Measuring Vulnerability: Addressing the Prevention of Trafficking and Forced Labor of Refugees in Jordan

The intersection of trafficking, forced labor, and refugees is well-cited in the international human rights community yet is rarely studied academically, especially in the Middle East. Given the massive Syrian refugee crisis that began in 2011, which increased the total global population of refugees to the largest total in history, it is more important than ever to study and better understand how refugees are vulnerable to trafficking and forced labor, particularly in impacted countries. The purpose of this research is to answer the question why refugees are vulnerable and how anti-trafficking and anti-forced labor initiatives can use vulnerability indicators as a tool of prevention. This thesis incorporates research from various academic disciplines to analyze potential vulnerability to labor exploitation of refugees in Jordan, one of the most impacted countries. I find that health, mobility, work status or income, demographics including age and gender, access to community, access to aide, and legal or registered status are significant indicators of vulnerability among refugees. An analysis of Jordanian government, IGO, and civil society prevention strategies provides context on how vulnerability indicators can be better implemented in these initiatives. I argue that this indicates Jordan is a good model for applying this prevention research. Borrowing from political science and international relations, I find that prevention occurs through levels of analysis including individual, group, state, and international approaches. A key conclusion of this thesis is the suggestion to separate prevention efforts into a distinct timeframe of direct and indirect prevention initiatives through these levels of analysis to better incorporate vulnerability indicators. I find that addressing vulnerability in these ways proves viable to prevent trafficking and forced labor of Syrian refugees in Jordan. This thesis thus demonstrates the importance of incorporating vulnerability indicators in prevention initiatives to dismantle the “greenhouse of human trafficking” that currently exists in the Middle East due to the Syrian refugee crisis

Preliminary Psychometrics for the Executive Function Challenge Task: A Novel, “Hot” Flexibility, and Planning Task for Youth

Objective: Executive functions (EF) drive health and educational outcomes and therefore are increasingly common treatment targets. Most treatment trials rely on questionnaires to capture meaningful change because ecologically valid, pediatric performance-based EF tasks are lacking. The Executive Function Challenge Task (EFCT) is a standardized, treatment-sensitive, objective measure which assesses flexibility and planning in the context of provocative social interactions, making it a “hot” EF task. Method: We investigate the structure, reliability, and validity of the EFCT in youth with autism (Autism Spectrum Disorder; n = 129), or attention deficit hyperactivity disorder with flexibility problems (n = 93), and typically developing (TD; n = 52) youth. Results: The EFCT can be coded reliably, has a two-factor structure (flexibility and planning), and adequate internal consistency and consistency across forms. Unlike a traditional performance-based EF task (verbal fluency), it shows significant correlations with parent-reported EF, indicating ecological validity. EFCT performance distinguishes youth with known EF problems from TD youth and is not significantly related to visual pattern recognition, or social communication/understanding in autistic children. Conclusions: The EFCT demonstrates adequate reliability and validity and may provide developmentally appropriate, treatment-sensitive, and ecologically valid assessment of “hot” EF in youth. It can be administered in controlled settings by masked administrators

Factors Associated With Referring Close Contacts to an App With Individually-Tailored Vaccine Information

Background: Infants too young to be fully vaccinated are vulnerable to potentially deadly influenza and pertussis infections. The cocooning strategy limits this risk by vaccinating those likely to interact with the infant and mother during this vulnerable time, such as close friends and family members. Distribution of accurate and accessible vaccine information through existing social networks could be an important tool in increasing vaccine confidence and coverage. Methods: We surveyed 1095 pregnant women from diverse prenatal care practices in Georgia and Colorado. These women were surveyed through a mobile app to assess vaccine intentions, attitudes, beliefs, norms, and levels of trust, and then presented brief individually-tailored educational videos about maternal and infant vaccines and the cocooning strategy. They were then given the opportunity to refer up to six contacts to enroll in the app and receive similar vaccine education. Results: Twenty-eight percent of these women referred at least one contact, with an average of 2.67 contacts per referring woman. Most referrals (93%) were partners, parents, siblings, relatives, or close friends. Attitudinal constructs significantly associated with increased likelihood of referring contacts included: intention to receive maternal influenza vaccine, perceived safety of maternal Tdap vaccine, perceived efficacy of maternal influenza vaccine, perceived susceptibility to and severity of influenza during pregnancy, and trust in vaccine information from the Centers for Disease Control and Prevention (CDC) and academic institutions. Uncertainty about infant vaccine intentions was associated with decreased likelihood of referring contacts. Conclusions: Pregnant women who valued vaccination and trusted vaccine information from academic institutions were more likely to refer an educational app about vaccines than those who did not. Further research is needed to determine the potential impact of this strategy on vaccine coverage when implemented on a large scale. Trial Registration: The survey informing this article was part of a randomized controlled trial funded by the National Institutes of Health [clinicaltrials.gov registration number NCT02898688]

SHIV-162P3 Infection of Rhesus Macaques Given Maraviroc Gel Vaginally Does Not Involve Resistant Viruses

Maraviroc (MVC) gels are effective at protecting rhesus macaques from vaginal SHIV transmission, but breakthrough infections can occur. To determine the effects of a vaginal MVC gel on infecting SHIV populations in a macaque model, we analyzed plasma samples from three rhesus macaques that received a MVC vaginal gel (day 0) but became infected after high-dose SHIV-162P3 vaginal challenge. Two infected macaques that received a placebo gel served as controls. The infecting SHIV-162P3 stock had an overall mean genetic distance of 0.294±0.027%; limited entropy changes were noted across the envelope (gp160). No envelope mutations were observed consistently in viruses isolated from infected macaques at days 14–21, the time of first detectable viremia, nor selected at later time points, days 42–70. No statistically significant differences in MVC susceptibilities were observed between the SHIV inoculum (50% inhibitory concentration [IC50] 1.87 nM) and virus isolated from the three MVC-treated macaques (MVC IC50 1.18 nM, 1.69 nM, and 1.53 nM, respectively). Highlighter plot analyses suggested that infection was established in each MVC-treated animal by one founder virus genotype. The expected Poisson distribution of pairwise Hamming Distance frequency counts was observed and a phylogenetic analysis did not identify infections with distinct lineages from the challenge stock. These data suggest that breakthrough infections most likely result from incomplete viral inhibition and not the selection of MVC-resistant variants

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871

Antenatal Magnesium and Cerebral Palsy in Preterm Infants

To evaluate the relationship of maternal antenatal magnesium sulfate (MgSO4) with neonatal cranial ultrasound abnormalities and cerebral palsy (CP)

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe