Disease-free Equilibrium Point Research Articles

A mathematical model with fractional order for obesity with positive and negative interactions and its impact on the diagnosis of diabetes

Overweight and obesity are current problems humankind faces and have serious health consequences because they contribute to diseases such as heart diseases and diabetes. In this paper, we present a mathematical model for the study of overweight and obesity in a population and its impact on the growth of the number of diabetics. For the construction of the model, we take into account social factors and the interactions between different elements of society. We use fractional-order derivatives in the Caputo sense because of the advantages of this type of technique with respect to the memory effect, and it shows different behaviors depending on the fractional order. We find the basic reproduction number and prove the local and global stability of the disease-free equilibrium points. We study the sensitivity index with respect to the basic reproduction number for parameters associated with weight gain due to social pressure and the rate of diagnosis of diabetes not associated with body weight. To validate the model, we perform computational simulations with data extracted from the literature. We conclude that for higher fractional orders a higher value of the basic reproduction number was reached. We show that at the end of the study for different fractional orders that normal-weight individuals are decreasing, and overweight, obese, and diabetic people are increasing.

Analyzing Dynamical Behavior of Tuberculosis Transmission

In this article, we investigated the dynamical behavior of a fuzzy mathematical model with tuberculosis (TB) treatment function. The considered model analyzes fuzzy basic reproduction numbers and stability analysis for both local and global stability conditions around disease-free equilibrium points, as well as its local stability conditions around endemic equilibrium points. We examine the TB model’s sensitivity analysis with a focus on the variation of each of its parameters. We propose predicting the extension of the virus load in TB using fuzzy bifurcation. At the end, we have given a numerical simulation to illustrate the outcomes by considering some special types of treatment functions.

MATHEMATICAL MODELS OF DENGUE TRANSMISSION DYNAMICS WITH VACCINATION AND WOLBACHIA PARAMETERS AND SEASONAL ASPECTS

The Aedes aegypti mosquito is the main carrier of dengue virus transmission to humans. In this study, a mathematical model for the transmission of the dengue virus is constructed using vaccination and Wolbachia parameters in an attempt to control the virus's spread. Furthermore, the fundamental reproduction number is set as a parameter of the infection threshold. Based on the stability of the equilibrium point analysis, it is found that the disease-free equilibrium point is locally asymptotically stable if . Then, a mathematical model of dengue was created by examining the seasonal aspect and adding a periodic term to the mosquito birth rate. Dengue virus transmission in mosquito populations is controlled by air temperature in addition to seasonal variables. In this study, three weather scenarios were simulated: scenario 1 for cold weather (air temperature 14 °C), scenario 2 for hot weather (air temperature 26 °C), and scenario 3 for moderate weather (air temperature between 14 and 26 °C).

ANALYSIS OF THE COVID-19 EPIDEMIC MODEL WITH SELF-ISOLATION AND HOSPITAL ISOLATION

This research developed the SIR model with self-isolation and hospital isolation. The analysis is carried out through the disease-free and endemic equilibrium point analysis and the sensitivity analysis of the basic reproduction number. Based on the disease-free equilibrium point analysis, for a certain period of time the population will be free from COVID-19 if the basic reproduction number is less than 1. If the basic reproduction number is more than 1, the disease will persist in the population, this will lead to an endemic equilibrium point. Based on the sensitivity analysis of parameter values on the basic reproduction number, the parameter for the isolation rate of individually infected individuals in hospitals is -0.4615166040, and the self-isolation rate at home is -0.01853667767. This indicates that isolation in hospitals is more effective than self-isolation in suppressing the spread of COVID-19.

A FRACTIONAL DIFFERENTIAL EQUATION MODEL FOR THE SPREAD OF POTATO LEAF ROLL VIRUS (PLRV) ON POTATOES

Potatoes infected with the PLRV virus will experience a decrease in production up to 90%. In this paper, The PLRV distribution fractional differential equation model with potato and vector populations is reformulated by adding one new parameter, namely the rate of vector death due to predators. The model is divided into susceptible and infected classes. The PLRV dispersion model was developed and converted to a fractional order form for 0<σ ≤ 1. Next, the invariant region, positive solutions, basic reproduction number, equilibrium point, and stability were determined. Based on the stability analysis, it is shown that the stability of the disease-free equilibrium point is locally stable and globally stable if the basic reproduction number (R0)<1, and the stability of the endemic equilibrium point is globally stable if the basic reproduction number (R0)>1. Numerical solutions were also carried out to determine the effect of several parameters on the PLRV distribution model on potatoes. The numerical solution results show that the elimination rate of infected potatoes and the infection rate of potatoes have a significant role in controlling the spread of PLRV in potatoes.

