System Dynamic simulation of treatment policies to address colliding epidemics of tuberculosis,drug resistant tuberculosis and injecting drug users driven HIV in Russia

The explosive increase in the number of people infected with tuberculosis (TB),multi drug resistant tuberculosis (MDRTB), and injecting drug users (IDU)HIV/AIDS has become a serious public health challenge in Russia. The WorldHealth Organization is recommending policies including simultaneous use ofhighly active antiretroviral therapy (HAART) to treat HIV/AIDS and second linedrugs to treat MDRTB. We developed a System Dynamics simulation model torepresent the dynamic transmission of TB, MDRTB and human immunodeficiency virus(HIV). The model simulated scenarios regarding MDRTB cure rate and HAARTcoverage, that is the HIV/AIDS population covered by HAART. The results over a20-year period indicate that reduction in TB and HIV-associated TB deaths wouldbe negligible for HAART coverage up to 50%. The reduction is onlysignificant for HAART coverage of 70% and above. Similarly, high MDRTBcure rate reduces significantly deaths from TB and MDRTB and this reduction ismore important as the HAART coverage is increased.     

Global stability of two models with incomplete treatment for tuberculosis

Two tuberculosis (TB) models with incomplete treatment are investigated. It is assumed that the treated individuals may enter either the latent compartment due to the remainder of Mycobacterium tuberculosis or the infectious compartment due to the treatment failure. The first model is a simple one with treatment failure reflecting the current TB treatment fact in most countries with high tuberculosis incidence. The second model refines the simple one by dividing the latent compartment into slow and fast two kinds of progresses. This improvement can be used to describe the case that the latent TB individuals have been infected with some other chronic diseases (such as HIV and diabetes) which may weaken the immunity of infected individuals and shorten the latent period of TB. Both of the two models assume mass action incidence and exponential distributions of transfers between different compartments. The basic reproduction numbers of the two models are derived and their intuitive epidemiological interpretations are given. The global dynamics of two models are all proved by using Liapunov functions. At last, some strategies to control the spread of tuberculosis are discussed.     

HIV dynamics: Analysis and robust multirate MPC-based treatment schedules

Analysis and control of human immunodeficiency virus (HIV) infection have attracted the interests of mathematicians and control engineers during the recent years. Several mathematical models exist and adequately explain the interaction of the HIV infection and the immune system up to the stage of clinical latency, as well as viral suppression and immune system recovery after treatment therapy. However, none of these models can completely exhibit all that is observed clinically and account the full course of infection. Besides model inaccuracies that HIV models suffer from, some disturbances/uncertainties from different sources may arise in the modelling. In this paper we study the basic properties of a 6-dimensional HIV model that describes the interaction of HIV with two target cells, CD4⁺ T cells and macrophages. The disturbances are modelled in the HIV model as additive bounded disturbances. Highly Active AntiRetroviral Therapy (HAART) is used. The control input is defined to be dependent on the drug dose and drug efficiency. We developed treatment schedules for HIV infected patients by using robust multirate Model Predictive Control (MPC)-based method. The MPC is constructed on the basis of the approximate discrete-time model of the nominal model. We established a set of conditions, which guarantee that the multirate MPC practically stabilizes the exact discrete-time model with disturbances. The proposed method is applied to the stabilization of the uninfected steady state of the HIV model. The results of simulations show that, after initiation of HAART with a strong dosage, the viral load drops quickly and it can be kept under a suitable level with mild dosage of HAART. Moreover, the immune system is recovered with some fluctuations due to the presence of disturbances.     

Modelling the effect of tuberculosis on the spread of HIV infection in a population with density-dependent birth and death rate

A nonlinear mathematical model is proposed to study the effect of tuberculosis on the spread of HIV infection in a logistically growing human population. The host population is divided into four sub classes of susceptibles, TB infectives, HIV infectives (with or without TB) and that of AIDS patients. The model exhibits four equilibria namely, a disease free, HIV free, TB free and an endemic equilibrium. The model has been studied qualitatively using stability theory of nonlinear differential equations and computer simulation. We have found a threshold parameter R₀ which is if less than one, the disease free equilibrium is locally asymptotically stable otherwise for R₀>1, at least one of the infections will be present in the population. It is shown that the positive endemic equilibrium is always locally stable but it may become globally stable under certain conditions showing that the disease becomes endemic. It is found that as the number of TB infectives decreases due to recovery, the number of HIV infectives also decreases and endemic equilibrium tends to TB free equilibrium. It is also observed that number of AIDS individuals decreases if TB is not associated with HIV infection. A numerical study of the model is also performed to investigate the influence of certain key parameters on the spread of the disease.     

