020. Finally, numerical analysis and graphical representations are provided to interpret the spread of virus. [ABSTRACT FROM AUTHOR]

In this paper, an SIRS model with age structure is proposed for recurrent infectious diseases by incorporating infectious delay and temporary immunity delay. Analysis shows that the disease will eventually disappear when the basic reproduction number ℛ 0 < 1. No matter how the infection delay τ 1 changes, as long as the temporary immunity loss delay τ 2 = 0 , the disease transmission will only be endemic and there will be no periodic oscillations when ℛ 0 > 1. Moreover, the stability and Hopf bifurcation will appear as τ 2 increases from zero. It indicates that the duration of temporary immunity can affect the form of disease transmission within the population. Our numerical simulations verified the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

During the outbreak of major emerging infectious diseases, virus droplets can survive in the environment as aerosols for hours to days, and their impact on human infectious diseases is often overlooked. In addition, the speed of transmission of infectious diseases is often closely related to transportation. Therefore, studying the impact of environmental viruses and transportation on disease development is significant for effective infectious disease prevention and control. We proposed a degenerate reaction–diffusion infectious disease model (SEAIR) considering environmental virus interference and established a well-posedness and threshold system for this model. We have obtained the system solution approaches the disease-free equilibrium (피0) when the basic reproduction number ℛ0 ≤ 1. The system has at least one positive steady state solution (PSS) when ℛ0 > 1. This paper used a non-standard finite difference method discretization model while data fitting and parameter estimation were performed based on data provided by the Health Commission. Further sensitivity analysis was conducted on ℛ0. At the same time, we also discussed the impact of various parameters in the early stages of the outbreak of major emerging infectious diseases on the development of the disease. Research found that even if the contact rate between people is controlled at a shallow level, the disease may persist. In the early stages of major emerging outbreak of infectious diseases, immediately reducing the use of transportation can effectively reduce the speed of disease spread. [ABSTRACT FROM AUTHOR]

The decline in amphibian populations in recent decades may be linked to the occurrence of infectious diseases such as chytridiomycosis, which is caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd). It is known that symbiotic bacteria protect the host due to their inhibitory nature. However, how the population dynamics of amphibians is affected by additional effects provided by symbiotic bacteria has not been analyzed in depth. In this paper, a model is proposed to describe the interaction among susceptible amphibians, susceptible amphibians with symbiotic bacteria and amphibians with chytrid fungus. When the modeling takes into account the additional reproductive benefits that the symbiont Pseudomonas sp. grants to the host, multiple endemic equilibrium points can exist if R0 < 1 (R0 is the basic reproduction number for Bd). In this scenario, the existence of a subcritical bifurcation at R0 = 1, which can occur in two different disease-free equilibrium points, gives rise to complex dynamics and stability scenarios. Particularly, the analysis of the model shows that a sudden increase of fungus-infected amphibians can occur even when R0 < 1 due to bistability phenomena. In this scenario, the existence of a subcritical bifurcation, which translates for the fungus into colonization even for values of R0 less than one, represents an advantage for the chytrid fungus Batrachochytrium dendrobatidis since the pathogen should benefit from remaining as close as possible to an endemic equilibrium. To control the fungal infection, R0 must be reduced to a value below one until the endemic equilibrium points disappear. Finally, we show that the amphibian population can reach a critical population level close to an extinction scenario when R0 increases. [ABSTRACT FROM AUTHOR]

Infectious disease outbreaks have caused significant losses to populations worldwide in terms of morbidity, social and economic costs. This has prompted governments to seek suitable intervention policies to suppress the outbreaks. This paper aims to explore the intrinsic impact of intervention strategies and the psychological behavior of people on the spread of infectious diseases. Employing the finite state Markov chain, we formulate a new stochastic SIS epidemic model under regime switching by using the Beddington–DeAngelis transmission function, in the presence of some governmental control measures. The study of the model is centered on three different scenarios in terms of varying two control parameters. We analyze the deterministic system for the global dynamics in terms of basic reproductive number. Some new threshold parameters are defined to discuss the extinction and the persistence of the disease in the stochastic setting. Numerical assessments were undertaken to validate theoretical findings for the deterministic and stochastic systems. Our findings strongly suggest that heightened awareness among susceptible individuals contributes significantly to the eradication of infection and fosters a stable epidemiological situation. As levels of public awareness increase, particularly within the susceptible population, a discernible trend toward the eradication of the infection emerges, ultimately ensuring sustained stability within the epidemiological landscape. [ABSTRACT FROM AUTHOR]

The summary measurement of an epidemic such as the final size is an important quantity that allows us to approximate the impact of the disease on the affected region. In recent years, final size measurements for vector-transmitted diseases have acquired importance because of the increased concern for mosquito-borne diseases like dengue, Zika, Chikungunya, etc. However, analytical expressions for this estimate in the stage-structured models applicable to vector-borne diseases are less, mostly focused on the classical Kermack–McKendrick model. In this paper, we first calculate the final size expressions for an SIR model with carrier state and a SEIR–SI host–vector model. Then we extend this for the SEIR–SI host–vector model with treatment class in the host, as well as for the model with vertical transmission in the vector population. Finally, we verify our final size expression with some real scenarios. [ABSTRACT FROM AUTHOR]

The primary objective of this paper is to conduct an in-depth analysis of the intricacies inherent in a gender-structured model depicting the dynamics of HIV–TB coinfection. The model is articulated through a set of nonlinear fractional-order differential equations. Our focus is on elucidating the stability characteristics around equilibrium points, employing advanced fractional stability techniques. We leverage sensitivity analysis as a powerful tool to discern the specific model parameters exerting significant influence on the transmission and control of the coinfection, as gauged by the basic reproduction number. Through this, we aim to identify key factors that drive the spread or containment of the dual affliction. Furthermore, we delve into the realm of optimization by formulating a fractional optimal control problem. The objective is to design and implement two control strategies that effectively mitigate the prevalence of coinfection, demonstrating a state of perfect protection. Notably, our findings reveal that the implementation of control measures at a rate exceeding 80% suffices to eliminate the infection entirely. We anticipate that the insights garnered from this research will prove instrumental for policymakers in crafting strategic interventions to curtail the tragic impact of HIV–TB coinfection. Our scientifically grounded study serves as a foundation upon which comprehensive plans can be devised to stem the devastating consequences of this dual health challenge. [ABSTRACT FROM AUTHOR]

In this paper, we propose a deterministic model to study the transmission dynamics of anthrax disease, which includes live animals, carcasses, spores in the environment and vectors. We derive three biologically plausible and insightful quantities (reproduction numbers) that determine the stability of the equilibria. We carry out rigorous mathematical analysis on the model dynamics, the global stability of the disease-free and vector-free equilibrium, the disease-free equilibrium and the vector-free disease equilibrium is proved. The global stability of the endemic equilibrium as the basic reproduction number is greater than one is derived in the special case in which the disease-related death rate is zero. The possibility of backward bifurcation is briefly discussed. Numerical analyses are carried out to understand the transmission dynamics of anthrax and investigate effective control strategies for the outbreaks of the disease. Our studies suggest that the larval vector control measure should be taken as early as possible to control the vector population size, a vaccination policy and an animal carcass removal policy are useful methods to control the prevalence of the diseases in infected animal populations, the adult vector control measure is also necessary to prevent the transmission of anthrax. [ABSTRACT FROM AUTHOR]

In this paper, we formulate the transmission phenomena of Hand–Foot–Mouth Disease (HFMD) through non-integer derivative. We interrogate the biological meaningful results of the recommended system of HFMD. The basic reproduction number is determined through next generation method and the impact of different parameters on the reproduction number is examined with the help of partial rank correlation coefficient (PRCC) technique. In addition, we concentrated on qualitative analysis and dynamical behavior of HFMD dynamics. Banach's and Schaefer's fixed-point theorems are used to analyze the uniqueness and existence of the solution of the proposed HFMD model. The HFMD system's Ulam–Hyers stability has been confirmed to be sufficient. To highlight the impact of the parameters on the dynamics of HFMD, we performed several simulations through numerical scheme to conceptualize the transmission route of the infection. To be more specific, numerical simulations are used to visualize the effect of input parameters on the systems dynamics. We have shown the key input parameters of the system for the control of infection in the society. [ABSTRACT FROM AUTHOR]

In this paper, a class of brucellosis transmission model with seasonal alternation, density-dependent growth, stage-structure, maturation delay, time-varying incubation is established. The basic reproduction number ℛ 0 is derived, by which we find that the brucellosis is uniformly persistent if ℛ 0 > 1 , while the disease-free periodic solution is globally attractive if ℛ 0 < 1. The theoretical results are illustrated by numerical simulation, from which we find that the brucellosis transmission would be overestimated (or underestimated) if we ignore the influence of time-varying incubation or maturation delay. If density-dependent growth of animals is ignored, the risk of brucellosis may be far underestimated, the extinction of brucellosis can be obtained by numerical simulation under the same conditions. Seasonality significantly affects the long-term dynamic behavior of brucellosis, and the inconsistency of parameter periods results in complex dynamic behavior. [ABSTRACT FROM AUTHOR]