GLOBAL STABILITY OF DISEASE-FREE EQUILIBRIA IN COVID-19 SPREAD THROUGH LIVING AND INANIMATE OBJECTS MATHEMATICAL MODEL

Covid-19 is a dangerous disease that is easily transmitted, both through living media in the form of interactions with infected human, as well as through inanimate objects in the form of surfaces contaminated with the Coronavirus. Various preventive and repressive efforts have been made to prevent the spread of this disease, such as isolating and recovering the infected human. In this study, the authors construct and analyze a new mathematical model in the form of a three-dimensional differential equations system that represent the interactions between subpopulations of coronavirus living on inanimate objects, susceptible human, and infected human within a population. The purpose of this study is to investigate the criteria that must be met in order to create a population free from Covid-19 by considering inanimate objects as a medium for its spread besides living objects. The model solution that represents the number of each subpopulation is non-negative and bounded, so it is in accordance with the biological condition that the number of subpopulations cannot be negative and there is always a limit for its value. The eradication rate of Coronavirus living on inanimate objects, the recovery rate of infected human, and the interaction rate between susceptible human and infected human such that the population is free from Covid-19 for any initial conditions of each subpopulation were investigated in this study through global stability analysis of the disease-free equilibrium point of the model.

Mathematical simulations and sensitivity visualization of fractional order disease model describing human immunodeficiency

In this study, we explore a mathematical model of human immunodeficiency virus type 1 (HIV-1) infection in CD4+ T-cells, considering fractional-order dynamics in the Caputo sense. Fractional models are of great significance due to their capacity to predict disease outbreaks while incorporating memory and non-local characteristics. To establish the existence and uniqueness of solutions for the fractional model, a fixed-point theorem and an iterative technique are employed. Furthermore, it is confirmed that the solutions of the model are both positive and bounded. The basic reproduction number, denoted as R0, is calculated using the next-generation matrix approach, and the equilibrium points of the model, including disease-free and endemic equilibrium points, are presented. A sensitivity analysis of R0 is performed by varying different parameters. To analyze the local stability of equilibrium points, the Routh-Hurwitz technique is employed. The global stability of equilibrium points is demonstrated using the Lyapunov function and LaSalle's principle, as well as through UlamHyers (UH) stability and the generalized UH stability conditions. The proposed numerical scheme Adams-Bashforth predictor-corrector is validated by comparing it with the fourth-order Runge-Kutta (RK4) technique. We examine the influence of the fractional order (ξ) by conducting numerical simulations for different values of ξ using the Adams-Bashforth predictor-corrector approach. Furthermore, graphical presentations illustrate how different crucial model parameters impact disease dynamics. The results obtained from this study demonstrate that the adopted strategies significantly improve prediction accuracy.

Dynamical analysis of a novel discrete fractional lumpy skin disease model

Lumpy skin disease is a viral disease that affects cattle and is caused by the lumpy skin disease virus. This work is devoted to presenting and analyzing the nonlinear dynamics of a novel discrete fractional model for lumpy skin disease. The equilibrium points of the proposed discrete fractional model are found. The stability analysis of equilibrium points is carried out. The influences of key parameters in the model are investigated, and then the stability regions of a disease-free steady state in the space of parameters are obtained. A proposed efficient control scheme is implemented to stabilize the disease-free equilibrium point when it is unstable. The influences of fractional-order parameters on the applied control scheme are explored. Finally, numerical simulations are performed to verify the theoretical findings obtained and confirm the effectiveness of the employed control scheme.

Time scale theory on stability of explicit and implicit discrete epidemic models: applications to Swine flu outbreak.

Time scales theory has been in use since the 1980s with many applications. Only very recently, it has been used to describe within-host and between-hosts dynamics of infectious diseases. In this study, we present explicit and implicit discrete epidemic models motivated by the time scales modeling approach. We use these models to formulate the basic reproduction number, which determines whether an outbreak occurs or the disease dies out. We discuss the stability of the disease-free and endemic equilibrium points using the linearization method and Lyapunov function. Furthermore, we apply our models to swine flu outbreak data to demonstrate that the discrete models can accurately describe the epidemic dynamics. Our comparison analysis shows that the implicit discrete model can best describe the data regardless of the data frequency. In addition, we perform the sensitivity analysis on the key parameters of the models to study how these parameters impact the basic reproduction number.

