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Background: Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data.Methods: Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample).Results: We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion.Conclusions: Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required when interpreting findings based on the sampling method. [ABSTRACT FROM AUTHOR]

AIMS: To identify factors associated with receptive syringe sharing among injection drug users (IDUs) and elucidate the association between syringe possession arrests and syringe sharing. DESIGN: Cross-sectional study. SETTING: Mexican border cities of Tijuana, Baja California and Ciudad Juarez, Chihuahua. PARTICIPANTS: IDUs in Tijuana (n = 222) and Ciudad Juarez (n = 206) were recruited using respondent-driven sampling (RDS). IDUs were > or = 18 years and had injected illicit drugs in the past month. MEASUREMENTS: An interviewer-administered survey was used to collect quantitative data on socio-demographic, behavioral and contextual characteristics, including self-reported syringe sharing and arrests for syringe possession. Associations with receptive syringe sharing were investigated using logistic regression with RDS adjustment. FINDINGS: Overall, 48% of participants reported ever being arrested for carrying an unused/sterile syringe, even though syringe purchase and possession is legal in Mexico. Arrest for possessing unused/sterile syringes was associated independently with receptive syringe sharing [adjusted odds ratio (AOR) = 2.05; 95% confidence interval (CI): 1.26, 3.35], as was injecting in a shooting gallery (AOR = 3.60; 95% CI: 2.21, 5.87), injecting in the street (AOR = 2.05; 95% CI: 1.18, 3.54) and injecting methamphetamine (AOR = 2.77; 95% CI: 1.41, 5.47) or cocaine (AOR = 1.96; 95% CI: 1.15, 3.36). More than half of participants (57%) had been arrested for possessing a used syringe; in a second model, arrest for used syringe possession was also associated independently with receptive sharing (AOR = 2.87; 95% CI: 1.76, 4.69). CONCLUSIONS: We documented high levels of syringe-related arrests in two Mexican-US border cities and an independent association between these arrests and risky injection practices. Public health collaborations with law enforcement to modify the risk environment in which drug use occurs are essential to facilitate safer injection practices. [ABSTRACT FROM AUTHOR]

Clinical diagnosis of venous thromboembolic (VTE) disease is often inaccurate because signs and symptoms are nonspecific. Testing for the absence of D-dimer levels in the blood of patients with suspected deep venous thrombosis and pulmonary embolism can assist in ruling out these illnesses. Some highly sensitive D-dimer assays have sufficient specificity to assist in the exclusion of VTE disease. Numerous clinical management trials using D-dimer measurement in association with additional diagnostic tests have shown that it is safe to withhold anticoagulant therapy in selected patients with suspected VTE disease who have negative D-dimer assay results. Applying these diagnostic strategies can potentially decrease the need for radiological testing. The simplicity of measuring D-dimer levels creates the potential for misuse. For safe patient management, clinicians must understand the indications for and limitations of D-dimer measurement in the diagnosis of VTE disease. [ABSTRACT FROM AUTHOR]

Syndromic surveillance, the collection of symptom data from individuals prior to or in the absence of diagnosis, is used throughout the developed world to provide rapid indications of outbreaks and unusual patterns of disease. However, the low cost of syndromic surveillance also makes it highly attractive for the developing world. We present a case study of electronic participatory syndromic surveillance, using participant-mobile phones in a rural region of Western Uganda, which has a high infectious disease burden, and frequent local and regional outbreaks. Our platform uses text messages to encode a suite of symptoms, their associated durations, and household disease burden, and we explore the ability of participants to correctly encode their symptoms, with an average of 75.2% of symptom reports correctly formatted between the second and 11th reporting timeslots. Concomitantly we identify divisions between participants able to rapidly adjust to this unusually participatory style of data collection, and those few for whom the study proved more challenging. We then perform analyses of the resulting syndromic time series, examining the clustering of symptoms by time and household to identify patterns such as a tendency towards the within-household sharing of respiratory illness.

Identifying the germline genes involved in immunoglobulin rearrangements is an essential first step in the analysis of antibody repertoires. Based on our prior work in analysing diverse recombinant viruses, we present IgSCUEAL (Immunoglobulin Subtype Classification Using Evolutionary ALgorithms), a phylogenetic approach to assign V and J regions of immunoglobulin sequences to their corresponding germline alleles, with D regions assigned using a simple pairwise alignment algorithm. We also develop an interactive web application for viewing the results, allowing the user to explore the frequency distribution of sequence assignments and CDR3 region length statistics, which is useful for summarizing repertoires, as well as a detailed viewer of rearrangements and region alignments for individual query sequences. We demonstrate the accuracy and utility of our method compared with sequence similarity-based approaches and other non-phylogenetic model-based approaches, using both simulated data and a set of evaluation datasets of human immunoglobulin heavy chain sequences. IgSCUEAL demonstrates the highest accuracy of V and J assignment amongst existing approaches, even when the reassorted sequence is highly mutated, and can successfully cluster sequences on the basis of shared V/J germline alleles.

We report here two novel HIV-1 recombinant forms (CRF01_AE/B) isolated from two HIV-positive male subjects infected through homosexual contact in Beijing, China. Recombination contributes substantially to the genetic diversity of HIV-1, and is likely to occur in populations in which multiple subtypes circulate. Molecular epidemiological studies showed that subtype B, CRF01_AE, and CRF07_BC are currently cocirculating in parallel among men who have sex with men (MSM) in China, providing the opportunity for the emergence of new recombinants. Phylogenetic analysis of near full-length genome (NFLG) sequences showed that the unique recombinant forms (URFs) were composed of gene regions from CRF01_AE and subtype B. The CRF01_AE region of the recombinants clustered together with a previously described cluster 4 lineage of CRF01_AE. The B regions of both the recombinants clustered within the B strains. The two recombinants were quite similar with six breakpoints in common. These data highlight the importance of continuous surveillance of the dynamic change of HIV-1 subtypes and new recombinants among the MSM population.