This paper delineates the mathematical modeling and dynamics of a novel coronavirus (COVID-19) an outbreak, and it is a control measurement; the effect of lockdown in terms of lakhs of cases and deaths. The lockdown effect is studied with a different lockdown success rate and also describes the multiple transmission route in the infection dynamics, and pushes the role of the environmental reservoir in the transmission and the spread of this disease. In this situation, mathematical models are an important tool to assign an impressive strategy in order to fight against this pandemic. We exhibit the boundedness of the system, the local stability analysis and global stability analysis of the equilibrium to examine its epidemiological relevance. We have also carried out numerical simulations to validate the analytical results. [ABSTRACT FROM AUTHOR]

A mathematical model considering two strains of hepatitis B virus (HBV) chronic carriers, to assess the impact of dose-structured imperfect vaccine, in a population, is designed and analyzed. The model is shown to have a locally and globally asymptotically stable disease-free equilibrium (DFE) whenever its associated reproduction number is numerically less than unity. Numerical analysis of the model shows that with the expected 50% minimum efficacy of the first vaccine dose, vaccinating 55% of the susceptible population with the first vaccine dose will be sufficient to effectively control the spread of hepatitis B infection. Such effective control can also be achieved if 50% of the first vaccine dose recipients take the second dose. Threshold analysis reveals that an imperfect HBV vaccine should have positive or negative population-level effect. Latin hypercube sampling–PRCC analysis illustrates that disease transmission rate, birth rate, natural death rate and proportion of children born with maternal immunity are most influential parameters in the disease dynamics. In this paper, the sensitivity analysis based on mathematical and in addition statistical techniques have been performed to determine the significance of the model parameters. It is observed that a number of the parameters play an important role to determine the magnitude of the basic reproduction number. Sensitivity analysis is achieved to determine model parameters' importance in disease dynamics. It is observed that the reproduction number is the most responsive quantity to the potent transmission rate of HBV and in addition also vital to control the spread of the disease. [ABSTRACT FROM AUTHOR]

An age-structured vector-borne disease model with horizontal transmission is proposed and studied in this paper, where the incubation ages of both host and vector and the immunity age of host are also introduced to consider the effects of multi-class-age structure. The reproductive number ℛ 0 is derived as a threshold value to determine the existence and stability of the disease-free and endemic steady states. Furthermore, by constructing suitable Lyapunov functionals, the global threshold dynamics of this model is established by ℛ 0 , that is, the disease-free equilibrium is globally asymptotically stable when ℛ 0 < 1 , while if ℛ 0 > 1 the endemic equilibrium is globally asymptotically stable. In addition, considering the limited budget of the centers for disease control and prevention (CDC) in the process of disease control, we present an optimal control problem with a fixed total expenditure, and discuss the existence of the most control strategy for this disease. Finally, some numerical simulations are performed to support the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a new delayed within host model for dengue fever with immune response and Beddington–DeAngelis incidence is investigated. The basic reproduction number is computed. In addition, a detailed analysis on the local and global dynamics of the model is conducted. Finally, sensitivity analysis is carried out on basic reproduction number and numerical simulations are given to elucidate our theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we formulate and analyze a compartmental model of visceral leishmaniasis (VL). We validate our model by calibrating it to the yearly VL incidence data for India and Bangladesh. The proposed model's basic reproduction number ( R 0 ) has been derived and estimated. We have proved the existence of backward bifurcation in our system. The phenomenon of backward bifurcation has public health implications because the classical requirement of R 0 < 1 , while necessary, is no longer sufficient for effective disease control (or elimination). In such a (backward bifurcation) situation, the initial sizes of the model's subpopulations (state variables) would determine the effectiveness of disease control or elimination. As a result, it is the first attempt to represent and study VL disease dynamics using active case detection (ACD) as a control strategy, although a few experimental studies have been conducted to evaluate ACD in disease transmission. We use sensitivity analysis to investigate the effects of the model's controllable parameters for the basic reproduction number. We found that σ 1 , σ 2 , σ 3 (monitoring rate to infected individuals) have negative impacts on R 0 . The numerical result suggests that the ACD strategy can be useful for the VL elimination program. Due to a small increment in the monitoring rate, the dynamic behavior of infected individuals dramatically decreased. Successful employment of ACD strategy may reduce more than 60–80% symptomatic and post kala-azar dermal leishmaniasis (PKDL) individuals. We found that healthcare organizations should prioritize ACD in symptomatic and PKDL individuals over asymptomatic individuals. We also observed that the use of only culling effect to the reservoirs is not beneficial to society in the control of VL, but spraying of insecticides and the use of treated bednets can be effective control strategies to curtail the outbreak of the disease. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear mathematical model for tuberculosis transmission, which incorporates multiple saturated exogenous reinfections, is proposed and explored. The existence of disease-free and endemic steady states is investigated. Disease-free equilibrium (DFE) is locally asymptotically stable (LAS) but not globally asymptotically stable (GAS) when the basic reproduction number, ℛ 0 < 1. However, it is GAS only when there is no exogenous reinfection. The local asymptotic stability and global asymptotic stability of the unique endemic equilibrium point (EEP) are established under certain conditions when ℛ 0 > 1. Further, the EEP is GAS when ℛ 0 > 1 , provided there is no exogenous reinfection. When ℛ 0 is below unity, the presence of multiple endemic equilibria is found which leads to backward bifurcation. It is demonstrated that the system encounters a Hopf-bifurcation when the transmission rate β crosses a critical value, resulting in the formation of limit cycles, i.e. periodic solutions bifurcate around the EEP when β passes a critical value. The stability and direction of Hopf-bifurcation are also studied. The results of the analytical work are validated through numerical simulations. A numerical simulation illustrates that EEP losses its stability via Hopf-bifurcation for specific parameters. However, when the bifurcation parameter β is increased further, the EEP regains its stability. In addition, Hopf-bifurcation occurs due to exogenous reinfection rates p and . Thus, our model shows some important nonlinear dynamical behaviors. [ABSTRACT FROM AUTHOR]

