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The control of opportunistic infections among HIV infected individuals should be one of the major public health concerns in reducing mortality rate of individuals living with HIV/AIDS. In this study a deterministic co-infection mathematical model is employed to provide a quantification of treatment at each contagious stage against Pneumocystis Pneumonia (PCP) among HIV infected individuals on ART. The disease-free equilibrium for the HIV/AIDS sub model, PCP sub model and the co-infection model are shown to be locally asymptotically stable when their associated disease threshold parameter is less than a unity. By use of suitable Lyapunov functions, the endemic equilibrium corresponding to HIV/AIDS and PCP sub models are globally asymptotically stable whenever $\mathcal{R}_{0H}>1$ and $\mathcal{R}_{0P}>1$ respectively. The sensitivity analysis results implicate that the effective contact rates are the main mechanisms fueling the proliferation of the two diseases and on the other hand treatment efforts play an important role in reducing the incidence. Numerical simulations show that treatment of PCP at all contagious stages reduces its burden on HIV/AIDS patients and dual treatm

With a 676% growth rate in HIV incidence between 2010 and 2021, the HIV/AIDS epidemic in the Philippines is the one that is spreading the quickest in the western Pacific. Although the full effects of COVID-19 on HIV services and development are still unknown, it is predicted that such disruptions could lead to a significant increase in HIV casualties. Therefore, the nation needs some modeling and forecasting techniques to foresee the spread pattern and enhance the governments prevention, treatment, testing, and care program. In this study, the researcher uses Multilayer Perceptron Neural Network to forecast time series during the period when the COVID-19 pandemic strikes the nation, using statistics taken from the HIV/AIDS and ART Registry of the Philippines. After training, validation, and testing of data, the study finds that the predicted cumulative cases in the nation by 2030 will reach 145,273. Additionally, there is very little difference between observed and anticipated HIV epidemic levels, as evidenced by reduced RMSE, MAE, and MAPE values as well as a greater coefficient of determination. Further research revealed that the Philippines seems far from achieving Sustainable D

In this article, we consider an HIV/AIDS epidemic model with four classes of individuals. We have discussed about basic properties of the system and found the basic reproduction number $R_0$ of the system. The stability analysis of the model shows that the system is locally as well as globally asymptotically stable at disease-free equilibrium $E_{0}$ when $R_0<1$. When $R_0>1$ endemic equilibrium $E_1$ exists and the system becomes locally asymptotically stable at $E_1$. An optimal controller is presented that considers the use of three different measures to combat the spread of HIV/AIDS, namely: the use of condoms, screening of unaware infective individuals, and treatment of the HIV infected population. The objective of the optimal controller is to minimize the size of the susceptible and infected populations. Our investigation of the controlled system starts with establishing the existence of the optimal control, followed by identifying the necessary conditions of optimality.

This book has seven chapters. The first chapter is introductory in nature and it speaks about the migrant labourers. In chapter two we use Fuzzy Cognitive Maps to analyze the socio-economic problems of HIV/AIDS infected migrant labourers in rural areas of Tamil Nadu. In chapter three we analyze the role played by the government helping these migrant labourers with HIV/AIDS and factors of migration and their vulnerability in catching HIV/AIDS. For the first time Neutrosophic Cognitive Maps are used in the study of migrant labourers who have become HIV/AIDS victims. This study is done in Chapter IV. In chapter V we use Neutrosophic Relational Maps and we define some new neutrosophic tools like Combined Disjoint Block FRM, Combined Overlap NRM and linked NRM. We adopt these new techniques in the study and analysis of this problem. Chapter VI gives a very brief sketch of the life history of these 60 HIV/AIDS infected migrant labourers so that people from different social and cultural backgrounds follow our analysis. The last chapter gives suggestions and conclusions based on our study.

We establish a stochastic HIV/AIDS model for the individuals with protection awareness and reveal how the protection awareness plays its important role in the control of AIDS. We firstly show that there exists a global positive solution for the stochastic model. By constructing Lyapunov functions, the ergodic stationary distribution when $R_{0}^{s}>1$ and the extinction when $R_{0}^{e}<1$ for the stochastic model are obtained. A number of numerical simulations by using positive preserving truncated Euler-Maruyama method (PPTEM) are performed to illustrate the theoretical results. Our new results show that the detailed publicity has great impact on the control of AIDS compared with the extensive publicity, while the continuous antiretroviral therapy (ART) is helpful in the control of HIV/AIDS.

