Cardiovascular disease (CVD) is a major contributor to the growing public health epidemic in chronic diseases. Much of the disease and disability burden from CVDs are in people under the age of 70 years in low- and middle-income countries (LMICs), formerly “the developing world”. The risk of CVD is heavily influenced by environmental conditions and lifestyle variables. In this article we review the scope of the CVD problem in LMICs, including economic factors, risk factors, at-risk groups, and explanatory frameworks that hypothesize the multi-factorial drivers. Finally we discuss current and potential interventions to reduce the burden of CVD in vulnerable populations including research needed to evaluate and implement promising solutions for those most at risk.

Abstract-The introduction of new services requiring large and dynamic bitrate connectivity can cause changes in the direction of the traffic in metro and even core network segments along the day. This leads to large overprovisioning in statically managed virtual network topologies (VNT), designed to cope with the traffic forecast. To reduce expenses while ensuring the required grade of service, in this paper we propose the VNT reconfiguration approach based on data analytics for traffic prediction (VENTURE); it regularly reconfigures the VNT based on predicted traffic thus, adapting the topology to both, the current and the predicted traffic volume and direction. A machine learning algorithm based on artificial neural network (ANN) is used to provide robust and adaptive traffic models. The reconfiguration problem that takes as input the traffic prediction is modelled mathematically and a heuristic is proposed to solve it in practical times. To support VENTURE, we propose an architecture that allows collecting and storing data from monitoring at the routers and that is used to train predictive models for every origin-destination pair. Exhaustive simulation results of the algorithm together with the experimental assessment of the proposed architecture are finally presented.

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Although several studies have evaluated one or more linkage services to improve early enrollment in HIV care in Tanzania, none have evaluated the package of linkage services recommended by the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO). We describe the uptake of each component of the CDC/WHO recommended package of linkage services, and early enrollment in HIV care and antiretroviral therapy (ART) initiation among persons with HIV who participated in a peer-delivered, linkage case management (LCM) program implemented in Bukoba, Tanzania, October 2014 –May 2017. Of 4206 participants (88% newly HIV diagnosed), most received recommended services including counseling on the importance of early enrollment in care and ART (100%); escort by foot or car to an HIV care and treatment clinic (CTC) (83%); treatment navigation at a CTC (94%); telephone support and appointment reminders (77% among clients with cellphones); and counseling on HIV-status disclosure and partner/family testing (77%), and on barriers to care (69%). During three periods with different ART-eligibility thresholds [CD4<350 (Oct 2014 –Dec 2015, n = 2233), CD4≤500 (Jan 2016 –Sept 2016, n = 1221), and Test & Start (Oct 2016 –May 2017, n = 752)], 90%, 96%, and 97% of clients enrolled in HIV care, and 47%, 67%, and 86% of clients initiated ART, respectively, within three months of diagnosis. Of 463 LCM clients who participated in the last three months of the rollout of Test & Start, 91% initiated ART. Estimated per-client cost was $44 United States dollars (USD) for delivering LCM services in communities and facilities overall, and $18 USD for a facility-only model with task shifting. Well accepted by persons with HIV, peer-delivered LCM services recommended by CDC and WHO can achieve near universal early ART initiation in the Test & Start era at modest cost and should be considered for implementation in facilities and communities experiencing <90% early enrollment in ART care.

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