In this paper, we construct an SIR epidemic model with a modified Beddington–De Angelis type incidence rate and saturated treatment rate. We modify the incidence rate to incorporate the isolation of infected individuals after detection, and separation of some susceptible individuals from the rest to avoid the infection, without an increase in the number of classes. We find that the system has a unique disease-free equilibrium (DFE) which is locally asymptotically stable when the reproduction number is less than unity. The multiple endemic equilibria may exist irrespective of the basic reproduction number. The existence of bistability is encountered. Supercritical transcritical (forward), as well as subcritical transcritical (backward) bifurcation, may occur at ℜ 0 = 1 where contact rate, β = β ∗ acts as the bifurcation parameter. Therefore, DFE need not be globally stable. The conditions for the existence of Andronov–Hopf bifurcation are deduced with maximum treatment capacity, c = c 0 as the bifurcation parameter. The impacts of isolation of confirmed infected cases and separation of some susceptible from rest are studied numerically as well as the effect of saturation in treatment. The existence of chaotic behavior is deduced by showing the maximum Lyapunov exponent to be positive as well as the sensitivity to initial conditions. The computation of the Kalpan–Yorke dimension to be fractional confirms the existence of fractal-type strange attractor. The positive Kolmogorov–Sinai entropy further strengthens the claim of the existence of chaos. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic SIS epidemic infectious diseases model with double stochastic perturbations is proposed. First, the existence and uniqueness of the positive global solution of the model are proved. Second, the controlling conditions for the extinction and persistence of the disease are obtained. Besides, the effects of the intensity of volatility ξ 1 and the speed of reversion 1 on the dynamical behaviors of the model are discussed. Finally, some numerical examples are given to support the theoretical results. The results show that if the basic reproduction number ℛ 0 s < 1 , the disease will be extinct, that is to say that we can control the threshold ℛ 0 s to suppress the disease outbreak. [ABSTRACT FROM AUTHOR]

This paper deals with the dynamics of tuberculosis transmission model with different genders and age structures. The basic reproduction numbers ℛ 0 = ℛ F + ℛ M are defined, where ℛ F and ℛ M are the basic reproduction number of tuberculosis transmission in female and male populations, respectively. The global stability of the disease-free equilibrium was discussed when ℛ 0 < 1 ; The existence, uniqueness and global stability of the endemic equilibrium, and the persistence of the system both were proved when ℛ 0 > 1. The findings indicate that the tuberculosis dynamical model with different genders and age structures will experience the classical threshold dynamic behaviors, that is, if ℛ 0 < 1 , the disease will disappear; while if ℛ 0 > 1 , the disease will spread within the population, and eventually lead to a endemic disease. Finally, the theoretical analysis of the model is verified by numerical simulation and we proposed that male infected individuals should be focused on in the prevention and control of tuberculosis in the future. [ABSTRACT FROM AUTHOR]

This paper deals with a three-dimensional nonlinear mathematical model to analyze an epidemic's future course when the public healthcare facilities, specifically the number of hospital beds, are limited. The feasibility and stability of the obtained equilibria are analyzed, and the basic reproduction number ( R 0 ) is obtained. We show that the system exhibits transcritical bifurcation. To show the existence of Bogdanov–Takens bifurcation, we have derived the normal form. We have also discussed a generalized Hopf (or Bautin) bifurcation at which the first Lyapunov coefficient evanescences. To show the existence of saddle-node bifurcation, we used Sotomayor's theorem. Furthermore, we have identified an optimal layout of hospital beds in order to control the disease with minimum possible expenditure. An optimal control setting is studied analytically using optimal control theory, and numerical simulations of the optimal regimen are presented as well. [ABSTRACT FROM AUTHOR]