Previous work has shown that asymmetry in viral phylogenies may be indicative of heterogeneity in transmission, for example due to acute HIV infection or the presence of 'core groups' with higher contact rates. Hence, evidence of asymmetry may provide clues to underlying population structure, even when direct information on, for example, stage of infection or contact rates, are missing. However, current tests of phylogenetic asymmetry (a) suffer from false positives when the tips of the phylogeny are sampled at different times and (b) only test for global asymmetry, and hence suffer from false negatives when asymmetry is localised to part of a phylogeny. We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with random phylogenies with the same sampling and coalescence times, to reduce the false positive rate. We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry. In combination with different metrics of asymmetry, this combined approach offers detailed insights of how phylogenies reconstructed from real viral datasets may deviate from the simplistic assumptions of commonly used coalescent and birth-death process models.

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health., (Copyright © 2015, American Association for the Advancement of Science.)

The field of phylodynamics, which attempts to enhance our understanding of infectious disease dynamics using pathogen phylogenies, has made great strides in the past decade. Basic epidemiological and evolutionary models are now well characterized with inferential frameworks in place. However, significant challenges remain in extending phylodynamic inference to more complex systems. These challenges include accounting for evolutionary complexities such as changing mutation rates, selection, reassortment, and recombination, as well as epidemiological complexities such as stochastic population dynamics, host population structure, and different patterns at the within-host and between-host scales. An additional challenge exists in making efficient inferences from an ever increasing corpus of sequence data., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Early warning and robust estimation of influenza burden are critical to inform hospital preparedness and operational, treatment, and vaccination policies. Methods to enhance influenza-like illness (ILI) surveillance are regularly reviewed. We investigated the use of hospital staff 'influenza-like absences' (hospital staff-ILA), i.e. absence attributed to colds and influenza, to improve capture of influenza dynamics and provide resilience for hospitals., Methods: Numbers and rates of hospital staff-ILA were compared to regional surveillance data on ILI primary-care presentations (15-64 years) and to counts of laboratory confirmed cases among hospitalised patients from April 2008 to April 2013 inclusive. Analyses were used to determine comparability of the ILI and hospital-ILA and how systems compared in early warning and estimating the burden of disease., Results: Among 20,021 reported hospital-ILA and 4661 community ILI cases, correlations in counts were high and consistency in illness measurements was observed. In time series analyses, both hospital-ILA and ILI showed similar timing of the seasonal component. Hospital-ILA data often commenced and peaked earlier than ILI according to a Bayesian prospective alarm algorithm. Hospital-ILA rates were more comparable to model-based estimates of 'true' influenza burden than ILI., Conclusions: Hospital-ILA appears to have the potential to be a robust, yet simple syndromic surveillance method that could be used to enhance estimates of disease burden and early warning, and assist with local hospital preparedness.

We report two different unique HIV-1 recombinant viruses from two HIV-positive men who have sex with men (MSM) in Beijing, China. Phylogenetic analysis of near full-length genomes (NFLG) showed that the unique recombinant forms (URFs) were comprised of gene regions from two circulating recombinant forms, CRF01_AE and CRF07_BC, both common in China. The parental CRF01_AE region of the recombinants clustered together with a previously described cluster 4 lineage of CRF01_AE. The CRF07_BC regions of both the recombinants clustered within the CRF07_BC radiation, but were distinct from other CRF07_BC reference sequences. The two recombinant forms had two breakpoints in common. The emergence of the two URFs indicates the ongoing generation of recombinant viruses involving CRF01_AE and CRF07_BC, and may provide insight into our understanding of the dynamics and complexity of the HIV-1 epidemic in China.

Many population genetic models have been developed for the purpose of inferring population size and growth rates from random samples of genetic data. We examine two popular approaches to this problem, the coalescent and the birth–death-sampling model (BDM), in the context of estimating population size and birth rates in a population growing exponentially according to the birth–death branching process. For sequences sampled at a single time, we found the coalescent and the BDM gave virtually indistinguishable results in terms of the growth rates and fraction of the population sampled, even when sampling from a small population. For sequences sampled at multiple time points, we find that the birth–death model estimators are subject to large bias if the sampling process is misspecified. Since BDMs incorporate a model of the sampling process, we show how much of the statistical power of BDMs arises from the sequence of sample times and not from the genealogical tree. This motivates the development of a new coalescent estimator, which is augmented with a model of the known sampling process and is potentially more precise than the coalescent that does not use sample time information.

Zoonotic pathogens cause an estimated 70% of emerging and re-emerging infectious diseases in humans. In sub-Saharan Africa, bushmeat hunting and butchering is considered the primary risk factor for human-wildlife contact and zoonotic disease transmission, particularly for the transmission of simian retroviruses. However, hunting is only one of many activities in sub-Saharan Africa that bring people and wildlife into contact. Here, we examine human-animal interaction in western Uganda, identifying patterns of injuries from animals and contact with nonhuman primates. Additionally, we identify individual-level risk factors associated with contact. Nearly 20% (246/1,240) of participants reported either being injured by an animal or having contact with a primate over their lifetimes. The majority (51.7%) of injuries were dog bites that healed with no long-term medical consequences. The majority (76.8%) of 125 total primate contacts involved touching a carcass; however, butchering (20%), hunting (10%), and touching a live primate (10%) were also reported. Red colobus (Piliocolobus rufomitratus tephrosceles) accounted for most primate contact events. Multivariate logistic regression indicated that men who live adjacent to forest fragments are at elevated risk of animal contact and specifically primate contact. Our results provide a useful comparison to West and Central Africa where "bushmeat hunting" is the predominant paradigm for human-wildlife contact and zoonotic disease transmission.

