On the role of social clusters in the transmission of infectious diseases

We introduce a spatial stochastic model for the spread of tuberculosis and HIV. We have three parameters: the size of the social cluster for each individual and the infection rates within and outside the social cluster. We show that when the infection rate from outside the cluster is low (this is presumably the case for tuberculosis and HIV) then an epidemic is possible only if the typical social cluster and the within infection rate are large enough. These results may be important in formulating new hypotheses for the transmission of TB and HIV.     

Bayesian Spatial Semi-Parametric Modeling of HIV Variation in Kenya

Spatial statistics has seen rapid application in many fields, especially epidemiology and public health. Many studies, nonetheless, make limited use of the geographical location information and also usually assume that the covariates, which are related to the response variable, have linear effects. We develop a Bayesian semi-parametric regression model for HIV prevalence data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (McMC). The model is applied to HIV prevalence data among men in Kenya, derived from the Kenya AIDS indicator survey, with n = 3,662. Past studies have concluded that HIV infection has a nonlinear association with age. In this study a smooth function based on penalized regression splines is used to estimate this nonlinear effect. Other covariates were assumed to have a linear effect. Spatial references to the counties were modeled as both structured and unstructured spatial effects. We observe that circumcision reduces the risk of HIV infection. The results also indicate that men in the urban areas were more likely to be infected by HIV as compared to their rural counterpart. Men with higher education had the lowest risk of HIV infection. A nonlinear relationship between HIV infection and age was established. Risk of HIV infection increases with age up to the age of 40 then declines with increase in age. Men who had STI in the last 12 months were more likely to be infected with HIV. Also men who had ever used a condom were found to have higher likelihood to be infected by HIV. A significant spatial variation of HIV infection in Kenya was also established. The study shows the practicality and flexibility of Bayesian semi-parametric regression model in analyzing epidemiological data.     

Semi-Parametric Spatial Joint Modeling of HIV and HSV-2 among Women in Kenya

Several diseases have common risk factors. The joint modeling of disease outcomes within a spatial statistical context may provide more insight on the interaction of diseases both at individual and at regional level. Spatial joint modeling allows for studying of the relationship between diseases and also between regions under study. One major approach for joint spatial modeling is the multivariate conditional autoregressive approach. In this approach, it is assumed that all the covariates in the study have linear effects on the multiple response variables. In this study, we relax this linearity assumption and allow some covariates to have nonlinear effects using the penalized regression splines. This model was used to jointly model the spatial variation of human immunodeficiency virus (HIV) and herpes simplex virus-type 2 (HSV-2) among women in Kenya. The model was applied to HIV and HSV-2 prevalence data among women aged 15–49 years in Kenya, derived from the 2007 Kenya AIDS indicator survey. A full Bayesian approach was used and the models were implemented in WinBUGS software. Both diseases showed significant spatial variation with highest disease burdens occurring around the Lake Victoria region. There was a nonlinear association between age of an individual and HIV and HSV-2 infection. The peak age for HIV was around 30 years while that of HSV-2 was about 40 years. A positive significant spatial correlation between HIV and HSV-2 was observed with a correlation of 0.6831(95% CI: 0.3859, 0.871).     

Kinetics of human immunodeficiency virus type 1 (HIV) DNA integration in acutely infected cells as determined using a novel assay for detection of integrated HIV DNA

We have developed a novel linker-primer PCR assay for the detection and quantification of integrated human immunodeficiency virus type 1 (HIV) DNA. This assay reproducibly allowed the detection of 10 copies of integrated HIV DNA, in a background of 2 x 10(5) cell equivalents of human chromosomal DNA, without amplifying extrachromosomal HIV DNA. We have used this assay and a near-synchronous one-step T-cell infection model to investigate the kinetics of viral DNA accumulation following HIV infection. We report here that integrated HIV DNA started accumulating 1 h after the first appearance of extrachromosomal viral DNA and accounted for approximately 10% of the total HIV DNA synthesized in the first round of viral replication. These results highlight the efficient nature of integrase-mediated HIV integration in infected T cells.     