HIV is a deadly virus transmitted either through having of unprotected sex, mother to child transmission, sharing of unsterilized objects that is capable of making cut or wounds on the body, through blood or bodily fluid transmission. AIDS has no permanent cure but remedies that help in suppressing the power effect of the virus are available. Previous studies has shown that the epidemic claimed more lives via vertical transmission, mother-to-child transmission, blood transfusion, sexual intercourse and injection drug users. The associated models were derived using diagnosis and treatments records of confirmed status of HIV/AIDS clients. A new model analysis were proposed that could handle cases of HIV/AIDS routes of transmission and treatments via vertical, mother-to-child, blood transfusion, sexual intercourse, injection drug users that were not considered in previous studies. The new model was solved using Fractional Differential Transformation by Caputo sense algorithm. The new model is a major contribution for optimal assessment, monitoring, evaluation, control and management of HIV/AIDS, with 75% accuracy.

We propose a population model for TB-HIV/AIDS coinfection transmission dynamics, which considers antiretroviral therapy for HIV infection and treatments for latent and active tuberculosis. The HIV-only and TB-only sub-models are analyzed separately, as well as the TB-HIV/AIDS full model. The respective basic reproduction numbers are computed, equilibria and stability are studied. Optimal control theory is applied to the TB-HIV/AIDS model and optimal treatment strategies for co-infected individuals with HIV and TB are derived. Numerical simulations to the optimal control problem show that non intuitive measures can lead to the reduction of the number of individuals with active TB and AIDS.

With the rapid proliferation and adoption of social media among healthcare professionals and organizations, social media-based HIV/AIDS intervention programs have become increasingly popular. However, the question of the effectiveness of the HIV/AIDS messages disseminated via social media has received scant attention in the literature. The current study applies content analysis to examine the relationship between Facebook messaging strategies employed by 110 HIV/AIDS nonprofit organizations and audience reactions in the form of liking, commenting, and sharing behavior. The results reveal that HIV/AIDS nonprofit organizations often use informational messages as one-way communication with their audience instead of dialogic interactions. Some specific types of messages, such as medication-focused messages, engender better audience engagement, in contrast, event-related messages and call-to-action messages appear to translate into lower corresponding audience reactions. The findings provide guidance to HIV/AIDS organizations in developing effective social media communication strategies.

This research reports on the relationship and significance of social-economic factors (age, sex, employment status) and modes of HIV/AIDS transmission to the HIV/AIDS spread. Logistic regression model, a form of probabilistic function for binary response was used to relate social-economic factors (age, sex, employment status) to HIV/AIDS spread. The statistical predictive model was used to project the likelihood response of HIV/AIDS spread with a larger population using 10,000 Bootstrap re-sampling observations.

This book has six chapters. The first chapter gives a brief introduction about HIV/AIDS among rural women in Tamil Nadu. Chapter 2 is an analysis of the situation using fuzzy theory in general and Fuzzy Relational Maps (FRM)in particular. The FRM tool is specially chosen for two reasons: It can give the hidden pattern of the dynamical system and as the socio-economic condition of women infected with HIV/AIDS is interdependent we choose this special fuzzy tool called FRM. In Chapter 3, we use Fuzzy Associative Memories (FAM) to analyze the problem because FAM is the only fuzzy tool that can give the gradations of each of the nodes/concepts. In Chapter 4 for the first time we use neutrosophic theory in general and neutrosophic relational maps (NRM) in particular to analyze this problem. Interested readers can compare and analyze the two models FRM and NRM. This chapter introduces the notion of Neutrosophic Associative Memories (NAMs) that is an analogous model of Fuzzy Associative Memories. NAMs are applied to this problem and conclusions are based on this analysis. The sixth chapter gives the translated version of the verbatim interviews of the 101 HIV/AIDS infected, rural, uneducat