Analisis Dinamik Model SIRC pada Transmisi Hepatitis B dengan Sirosis Hati

Hepatitis B is an infection of the liver that can cause liver cirrhosis. Liver cirrhosis can occur due to the formation of scar tissue in individuals who have prolonged hepatitis B. Transmission of hepatitis B can occur in two ways, namely horizontal and vertical. In this research, this problem is modeled in a mathematical model using the SIRC model, where the population is grouped into four sub-populations, namely susceptible (S), infected (I), cured or immune due to vaccination (R) and cirrhosis. liver (C). From the analysis, two equilibrium points were obtained, namely the disease-free equilibrium point the endemic equilibrium point The basic reproduction number is obtained using the Next Generation Matrix. The analysis results show that if , then the disease-free equilibrium point is locally asymptotically stable, which means that hepatitis B transmission in liver cirrhosis does not spread. Meanwhile, if , then the disease-free equilibrium point is locally asymptotically stable, which means that hepatitis B transmission in liver cirrhosis does not spread. Meanwhile, if , this means that hepatitis B transmission in liver cirrhosis is influenced by contact between susceptible and infectious individuals. To support the results of the analytical analysis, numerical simulations are provided to describe the behavior of the SIRC model.

Theoretical and Numerical Simulations on the Hepatitis B Virus Model through a Piecewise Fractional Order

In this study, we introduce the dynamics of a Hepatitis B virus (HBV) model with the class of asymptomatic carriers and conduct a comprehensive analysis to explore its theoretical aspects and examine the crossover effect within the HBV model. To investigate the crossover behavior of the operators, we divide the study interval into two subintervals. In the first interval, the classical derivative is employed to study the qualitative properties of the proposed system, while in the second interval, we utilize the ABC fractional differential operator. Consequently, the study is initiated using the piecewise Atangana–Baleanu derivative framework for the systems. The HBV model is then analyzed to determine the existence, Hyers–Ulam (HU) stability, and disease-free equilibrium point of the model. Moreover, we showcase the application of an Adams-type predictor-corrector (PC) technique for Atangana–Baleanu derivatives and an extended Adams–Bashforth–Moulton (ABM) method for Caputo derivatives through numerical results. Subsequently, we employ computational methods to numerically solve the models and visually present the obtained outcomes using different fractional-order values. This network is designed to provide more precise information for disease modeling, considering that communities often interact with one another, and the rate of disease spread is influenced by this factor.

MATHEMATICAL MODEL OF MEASLES DISEASE SPREAD WITH TWO-DOSE VACCINATION AND TREATMENT

This study developed a model for the spread of measles based on the SEIR model by adding the factors of using the first dose of vaccination, the second dose of vaccination, and treatment. Making this model begins with making a compartment diagram of the spread of the disease, which consists of seven subpopulations, namely susceptible subpopulations, subpopulations that have received the first dose of vaccination, subpopulations that have received the second dose vaccination, exposed subpopulations, infected subpopulations, subpopulations that have received treatment, and subpopulations healed. After the model is formed, the disease-free equilibrium point, endemic equilibrium point, and basic reproduction number (R_0) are obtained. Analysis of the stability of the disease-for equilibrium point was locally asymptotically stable when (R_0)<1. The backward bifurcation analysis occurs when (R_C) is present and R_C<R_0. Numerical simulations of disease-free and endemic equilibrium points are carried out to provide an overview of the results analyzed with parameter values from several sources. The results of the numerical simulation are in line with the analysis carried out. From the model analysis, the disease will disappear more quickly when the level of vaccine used and individuals who carry out treatment are enlarged.

Investigations of transmission dynamics of Nipah virus in Bangladesh

This study has focused on the transmission dynamics of the Nipah Virus (NiV) and its controlling system. In this respect, we have developed a virus transmission model based on several compartments and discussed the model's basic reproduction number and stability analysis at disease-free equilibrium (DFE) and endemic equilibrium (EE) points. It is observed that the model is locally and globally asymptotically stable at DFE and EE for the basic reproduction number R0<1 and R0>1, respectively. We have also solved the model equations numerically using the Runge-Kutta (RK-45) method to investigate the effect of disease parameters. In the calculation, some parameter values are taken from several references. Lastly, the calculated results show that the infection rate of the exposed individuals highly influences the disease compartments. Furthermore, drug resistance is observed to be less effective than the treatment rate. In addition, it is found that the number of infected people is reducing with the increasing treatment rate.