Spatial Distributions of HIV Infection in an Endemic Area of Western Kenya: Guiding Information for Localized HIV Control and Prevention

HIV is still a major health problem in developing countries. Even though high HIV-risk-taking behaviors have been reported in African fishing villages, local distribution patterns of HIV infection in the communities surrounding these villages have not been thoroughly analyzed. The objective of this study was to investigate the geographical distribution patterns of HIV infection in communities surrounding African fishing villages. In 2011, we applied age- and sex-stratified random sampling to collect 1,957 blood samples from 42,617 individuals registered in the Health and Demographic Surveillance System in Mbita, which is located on the shore of Lake Victoria in western Kenya. We used these samples to evaluate existing antibody detection assays for several infectious diseases, including HIV antibody titers. Based on the results of the assays, we evaluated the prevalence of HIV infection according to sex, age, and altitude of participating households. We also used Kulldorff’s spatial scan statistic to test for HIV clustering in the study area. The prevalence of HIV at our study site was 25.3%. Compared with the younger age group (15–19 years), adults aged 30–34 years were 6.71 times more likely to be HIV-positive, and the estimated HIV-positive population among women was 1.43 times larger than among men. Kulldorff’s spatial scan statistic detected one marginally significant (P = 0.055) HIV-positive and one significant HIV-negative cluster (P = 0.047) in the study area. These results suggest a homogeneous HIV distribution in the communities surrounding fishing villages. In addition to individual behavior, more complex and diverse factors related to the social and cultural environment can contribute to a homogeneous distribution pattern of HIV infection outside of African fishing villages. To reduce rates of transmission in HIV-endemic areas, HIV prevention and control programs optimized for the local environment need to be developed.     

Parameters of human immunodeficiency virus infection of human cervical tissue and inhibition by vaginal virucides

Heterosexual transmission of human immunodeficiency virus (HIV) is the most frequent mode of infection worldwide. However, the immediate events between exposure to infectious virus and establishment of infection are still poorly understood. This study investigates parameters of HIV infection of human female genital tissue in vitro using an explant culture model. In particular, we investigated the role of the epithelium and virucidal agents in protection against HIV infection. We have demonstrated that the major target cells of infection reside below the genital epithelium, and thus HIV must cross this barrier to establish infection. Immune activation enhanced HIV infection of such subepithelial cells. Furthermore, our data suggest that genital epithelial cells were not susceptible to HIV infection, appear to play no part in the transfer of infectious virus across the epithelium, and thus may provide a barrier to infection. In addition, experiments using a panel of virucidal agents demonstrated differential efficiency to block HIV infection of subepithelial cells from partial to complete inhibition. This is the first demonstration that virucidal agents designed for topical vaginal use block HIV infection of genital tissue. Such agents have major implications for world health, as they will provide women with a mechanism of personal and covert protection from HIV infection.     

Primary cell model for activation-inducible human immunodeficiency virus

Quiescent T lymphocytes containing latent human immunodeficiency virus (HIV) provide a long-lived viral reservoir. This reservoir may be the source of active infection that is reinitiated following the cessation of antiretroviral therapy. Therefore, it is important to understand the mechanisms involved in latent infection to develop new strategies to eliminate the latent HIV reservoir. We have previously demonstrated that latently infected quiescent lymphocytes can be generated during thymopoiesis in vivo in the SCID-hu mouse system. However, there is still a pressing need for an in vitro model of HIV latency in primary human cells. Here, we present a novel in vitro model that recapitulates key aspects of dormant HIV infection. Using an enhanced green fluorescent protein-luciferase fusion protein-containing reporter virus, we have generated a stable infection in primary human CD4(+) CD8(+) thymocytes in the absence of viral gene expression. T-cell activation induces a >200-fold induction of reporter activity. The induced reporter activity originates from a fully reverse-transcribed and integrated genome. We further demonstrate that this model can be useful to study long terminal repeat regulation, as previously characterized NF-kappaB response element mutations decrease the activation of viral gene expression. This model can therefore be used to study intricate molecular aspects of activation-inducible HIV infection in primary cells.     

Cellular automata and its advances to drug therapy for HIV infection

This paper gives an over view of the use of cellular automata (CA) model of drug therapy for HIV infection. Nonuniform CA is employed to simulate drug treatment of HIV infection, where each computational domain may contain different CA rules, in contrast to normal uniform CA models. Ordinary (or partial) differential equation models are insufficient to describe the two extreme time scales involved in HIV infection (days and decades), as well as the implicit spatial heterogeneity. Zorzenon and Coutinho [Phy Rev Lett, 16 (2001) 1] reported a cellular automata approach to simulate three-phase patterns of human immunodeficiency virus (HIV) infection consisting of primary response, clinical latency and onset of acquired immunodeficiency syndrome (AIDS). But here we present a related model, based on non-uniform CA to study the dynamics of drug therapy of HIV infection. The main aim in this model is to simulate the four phases (acute, chronic, drug treatment responds and onset of AIDS). The results shown here indicate that both simulations (with and without treatments) evolve to the relatively same steady state (characteristics of Wolfram's class II behavior). Different kinds of drug therapies can also be simulated in this model, which can be found useful for developing a proper drug therapy.     