HIV low viral load persistence under treatment: Insights from a model of cell-to-cell viral transmission

HIV infection persists despite long-term administration of antiretroviral therapy. The mechanisms underlying HIV persistence are not fully understood. Direct viral transmission from infected to uninfected cells (cell-to-cell transmission) may be one of them. During cell-to-cell transmission, multiple virions are delivered to an uninfected cell, making it possible that at least one virion can escape HIV drugs and establish infection. In this paper, we develop a mathematical model that includes cell-to-cell viral transmission to study HIV persistence. During cell-to-cell transmission, it is assumed that various number of virus particles are transmitted with different probabilities and antiretroviral therapy has different effectiveness in blocking their infection. We analyze the model by deriving the basic reproduction number and investigating the stability of equilibria. Sensitivity analysis and numerical simulation show that the viral load is still sensitive to the change of the treatment effectiveness in blocking cell-free virus infection. To reduce this sensitivity, we modify the model by including density-dependent infected cell death or HIV latent infection. The model results suggest that although cell-to-cell transmission may have reduced susceptibility to HIV drugs, HIV latency represents a major reason for HIV persistence in patients on suppressive treatment.     

Optimal control applied on an HIV‐1 within‐host model

The treatment of human immunodeficiency virus (HIV) remains a major challenge, even if significant progress has been made in infection treatment by ‘drug cocktails’. Nowadays, research trend is to minimize the number of pills taken when treating infection. In this paper, an HIV‐1 within host model where healthy cells follow a simple logistic growth is considered. Basic reproduction number of the model is calculated using next generation matrix method, steady states are derived; their local, as well as global stability, is discussed using the Routh–Hurwitz criteria, Lyapunov functions and the Lozinskii measure approach. The optimal control policy is formulated and solved as an optimal control problem. Numerical simulations are performed to compare several cases, representing a treatment by Interleukin2 alone, classical treatment by multitherapy drugs alone, then both treatments at the same time. Objective functionals aim to (i) minimize infected cells quantity; (ii) minimize free virus particles number; and (iii) maximize healthy cells density in blood. Copyright © 2015 John Wiley & Sons, Ltd.     

Optimal strategies for mitigating the HIV/AIDS epidemic in the Philippines

The human immunodeficiency virus (HIV) impairs a person's immune system against many infections and some types of cancer, leading to acquired immunodeficiency syndrome (AIDS), which is characterized by severe illnesses. The number of HIV infections in the Philippines has increased, more than doubled, within the last decade. This alarming HIV crisis in the country requires urgent actions. In this study, a mathematical model is developed to describe the disease transmission in the Philippines. Disease-free and endemic equilibria are obtained, stability analysis is performed, and the basic reproduction number is computed. Sensitivity analyses and subset selection are performed to identify influential parameters and to determine an identifiable parameter set given measurements, respectively. Available data on the number of asymptomatic aware infectious, those who are in the AIDS stage, and those under treatment are utilized to estimate key epidemiological parameters such as transmission, treatment, and screening rates. Uncertainty of these parameter estimates is quantified through bootstrapping method. Furthermore, intervention strategies are investigated in the framework of optimal control theory. Control measures include precaution, HIV screening, antiretroviral treatment, and pre-exposure prophylaxis (PrEP) treatment. These various control efforts are compared with regard to cost efficiency and effectiveness in reducing the number of infected individuals. Given limited available control measures, the PrEP-only scenario is shown to be the most cost-effective, followed by other scenarios that combine PrEP with other controls.     

