HyPhy 2.5-A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies.

HYpothesis testing using PHYlogenies (HyPhy) is a scriptable, open-source package for fitting a broad range of evolutionary models to multiple sequence alignments, and for conducting subsequent parameter estimation and hypothesis testing, primarily in the maximum likelihood statistical framework. It has become a popular choice for characterizing various aspects of the evolutionary process: natural selection, evolutionary rates, recombination, and coevolution. The 2.5 release (available from www.hyphy.org) includes a completely re-engineered computational core and analysis library that introduces new classes of evolutionary models and statistical tests, delivers substantial performance and stability enhancements, improves usability, streamlines end-to-end analysis workflows, makes it easier to develop custom analyses, and is mostly backward compatible with previous HyPhy releases.

Parsing social network survey data from hidden populations using stochastic context-free grammars.

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.

Using respondent-driven sampling in a hidden population at risk of HIV infection: who do HIV-positive recruiters recruit?

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.

Syringe possession arrests are associated with receptive syringe sharing in two Mexico-US border cities.

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.

Respondent-driven sampling of injection drug users in two U.S.-Mexico border cities: recruitment dynamics and impact on estimates of HIV and syphilis prevalence.

Respondent-driven sampling (RDS), a chain referral sampling approach, is increasingly used to recruit participants from hard-to-reach populations, such as injection drug users (IDUs). Using RDS, we recruited IDUs in Tijuana and Ciudad (Cd.) Juárez, two Mexican cities bordering San Diego, CA and El Paso, TX, respectively, and compared recruitment dynamics, reported network size, and estimates of HIV and syphilis prevalence. Between February and April 2005, we used RDS to recruit IDUs in Tijuana (15 seeds, 207 recruits) and Cd. Juárez (9 seeds, 197 recruits), Mexico for a cross-sectional study of behavioral and contextual factors associated with HIV, HCV and syphilis infections. All subjects provided informed consent, an anonymous interview, and a venous blood sample for serologic testing of HIV, HCV, HBV (Cd. Juárez only) and syphilis antibody. Log-linear models were used to analyze the association between the state of the recruiter and that of the recruitee in the referral chains, and population estimates of the presence of syphilis antibody were obtained, correcting for biased sampling using RDS-based estimators. Sampling of the targeted 200 recruits per city was achieved rapidly (2 months in Tijuana, 2 weeks in Cd. Juárez). After excluding seeds and missing data, the sample prevalence of HCV, HIV and syphilis were 96.6, 1.9 and 13.5% respectively in Tijuana, and 95.3, 4.1, and 2.7% respectively in Cd. Juárez (where HBV prevalence was 84.7%). Syphilis cases were clustered in recruitment trees. RDS-corrected estimates of syphilis antibody prevalence ranged from 12.8 to 26.8% in Tijuana and from 2.9 to 15.6% in Ciudad Juárez, depending on how recruitment patterns were modeled, and assumptions about how network size affected an individual's probability of being included in the sample. RDS was an effective method to rapidly recruit IDUs in these cities. Although the frequency of HIV was low, syphilis prevalence was high, particularly in Tijuana. RDS-corrected estimates of syphilis prevalence were sensitive to model assumptions, suggesting that further validation of RDS is necessary.