Paradoxical suppression of poly-specific broadly neutralizing antibodies in the presence of strain-specific neutralizing antibodies following HIV infection

One of the first immunologic responses against HIV infection is the presence of neutralizing antibodies that seem able to inactivate several HIV strains. Moreover, in vitro studies have shown the existence of monoclonal antibodies that exhibit broad crossclade neutralizing potential. Yet their number is low and slow to develop in vivo. In this paper, we investigate the potential benefits of inducing poly-specific neutralizing antibodies in vivo throughout immunization. We develop a mathematical model that considers the activation of families of B lymphocytes producing poly-specific and strain-specific antibodies and use it to demonstrate that, even if such families are successful in producing neutralizing antibodies, the competition between them may limit the poly-specific response allowing the virus to escape. We modify this model to account for viral evolution under the pressure of antibody responses in natural HIV infection. The model can reproduce viral escape under certain conditions of B lymphocyte competition. Using these models we provide explanations for the observed antibody failure in controlling natural infection and predict quantitative measures that need to be satisfied for long-term control of HIV infection.     

Estimation of the Distribution of Infection Times Using Longitudinal Serological Markers of HIV: Implications for the Estimation of HIV Incidence

Summary In the last decade, interest has been focused on human immunodeficiency virus (HIV) antibody assays and testing strategies that could distinguish recent infections from established infection in a single serum sample. Incidence estimates are obtained by using the relationship between prevalence, incidence, and duration of recent infection (window period). However, recent works demonstrated limitations of this approach due to the use of an estimated mean “window period.” We propose an alternative approach that consists in estimating the distribution of infection times based on serological marker values at the moment when the infection is first discovered. We propose a model based on the repeated measurements of virological markers of seroconversion for the marker trajectory. The parameters of the model are estimated using data from a cohort of HIV‐infected patients enrolled during primary infection. This model can be used for estimating the distribution of infection times for newly HIV diagnosed subjects reported in a HIV surveillance system. An approach is proposed for estimating HIV incidence from these results.     

Augmented designs to assess immune response in vaccine trials

This article introduces methods for use in vaccine clinical trials to help determine whether the immune response to a vaccine is actually causing a reduction in the infection rate. This is not easy because immune response to the (say HIV) vaccine is only observed in the HIV vaccine arm. If we knew what the HIV-specific immune response in placebo recipients would have been, had they been vaccinated, this immune response could be treated essentially like a baseline covariate and an interaction with treatment could be evaluated. Relatedly, the rate of infection by this baseline covariate could be compared between the two groups and a causative role of immune response would be supported if infection risk decreased with increasing HIV immune response only in the vaccine group. We introduce two methods for inferring this HIV-specific immune response. The first involves vaccinating everyone before baseline with an irrelevant vaccine, for example, rabies. Randomization ensures that the relationship between the immune responses to the rabies and HIV vaccines observed in the vaccine group is the same as what would have been seen in the placebo group. We infer a placebo volunteer's response to the HIV vaccine using their rabies response and a prediction model from the vaccine group. The second method entails vaccinating all uninfected placebo patients at the closeout of the trial with the HIV vaccine and recording immune response. We pretend this immune response at closeout is what they would have had at baseline. We can then infer what the distribution of immune response among placebo infecteds would have been. Such designs may help elucidate the role of immune response in preventing infections. More pointedly, they could be helpful in the decision to improve or abandon an HIV vaccine with mediocre performance in a phase III trial.     