In this paper, we have identified and analyzed the emergence, structure and dynamics of the paradigmatic research fronts that established the fundamentals of the biomedical knowledge on HIV/AIDS. A search of papers with the identifiers "HIV/AIDS", "Human Immunodeficiency Virus", "HIV-1" and "Acquired Immunodeficiency Syndrome" in the Web of Science (Thomson Reuters), was carried out. A citation network of those papers was constructed. Then, a sub-network of the papers with the highest number of inter-citations (with a minimal in-degree of 28) was selected to perform a combination of network clustering and text mining to identify the paradigmatic research fronts and analyze their dynamics. Thirteen research fronts were identified in this sub-network. The biggest and oldest front is related to the clinical knowledge on the disease in the patient. Nine of the fronts are related to the study of specific molecular structures and mechanisms and two of these fronts are related to the development of drugs. The rest of the fronts are related to the study of the disease at the cellular level. Interestingly, the emergence of these fronts occurred in successive "waves" over the time which sugg

While probabilistic projection methods for projecting life expectancy exist, few account for covariates related to life expectancy. Generalized HIV/AIDS epidemics have a large, immediate negative impact on the life expectancy in a country, but this impact can be mitigated by widespread use of antiretroviral therapy (ART). Thus projection methods for countries with generalized HIV/AIDS epidemics could be improved by accounting for HIV prevalence, the future course of the epidemic and coverage of ART. We propose a method for making probabilistic projections of life expectancy to 2100 for all countries in the world accounting for HIV prevalence, the future course of the epidemic and its uncertainty, and adult ART coverage. We extend the current Bayesian probabilistic life expectancy projection methods of Raftery et al. (2013) to account for HIV prevalence and adult ART coverage. We evaluate our method using out-of-sample validation. We find that the proposed method performs better than the method that does not account for HIV prevalence or ART coverage for projections of life expectancy in countries with a generalized epidemic, while projections for countries without an epidemic remai

We consider a time-delayed HIV/AIDS epidemic model with education dissemination and study the asymptotic dynamics of solutions as well as the asymptotic behavior of the endemic equilibrium with respect to the amount of information disseminated about the disease. Under appropriate assumptions on the infection rates, we show that if the basic reproduction number is less than or equal to one, then the disease will be eradicated in the long run and any solution to the Cauchy problem converges to the unique disease-free equilibrium of the model. On the other hand, when the basic reproduction number is greater than one, we prove that the disease will be permanent but its impact on the population can be significantly minimized as the amount of education dissemination increases. In particular, under appropriate hypothesis on the model parameters, we establish that the size of the component of the infected population of the endemic equilibrium decreases linearly as a function of the amount of information disseminated. We also fit our model to a set of data on HIV/AIDS in order to estimate the infection, effective response, and information rates of the disease. We then use these estimates to

The United Nations (UN) issued official probabilistic population projections for all countries to 2100 in July 2015. This was done by simulating future levels of total fertility and life expectancy from Bayesian hierarchical models, and combining the results using a standard cohort-component projection method. The 40 countries with generalized HIV/AIDS epidemics were treated differently from others, in that the projections used the highly multistate Spectrum/EPP model, a complex 15-compartment model that was designed for short-term projections of quantities relevant to policy for the epidemic. Here we propose a simpler approach that is more compatible with the existing UN probabilistic projection methodology for other countries. Changes in life expectancy are projected probabilistically using a simple time series regression model on current life expectancy, HIV prevalence and ART coverage. These are then converted to age- and sex-specific mortality rates using a new family of model life tables designed for countries with HIV/AIDS epidemics that reproduces the characteristic hump in middle adult mortality. These are then input to the standard cohort-component method, as for other co

Stochastic volatility often implies increasing risks that are difficult to capture given the dynamic nature of real-world applications. We propose using arc length, a mathematical concept, to quantify cumulative variations (the total variability over time) to more fully characterize stochastic volatility. The hazard rate, as defined by the Cox proportional hazards model in survival analysis, is assumed to be impacted by the instantaneous value of a longitudinal variable. However, when cumulative variations pose a significant impact on the hazard, this assumption is questionable. Our proposed Bayesian Arc Length Survival Analysis Model (BALSAM) infuses arc length into a united statistical framework by synthesizing three parallel components (joint models, distributed lag models, and arc length). We illustrate the use of BALSAM in simulation studies and also apply it to an HIV/AIDS clinical trial to assess the impact of cumulative variations of CD4 count (a critical longitudinal biomarker) on mortality while accounting for measurement errors and relevant variables.