Introduction: Respondent-driven sampling (RDS) is a variant of a link-tracing design intended for generating unbiased estimates of the composition of hidden populations that typically involves giving participants several coupons to recruit their peers into the study. RDS may generate biased estimates if coupons are distributed non-randomly or if potential recruits present for interview non-randomly. We explore if biases detected in an RDS study were due to either of these mechanisms, and propose and apply weights to reduce bias due to non-random presentation for interview., Methods: Using data from the total population, and the population to whom recruiters offered their coupons, we explored how age and socioeconomic status were associated with being offered a coupon, and, if offered a coupon, with presenting for interview. Population proportions were estimated by weighting by the assumed inverse probabilities of being offered a coupon (as in existing RDS methods), and also of presentation for interview if offered a coupon by age and socioeconomic status group., Results: Younger men were under-recruited primarily because they were less likely to be offered coupons. The under-recruitment of higher socioeconomic status men was due in part to them being less likely to present for interview. Consistent with these findings, weighting for non-random presentation for interview by age and socioeconomic status group greatly improved the estimate of the proportion of men in the lowest socioeconomic group, reducing the root-mean-squared error of RDS estimates of socioeconomic status by 38%, but had little effect on estimates for age. The weighting also improved estimates for tribe and religion (reducing root-mean-squared-errors by 19-29%), but had little effect for sexual activity or HIV status., Conclusions: Data collected from recruiters on the characteristics of men to whom they offered coupons may be used to reduce bias in RDS studies. Further evaluation of this new method is required.

Understanding the genetic, antigenic and structural changes that occur during HIV-1 infection in response to pre-existing immunity will facilitate current efforts to develop an HIV-1 vaccine. Much is known about HIV-1 variation at the population level but little with regard to specific changes occurring in the envelope glycoprotein within a host in response to immune pressure elicited by antibodies. The aim of this study was to track and map specific early genetic changes occurring in the viral envelope gene following vaccination using a highly controlled viral challenge setting in the SHIV macaque model. We generated 449 full-length env sequences from vaccinees, and 63 from the virus inoculum. Analysis revealed a different pattern in the distribution and frequency of mutations in the regions of the envelope gene targeted by the vaccine as well as different patterns of diversification between animals in the naïve control group and vaccinees. Given the high stringency of the model it is remarkable that we were able to identify genetic changes associated with the vaccination. This work provides insight into the characterization of breakthrough viral populations in less than fully efficacious vaccines and illustrates the value of HIV-1 Env SHIV challenge model in macaques to unravel the mechanisms driving HIV-1 envelope genetic diversity in the presence of vaccine induced-responses.

Epidemiological models have highlighted the importance of population structure in the transmission dynamics of infectious diseases. Using HIV-1 as an example of a model evolutionary system, we consider how population structure affects the shape and the structure of a viral phylogeny in the absence of strong selection at the population level. For structured populations, the number of lineages as a function of time is insufficient to describe the shape of the phylogeny. We develop deterministic approximations for the dynamics of tips of the phylogeny over evolutionary time, the number of 'cherries', tips that share a direct common ancestor, and Sackin's index, a commonly used measure of phylogenetic imbalance or asymmetry. We employ cherries both as a measure of asymmetry of the tree as well as a measure of the association between sequences from different groups. We consider heterogeneity in infectiousness associated with different stages of HIV infection, and in contact rates between groups of individuals. In the absence of selection, we find that population structure may have relatively little impact on the overall asymmetry of a tree, especially when only a small fraction of infected individuals is sampled, but may have marked effects on how sequences from different subpopulations cluster and co-cluster.

The CD8+ T cell effector mechanisms that mediate control of HIV-1 and SIV infections remain poorly understood. Recent work suggests that the mechanism may be primarily non-lytic. This is in apparent conflict with the observation that SIV and HIV-1 variants that escape CD8+ T cell surveillance are frequently selected. Whilst it is clear that a variant that has escaped a lytic response can have a fitness advantage compared to the wild-type, it is less obvious that this holds in the face of non-lytic control where both wild-type and variant infected cells would be affected by soluble factors. In particular, the high motility of T cells in lymphoid tissue would be expected to rapidly destroy local effects making selection of escape variants by non-lytic responses unlikely. The observation of frequent HIV-1 and SIV escape poses a number of questions. Most importantly, is the consistent observation of viral escape proof that HIV-1- and SIV-specific CD8+ T cells lyse infected cells or can this also be the result of non-lytic control? Additionally, the rate at which a variant strain escapes a lytic CD8+ T cell response is related to the strength of the response. Is the same relationship true for a non-lytic response? Finally, the potential anti-viral control mediated by non-lytic mechanisms compared to lytic mechanisms is unknown. These questions cannot be addressed with current experimental techniques nor with the standard mathematical models. Instead we have developed a 3D cellular automaton model of HIV-1 which captures spatial and temporal dynamics. The model reproduces in vivo HIV-1 dynamics at the cellular and population level. Using this model we demonstrate that non-lytic effector mechanisms can select for escape variants but that outgrowth of the variant is slower and less frequent than from a lytic response so that non-lytic responses can potentially offer more durable control.

Identifying the source of transmission using pathogen genetic data is complicated by numerous biological, immunological, and behavioral factors. A large source of error arises when there is incomplete or sparse sampling of cases. Unsampled cases may act as either a common source of infection or as an intermediary in a transmission chain for hosts infected with genetically similar pathogens. It is difficult to quantify the probability of common source or intermediate transmission events, which has made it difficult to develop statistical tests to either confirm or deny putative transmission pairs with genetic data. We present a method to incorporate additional information about an infectious disease epidemic, such as incidence and prevalence of infection over time, to inform estimates of the probability that one sampled host is the direct source of infection of another host in a pathogen gene genealogy. These methods enable forensic applications, such as source-case attribution, for infectious disease epidemics with incomplete sampling, which is usually the case for high-morbidity community-acquired pathogens like HIV, Influenza and Dengue virus. These methods also enable epidemiological applications such as the identification of factors that increase the risk of transmission. We demonstrate these methods in the context of the HIV epidemic in Detroit, Michigan, and we evaluate the suitability of current sequence databases for forensic and epidemiological investigations. We find that currently available sequences collected for drug resistance testing of HIV are unlikely to be useful in most forensic investigations, but are useful for identifying transmission risk factors.