Estimation of HIV infection and incubation via state space models

By using the state space model (Kalman filter model) of the HIV epidemic, in this paper we have developed a general Bayesian procedure to estimate simultaneously the HIV infection distribution, the HIV incubation distribution, the numbers of susceptible people, infective people and AIDS cases. The basic approach is to use the Gibbs sampling method combined with the weighted bootstrap method. We have applied this method to the San Francisco AIDS incidence data from January 1981 to December 1992. The results show clearly that both the probability density function of the HIV infection and the probability density function of the HIV incubation are curves with two peaks. The results of the HIV infection distribution are clearly consistent with the finding by Tan et al. [W.Y. Tan, S.C. Tang, S.R. Lee, Estimation of HIV seroconversion and effects of age in San Francisco homosexual populations, J. Appl. Stat. 25 (1998) 85]. The results of HIV incubation distribution seem to confirm the staged model used by Satten and Longini [G. Satten, I. Longini, Markov chain with measurement error: estimating the 'true' course of marker of the progression of human immunodeficiency virus disease, Appl. Stat. 45 (1996) 275].     

Impact of Male Circumcision on the HIV Epidemic in Papua New Guinea: A Country with Extensive Foreskin Cutting Practices

The degree to which adult medical male circumcision (MC) programs can reduce new HIV infections in a moderate HIV prevalence country like Papua New Guinea (PNG) are uncertain especially given the widespread prevalence of longitudinal foreskin cuts among adult males. We estimated the likely impact of a medical MC intervention in PNG using a mathematical model of HIV transmission. The model was age-structured and incorporated separate components for sex, rural/urban, men who have sex with men and female sex workers. Country-specific data of the prevalence of foreskin cuts, sexually transmitted infections, condom usage, and the acceptability of MC were obtained by our group through related studies. If longitudinal foreskin cutting has a protective efficacy of 20% compared to 60% for MC, then providing MC to 20% of uncut males from 2012 would require 376,000 procedures, avert 7,900 HIV infections by 2032, and require 143 MC per averted infection. Targeting uncut urban youths would achieve the most cost effective returns of 54 MC per HIV infection averted. These numbers of MC required to avert an HIV infection change little even with coverage up to 80% of men. The greater the protective efficacy of longitudinal foreskin cuts against HIV acquisition, the less impact MC interventions will have. Dependent on this efficacy, increasing condom use could have a much greater impact with a 10 percentage point increase averting 18,400 infections over this same period. MC programs could be effective in reducing HIV infections in PNG, particularly in high prevalence populations. However the overall impact is highly dependent on the protective efficacy of existing longitudinal foreskin cutting in preventing HIV.     

How fast could HIV change gene frequencies in the human population?

Infectious diseases have the potential to act as strong forces for genetic selection on the populations they affect. Human immunodeficiency virus (HIV) is a prime candidate to impose such genetic selection owing to the vast number of people it infects and the varying susceptibility of different human leucocyte antigen (HLA) types to HIV disease progression. We have constructed a model of HIV infection that differentiates between these HLA types, and have used reported estimates of the number of people infected with HIV and the different rates of progression to acquired immunodeficiency syndrome (AIDS) to provide a lower bound estimate on the length of time it would take for HIV to impose major genetic change in humans. We find that an HIV infection similar to that currently affecting sub-Saharan Africa could not yet have caused more than a 3 per cent decrease in the proportion of individuals who progress quickly to disease. Such an infection is unlikely to cause major genetic change (defined as a decrease in the proportion of quickly progressing individuals to under 50 per cent of their starting proportion) until 400 years have passed since HIV emergence. However, in very severely affected populations, there is a chance of observing such major genetic changes after another 50 years.     

Sampling HIV Intrahost Genealogies Based on a Model of Acute Stage CTL Response

Cytotoxic T lymphocytes (CTLs) play an important role in the immune response to HIV during the acute stage of infection, but the effect of CTLs on HIV intrahost genetic diversity is poorly understood. We introduce a model of CTL attack during the acute stage. Assuming this model, we develop a method to sample HIV intrahost genealogies. Using our sampling approach, we characterize the evolutionary forces that shape HIV genealogies. In particular, we show that early mutation events can have significant impact on HIV genealogies and that certain types of CTL attack are best at controlling HIV genetic diversity. Our sampler represents a first step toward using HIV genetic data to infer properties of CTL attack.     