Analysis of a viral infection model with delayed immune response

It is well known that the immune response plays an important role in eliminating or controlling the disease after human body is infected by virus. In this paper, we investigate the dynamical behavior of a viral infection model with retarded immune response. The effect of time delay on stability of the equilibria of the system has been studied and sufficient condition for local asymptotic stability of the infected equilibrium and global asymptotic stability of the infection-free equilibrium and the immune-exhausted equilibrium are given. By numerical simulating,we observe that the stationary solution becomes unstable at some critical immune response time, while the delay time and birth rate of susceptible host cells increase, and we also discover the occurrence of stable periodic solutions and chaotic dynamical behavior. The results can be used to explain the complexity of the immune state of patients.     

The role of CD4 T cells in immune system activation and viral reproduction in a simple model for HIV infection

CD4 T cells play a fundamental role in the adaptive immune response including the stimulation of cytotoxic lymphocytes (CTLs). Human immunodeficiency virus (HIV) which infects and kills CD4 T cells causes progressive failure of the immune system. However, HIV particles are also reproduced by the infected CD4 T cells. Therefore, during HIV infection, infected and healthy CD4 T cells act in opposition to each other, reproducing virus particles and activating and stimulating cellular immune responses, respectively. In this investigation, we develop and analyze a simple system of four ordinary differential equations that accounts for these two opposing roles of CD4 T cells. The model illustrates the importance of the CTL immune response during the asymptomatic stage of HIV infection. In addition, the solution behavior exhibits the two stages of infection, asymptomatic and final AIDS stages. In the model, a weak immune response results in a short asymptomatic stage and faster development of AIDS, whereas a strong immune response illustrates the long asymptomatic stage. A model with a latent stage for infected CD4 T cells is also investigated and compared numerically with the original model. The model shows that strong stimulation of CTLs by CD4 T cells is necessary to prevent progression to the AIDS stage.     

Results on the dynamics for models for the sexual transmission of the human immunodeficiency virus

In this note, we report on the formulation and mathematical analysis of single and multiple group models for the spread of the human immuno-deficiency virus (HIV), which is the etiological agent for the acquired immunodeficiency syndrome (AIDS). Results on the robustness of a single group model are stated for specific and arbitrary survivorship functions. In addition, we provide results that show that multiple group models can have multiple endemic equilibria.     

Dynamics of an HIV‐1 virus model with both virus‐to‐cell and cell‐to‐cell transmissions,general incidence rate,intracellular delay,and CTL immune responses

Direct cell‐to‐cell transmission of HIV‐1 is a more efficient means of virus infection than virus‐to‐cell transmission. In this paper, we incorporate both these transmissions into an HIV‐1 virus model with nonlinear general incidence rate, intracellular delay, and cytotoxic T lymphocyte (CTL) immune responses. This model admits three types of equilibria: infection‐free equilibrium, CTL‐inactivated equilibrium, and CTL‐activated equilibrium. By using Lyapunov functionals and LaSalle invariance principle, it is verified that global threshold dynamics of the model can be explicitly described by the basic reproduction numbers.     

Quantifying the strength and durability of induced immunity to HIV infection in women engaging in unprotected sexual contacts with infected men