In this paper, a SEIR epidemic model related to media coverage and exogenous reinfections is established to explore the transmission dynamics of COVID-19. The basic reproduction number is calculated using the next generation matrix method. First, the existence of equilibrium points is investigated, and different kinds of equilibrium points indicate that the disease may disappear, or exist that result in different quantity of susceptible individuals, pre-symptomatic infected individuals and symptomatic infected individuals. The stability of the equilibria is discussed by a geometric approach, and it is found that controlling reproduction number to be lower than 1 is not sufficient for eradication of COVID-19. Second, transcritical bifurcation is explored, and it is found that improving the ratio of exogenous reinfection may lead to backward bifurcation under poor medical conditions, which indicates that two endemic equilibrium points appear. Third, to investigate the influence of parameters on the basic reproduction, sensitivity analysis is done to choose relatively sensitive parameters, and the parameters for treatment and media coverage are selected. An optimal control model is established to balance the treatment and media awareness. By exploring the existence and the uniqueness of the optimal control solution, the optimal control strategies are given. Finally, we run numerical simulations to verify the theoretical analysis on actual data of China, and the data from the four different states of India is used for forecasting the situation of infected individuals in a short period. It is found by the simulation that the co-function of treatment and media coverage results in the reduced number of infectious individuals. [ABSTRACT FROM AUTHOR]

Vector-borne disease malaria is transmitted to humans by arthropod vectors (mosquitoes) and contributes significantly to the global disease burden. TV and social media play a key role to disseminate awareness among people by broadcasting awareness programs. In this paper, a nonlinear model is formulated and analyzed in which cumulative number of advertisements through TV and social media is taken as dynamical variable that propagates awareness among people to control the prevalence of vector-borne disease. The human population is partitioned into susceptible, infected and aware classes, while the vector population is divided into susceptible and infected classes. Humans become infected and new cases arise when bitten by infected vectors (mosquitoes) and susceptible vectors get infected as they bite infected humans. The feasibility of equilibria is justified and their stability conditions are discussed. A crucial parameter, basic reproduction number, which measures the disease transmission potentiality is obtained. Bifurcation analysis is performed by varying the sensitive parameters, and it is found that the proposed system shows different kinds of bifurcations, such as transcritical bifurcation, saddle-node bifurcation and Hopf bifurcation, etc. The analysis of the model shows that reduction in vector population due to intervention of people of aware class would not efficiently reduce the infective cases, rather we have to minimize the transmission rates anyhow, to control the disease outbreak. [ABSTRACT FROM AUTHOR]

Age structure and delay play a significant role in determining the dynamics of the diseases. In this paper, an SEIRS epidemic model with age structure and time delay is investigated, where the loss of the acquired immunity and delay are incorporated. Through some rigorous analyses, an explicit formula for the basic reproduction number of the model is calculated, and some results about stability and instability of equilibria for the model are established. The findings show that the age structure and delay can produce Hopf bifurcation for an SEIRS model. The numerical examples are executed to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Mathematical models for the transmission dynamics of infectious diseases have aided our understanding of the important factors that drive epidemic patterns. In this paper, we formulate and analyze a stochastic epidemic model, a continuous-time Markov chain, in order to understand rotavirus dynamics with a contaminated environment. The assumptions of the deterministic model are utilized in the formulation of the corresponding stochastic model. We perform both local and global stability analyses of the equilibria of the deterministic model with respect to the basic reproduction number. The extinction threshold for the stochastic model and conditions for either disease extinction or persistence are derived by employing the branching process to the infectious classes only. It is shown that the probability of rotavirus extinction obtained from the branching process is in excellent agreement with the numerically approximated probability. Numerical results indicate that the probability of rotavirus extinction is the highest if the contaminated environment introduces the virus into a totally susceptible population at the beginning of the epidemic process. Thus, a major rotavirus outbreak is likely if the virus emanates from infectious children at the onset of the epidemic. Results of sensitivity analysis showed that shedding of the virus into the environment by infectious children is the most sensitive parameter of the model. Further, it is shown that decreasing the shedding rate leads to an increase in the probability of disease extinction and vice versa. This, therefore, implies that disposal of stool of infectious children should be well managed if efforts to curb further spread of the disease or even eliminating it are to bear desirable fruits. [ABSTRACT FROM AUTHOR]