Objectives: We determined the factors associated with hepatitis C (HCV) infection among rural Appalachian drug users., Methods: This study included 394 injection drug users (IDUs) participating in a study of social networks and infectious disease risk in Appalachian Kentucky. Trained staff conducted HCV, HIV, and herpes simplex-2 virus (HSV-2) testing, and an interviewer-administered questionnaire measured self-reported risk behaviors and sociometric network characteristics., Results: The prevalence of HCV infection was 54.6% among rural IDUs. Lifetime factors independently associated with HCV infection included HSV-2, injecting for 5 or more years, posttraumatic stress disorder, injection of cocaine, and injection of prescription opioids. Recent (past-6-month) correlates of HCV infection included sharing of syringes (adjusted odds ratio = 2.24; 95% confidence interval = 1.32, 3.82) and greater levels of eigenvector centrality in the drug network., Conclusions: One factor emerged that was potentially unique to rural IDUs: the association between injection of prescription opioids and HCV infection. Therefore, preventing transition to injection, especially among prescription opioid users, may curb transmission, as will increased access to opioid maintenance treatment, novel treatments for cocaine dependence, and syringe exchange.

Phylogenies of highly genetically variable viruses such as HIV-1 are potentially informative of epidemiological dynamics. Several studies have demonstrated the presence of clusters of highly related HIV-1 sequences, particularly among recently HIV-infected individuals, which have been used to argue for a high transmission rate during acute infection. Using a large set of HIV-1 subtype B pol sequences collected from men who have sex with men, we demonstrate that virus from recent infections tend to be phylogenetically clustered at a greater rate than virus from patients with chronic infection ('excess clustering') and also tend to cluster with other recent HIV infections rather than chronic, established infections ('excess co-clustering'), consistent with previous reports. To determine the role that a higher infectivity during acute infection may play in excess clustering and co-clustering, we developed a simple model of HIV infection that incorporates an early period of intensified transmission, and explicitly considers the dynamics of phylogenetic clusters alongside the dynamics of acute and chronic infected cases. We explored the potential for clustering statistics to be used for inference of acute stage transmission rates and found that no single statistic explains very much variance in parameters controlling acute stage transmission rates. We demonstrate that high transmission rates during the acute stage is not the main cause of excess clustering of virus from patients with early/acute infection compared to chronic infection, which may simply reflect the shorter time since transmission in acute infection. Higher transmission during acute infection can result in excess co-clustering of sequences, while the extent of clustering observed is most sensitive to the fraction of infections sampled.

Adjuvant formulations capable of inducing high titer and high affinity antibody responses would provide a major advance in the development of vaccines to viral infections such as HIV-1. Although oil-in-water emulsions, such as Freund's adjuvant (FCA/FIA), are known to be potent, their toxicity and reactogenicity make them unacceptable for human use. Here, we explored different adjuvants and compared their ability to elicit antibody responses to FCA/FIA. Recombinant soluble trimeric HIV-1 gp140 antigen was formulated in different adjuvants, including FCA/FIA, Carbopol-971P, Carbopol-974P and the licensed adjuvant MF59, or combinations of MF59 and Carbopol. The antigen-adjuvant formulation was administered in a prime-boost regimen into rabbits, and elicitation of antigen binding and neutralizing antibodies (nAbs) was evaluated. When used individually, only FCA/FIA elicited significantly higher titer of nAbs than the control group (gp140 in PBS (p<0.05)). Sequential prime-boost immunizations with different adjuvants did not offer improvements over the use of FCA/FIA or MF59. Remarkably however, the concurrent use of the combination of Carbopol-971P and MF59 induced potent adjuvant activity with significantly higher titer nAbs than FCA/FIA (p<0.05). This combination was not associated with any obvious local or systemic adverse effects. Antibody competition indicated that the majority of the neutralizing activities were directed to the CD4 binding site (CD4bs). Increased antibody titers to the gp41 membrane proximal external region (MPER) and gp120 V3 were detected when the more potent adjuvants were used. These data reveal that the combination of Carbopol-971P and MF59 is unusually potent for eliciting nAbs to a variety of HIV-1 nAb epitopes.

Adaptive evolution frequently occurs in episodic bursts, localized to a few sites in a gene, and to a small number of lineages in a phylogenetic tree. A popular class of "branch-site" evolutionary models provides a statistical framework to search for evidence of such episodic selection. For computational tractability, current branch-site models unrealistically assume that all branches in the tree can be partitioned a priori into two rigid classes--"foreground" branches that are allowed to undergo diversifying selective bursts and "background" branches that are negatively selected or neutral. We demonstrate that this assumption leads to unacceptably high rates of false positives or false negatives when the evolutionary process along background branches strongly deviates from modeling assumptions. To address this problem, we extend Felsenstein's pruning algorithm to allow efficient likelihood computations for models in which variation over branches (and not just sites) is described in the random effects likelihood framework. This enables us to model the process at every branch-site combination as a mixture of three Markov substitution models--our model treats the selective class of every branch at a particular site as an unobserved state that is chosen independently of that at any other branch. When benchmarked on a previously published set of simulated sequences, our method consistently matched or outperformed existing branch-site tests in terms of power and error rates. Using three empirical data sets, previously analyzed for episodic selection, we discuss how modeling assumptions can influence inference in practical situations.

