Effectiveness of a multivitamin supplementation program among HIV-infected adults in Tanzania

Objective: The objective of this study was to assess the effectiveness of a routine multivitamin supplementation program for adults living with HIV in Tanzania. Design: We conducted a retrospective cohort study of 67,707 adults enrolled in the Dar es Salaam HIV care and treatment program during 2004-2012. Methods: The Dar es Salaam HIV care and treatment program intended to provide all adult patients with multivitamin supplements (vitamins B-complex, C, and E) free of charge; however, intermittent stockouts and other implementation issues did not afford universal coverage. We use Cox proportional hazard models to assess the time-varying association of multivitamin supplementation with mortality and clinical outcomes. Results: The study cohort contributed 41,540 and 129,315 person-years of follow-up time to the ART-naïve and ART-experienced analyses, respectively. Among 48,207 ART-naïve adults, provision of multivitamins reduced the risk of mortality (adjusted hazard ratio (aHR): 0.69; 95% CI: 0.59-0.81), incident tuberculosis (TB) (aHR: 0.83; 0.76-0.91), and meeting ART eligibility criteria (aHR: 0.78; 95% CI: 0.73-0.83) after adjustment for time-varying confounding. Among 46,977 ART-experienced patients, multivitamins reduced mortality (HR: 0.86; 95% CI: 0.80-0.92), incident TB (aHR: 0.78; 95% CI: 0.73-0.84), and immunologic failure (aHR: 0.70; 95% CI: 0.67-0.73). The survival benefits associated with provision multivitamins appeared to be greatest during the first year of ART and declined over time (p-value \u3c0.001). Conclusion: Multivitamin supplementation appears to be a simple, effective, safe, and scalable program to improve survival, reduce incidence of TB, and improve treatment outcomes for adult HIV patients in Tanzania

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Corrigendum to “Counting adolescents in: the development of an adolescent health indicator framework for population-based settings”

The authors were recently made aware of an oversight such that parts of the text in the Introduction and Methods sections, which describe shortcomings in the existing literature and the methods in this work to identify frameworks and indicators, were missing attribution to published work cited elsewhere in the manuscript. To clarify, we adjust the relevant sections to fully attribute the prior work in three areas, as described below. Underlined text is additional to the original: While both school- and community-based modalities can provide nationally representative data among eligible adolescents, several shortcomings in adolescent health measurement in LMICs were noted by the GAMA Advisory Group (Reference 13 as in the original paper). First, these measurements do not equally cover all adolescent subgroups, with evidence gaps being largest for males, younger adolescents aged 10–14 years, adolescents of diverse genders, ethnicities, and religions, as well as those out of school and migrants. Second, age-disaggregated data are often lacking—due in part to incomplete age coverage—limiting their use for program planning. Third, several aspects of adolescent health are inadequately covered including mental health, substance use, injury, sexual and reproductive health among unmarried adolescents, and positive aspects of adolescent health and well-being. Fourth, the definitions and assessment methods used across adolescent health indicator frameworks are inconsistent. For example, adolescent overweight and obesity—a major cause of non-communicable diseases and a public health risk for future and intergeneration health—is inconsistently captured across indicator frameworks and strikingly absent from the SDGs (Reference 13 as in the original paper). Additional shortcomings include, current adolescent health data systems often lack intersectoral coordination beyond health (e.g., with education, water and sanitation, and social protection systems) and suffer from irregularities in coverage and timing (Reference 6 as in the original paper). Broadly, these indicator frameworks and strategy documents captured disease burden, health risks, and prominent social determinants of health during adolescence. To be congruent with the existing global recommendations and guidelines (References 3–7 as in the original paper) and global measurement efforts (References 10 and 16 as in the original paper), the indicator framework documents had to meet three inclusion criteria, as laid out by the GAMA Advisory Group (Reference 14 as in the original paper): (1) provide recommendations about the measurement of adolescents' health and well-being; (2) include indicators for “adolescents” covering the adolescent age range (10–19 years) in the whole or part; and (3) be global or regional in scope. Using the GAMA's approach (Reference 13 as in the original paper), the recommendations of Lancet Adolescent Health Commission (Reference 6 as in the original paper), and several other guidelines (References 7, 9, 12, 17–19 as in the original paper), we selected adolescent health and well-being domains based on four key aspects of adolescents in LMICs: a) population trends; b) disease burden; c) drivers of health inequality; and d) opportunity for interventions

Counting adolescents in: the development of an adolescent health indicator framework for population-based settings