Dynamics of simian immunodeficiency virus SIVmac239 infection in pigtail macaques

Pigtail macaques (PTM) are an excellent model for HIV research; however, the dynamics of simian immunodeficiency virus (SIV) SIVmac239 infection in PTM have not been fully evaluated. We studied nine PTM prior to infection, during acute and chronic SIVmac239 infections, until progression to AIDS. We found PTM manifest clinical AIDS more rapidly than rhesus macaques (RM), as AIDS-defining events occurred at an average of 42.17 weeks after infection in PTM compared to 69.56 weeks in RM (P = 0.0018). However, increased SIV progression was not associated with increased viremia, as both peak and set-point plasma viremias were similar between PTM and RM (P = 0.7953 and P = 0.1006, respectively). Moreover, this increased disease progression was not associated with rapid CD4(+) T cell depletion, as CD4(+) T cell decline resembled other SIV/human immunodeficiency virus (HIV) models. Since immune activation is the best predictor of disease progression during HIV infection, we analyzed immune activation by turnover of T cells by BrdU decay and Ki67 expression. We found increased levels of turnover prior to SIV infection of PTM compared to that observed with RM, which may contribute to their increased disease progression rate. These data evaluate the kinetics of SIVmac239-induced disease progression and highlight PTM as a model for HIV infection and the importance of immune activation in SIV disease progression.     

The cytokine network of acute HIV infection: a promising target for vaccines and therapy to reduce viral set-point?

Cytokines play a central role in the pathogenesis of many diseases, including HIV infection. However, the role of the cytokine network in early HIV infection is only now starting to be elucidated. A number of studies conducted in recent years have indicated that cytokines of the acute/early stages of HIV and SIV infection can impact viral set-point months later, and this is of critical importance since viral set-point during chronic HIV infection affects virus transmission and disease progression. This raises the question whether modulating the cytokine environment during acute/early HIV infection can be a target for novel approaches to develop a vaccine and therapeutics. In this review we focus on the kinetics and function of cytokines during acute HIV and SIV infection and how these may impact viral set-point. We also discuss unresolved questions that are essential for our understanding of the role of acute infection cytokines in HIV infection and that, if answered, may suggest novel therapeutic and vaccine strategies to control the worldwide HIV pandemic.     

An In Vitro Model for Measuring Immune Responses to Malaria in the Context of HIV Co-infection

Malaria and HIV co-infection is a growing health priority. However, most research on malaria or HIV currently focuses on each infection individually. Although understanding the disease dynamics for each of these pathogens independently is vital, it is also important that the interactions between these pathogens are investigated and understood. We have developed a versatile in vitro model of HIV-malaria co-infection to study host immune responses to malaria in the context of HIV infection. Our model allows the study of secreted factors in cellular supernatants, cell surface and intracellular protein markers, as well as RNA expression levels. The experimental design and methods used limit variability and promote data reliability and reproducibility. All pathogens used in this model are natural human pathogens (Plasmodium falciparum and HIV-1), and all infected cells are naturally infected and used fresh. We use human erythrocytes parasitized with P. falciparum and maintained in continuous in vitro culture. We obtain freshly isolated peripheral blood mononuclear cells from chronically HIV-infected volunteers. Every condition used has an appropriate control (P. falciparum parasitized vs. normal erythrocytes), and every HIV-infected donor has an HIV uninfected control, from which cells are harvested on the same day. This model provides a realistic environment to study the interactions between malaria parasites and human immune cells in the context of HIV infection.     

The differential infectivity and staged progression models for the transmission of HIV

Recent studies of HIV RNA in infected individuals show that viral levels vary widely between individuals and within the same individual over time. Individuals with higher viral loads during the chronic phase tend to develop AIDS more rapidly. If RNA levels are correlated with infectiousness, these variations explain puzzling results from HIV transmission studies and suggest that a small subset of infected people may be responsible for a disproportionate number of infections. We use two simple models to study the impact of variations in infectiousness. In the first model, we account for different levels of virus between individuals during the chronic phase of infection, and the increase in the average time from infection to AIDS that goes along with a decreased viral load. The second model follows the more standard hypothesis that infected individuals progress through a series of infection stages, with the infectiousness of a person depending upon his current disease stage. We derive and compare threshold conditions for the two models and find explicit formulas of their endemic equilibria. We show that formulas for both models can be put into a standard form, which allows for a clear interpretation. We define the relative impact of each group as the fraction of infections being caused by that group. We use these formulas and numerical simulations to examine the relative importance of different stages of infection and different chronic levels of virus to the spreading of the disease. The acute stage and the most infectious group both appear to have a disproportionate effect, especially on the early epidemic. Contact tracing to identify super-spreaders and alertness to the symptoms of acute HIV infection may both be needed to contain this epidemic.