Dynamical behavior of fractional order SEIR epidemic model with multiple time delays and its stability analysis

With multiple time delays, we investigated a Caputo fractional order dynamical system involving susceptible, exposed, infected, and recovered individuals. Positivity and boundedness are also theoretically demonstrated using Laplace transform and Mittag-Leffler function. The stability of the disease-free and epidemic equilibrium points has been studied for both delayed and non-delayed model. For generating numerical solutions to the model system, we used the Adam-Bashforth-Moulton predictor-corrector technique. With the help of MATLAB (2018a), we were able to conduct graphical demonstrations and numerical simulations. The system displays Hopf bifurcation and the solutions are no longer periodic beyond a certain threshold value of the time delay parameters.

Dynamic Analysis of the Susceptible-Exposed-Infected-Hospitalized-Critical-Recovered-Dead (SEIHCRD)

This study discusses the dynamic analysis of the Susceptible–Exposed–Infected–Hospitalized–Critical–Recovered–Dead (SEIHCRD) model using the fourth order Runge-Kutta method. The data used in this study is original data on Infected, Hospitalized and Critical cases in Indonesia from August to October 2021. Dynamic analysis of the model is carried out by determining disease-free and endemic equilibrium points, local stability analysis of disease-free and endemic equilibrium points, and determine the basic reproduction number. The result of this analysis is that the number of new infection cases in Indonesia will decrease over time and the COVID-19 outbreak will end. Then a numerical simulation was carried out using the fourth order Runge-Kutta method in dealing with COVID-19 cases in Indonesia. The simulations and calculations show that the rate of contact of susceptible individuals with infected individuals is 0.06 per day, the rate of movement of individuals in the Exposed class to the Infected class is 0.14 per day, the probability of infected individuals being hospitalized with a value of 0.95, the probability that COVID-19 patients become critical and enter the Intensive Care Unit (ICU) with a value of 0.485, and the probability of a critical patient dying with a value of 0.25 affects the slope of Infected, Hospitalized and Critical cases in Indonesia. Where Infected cases will be sloping with an absolute error value of 28%, Hospitalized cases with an absolute error value of 20% and Critical cases with an absolute error value of 33%. This research provides information that it is estimated that the daily infection cases of COVID-19 will decrease and be close to zero. So that infected patients who must be hospitalized and admitted to the Intensive Care Unit (ICU) are also decreasing, it is hoped that the COVID-19 pandemic will not happen again

MATHEMATICAL MODELLING AND STABILITY ANALYSIS OF MONKEY POX TRANSMISSION DYNAMICS IN NIGERIA

In this paper, we proposed a mathematical model for monkey pox disease dynamics. This model is divided into two sub-population which is a system of non-linear differential equations. It is made up of seven (7) compartments such as the Susceptible, the Infectious, the Treatment, the Recovery, the Susceptible, the Infectious, and the Recovery (SITR-SIR). The model is formulated with the aid of a schematic diagram using appropriate parameters. The model analysis was carried out to show the feasible region, the disease-free equilibrium points, the basic reproduction number, and the local stability of the model. The model was solved to show the effect of the parameters.

Fractional optimal control strategies for hepatitis B virus infection with cost-effectiveness analysis

Hepatitis B disease is a communicable disease that is caused by the hepatitis B virus and has become a significant health problem in the world. It is a contagious disease that is transmittable from person to person either horizontally or vertically. This current study is aimed at sensitivity analysis and optimal control strategies for a fractional hepatitis B epidemic model with a saturated incidence rate in the sense of the Caputo order fractional derivative approach. Fundamental properties of the proposed fractional order model are obtained and discussed. A detailed analysis of disease-free equilibrium and endemic equilibrium points is given by applying fractional calculus theory, which is a generalized version of classical calculus. Sensitivity indexes are calculated for the classical order model. Illustrative graphics that show the dependence of the sensitivity index on fractional order derivative for alpha in (0,1) are provided. Based on the results of the sensitivity analysis and using Pontryagin’s Maximum Principle, optimal control strategies for preventing hepatitis B infection with vaccination and treatment are considered. Fractional Euler’s method is used to carry out the numerical simulation for the proposed fractional optimal control system and the obtained results are analyzed. The results of the analysis reveal that hepatitis B disease can be prevented if necessary precautionary is taken or effective vaccination and treatment control measures are applied. The analysis of cost-effectiveness is also conducted and discussed.

