Dataset Information

Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.

ABSTRACT: Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation?>?90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods' development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention.

SUBMITTER: Ratmann O

PROVIDER: S-EPMC5854118 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.

Ratmann Oliver O Hodcroft Emma B EB Pickles Michael M Cori Anne A Hall Matthew M Lycett Samantha S Colijn Caroline C Dearlove Bethany B Didelot Xavier X Frost Simon S Hossain A S Md Mukarram AS Joy Jeffrey B JB Kendall Michelle M Kühnert Denise D Leventhal Gabriel E GE Liang Richard R Plazzotta Giacomo G Poon Art F Y AF Rasmussen David A DA Stadler Tanja T Volz Erik E Weis Caroline C Leigh Brown Andrew J AJ Fraser Christophe C

Molecular biology and evolution 20161007 1

Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Afri ...[more]

PMID: 28053012

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Project description:BackgroundIn a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.Methods and findingsThe model represents a vector of age-specific mortality rates as the weighted sum of three independent age-varying components. We derive the age-varying components from a Singular Value Decomposition of the matrix of age-specific mortality rate schedules. The weights are modeled as a function of HIV prevalence and one of three possible sets of inputs: life expectancy at birth, a measure of child mortality, or child mortality with a measure of adult mortality. We calibrate the model with 320 five-year life tables for each sex from the World Population Prospects 2010 revision that come from the 40 countries of the world that have and are experiencing a generalized HIV epidemic. Cross validation shows that the model is able to outperform several existing model life table systems.ConclusionsWe present a flexible, parsimonious model of age-specific mortality for countries with generalized HIV epidemics. Combined with the outputs of existing epidemiological and demographic models, this model makes it possible to project future age-specific mortality profiles and number of deaths for countries with generalized HIV epidemics.

Project description:A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.). Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters--a basic particle filter (PF) with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF), and particle Markov chain Monte Carlo (pMCMC)--and three ensemble filters--the ensemble Kalman filter (EnKF), the ensemble adjustment Kalman filter (EAKF), and the rank histogram filter (RHF)--were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS) model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003-2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable; the three particle filters perform slightly better predicting peaks 1-5 weeks in the future; the ensemble filters are more accurate predicting peaks in the past.

Project description:BackgroundAIDS-related illness is the leading cause of mortality for adolescents in sub-Saharan Africa. Together, Kenya, Tanzania, and Uganda account for 21% of HIV-infected adolescents in sub-Saharan Africa. The United Nations framework for addressing the epidemic among adolescents calls for comprehensive sexual and reproductive health education. These HIV prevention efforts could be informed by a synthesis of existing research about the formal and informal sexual education of adolescents in countries experiencing generalized epidemics. The purpose of this study was to describe the process of sexual learning among East African adolescents living in the context of generalized HIV epidemics.MethodsQualitative metasynthesis, a systematic procedure for integrating the results of multiple qualitative studies addressing a similar phenomenon, was used. Thirty-two research reports met study inclusion criteria. The reports were assessed in a four-step analytic process: appraisal, classification of findings, synthesis of findings, and construction of a framework depicting the process of sexual learning in this population.ResultsThe framework includes three phases of sexual learning: 1) being primed for sex, 2) making sense of sex, and 3) having sexual experiences. Adolescents were primed for sex through gender norms, cultural practices, and economic structures as well as through conversations and formal instruction. They made sense of sex by acquiring information about sexual intercourse, reproduction and pregnancy, sexually transmitted infections, and relationships and by developing a variety of beliefs and attitudes about these topics. Some adolescents described having sexual experiences that met wants or needs, but many experienced sex that was coerced or violent. Whether sex was wanted, coerced, or violent, adolescents experienced worry about sexually transmitted infections or premarital pregnancy.ConclusionsThe three phases of sexual learning interact to shape adolescents' sexual lives and their risk for HIV infection. This framework will contribute to the development of sexual education programs that address HIV risk within the broader context of sexual learning.

Dataset Information

Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.

Publications

Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.

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