Changing realities in low- and middle-income countries (LMICs) in terms of inequalities, urbanization, globalization, migration, and economic adversity shape adolescent development and health, as well as successful transitions between adolescence and young adulthood. It is estimated that 90% of adolescents live in LMICs in 2019, but inadequate data exist to inform evidence-based and concerted policies and programs tailored to address the distinctive developmental and health needs of adolescents. Population-based data surveillance such as Health and Demographic Surveillance Systems (HDSS) and school-based surveys provide access to a well-defined population and provide cost-effective opportunities to fill in data gaps about adolescent health and well-being by collecting population-representative longitudinal data. The Africa Research Implementation Science and Education (ARISE) Network, therefore, systematically developed adolescent health and well-being indicators and a questionnaire for measuring these indicators that can be used in population-based LMIC settings. We conducted a multistage collaborative and iterative process led by network members alongside consultation with health-domain and adolescent health experts globally. Seven key domains emerged from this process: socio-demographics, health awareness and behaviors; nutrition; mental health; sexual and reproductive health; substance use; and healthcare utilization. For each domain, we generated a clear definition; rationale for inclusion; sub-domain descriptions, and a set of questions for measurement. The ARISE Network will implement the questionnaire longitudinally (i.e., at two time-points one year apart) at ten sites in seven countries in sub-Saharan Africa and two countries in Asia. Integrating the questionnaire within established population-based data collection platforms such as HDSS and school settings can provide measured experiences of young people to inform policy and program planning and evaluation in LMICs and improve adolescent health and well-being

The associations of parity and maternal age with small-for-gestational-age, preterm, and neonatal and infant mortality: a meta-analysis

Background: Previous studies have reported on adverse neonatal outcomes associated with parity and maternal age. Many of these studies have relied on cross-sectional data, from which drawing causal inference is complex. We explore the associations between parity/maternal age and adverse neonatal outcomes using data from cohort studies conducted in low- and middle-income countries (LMIC). / Methods: Data from 14 cohort studies were included. Parity (nulliparous, parity 1-2, parity ≥3) and maternal age (<18 years, 18-<35 years, ≥35 years) categories were matched with each other to create exposure categories, with those who are parity 1-2 and age 18-<35 years as the reference. Outcomes included small-for-gestational-age (SGA), preterm, neonatal and infant mortality. Adjusted odds ratios (aOR) were calculated per study and meta-analyzed. / Results: Nulliparous, age <18 year women, compared with women who were parity 1-2 and age 18-<35 years had the highest odds of SGA (pooled adjusted OR: 1.80), preterm (pooled aOR: 1.52), neonatal mortality (pooled aOR: 2.07), and infant mortality (pooled aOR: 1.49). Increased odds were also noted for SGA and neonatal mortality for nulliparous/age 18-<35 years, preterm, neonatal, and infant mortality for parity ≥3/age 18-<35 years, and preterm and neonatal mortality for parity ≥3/≥35 years. / Conclusions: Nulliparous women <18 years of age have the highest odds of adverse neonatal outcomes. Family planning has traditionally been the least successful in addressing young age as a risk factor; a renewed focus must be placed on finding effective interventions that delay age at first birth. Higher odds of adverse outcomes are also seen among parity ≥3 / age ≥35 mothers, suggesting that reproductive health interventions need to address the entirety of a woman’s reproductive period. / Funding: Funding was provided by the Bill & Melinda Gates Foundation (810-2054) by a grant to the US Fund for UNICEF to support the activities of the Child Health Epidemiology Reference Group

Reconciling conflicting clinical studies of antioxidant supplementation as HIV therapy: a mathematical approach

<p>Abstract</p> <p>Background</p> <p>Small, highly reactive molecules called reactive oxygen species (ROS) play a crucial role in cell signalling and infection control. However, high levels of ROS can cause significant damage to cell structure and function. Studies have shown that infection with the human immunodeficiency virus (HIV) results in increased ROS concentrations, which can in turn lead to faster progression of HIV infection, and cause CD4⁺T-cell apoptosis. To counteract these effects, clinical studies have explored the possibility of raising antioxidant levels, with mixed results.</p> <p>Methods</p> <p>In this paper, a mathematical model is used to explore this potential therapy, both analytically and numerically. For the numerical work, we use clinical data from both HIV-negative and HIV-positive injection drug users (IDUs) to estimate model parameters; these groups have lower baseline concentrations of antioxidants than non-IDU controls.</p> <p>Results</p> <p>Our model suggests that increases in CD4⁺T cell concentrations can result from moderate levels of daily antioxidant supplementation, while excessive supplementation has the potential to cause periods of immunosuppression.</p> <p>Conclusion</p> <p>We discuss implications for HIV therapy in IDUs and other populations which may have low baseline concentrations of antioxidants.</p