Background: Respondent-driven sampling(RDS) is an increasingly widely used variant of a link tracing design for recruiting hidden populations. The role of the spatial distribution of the target population has not been robustly examined for RDS. We examine patterns of recruitment by location, and how they may have biased an RDS study findings., Methods: Total-population data were available on a range of characteristics on a population of 2402 male household-heads from an open cohort of 25 villages in rural Uganda. The locations of households were known a-priori. An RDS survey was carried out in this population, employing current RDS methods of sampling and statistical inference., Results: There was little heterogeneity in the population by location. Data suggested more distant contacts were less likely to be reported, and therefore recruited, but if reported more distant contacts were as likely as closer contacts to be recruited. There was no evidence that closer proximity to a village meeting place was associated with probability of being recruited, however it was associated with a higher probability of recruiting a larger number of recruits. People living closer to an interview site were more likely to be recruited., Conclusions: Household location affected the overall probability of recruitment, and the probability of recruitment by a specific recruiter. Patterns of recruitment do not appear to have greatly biased estimates in this study. The observed patterns could result in bias in more geographically heterogeneous populations. Care is required in RDS studies when choosing the network size question and interview site location(s).

In order to design strategies for eradication of HIV-1 from infected individuals, detailed insight into the HIV-1 reservoirs that persist in patients on suppressive antiretroviral therapy (ART) is required. In this regard, most studies have focused on integrated (proviral) HIV-1 DNA forms in cells circulating in blood. However, the majority of proviral DNA is replication-defective and archival, and as such, has limited ability to reveal the dynamics of the viral population that persists in patients on suppressive ART. In contrast, extrachromosomal (episomal) viral DNA is labile and as a consequence is a better surrogate for recent infection events and is able to inform on the extent to which residual replication contributes to viral reservoir maintenance. To gain insight into the diversity and compartmentalization of HIV-1 under suppressive ART, we extensively analyzed longitudinal peripheral blood mononuclear cells (PBMC) samples by deep sequencing of episomal and integrated HIV-1 DNA from patients undergoing raltegravir intensification. Reverse-transcriptase genes selectively amplified from episomal and proviral HIV-1 DNA were analyzed by deep sequencing 0, 2, 4, 12, 24 and 48 weeks after raltegravir intensification. We used maximum likelihood phylogenies and statistical tests (AMOVA and Slatkin-Maddison (SM)) in order to determine molecular compartmentalization. We observed low molecular variance (mean variability ≤0.042). Although phylogenies showed that both DNA forms were intermingled within the phylogenetic tree, we found a statistically significant compartmentalization between episomal and proviral DNA samples (P<10(-6) AMOVA test; P = 0.001 SM test), suggesting that they belong to different viral populations. In addition, longitudinal analysis of episomal and proviral DNA by phylogeny and AMOVA showed signs of non-chronological temporal compartmentalization (all comparisons P<10(-6)) suggesting that episomal and proviral DNA forms originated from different anatomical compartments. Collectively, this suggests the presence of a chronic viral reservoir in which there is stochastic release of infectious virus and in which there are limited rounds of de novo infection. This could be explained by the existence of different reservoirs with unique pharmacological accessibility properties, which will require strategies that improve drug penetration/retention within these reservoirs in order to minimise maintenance of the viral reservoir by de novo infection.

Since the demonstration that almost 80% of human immunodeficiency virus type 1 (HIV-1) infections result from the transmission of a single variant from the donor, biological features similar to those of HIV mucosal transmission have been reported for macaques inoculated with simian immunodeficiency virus (SIV). Here we describe the early diversification events and the impact of challenge doses on viral kinetics and on the number of variants transmitted in macaques infected with the chimeric simian/human immunodeficiency virus SHIV(sf162p4). We show that there is a correlation between the dose administered and the number of variants transmitted and that certain inoculum variants are preferentially transmitted. This could provide insight into the viral determinants of transmission and could aid in vaccine development. Challenge through the mucosal route with high doses results in the transmission of multiple variants in all the animals. Such an unrealistic scenario could underestimate potential intervention measures. We thus propose the use of molecular evolution analysis to aid in the determination of challenge doses that better mimic the transmission dynamics seen in natural HIV-1 infection.

Human immunodeficiency virus type 1 (HIV-1) genomes often carry one or more mutations associated with drug resistance upon transmission into a therapy-naïve individual. We assessed the prevalence and clinical significance of transmitted drug resistance (TDR) in chronically-infected therapy-naïve patients enrolled in a multi-center cohort in North America. Pre-therapy clinical significance was quantified by plasma viral load (pVL) and CD4+ cell count (CD4) at baseline. Naïve bulk sequences of HIV-1 protease and reverse transcriptase (RT) were screened for resistance mutations as defined by the World Health Organization surveillance list. The overall prevalence of TDR was 14.2%. We used a Bayesian network to identify co-transmission of TDR mutations in clusters associated with specific drugs or drug classes. Aggregate effects of mutations by drug class were estimated by fitting linear models of pVL and CD4 on weighted sums over TDR mutations according to the Stanford HIV Database algorithm. Transmitted resistance to both classes of reverse transcriptase inhibitors was significantly associated with lower CD4, but had opposing effects on pVL. In contrast, position-specific analyses of TDR mutations revealed substantial effects on CD4 and pVL at several residue positions that were being masked in the aggregate analyses, and significant interaction effects as well. Residue positions in RT with predominant effects on CD4 or pVL (D67 and M184) were re-evaluated in causal models using an inverse probability-weighting scheme to address the problem of confounding by other mutations and demographic or risk factors. We found that causal effect estimates of mutations M184V/I (-1.7 log₁₀pVL) and D67N/G (-2.1[³√CD4] and 0.4 log₁₀pVL) were compensated by K103N/S and K219Q/E/N/R. As TDR becomes an increasing dilemma in this modern era of highly-active antiretroviral therapy, these results have immediate significance for the clinical management of HIV-1 infections and our understanding of the ongoing adaptation of HIV-1 to human populations.

