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The TENDAI study: Task shifting to treat depression and HIV medication nonadherence in low resource settings by KING’S COLLEGE LONDON (The Research University TRU)



Background. HIV care has been rapidly decentralized in high-prevalence countries like Zimbabwe, in thedrive to expand access to antiretroviral therapy (ART) and to achieve viral suppression in people living withHIV/AIDS (PLWH).1,2 Optimising adherence to simple affordable regimens is especially critical in settingswhere third-line ART is barely available. Depression in Zimbabwe, like elsewhere, is common in PLWH3and a key barrier to ART adherence.4 There is a dearth of interventions for depression and poor ARTadherence which are feasible for non-specialists to deliver. These facts underscore the public healthsignificance of focusing on those with depression and a detectable viral load receiving ART regimens.Preliminary work. We have conducted extensive preliminary work to evaluate the cultural appropriatenessand feasibility of a stepped care, task-shifted intervention for treating depression and non-adherence inZimbabwe. Using available lay adherence counselors, this intervention links with the existing ZimbabweanHIV care pathway. We 1) culturally adapted the Life-Steps adherence intervention through qualitativestudies and tested it in 100 PLWH,5 2) developed a combined depression-adherence intervention calledTENDAI (meaning ?thankful? in the Shona language) through integrating the adapted adherenceintervention with Problem-Solving Therapy for depression (a simple culturally-acceptable treatment fordepression used in Zimbabwe)6 and 3) successfully completed an open trial and then a pilot randomizedtrial of TENDAI.7 Together, these studies show feasibility, acceptability and potential beneficial effects ondepression, adherence, and HIV viral suppression. Our combined US, UK and Zimbabwean consortiumbring together a history of successful trials in HIV and depression.8-10 Our proposal is strongly endorsed bythe Ministry of Health AIDS and TB Unit. Design: we propose a two-arm effectiveness RCT of the TENDAIintervention in HIV clinics in rural Zimbabwe in 290 people on ART (first, second or third line treatment) witha detectable viral load (=> 1000 viral RNA copies) and clinically significant depression. The TENDAIintervention will be compared to Enhanced Usual Care (EUC). Primary outcomes at 12 months (Aim 1)include proportion of HIV viral suppression in each condition, adherence to ART (assessed electronicallyand by ART detection in Dried Blood Spot), and depression (assessed via a locally validated questionnaireby an independent evaluator). We will also test (Aim 2) moderators (sex, depression severity) of thetreatment effect, and examine changes in adherence and depression as mediators of the effect on viralsuppression. Through collecting resource utilization and cost data we will examine the cost-effectiveness ofour novel treatment compared to EUC on reduced depression and, potentially, on better HIV outcomes(Aim 3). If successful, the RCT results will enable us to recommend a strategy for adherence counselingand depression care locally and in the east and southern African region.


AfricaUniversity Affairs

Harnessing Data Science for Health Discovery and Innovation in Africa: NIH joins Africa Movement Thinking initiative

We are experiencing an explosion of data relevant to human health, from both biological and non-health sources, that currently exceeds our ability to capture and interpret. This gap applies to every field of biomedical and behavioral research. If we don’t invest in the data itself, applying known and developing new Data Science (DS) approaches, we are wasting an incredible opportunity to improve Human Health. This set of initiatives addresses that gap for Global Health research and Public Health application in low resource settings.

In the next decade, rapid advances in DS, including new approaches to the description, collection, storage, integration, and analysis of large, heterogeneous, structured and unstructured data sets, and new computational methods such as advanced deep learning, digital phenotypes, machine/artificial intelligence, and 3D imaging are expected to transform biomedical and behavioral research and lead to improved health for individuals and populations. Traditional datasets (e.g. national health systems, surveillance, surveys) are becoming deeper and richer while new sources of data based on new technologies and sensors (e.g. social media, geospatial data, mobile phones, wearables, electronic medical records, bioimaging, and genomics) are emerging that may be of greatest value when linked to DS. Progress in development of huge new data sets and advanced methods for mining them underpin advances in diagnostics, technology development, and the potential for precision public health. This initiative examines whether advances in DS developed and/or applied in the African context can be used to spur discoveries and innovations that ultimately promote significant improvements in health for African individuals, communities, and populations. We define DS as “the interdisciplinary field of inquiry in which quantitative and analytical approaches, processes, and systems are developed and used to extract knowledge and insights from increasingly large and/or complex sets of data” (NIH Strategic Plan for Data Science).

While advances in the United States and other high-income countries (HICs) are being actively explored and increasingly supported in both the public and private sectors, applications that are relevant, affordable, acceptable, and scalable in low- and middle-income countries (LMICs) are largely undeveloped. Moreover, in most cases applications and tools cannot simply be adapted from HICs for use in LMICS as they are generated from data collections biased towards European ancestry populations and may not apply to other genetic backgrounds (this is true, for example, for GWAS studies, clinical imaging data used as a basis for machine learning, and major disease biomarkers). However, we can leverage the momentum and knowledge generated in this field in HICs to stimulate new investment, knowledge generation and innovations for LMIC populations.

What is InventXR is solving for?

While advances in the United States and other high-income countries (HICs) are being actively explored and increasingly supported in both the public and private sectors, applications that are: relevant, affordable, acceptable, and scalable in low- and middle-income countries (LMICs) are largely undeveloped. 

  • We focus this initiative in Africa for several reasons: 
    • First, despite recent progress, Africa carries a disproportionate share of the global burden of disease. DS has the potential to significantly impact both quantitative and qualitative research and health on the continent. 
    • Second, the African population is growing faster than other world regions and some African leaders are eager to transition to knowledge-based economies that InventXR infrastructure is well designed for. Extensive mobile phone coverage in Africa has led to major innovations in banking, agriculture, and other sectors and has the potential to “leopard frog” in health care delivery systems, bringing the clinic to the patient through Point of Care (POC) technologies and self-management systems, with applications to rural and underserved populations worldwide. 
    • Third, this initiative is synergistic with and leverages the substantial investments NIH has already made in research and research training in Africa.
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