Mathematical and Stability Analysis of Dengue–Malaria Co-Infection with Disease Control Strategies

Historically, humans have been infected by mosquito-borne diseases, including dengue fever and malaria fever. There is an urgent need for comprehensive methods in the prevention, control, and awareness of the hazards posed by dengue and malaria fever to public health. We propose a new mathematical model for dengue and malaria co-infection with the aim of comprehending disease dynamics better and developing more efficient control strategies in light of the threat posed to public health by co-infection. The proposed mathematical model comprises four time-dependent vector population classes (SEIdIm) and seven host population classes (SEIdImIdmTR). First, we show that the proposed model is well defined by proving that it is bounded and positive in a feasible region. We further identify the equilibrium states of the model, including disease-free and endemic equilibrium points, where we perform stability analysis at equilibrium points. Then, we determine the reproduction number R0 to measure the level of disease containment. We perform a sensitivity analysis of the model’s parameters to identify the most critical ones for potential control strategies. We also prove that the proposed model is well posed. Finally, the article examines three distinct co-infection control measures, including spraying or killing vectors, taking precautions for one’s own safety, and reducing the infectious contact between the host and vector populations. The control analysis of the proposed model reveals that all control parameters are effective in disease control. However, self-precaution is the most effective and accessible method, and the reduction of the vector population through spraying is the second most effective strategy to implement. Disease eradication is attainable as the vector population decreases. The effectiveness of the implemented strategies is also illustrated with the help of graphs.

An age-structured differential equations model for transmission dynamics of pneumonia with treatment and nutrition intervention

Pneumonia is the leading infectious disease that threatens the lives of children under five and elders over 65. It is an infection that is commonly caused by Streptococcus pneumoniae. In this study, an age-structured (children and elders) model for pneumonia was formulated and analyzed to determine the impact of treatment and proper nutrition on the transmission dynamics of the disease in the two age groups. The effective reproduction number (Re) was determined using the next-generation method. The disease-free equilibrium point was determined and found locally and globally asymptotically stable if Re<1. Sensitivity analysis of the model parameters was performed using the normalized forward sensitivity index method, and the findings show that transmission rates are the most positive parameters to the effective reproduction number, while proper nutrition was the most negatively sensitive parameter. Additionally, numerical simulations were performed, and it was observed that the combination of proper nutrition and treatment was more effective in reducing the number of pneumonia-infected individuals. The study encourages the joint use of proper nutrition and treatment to control pneumonia transmission among children and elders, especially in the developing world, where economic constraints, infrastructure, and distribution challenges limit vaccine availability.

A non-integer order model for Zika and Dengue co-dynamics with cross-enhancement

A novel fractional derivative model with nine compartments is formulated to investigate the transmission dynamics of zika and dengue co-infection. The Atangana–Baleanu fractional derivative in the Caputo sense was employed. The conditions for a unique solution are identified, and the solutions’ positivity and boundedness are demonstrated. The disease-free equilibrium point (DFE) and basic reproduction number, R0, were obtained. The DFE was shown to be locally asymptotically stable when the basic reproduction number is less than one. Zika-associated reproduction number, R0z, and dengue-associated reproduction number, R0d, were estimated to be 1.0144 and 1.1724, respectively. The system was shown to be generalized Ulam Hyers–Rassias stable, and the Adam–Bashforth method was used to provide its’ numerical solution. Sensitivity analysis using the Latin Hyper-cube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) (|PRCC|> 0.45) with 200 runs was carried out using various variables as response functions per time. The most significant parameters were found to be zika human-to-human transmission rate, βhz1, vector death rate, μv, zika recovery rate, γhz1 and dengue vector-to-human transmission rate, βhd. Real data from Espirito Santo in Brazil is used to validate the model and fit needed parameter values. Numerical simulations illustrated the impact of varying the fractional order derivative, recovery rates, transmission rates, and cross-enhancement parameters on the infected human compartments. The zika Human-to-human transmission rate, βhz1, was found to be a very significant parameter in the control of zika disease transmission. Increasing the vector death rate, μv, was more important in curbing dengue prevalence and incidence than the attainment of recovery from the dengue disease, and the absence of the zika Vector-to-human transmission rate, βhz3, was almost insignificant in the presence of the zika Human-to-human transmission rate, βhz1, for disease eradication. This study suggested control measures and strategies to decrease the dengue and zika human-to-human transmission rates.