Objectives: To test the use of a rapid assessment tool to determine social network size, and to test whether social networks with a high density of HIV/sexually transmitted infection (STI) or substance using persons were independent predictors of HIV and STI status among men who have sex with men (MSM) using a rapid tool for collecting network information., Methods: We interviewed 609 MSM from 14 bars in San Diego, California, USA, using an enhanced version of the Priorities for Local AIDS Control Efforts (PLACE) methodology. Social network size was assessed using a series of 19 questions of the form 'How many people do you know that have the name X?', where X included specific male and female names (eg, Keith), use illicit substances, and have HIV. Generalised linear models were used to estimate average and group-specific network sizes, and their association with HIV status, STI history and methamphetamine use., Results: Despite possible errors in ascertaining network size, average reported network sizes were larger for larger groups. Those who reported having HIV infection or having past STI reported significantly more HIV infected and methamphetamine or popper using individuals in their social network. There was a dose-dependent effect of social network size of HIV infected individuals on self-reported HIV status, past STI and use of methamphetamine in the last 12 months, after controlling for age, ethnicity and numbers of sexual partners in the last year., Conclusions: Relatively simple measures of social networks are associated with HIV/STI risk, and may provide a useful tool for targeting HIV/STI surveillance and prevention.

Background: There is growing concern regarding the safety of blood pressure-lowering medications administered during the perioperative period. Whether loop diuretics also induce intraoperative hypotension is uncertain. Our objective was to compare the effects of continuing or withholding furosemide on the day of noncardiac elective surgery on intraoperative hypotension among chronic users of furosemide., Methods: A double blind, randomized, placebo controlled trial was conducted at 3 North American university centers between September 2000 and December 2006. Participants were randomly assigned in a 1:1 ratio to receive either furosemide or placebo on the day of surgery. The primary outcome was risk of developing intraoperative hypotension. A priori secondary outcomes included risk of heart failure; composite cardiovascular event (myocardial infarction, arrhythmia, stroke or transient ischemic attack, or death); and change in renal function and electrolytes., Results: Of the 212 patients enrolled, 193 patients underwent surgery. There was no significant difference in risk of developing intraoperative hypotension between the furosemide (49%) and placebo (51.9%) groups (relative risk [RR], 0.95; 95% confidence interval [CI], 0.72-1.24; P = .78). The intraoperative administration of vasopressors and fluids were similar between both groups. The risk of developing postoperative cardiovascular events was not significantly different between those randomized to furosemide (4.8%) or placebo (2.8%) (RR, 1.73; 95% CI, 0.42-7.06; P = .49). There was no significant difference in renal function or electrolytes between the 2 groups., Conclusion: Among elective, noncardiac surgeries in patients chronically treated with furosemide, the administration of furosemide on the day of surgery did not significantly increase the risk for intraoperative hypotension., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.

Information on the dynamics of the effective population size over time can be obtained from the analysis of phylogenies, through the application of time-varying coalescent models. This approach has been used to study the dynamics of many different viruses, and has demonstrated a wide variety of patterns, which have been interpreted in the context of changes over time in the 'effective number of infections', a quantity proportional to the number of infected individuals. However, for infectious diseases, the rate of coalescence is driven primarily by new transmissions i.e. the incidence, and only indirectly by the number of infected individuals through sampling effects. Using commonly used epidemiological models, we show that the coalescence rate may indeed reflect the number of infected individuals during the initial phase of exponential growth when time is scaled by infectivity, but in general, a single change in time scale cannot be used to estimate the number of infected individuals. This has important implications when integrating phylogenetic data in the context of other epidemiological data.

Rapidly evolving viruses such as HIV-1 display extensive sequence variation in response to host-specific selection, while simultaneously maintaining functions that are critical to replication and infectivity. This apparent conflict between diversifying and purifying selection may be resolved by an abundance of epistatic interactions such that the same functional requirements can be met by highly divergent sequences. We investigate this hypothesis by conducting an extensive characterization of sequence variation in the HIV-1 nef gene that encodes a highly variable multifunctional protein. Population-based sequences were obtained from 686 patients enrolled in the HOMER cohort in British Columbia, Canada, from which the distribution of nonsynonymous substitutions in the phylogeny was reconstructed by maximum likelihood. We used a phylogenetic comparative method on these data to identify putative epistatic interactions between residues. Two interactions (Y120/Q125 and N157/S169) were chosen to further investigate within-host evolution using HIV-1 RNA extractions from plasma samples from eight patients. Clonal sequencing confirmed strong linkage between polymorphisms at these sites in every case. We used massively parallel pyrosequencing (MPP) to reconstruct within-host evolution in these patients. Experimental error associated with MPP was quantified by performing replicates at two different stages of the protocol, which were pooled prior to analysis to reduce this source of variation. Phylogenetic reconstruction from these data revealed correlated substitutions at Y120/Q125 or N157/S169 repeated across multiple lineages in every host, indicating convergent within-host evolution shaped by epistatic interactions.