Evidence is accumulating that exposure to human immunodeficiency virus (HIV) can lead to an increased resistance or immunity to subsequent infection. A multirisk model that permits either induced immunity or infection to develop after heterosexual inoculation with HIV is shown to be compatible with a wide spectrum of disparate male-to-female transmission data.When the model is applied to time-dependent, HIV-seroprevalence data, the probability that an unexposed woman would remain unexposed after an unprotected contact with an infected man was estimated to be greater than 0.95 on the average. Thus, it would require at least 14 unprotected sexual contacts with HIV-infected men for 50% of an unexposed cohort of women to become exposed to the virus. This suggests that there is a low probability that HIV virions will be found to have penetrated the mucosal barriers of the reproductive tract after a contact.The model also predicts, that the average woman whose mucosal barriers have been breached by HIV has a significant probability of developing immunity to the virus rather than infection. Modelling data for a cohort of unexposed Nairobi women leads to the prediction that the probability of acquiring induced immunity per contact is about 60% of the probability of acquiring the disease per contact.The modelling results also predict that those who had developed resistance to HIV run the small, but significant risk of becoming infected nonetheless by continuing high-risk behavior. For the common contact rate of ten per month, the modelling predicts that the HIV-transmission risk per contact for unexposed women in the Nairobi cohort is 1/178 while the transmission risk for the cohort's immunized women is 1/1548. These numbers suggest that HIV infection is difficult to transmit through heterosexual intercourse on the average and that male-to-female HIV-transmission risk per contact for African women lies between 1/178 and 1/1548.Direct confirmation of the predictions in the last paragraph has been subsequently observed in two completely independent studies. The Nairobi research team recently reported that a notable number of Nairobi prostitutes previously identified to be members of the HIV-resistant group became infected nonetheless. Second, in a study of 174 sexually monogamous, discordant couples in Rakai, Uganda reporting contacts rates of nine to ten per month, the male-to-female HIV-transmission risk per contact was found to be 1/769 by direct measurement, a value that falls between the above limits of 1/178 and 1/1548 predicted by the modelling. Thus, a second major prediction of this paper has been directly confirmed, and induced immunity to HIV is limited and not absolutely protective.Circumstantial evidence suggests that the induced immunity to HIV predicted by the model could be generated and/or initiated by nonspecific innate immune responses, specific immunological responses, including IgA-mediated mucosal immunity and cytotoxic T lymphocytes (CTL) immunity, or some combination of the above. It is suggested here, that a decrease in the ability of HIV virions to penetrate the protective mucus layer of the reproductive tract may be a prerequisite, cofactor, or the principle cause of the induced immunity or resistance demonstrated to exist in this paper. The value of the probability that induced immunity to HIV will develop after a contact is shown to be a sensitive function of the woman's human leucocyte antigen (HLA) supertype profile.     

A piecewise model of virus-immune system with effector cell-guided therapy

To assess the effectiveness of structured treatment interruptions (STIs) for treating HIV patients, recent clinical studies have investigated the plasma HIV RNA and CD4 T cell-guided therapies. Here, we consider a piecewise model with a particular focus on the effector cell-guided therapy. We prove that there always exist two sliding segments, and under certain conditions two pseudo-equilibria can occur simultaneously. We also examine the global dynamics of the model by using the theory of sliding dynamics. Compared with our previous work on the system with HIV RNA-guided therapy, we show that the model for effector cell-guided therapy captures much more complex dynamics, including the coexistence of multiple attractors and infinitely many possible topological structures of the attractors. Our analysis show that with appropriate use of the effector cell-guided therapy, we can enlarge the controllable region substantially in a variety of ways for different attractors. We also note that the virus load may grow to infinity for certain initial conditions (which are patient dependent). Therefore, an optimal control strategy for the effector cell-guided therapy should be personalized, by taken into account individual patient data.     

Forecasting concentrations of air pollutants by logarithm support vector regression with immune algorithms

The need to minimize the potential impact of air pollutants on humans has made the accurate prediction of concentrations of air pollutants a crucial subject in environmental research. Support vector regression (SVR) models have been successfully employed to solve time series problems in many fields. The use of SVR models for forecasting concentrations of air pollutants has not been widely investigated. Data preprocessing procedures and the parameter selection of SVR models can radically influence forecasting performance. This study proposes a support vector regression with logarithm preprocessing procedure and immune algorithms (SVRLIA) model which takes advantage of the structural risk minimization of SVR models, the data smoothing of preprocessing procedures, and the optimization of immune algorithms, in order to more accurately forecast concentrations of air pollutants. Three pollutants, namely particulate matter (PM₁₀), nitrogen oxide, (NO_x), and nitrogen dioxide (NO₂), are collected and examined to determine the feasibility of the developed SVRLIA model. Experimental results reveal that the SVRLIA model can accurately forecast concentrations of air pollutants.     

Bifurcation analysis of a multidelayed HIV model in presence of immune response and understanding of in‐host viral dynamics

In this paper, we proposed a multidelayed in‐host HIV model to represent the interaction between human immunodeficiency virus and immune response. One delay was considered to incorporate the time required by the virus for various intracellular events to make a host cell productively infective, and the second delay was introduced to take into account the time required for adaptive immune system to respond against infection. We extensively analyzed this multidelayed model analytically and numerically. We show that delay may have both destabilizing and stabilizing effects even when the system contains a single immune response delay. It happens when there exists two sequences of critical values of this delay. If the system starts with stable state in absence of delay, then the smallest value of these critical delays causes instability and the next higher value causes stability. The system may also show stability switching for different values of the virus replication factor. These results demonstrate the possible reasons of intrapatients and interpatients variability of CD4⁺ T cells and virus counts in HIV‐infected patients.     