A coarsened multinomial regression model for perinatal mother to child transmission of HIV

Background: In trials designed to estimate rates of perinatal mother to child transmission of HIV, HIV assays are scheduled at multiple points in time. Still, infection status for some infants at some time points may be unknown, particularly when interim analyses are conducted. Methods: Logistic regression models are commonly used to estimate covariate-adjusted transmission rates, but their methods for handling missing data may be inadequate. Here we propose using coarsened multinomial regression models to estimate cumulative and conditional rates of HIV transmission. Through simulation, we compare the proposed models to standard logistic models in terms of bias, mean squared error, coverage probability, and power. We consider a range of treatment effect and visit process scenarios, while including imperfect sensitivity of the assay and contamination of the endpoint due to early breastfeeding transmission. We illustrate the approach through analysis of data from a clinical trial designed to prevent perinatal transmission. Results: The proposed cumulative and conditional models performed well when compared to their logistic counterparts. Performance of the proposed cumulative model was particularly strong under scenarios where treatment was assumed to increase the risk of in utero transmission but decrease the risk of intrapartum and overall perinatal transmission and under scenarios designed to represent interim analyses. Power to estimate intrapartum and perinatal transmission was consistently higher for the proposed models. Conclusion: Coarsened multinomial regression models are preferred to standard logistic models for estimation of perinatal mother to child transmission of HIV, particularly when assays are missing or occur off-schedule for some infants.U.S. National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), and Dept. of Health and Human Services (DHHS)

Exploring the “Middle Earth” of network spectra via a Gaussian matrix function

We study a Gaussian matrix function of the adjacency matrix of artificial and real-world networks. We motivate the use of this function on the basis of a dynamical process modeled by the time-dependent Schrodinger equation with a squared Hamiltonian. In particular, we study the Gaussian Estrada index - an index characterizing the importance of eigenvalues close to zero. This index accounts for the information contained in the eigenvalues close to zero in the spectra of networks. Such method is a generalization of the so-called "Folded Spectrum Method" used in quantum molecular sciences. Here we obtain bounds for this index in simple graphs, proving that it reaches its maximum for star graphs followed by complete bipartite graphs. We also obtain formulas for the Estrada Gaussian index of Erdos-Renyi random graphs as well as for the Barabasi-Albert graphs. We also show that in real-world networks this index is related to the existence of important structural patters, such as complete bipartite subgraphs (bicliques). Such bicliques appear naturally in many real-world networks as a consequence of the evolutionary processes giving rise to them. In general, the Gaussian matrix function of the adjacency matrix of networks characterizes important structural information not described in previously used matrix functions of graphs

Effect of Multivitamin Supplementation on Measles Vaccine Response among HIV-exposed Uninfected Tanzanian Infants.

Immunization and nutritional interventions are mainstays of child health programs in sub-Saharan Africa, yet few published data exist on their interactions. HIV-exposed (but uninfected) infants enrolled in a randomized placebo-controlled trial of multivitamin supplements (vitamins B complex, C, and E) conducted in Tanzania were sampled for an assessment of measles IgG quantity and avidity at 15 to 18 months. Infants were vaccinated between 8.5 and 12 months of age, and all mothers received high-dose multivitamins as the standard of care. Of 201 HIV-exposed infants who were enrolled, 138 (68.7%) were seropositive for measles. There were no effects of infant multivitamin supplementation on measles seroconversion proportions, IgG concentrations, or IgG avidity (P > 0.05). The measles seroconversion proportion was greater for HIV-exposed infants vaccinated at 10 to 11 months of age than for those vaccinated at 8.5 to 10 months (P = 0.032) and greater for infants whose mothers had a CD4 T-cell count of <200 cells/μl than for infants whose mothers had a CD4 T-cell count of >350 cells/μl (P = 0.039). Stunted infants had a significantly decreased IgG quantity compared to nonstunted infants (P = 0.012). As for measles avidity, HIV-exposed infants vaccinated at 10 to 11 months had increased antibody avidity compared to those vaccinated at 8.5 to 10 months (P = 0.031). Maternal CD4 T-cell counts of <200 cells/μl were associated with decreased avidity compared to counts of >350 cells/μl (P = 0.047), as were lower infant height-for-age z-scores (P = 0.016). Supplementation with multivitamins containing B complex, C, and E does not appear to improve measles vaccine responses for HIV-exposed infants. Studies are needed to better characterize the impact of maternal HIV disease severity on the immune system development of HIV-exposed infants and the effect of malnutrition interventions on vaccine responses. (This study has been registered at ClinicalTrials.gov under registration no. NCT00197730.)