Over time, natural selection molds every gene into a unique mosaic of sites evolving rapidly or resisting change-an "evolutionary fingerprint" of the gene. Aspects of this evolutionary fingerprint, such as the site-specific ratio of nonsynonymous to synonymous substitution rates (dN/dS), are commonly used to identify genetic features of potential biological interest; however, no framework exists for comparing evolutionary fingerprints between genes. We hypothesize that protein-coding genes with similar protein structure and/or function tend to have similar evolutionary fingerprints and that comparing evolutionary fingerprints can be useful for discovering similarities between genes in a way that is analogous to, but independent of, discovery of similarity via sequence-based comparison tools such as Blast. To test this hypothesis, we develop a novel model of coding sequence evolution that uses a general bivariate discrete parameterization of the evolutionary rates. We show that this approach provides a better fit to the data using a smaller number of parameters than existing models. Next, we use the model to represent evolutionary fingerprints as probability distributions and present a methodology for comparing these distributions in a way that is robust against variations in data set size and divergence. Finally, using sequences of three rapidly evolving RNA viruses (HIV-1, hepatitis C virus, and influenza A virus), we demonstrate that genes within the same functional group tend to have similar evolutionary fingerprints. Our framework provides a sound statistical foundation for efficient inference and comparison of evolutionary rate patterns in arbitrary collections of gene alignments, clustering homologous and nonhomologous genes, and investigation of biological and functional correlates of evolutionary rates.

Background: Respondent-driven sampling (RDS) is a network-based method used to recruit hidden populations. Since it is respondent-driven, RDS is prone to bias. However, these biases could facilitate recruitment of high-risk networks. We examined recruitment patterns of human immunodeficiency virus (HIV)-positive injection drug users (IDUs) and identified factors associated with being recruited by an HIV-positive IDU in a RDS-based study., Methods: IDUs aged > or =18, who injected within the last month and resided in Tijuana, Mexico, were recruited using RDS and underwent interviews and testing for HIV, syphilis, and tuberculosis. Weighted logistic regression was used to identify predictors of being recruited by an HIV-positive IDU., Results: Of 1056 IDUs, HIV-positive subjects comprised 4.4% of the sample and generated 4.7% of recruits, indicating that recruitment effectiveness did not vary by HIV-status. However, 10% of the subjects recruited by HIV-positive recruiters were infected with HIV as compared to 4.1% of subjects recruited by HIV-negative recruiters, (P = 0.06), a difference that, after controlling for whether the recruiter and recruit injected drugs together, attained statistical significance (P = 0.04), indicating that recruitment patterns differed by HIV-status. Factors independently associated with being recruited by an HIV-positive IDU included lifetime syphilis infection, ever having sex with an HIV-positive person, knowing someone with HIV/AIDS, being recruited at a shooting gallery, having recently used the local needle exchange program, and having a larger number of recent arrests for track marks., Conclusion: HIV-positive IDUs have different recruitment patterns than HIV-negative IDUs, with HIV-positive IDUs tending to recruit other HIV-positive IDUs. Social and environmental factors along with risk behaviors were independently associated with being the recruit of an HIV-positive IDU in Tijuana. Although the goal of this study was not to recruit HIV+ or other high-risk persons, our results suggest that RDS has the potential to successfully be used in the identification of HIV+ or other high risk individuals.

We present a formalism for unifying the inference of population size from genetic sequences and mathematical models of infectious disease in populations. Virus phylogenies have been used in many recent studies to infer properties of epidemics. These approaches rely on coalescent models that may not be appropriate for infectious diseases. We account for phylogenetic patterns of viruses in susceptible-infected (SI), susceptible-infected-susceptible (SIS), and susceptible-infected-recovered (SIR) models of infectious disease, and our approach may be a viable alternative to demographic models used to reconstruct epidemic dynamics. The method allows epidemiological parameters, such as the reproductive number, to be estimated directly from viral sequence data. We also describe patterns of phylogenetic clustering that are often construed as arising from a short chain of transmissions. Our model reproduces the moments of the distribution of phylogenetic cluster sizes and may therefore serve as a null hypothesis for cluster sizes under simple epidemiological models. We examine a small cross-sectional sample of human immunodeficiency (HIV)-1 sequences collected in the United States and compare our results to standard estimates of effective population size. Estimated prevalence is consistent with estimates of effective population size and the known history of the HIV epidemic. While our model accurately estimates prevalence during exponential growth, we find that periods of decline are harder to identify.

Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear.

Background: Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a OhiddenO population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process., Methodology/principal Findings: Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits., Conclusions: SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics.

Introduction: We hypothesized that pleocytosis, which is a marker of central nervous system (CNS) inflammation, would result in viral genetic equilibration or de-compartmentalization between HIV populations in the blood and cerebrospinal fluid (CSF), suggesting viral trafficking., Methods: Study subjects, who started or interrupted their antiretroviral treatment, had viral loads measured and clonal viral env sequences generated from HIV RNA extracted from paired blood and CSF samples. White blood counts in CSF were also measured at each timepoint. Degree of inter-compartment segregation was calculated by posterior probability using linear discriminant analysis and multidimensional scaling. Co-receptor usage was determined using a trained support vector machine., Results: Pleocytosis was strongly associated with disruption of viral compartmentalization., Conclusions: Inflammation in the CNS, marked by pleocytosis, allows HIV populations to mix between blood and CSF, which may increase the overall viral genetic diversity within the CSF.

Background: Current public health efforts often use molecular technologies to identify and contain communicable disease networks, but not for HIV. Here, we investigate how molecular epidemiology can be used to identify highly related HIV networks within a population and how voluntary contact tracing of sexual partners can be used to selectively target these networks., Methods: We evaluated the use of HIV-1 pol sequences obtained from participants of a community-recruited cohort (n = 268) and a primary infection research cohort (n = 369) to define highly related transmission clusters and the use of contact tracing to link other individuals (n = 36) within these clusters. The presence of transmitted drug resistance was interpreted from the pol sequences (Calibrated Population Resistance v3.0)., Results: Phylogenetic clustering was conservatively defined when the genetic distance between any two pol sequences was less than 1%, which identified 34 distinct transmission clusters within the combined community-recruited and primary infection research cohorts containing 160 individuals. Although sequences from the epidemiologically linked partners represented approximately 5% of the total sequences, they clustered with 60% of the sequences that clustered from the combined cohorts (odds ratio 21.7; P < or = 0.01). Major resistance to at least one class of antiretroviral medication was found in 19% of clustering sequences., Conclusion: Phylogenetic methods can be used to identify individuals who are within highly related transmission groups, and contact tracing of epidemiologically linked partners of recently infected individuals can be used to link into previously defined transmission groups. These methods could be used to implement selectively targeted prevention interventions.