COVID-19 disease, a deadly pandemic ravaging virtually throughout the world today, is undoubtedly a great calamity to human existence. There exists no complete curative medicine or successful vaccines that could be used for the complete control of this deadly pandemic at the moment. Consequently, the study of the trends of this pandemic is critical and of great importance for disease control and risk management. Computation of the basic reproduction number by means of mathematical modeling can be helpful in estimating the potential and severity of an outbreak and providing insightful information which is useful to identify disease intensity and necessary interventions. Considering the enormity of the challenge and the burdens which the spread of this COVID-19 disease placed on healthcare system, the present paper attempts to study the pattern and the trend of spread of this disease and prescribes a mathematical model which governs COVID-19 pandemic using Caputo type derivative. Local stability of the equilibria is also discussed in the paper. Some numerical simulations are given to illustrate the analytical results. The obtained results shows that applied numerical technique is computationally strong for modeling COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

In this paper, we investigate an epidemic model with quarantine and recovery-age effects. Reformulating the model as an abstract nondensely defined Cauchy problem, we discuss the existence and uniqueness of solutions to the model and study the stability of the steady state based on the basic reproduction number. After analyzing the distribution of roots to a fourth degree exponential polynomial characteristic equation, we also derive the conditions of Hopf bifurcation. Numerical simulations are performed to illustrate the results. [ABSTRACT FROM AUTHOR]

This paper mainly targets to deduce an optimal treatment strategy for combined antiretroviral drugs, which can maximize healthy CD4+ T cells level with minimum side effects and cost. For this purpose, we consider a within-host treatment model for the HIV infection with two controls incorporating full logistic proliferation of healthy CD4+ T cells, cure rate and fusion effect. These two controls represent the effects of reverse transcriptase inhibitors (RTIs) and protease inhibitors (PIs), respectively. The model analysis begins with proving different basic properties like non-negativity, boundedness of the model solutions and calculation of the basic reproduction number of the model under consideration. Then, stability results are obtained for HIV infection-free equilibrium point and also, a critical efficacy for the combined therapies is calculated. After that, the optimal control problem is proposed and solved numerically using a forward–backward iterative method. Finally, we obtain an optimal treatment strategy that can maximize healthy CD4+ T cells count and control the viral load, and HIV-infected CD4+ T cells count to an undetectable level resulting in improved health conditions of infected individuals. [ABSTRACT FROM AUTHOR]

In this paper, a model describing the transmission of Human Papilloma Virus (HPV) in a bisexually active human host community is presented. We analyze the model in a feasible region where the model is realistic in the sense of HPV transmission. Since the trivial equilibrium does not exist, we obtain the HPV-free equilibrium solutions and make use of the next generation matrix method to compute the basic reproduction number R h p v , which governs HPV extinction and persistence whenever it is less or greater than unity, respectively. We perform the sensitivity analysis of the model parameters of R h p v as to HPV prevalence and found that parameters β 1 , β 2 , γ o and γ 1 , which are the effective HPV transmission and progression to recovery parameters, are positively sensitive to R h p v . In order to minimize the increasing effect of R h p v as regards the positive sensitive parameters, we re-construct the model via optimal control theory to incorporate controls of condom usage u 1 , vaccination u 2 and medical counseling u 3 respectively. With these controls, we characterize and discuss the existence and uniqueness of the control model and solve the optimality system using the forward–backward Runge–Kutta fourth-order technique via the Matlab computational software. Simulations show that each of the control strategies is potent in combating HPV but the combination of the three controls proved more efficient in minimizing HPV infection in the human bisexual host community. [ABSTRACT FROM AUTHOR]

In this paper, we consider an SI epidemic model incorporating additive Allee effect and time delay. The primary purpose of this paper is to study the dynamics of the above system. Firstly, for the model without time delay, we demonstrate the existence and stability of equilibria for three different cases, i.e. with weak Allee effect, with strong Allee effect, and in the critical case. We also investigate the existence and uniqueness of Hopf bifurcation and limit cycle. Secondly, for the model with time delay, the stability of equilibria and the existence of Hopf bifurcation are discussed. All the above show that both additive Allee effect and time delay have vital effects on the prevalence of the disease. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of disease spreading dynamics through the application of a nonlinear fractional order epidemic SEIRS model. By incorporating the Crowley–Martin type functional response and a saturated treatment function, the model effectively captures the intricacies of real-world epidemics. Our research establishes the existence, uniqueness, non-negativity and boundedness of the solution, while also investigating the model’s fundamental reproduction number. Additionally, we conduct a thorough analysis of the specific conditions governing the local and global stability of the model’s equilibriums. A notable observation is the variation of the reproduction number with the fractional-order α, which represents a memory effect on individuals’ dynamic behavior and reveals the influence of interactions between compartments. To validate these theoretical findings, we employ numerical simulations using Matlab, demonstrating that inhibition measures for susceptibles and the saturated treatment parameters play a pivotal role in determining the disease state. Specifically, we observe that as these parameter values increase, the transition from endemic equilibrium to disease-free equilibrium occurs. [ABSTRACT FROM AUTHOR]

