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IntroductionViral load is one of the most important determinants for HIV transmission. Identification of people with high viral load (PHVL) can be effective in limiting onward HIV transmission. In order to improve the identification of these individuals within risk networks, we determined a) the number of PHVL recruited through risk networks b) their socio-demographic, behavioural and clinical characteristics and c) the characteristics of individuals who referred these PHVL to the study.MethodologyFrom November 2013 to March 2016, in Odessa, Ukraine, Transmission Reduction Intervention Project (TRIP) was implemented to identify people recently infected with HIV within the risk networks of "seeds" and "venues" where they engaged in risk behaviour.ResultsTRIP identified 53 PHVL, of whom 32 (60%) injected drugs; 42 (79%) were unaware of their HIV status; 25 (47%) had more than one sex partner, and only 14 (26%) were using condoms. There were 164 people who referred individuals into the study; 33 of them (20%) referred PHVL. In terms of referrers, those with lower than secondary level of education, not living with a sex partner, and reporting regular condom use were significantly more likely (p < 0.05) to refer PHVL. Most PHVL (38, 72%) and their referrers (27, 82%) were found through venues.ConclusionsIn Odessa city, PHVL are at high risk of transmitting HIV as the majority inject drugs, do not know their HIV status, and have unprotected sex and/or multiple partners. Targeting these individuals for HIV prevention, harm reduction and initiation of antiretroviral treatment (ART) is urgent.

IntroductionThis paper examines the extent to which an intervention succeeded in locating people who had recently become infected with HIV in the context of the large-scale Ukrainian epidemic. Locating and intervening with people who recently became infected with HIV (people with recent infection, or PwRI) can reduce forward HIV transmission and help PwRI remain healthy.MethodsThe Transmission Reduction Intervention Project (TRIP) recruited recently-infected and longer-term infected seeds in Odessa, Ukraine, in 2013 to 2016, and asked them to help recruit their extended risk network members. The proportions of network members who were PwRI were compared between TRIP arms (i.e. networks of recently-infected seeds vs. networks of longer-term infected seeds) and to the proportion of participants who were PwRI in an RDS-based Integrated Biobehavioral Surveillance of people who inject drugs in 2013.ResultsThe networks of PwRI seeds and those of longer-term infected seeds had similar (2%) proportions who were themselves PwRI. This was higher than the 0.25% proportion in IBBS (OR = 7.80; p = 0.016). The odds ratio among the subset of participants who injected drugs was 11.17 (p = 0.003). Cost comparison analyses using simplified ingredients-based methods found that TRIP spent no more than US $4513 per PwRI located whereas IBBS spent $11,924.ConclusionsFurther research is needed to confirm these results and improve TRIP further, but our findings suggest that interventions that trace the networks of people who test HIV-positive are a cost-effective way to locate PwRI and reduce HIV transmission and should therefore be implemented.

IntroductionProviding HIV healthcare and Treatment as Prevention both depend on diagnosing HIV cases, preferably soon after initial infection. We hypothesized that tracing risk networks recruits higher proportions of undiagnosed positives than outreach-based testing or respondent-driven sampling (RDS) in Odessa, Ukraine.MethodsThe Transmission Reduction Intervention Project (TRIP) used risk network tracing to recruit sexual and injection networks of recently-infected and longer-term infected (LTs) seeds (2013 to 2016). Integrated Biobehavioural Surveillance (IBBS) (2013) used RDS to recruit people who inject drugs (PWID). Outreach Testing tested PWID for HIV at community outreach sites (2013 to 2016). Proportions of undiagnosed positives among those tested were compared TRIP versus IBBS; TRIP versus Outreach Testing and between TRIP arms. Costs were compared across the projects.ResultsTRIP tested 1252 people (21% women) in seeds' risk networks; IBBS tested 400 (18% women); Outreach Testing 13,936 (31% women). TRIP networks included a higher proportion of undiagnosed positives (14.6%) than IBBS (5.0%) or Outreach Testing (2.4%); odds ratio (OR) 3.25 (95% CI 2.07, 5.12) versus IBBS and 7.03 (CI 5.95, 8.31) versus Outreach Testing respectively. Findings remained significant in analyses stratified by sex and when PWID in TRIP networks were compared with Outreach Testing and IBBS. Within TRIP, recently-infected participants' networks contained higher proportions of undiagnosed positives (16.3%) than LTs' networks (12.2%); OR 1.41 (CI 1.01, 1.95). TRIP located undiagnosed positives less expensively than did RDS or Outreach Testing.ConclusionsTRIP's recruiting techniques, including prioritizing networks of the recently infected, find undiagnosed HIV-positive people efficiently. They should be integrated with standard practice to improve case-finding. Research should test these techniques in other socio-epidemiologic contexts.Clinical trial registryRegistered ClinicalTrials.gov: NCT01827228.