复杂网络上的病毒免疫策略研究

为了给预防病毒传播提供指导意见并且更好地对病毒传播行为进行预测和控制,主要研究了几种经典复杂网络中病毒传播的模型,并对几种复杂网络病毒免疫的模型特点进行了分析,通过对这些病毒免疫模型在多局域加权网络中应用不足的分析,对多局域加权网络的病毒免疫策略进行了相应的研究.     

A mathematical approach to HIV infection dynamics

In order to obtain a comprehensive form of mathematical models describing nonlinear phenomena such as HIV infection process and AIDS disease progression, it is efficient to introduce a general class of time-dependent evolution equations in such a way that the associated nonlinear operator is decomposed into the sum of a differential operator and a perturbation which is nonlinear in general and also satisfies no global continuity condition. An attempt is then made to combine the implicit approach (usually adapted for convective diffusion operators) and explicit approach (more suited to treat continuous-type operators representing various physiological interactions), resulting in a semi-implicit product formula. Decomposing the operators in this way and considering their individual properties, it is seen that approximation–solvability of the original model is verified under suitable conditions. Once appropriate terms are formulated to describe treatment by antiretroviral therapy, the time-dependence of the reaction terms appears, and such product formula is useful for generating approximate numerical solutions to the governing equations. With this knowledge, a continuous model for HIV disease progression is formulated and physiological interpretations are provided. The abstract theory is then applied to show existence of unique solutions to the continuous model describing the behavior of the HIV virus in the human body and its reaction to treatment by antiretroviral therapy. The product formula suggests appropriate discrete models describing the dynamics of host pathogen interactions with HIV1 and is applied to perform numerical simulations based on the model of the HIV infection process and disease progression. Finally, the results of our numerical simulations are visualized and it is observed that our results agree with medical and physiological aspects.     

Analysis of an HIV model with post-treatment control

Recent investigation indicated that latent reservoir and immune impairment are responsible for the post-treatment control of HIV infection. In this paper, we simplify the disease model with latent reservoir and immune impairment and perform a series of mathematical analysis. We obtain the basic infection reproductive number $R_{0}$ to characterize the viral dynamics. We prove that when $R_{0}<1$, the uninfected equilibrium of the proposed model is globally asymptotically stable. When $R_{0}>1$, we obtain two thresholds, the post-treatment immune control threshold and the elite control threshold. The model has bistable behaviors in the interval between the two thresholds. If the proliferation rate of CTLs is less than the post-treatment immune control threshold, the model does not have positive equilibria. In this case, the immune free equilibrium is stable and the system will have virus rebound. On the other hand, when the proliferation rate of CTLs is greater than the elite control threshold, the system has stable positive immune equilibrium and unstable immune free equilibrium. Thus, the system is under elite control.     

Bayesian segmental growth mixture Tobit models with skew distributions

This paper presents an extension of the standard Tobit to simultaneously address segmental phases, subpopulation heterogeneity, lower limit of detection, and skewness in outcomes of human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome (AIDS) longitudinal data. A major problem often encountered in an HIV/AIDS research is the development of drug resistance to antiretroviral (ARV) drug or therapy. For dealing with drug resistance problem, estimating the time at which drug resistance would develop is usually sought. Following ARV treatment, the profile of each subject’s viral load tends to follow a ‘broken stick’ like growth trajectory, indicating multiple phases of decline and increase in viral loads. Such multiple phases with multiple change-points are captured by subject-specific random parameters of growth curve models. To account subpopulation heterogeneity of drug resistance among patients, the turning-points are also allowed to differ by latent classes of patients on the basis of trajectories of observed viral loads. These features of viral longitudinal data are jointly modeled in a unified framework of segmental growth mixture Tobit mixed-effects models with skew distributions for a response variable with left censoring and skewness under the Bayesian approach. The proposed methods are illustrated using real data from an AIDS clinical study.