Tumor immune escape refers to the inability of the immune system to clear tumor cells, which is one of the major obstacles in designing effective treatment schemes for cancer diseases. Although clinical studies have led to promising treatment outcomes, it is imperative to design theoretical models to investigate the long-term treatment effects. In this paper, we develop a mathematical model to study the interactions among tumor cells, immune escape tumor cells, and T lymphocyte. The chimeric antigen receptor (CAR) T-cell therapy is also described by the mathematical model. Bifurcation analysis shows that there exists backward bifurcation and saddle-node bifurcation when the immune intensity is used as the bifurcation parameter. The proposed model also exhibits bistability when its parameters are located between the saddle-node threshold and backward bifurcation threshold. Sensitivity analysis is performed to illustrate the effects of different mechanisms on the backward bifurcation threshold and basic immune reproduction number. Simulation studies confirm the bifurcation analysis results and predict various types of treatment outcomes using different CAR T-cell therapy strengths. Analysis and simulation results show that the immune intensity can be used to control the tumor size, but it has no effect on the control of the immune escape tumor size. The introduction of the CAR T-cell therapy will reduce the immune escape tumor size and the treatment effect depends on the CAR T-cell therapy strength. [ABSTRACT FROM AUTHOR]

The pharmaceutical interventions of emerging infectious diseases are constrained by the available medical resources such as drugs, vaccines, hospital beds, isolation places and the efficiency of the treatment. The awareness of the population also plays an important role in reducing contacts and consequently, reducing the disease transmission rate. In this paper, we propose a multi-group Susceptible, Infected and Recovered (SIR) epidemic model incorporating the awareness of population and the saturated treatment function that describes the effects of the availability of medical resources for treatment. We assume that the treatment of the infected individuals of a group is affected by the medical resources for the treatment of each group. We calculate the basic reproduction number R 0 in the term of the awareness parameter using the next generation approach. We determine the local and global stabilities of equilibrium (disease free equilibrium and endemic equilibrium) in terms of R 0 and the availability of medical resources for treatment. We obtain that backward bifurcation occurs at R 0 = 1 along with the existence of multiple endemic equilibria when R 0 < 1. Further, we consider the special case with a single group epidemic system and ensure the existence of multiple endemic equilibria. We showed a necessary condition on the parameter related to the availability of medical resources when backward bifurcation occurs. This situation indicates that reducing the basic reproduction number below unity is not sufficient to remove the disease when the medical resources for treatment are scarce. We used numerical simulations to support and counterpart our theoretical results and discussed the impacts of the awareness of susceptible population and availability of medical resources for treatment in each group, on the epidemic size of each group. Our findings suggest that in the case of limited medical resources, the high treatment rate and awareness of the population are very helpful to control the disease (to reduce the prevalence of infection) and the eradication of disease also depends on initial population sizes. More importantly, it is also obtained that sufficient medical resources for every group are required to eradicate the disease from an entire population. [ABSTRACT FROM AUTHOR]

Influenced by seasonal changes, the infection rate of many infectious diseases fluctuates in cycles. In this paper, we propose and investigate an SIRS model on a scale-free network. To model seasonality, we assume that the infection rate is periodic. The existence and positivity of solutions of the proposed model are proved and the basic reproduction number ℜ 0 is defined. The global stability of steady states is determined by rigorous mathematical analysis. When ℜ 0 < 1 , the disease-free equilibrium E 0 is globally asymptotically stable. When ℜ 0 > 1 , the system has a unique positive periodic solution E * , and E * is globally asymptotically stable. Numerical simulations are performed to support our theoretic results, and the effects of various parameters on the amplitude and mean of infected individuals are studied. The sensitivity of parameters of the basic reproduction number ℜ 0 is solved by the Sobol global sensitivity analysis method, and the results show that the effects of the parameters β 0 and α on ℜ 0 are remarkable. [ABSTRACT FROM AUTHOR]

This paper studies an SIS-type Lyme transmission model incorporating insecticides spraying and vaccination as interventions. We obtain the positivity and boundedness of solutions, calculate the basic reproduction number, and discuss the global stability of disease-free and endemic equilibria when the basic reproduction number ℛ 0 < 1 and ℛ 0 > 1 , respectively. We apply Pontryagin's maximum principle to explore an optimal control strategy to minimize the number of infected ticks and hosts and the cost of using insecticides and vaccination. We design numerical simulations to illustrate the effectiveness of theoretical analysis. [ABSTRACT FROM AUTHOR]

Anthrax is a disease caused by Bacillus anthracis, commonly affects animals as well as humans health. In this paper, a nonlinear deterministic anthrax model involving human and animal is proposed and analyzed. The reproduction number ℛ 0 and equilibrium points are explored to study the dynamic behavior of the disease. The existence and stability of equilibrium points are discussed. For ℛ 0 < 1 , the disease-free equilibrium E 0 is globally stable. However, it is unstable when ℛ 0 > 1 and a locally stable endemic equilibrium point E * exists. The model is then extended to optimal control model considering human vaccination, animal vaccination and proper removal of carcass. The vaccination class of human and animal population appears separately in a model. The existence and characterization of optimal control are discussed. The numerical simulations are carried out for the choice of parametric values and initial conditions. These illustrate scavengers in the suspected area which eat infected dead body of animals contributing to the effort of reducing the expansion of disease. In addition, numerical comparison analysis with four distinct control strategies is carried out. Our findings show that each control technique has its own influence on reducing the total number of infections in the human and animal populations. The cumulative impact of all control measures is found to be extremely effective in lowering the prevalence of the disease. [ABSTRACT FROM AUTHOR]

A recent paper [W. D. Wang, Modeling adaptive behavior in influenza transmission, Math. Model. Nat. Phenom. 7(3) (2012) 253-262] presented the local stability of the endemic equilibrium of an influenza transmission model incorporating human mobility behavior. In the present paper, we prove that is globally stable if the basic reproduction number . [ABSTRACT FROM AUTHOR]

In this paper, a mathematical analysis of the global dynamics of a viral infection model in vivo is carried out. We study the dynamics of a hepatitis C virus (HCV) model, under therapy, that considers both extracellular and intracellular levels of infection. At present, most mathematical modeling of viral kinetics after treatment only addresses the process of infection of a cell by the virus and the release of virions by the cell, while the processes taking place inside the cell are not included. We prove that the solutions of the new model with positive initial values are positive, exist globally in time and are bounded. The model has two virus-free steady states. They are distinguished by the fact that viral RNA is absent inside the cells in the first state and present inside the cells in the second. There are basic reproduction numbers associated to each of these steady states. If the basic reproduction number of the first steady state is less than one, then that state is asymptotically stable. If the basic reproduction number of the first steady state is greater than one and that of the second less than one, then the second steady state is asymptotically stable. If both basic reproduction numbers are greater than one, then we obtain various conclusions which depend on different restrictions on the parameters of the model. Under increasingly strong assumptions, we prove that there is at least one positive steady state (infected equilibrium), that there is a unique positive steady state and that the positive steady state is stable. We also give a condition under which every positive solution converges to a positive steady state. This is proved by methods of Li and Muldowney. Finally, we illustrate the theoretical results by numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, we solve a nonlinear fractional-order model for analyzing the dynamical behavior of vector-borne diseases within the frame of Caputo-fractional derivative. The proposed mathematical model advances the existing integer-order model on transmission and cure of vector-borne diseases. The existence and uniqueness of the solutions of the fractional-order model are proved using the Banach contraction principle. We investigate the local asymptomatic stability for the obtained disease-free equilibrium point and global stability for the proposed model in the sense of Ulam–Hyers stability criteria, respectively. Besides that, we obtain a numerical solution for the projected model using the Corrector-Predictor algorithm. Finally, to illustrate the obtained theoretical results, we perform numerical simulations for different values of fractional-order derivative and make a comparison with the results of the integer-order derivative. [ABSTRACT FROM AUTHOR]

Recent studies have demonstrated that immune impairment is an essential factor in viral infection for disease development and treatment. In this paper, we formulate an age-structured viral infection model with a nonmonotonic immune response and perform dynamical analysis to explore the effects of both immune impairment and virus control. The basic infection reproduction number is derived for a general viral production rate, which determines the global stability of the infection-free equilibrium. For the immune intensity, we get two important thresholds, the post-treatment control threshold and the elite control threshold. The interval between the two thresholds is a bistable interval, where there are two immune-present infected equilibria. When the immune intensity is greater than the elite control threshold, only one immune-present infected equilibrium exists and it is stable. By assuming the death rate and virus production rate of infected cells to be constants, with the immune intensity as a bifurcation parameter, the system exhibits saddle-node bifurcation, transcritical bifurcation, and backward/forward bifurcation. [ABSTRACT FROM AUTHOR]