This study examines the mediating role of job resources on the relationship between leadership and the work engagement of healthcare professionals. A stratified random sample from across the public healthcare sector of Cyprus was used. Data from a total of 605 respondents were analyzed: nurses (n = 348), physicians (n = 114), and other health professionals (n = 143). Using exploratory factor analysis, the antecedents of engagement were extracted, and a structural equation model was developed to investigate the hypothesized relationships. The results suggest that leadership factors such as leadership role encouragement and employee orientation leadership could elicit greater engagement among healthcare professionals by facilitating improved job resources (line-management supervision, development and training opportunities, and shared organizational vision). Notably, our results highlight the important role of a shared organizational vision in enhancing employee engagement. Our study provides important insights that can help managers and decision-makers further engage public healthcare employees. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer-associated thrombosis (CAT) is a severe cause of mortality and morbidity in cancer patients, while active cancer is present in 20% of all patients with venous thromboembolism (VTE). CAT presents several peculiarities that distinguish this entity from other clinical settings associated with VTE. Management of thromboembolic events in CAT is extremely challenging because of the multifactorial pathophysiology of this clinical setting. The objective of this review is to enlighten the complicated pathophysiology of CAT, discuss the available biomarkers for early identification of high-risk patients, and summarize the current guidelines regarding the treatment and management of thrombotic events in cancer patients. Dysregulated hemostasis in cancer patients is associated with various clinical conditions, from thromboembolic complications to disseminated intravascular coagulation. Despite the well-established association between cancer and thromboembolic complications, the mechanisms involved are not completely elucidated. There are several predisposing factors in cancer for increased thrombus generation, such as immobilization and chemotherapy. The term cancer-associated thrombosis (CAT) has been introduced to describe the close bidirectional relationship between cancer and thromboembolic events. Conventional coagulation tests (PT/aPTT) are more accurate in detecting a hypocoagulable rather than a hypercoagulable state; thus, their contribution to CAT management is limited. Traditionally, D-dimer levels have been the most common laboratory study for the evaluation of thrombotic risk. However, D-dimer levels only display a snapshot of the coagulation cascade, and they cannot provide a dynamic evaluation of evolving clot formation. Non-conventional assays, such as viscoelastic methods and microparticle formation are promising tools for the identification of patients at risk for developing CAT. Recent guidelines from the American Society of Clinical Oncology counsel against the estimation of thrombotic risk through a single test and recommend the use of scoring systems that take into account several risk factors. The present review outlines the current insights into the pathophysiological mechanisms of CAT and provides a comprehensive review of the latest advances in the laboratory assessment of CAT and the recent guidelines for the management of patients at risk for developing thromboembolic complications. [ABSTRACT FROM AUTHOR]

Researchers across a wide array of disciplines are interested in finding the most influential subjects in a network. In a network setting, intervention effects and health outcomes can spill over from one node to another through network ties, and influential subjects are expected to have a greater impact than others. For this reason, network research in public health has attempted to maximize health and behavioral changes by intervening on a subset of influential subjects. Although influence is often defined only implicitly in most of the literature, the operative notion of influence is inherently causal in many cases: influential subjects are those we should intervene on to achieve the greatest overall effect across the entire network. In this work, we define a causal notion of influence using potential outcomes. We review existing influence measures, such as node centrality, that largely rely on the particular features of the network structure and/or on certain diffusion models that predict the pattern of information or diseases spreads through network ties. We provide simulation studies to demonstrate when popular centrality measures can agree with our causal measure of influence. As an illustrative example, we apply several popular centrality measures to the HIV risk network in the Transmission Reduction Intervention Project and demonstrate the assumptions under which each centrality can represent the causal influence of each participant in the study. [ABSTRACT FROM AUTHOR]