The Sustainable Development Goals (SDGs) of the United Nations provide a blueprint of a better future by 'leaving no one behind', and, to achieve the SDGs by 2030, poor countries require immense volumes of development aid. In this paper, we develop a causal machine learning framework for predicting heterogeneous treatment effects of aid disbursements to inform effective aid allocation. Specifically, our framework comprises three components: (i) a balancing autoencoder that uses representation learning to embed high-dimensional country characteristics while addressing treatment selection bias; (ii) a counterfactual generator to compute counterfactual outcomes for varying aid volumes to address small sample-size settings; and (iii) an inference model that is used to predict heterogeneous treatment-response curves. We demonstrate the effectiveness of our framework using data with official development aid earmarked to end HIV/AIDS in 105 countries, amounting to more than USD 5.2 billion. For this, we first show that our framework successfully computes heterogeneous treatment-response curves using semi-synthetic data. Then, we demonstrate our framework using real-world HIV data. Our fra

The probability-scale residual (PSR) is well defined across a wide variety of variable types and models, making it useful for studies of HIV/AIDS. In this manuscript, we highlight some of the properties of the PSR and illustrate its application with HIV data. As a residual, it can be useful for model diagnostics; we demonstrate its use with ordered categorical data and semiparametric transformation models. The PSR can also be used to construct tests of residual correlation. In fact, partial Spearman's rank correlation between $X$ and $Y$ while adjusting for covariates $Z$ can be constructed as the correlation between PSRs from models of $Y$ on $Z$ and of $X$ on $Z$. The covariance of PSRs is also useful in some settings. We apply these methods to a variety of HIV datasets including 1) a study examining risk factors for more severe forms of cervical lesions among 145 women living with HIV in Zambia, 2) a study investigating the association between 21 metabolomic biomarkers among 70 HIV-positive patients in the southeastern United States, and 3) a genome wide association study investigating the association between single nucleotide polymorphisms and tenofovir clearance among 501 HIV-

The epidemic of HIV in Malawi started early and at its peak 15% of all adults were infected with HIV. Malawi is a low-income country and the cost of putting all HIV-positive people in Malawi onto ART, expressed as a percentage of the gross domestic product, is the highest in the world. Nevertheless, Malawi has made great progress and the greatly reduced cost of potent anti-retroviral therapy (ART) makes it possible to contemplate ending the epidemic of HIV/AIDS. Here we consider what would have happened without ART, the No ART counterfactual, the impact if the current level of roll-out of ART is maintained, the Current Programme, and the likely impact if treatment is made available to everyone who is eligible under the 2013 guidelines of the World Health Organization reaching full coverage by 2020, the Expanded Programme. The Current Programme has substantially reduced the epidemic of HIV and the number of people dying of AIDS. The Expanded Programme has the potential to avert more infections, save more lives and end the epidemic. The annual cost of managing HIV will increase from about US$132 million in 2014 to about US$155 million in 2020 but will fall after that. If the Expanded

An increasing number of control techniques are introduced to HIV infection problem to explore the options of helping clinical testing, optimizing drug treatments and to study the drug resistance situations. In such cases, complete/accurate knowledge of the HIV model and/or parameters is critical not only to monitor the dynamics of the system, but also to adjust the therapy accordingly. In those studies, existence of any type of unknown parameters imposes severe set-backs and becomes problematic for the treatment of the patients. In this work, we develop a real-time adaptive nonlinear receding horizon control approach to aid such scenarios and to estimate unknown constant/time-varying parameters of nonlinear HIV system models. For this purpose, the problem of estimation is updated by a series of finite-time optimization problem which can be solved by backwards sweep Riccati method in real time without employing any iteration techniques. The simulation results demonstrates the fact that proposed algorithm is able to estimate unknown constant/time-varying parameters of HIV/AIDS model effectively and provide a unique, adaptive solution methodology to an important open problem.