The cellular source(s) and the clinical significance of persistent low-level viremia, below 50 HIV RNA copies per ml of plasma, achieved in many patients with high adherence to highly active antiretroviral therapy (HAART) remain unclear. Also, it is not clear if residual plasma HIVs during HAART can become predominant populations in the rebounding plasma viral loads after therapy interruption. Since, different HIV quasispecies tend to compartmentalize in various cell types and tissue locations in patients during chronic infection, the phylogenetic relationships between HIV sequences amplified from residual plasma viruses and CD4 T cells of five patients on long-term suppressive therapy were examined. Three of these patients stopped therapy voluntarily for 3 weeks, but only one of them demonstrated viral load rebound in plasma. In phylogenetic analyses, the residual plasma viruses were found to be distinct genetically from the majority of CD4 T cell-associated virus populations in four of five patients. The compartmental analyses revealed that in all patients, plasma- and CD4 T cell-derived viral sequences were compartmentalized separately. Interestingly, the plasma sequences obtained before and after HAART-off in two patients were produced apparently from the same compartment, which was different from the circulating CD4 T cell-compartment. These results suggest the possibility that residual plasma viruses in patients on long-term suppressive HAART may be produced persistently from a cellular source yet to be identified, and are capable of spreading quickly in vivo, accounting for the rapid rebound of viral loads in plasma after therapy interruption.

The spread of hepatitis C virus (HCV) infection involves a complex interplay of social risks, and molecular factors of both virus and host. Injection drug abuse is the most powerful risk factor for HCV infection, followed by sexual transmission and additional non-injection drug abuse factors such as co-infection with other viruses and barriers to treatment. It is clearly important to understand the wider context in which the factors related to HCV infection occur. This understanding is required for a comprehensive approach leading to the successful prevention, diagnosis, and treatment of HCV. An additional consideration is that current treatments and advanced molecular methods are generally unavailable to socially disadvantaged patients. Thus, the recognition of behavioral/social, viral, and host factors as components of an integrated approach to HCV is important to help this vulnerable group. Equally important, this approach is key to the development of personalized patient treatment - a significant goal in global healthcare. In this review, we discuss recent findings concerning the impact of drug abuse, epidemiology, social behavior, virology, immunopathology, and genetics on HCV infection and the course of disease.

Natural selection is a fundamental process affecting all evolving populations. In the simplest case, positive selection increases the frequency of alleles that confer a fitness advantage relative to the rest of the population, or increases its genetic diversity, and negative selection removes those alleles that are deleterious. Codon-based models of molecular evolution are able to infer signatures of selection from alignments of homologous sequences by estimating the relative rates of synonymous (dS) and non-synonymous substitutions (dN). Datamonkey (http://www.datamonkey.org) provides a user-friendly web interface to a wide collection of state-of-the-art statistical techniques for estimating dS and dN and identifying codons and lineages under selection, even in the presence of recombinant sequences.

Purpose of Review: We investigate the role that sexual networks may play in the dynamics of transmitted drug resistance (TDR) in human immunodeficiency virus (HIV) infection., Recent Findings: Studies examining individual correlates of TDR have generally failed to find strong predictors of TDR, with most only examining basic demographics and risk groups. Ecological studies that compare potential transmitters of drug resistance and the frequency of TDR in drug naïve individuals have demonstrated that declines in TDR in some populations are mirrored by increasing efficacy of antiretroviral therapy and that the frequency of TDR is low given the number of potential transmitters; sexual networks may play a role in these phenomena. Phylogenetic approaches are becoming increasingly used to examine transmission networks of HIV but have yet to convincingly demonstrate clustering of sequences by drug resistance., Summary: There are relatively few studies that suggest a role of sexual networks in the transmission of drug-resistant HIV. We believe that this is due to the difficulty in collecting sexual network data. Studies that integrate genotypic and behavioral data collection on recently HIV-infected individuals, potential transmitters, and their partners are needed in order to establish causal links between the structure of the sexual network and transmission of drug-resistant HIV.

Human immunodeficiency virus (HIV-1) can rapidly evolve due to selection pressures exerted by HIV-specific immune responses, antiviral agents, and to allow the virus to establish infection in different compartments in the body. Statistical models applied to HIV-1 sequence data can help to elucidate the nature of these selection pressures through comparisons of non-synonymous (or amino acid changing) and synonymous (or amino acid preserving) substitution rates. These models also need to take into account the non-independence of sequences due to their shared evolutionary history. We review how we have developed these methods and have applied them to characterize the evolution of HIV-1 in vivo. To illustrate our methods, we present an analysis of compartment-specific evolution of HIV-1 env in blood and cerebrospinal fluid and of site-to-site variation in the gag gene of subtype C HIV-1.

We develop a model-based phylogenetic maximum likelihood test for evidence of preferential substitution toward a given residue at individual positions of a protein alignment--directional evolution of protein sequences (DEPS). DEPS can identify both the target residue and sites evolving toward it, help detect selective sweeps and frequency-dependent selection--scenarios that confound most existing tests for selection, and achieve good power and accuracy on simulated data. We applied DEPS to alignments representing different genomic regions of influenza A virus (IAV), sampled from avian hosts (H5N1 serotype) and human hosts (H3N2 serotype), and identified multiple directionally evolving sites in 5/8 genomic segments of H5N1 and H3N2 IAV. We propose a simple descriptive classification of directionally evolving sites into 5 groups based on the temporal distribution of residue frequencies and document known functional correlates, such as immune escape or host adaptation.