Background In high income nations, traumatic life experiences such as childhood sexual abuse are much more common in people living with HIV/AIDS (PLWHA) than the general population, and trauma is associated with worse current health and functioning. Virtually no data exist on the prevalence or consequences of trauma for PLWHA in low income nations. Methodology/Principal Findings We recruited four cohorts of Tanzanian patients in established medical care for HIV infection (n = 228), individuals newly testing positive for HIV (n = 267), individuals testing negative for HIV at the same sites (n = 182), and a random sample of community-dwelling adults (n = 249). We assessed lifetime prevalence of traumatic experiences, recent stressful life events, and current mental health and health-related physical functioning. Those with established HIV infection reported a greater number of childhood and lifetime traumatic experiences (2.1 and 3.0 respectively) than the community cohort (1.8 and 2.3). Those with established HIV infection reported greater post-traumatic stress disorder (PTSD) symptomatology and worse current health-related physical functioning. Each additional lifetime traumatic experience was associated with increased PTSD symptomatology and worse functioning. Conclusions/Significance This study is the first to our knowledge in an HIV population from a low income nation to report the prevalence of a range of potentially traumatic life experiences compared to a matched community sample and to show that trauma history is associated with poorer health-related physical functioning. Our findings underscore the importance of considering psychosocial characteristics when planning to meet the health needs of PLWHA in low income countries.
Abstract Introduction Little is known about when youth living with HIV (YLHIV) are most susceptible to disengagement from HIV care. The longitudinal HIV care continuum is an underutilized tool that can provide a holistic understanding of population-level HIV care trajectories and be used to compare treatment outcomes across groups. We aimed to explore effects of the Universal Test and Treat policy (UTT) on longitudinal care outcomes among South African youth living with HIV (YLHIV) and identify temporally precise opportunities for re-engaging this priority population. Methods Using medical record and census data, we conducted a retrospective cohort study among youth aged 18-24 newly diagnosed with HIV between August 2015 and December 2018 in nine health care facilities in rural South Africa. We used weighted Fine and Grey sub-distribution proportional hazards models to characterize longitudinal care continuum outcomes in the population overall and stratified by treatment era of diagnosis. We estimated the proportion of individuals in each stage of the continuum over time and the mean time spent in each stage in the first year following diagnosis. Estimates for the two groups were compared using differences (diagnosis pre-UTT=referent). Results A total of 420 YLHIV were included. By the end of the first year following diagnosis, just 23% of individuals had no 90-or-more-day lapse in care and were virally suppressed. Those diagnosed in the UTT era spent less time as ART-naïve (mean difference=-19.3 days; 95% CI: - 27.7, -10.9) and more time virally suppressed (mean difference=17.7; 95% CI: 1.0, 34.4) compared to those diagnosed pre-UTT adoption. Most individuals who were diagnosed in the UTT era and experienced a 90-or-more-day lapse in care disengaged between diagnosis and linkage to care or ART initiation and viral suppression. Conclusions Implementation of UTT yielded modest improvements in time spent on ART and virally suppressed among South African YLHIV. However, meeting UNAIDS’ 95-95-95 targets remains a challenge in this priority population. Retention in care and re-engagement interventions that can be implemented between diagnosis and linkage to care (e.g., longitudinal counseling following diagnosis) or ART initiation and viral suppression may be particularly important to improving treatment outcomes among South African YLHIV.
Objective: To estimate the effect of intimate partner violence (IPV) on oral pre-exposure prophylaxis (PrEP) adherence among adolescent girls and young women (AGYW). Design: We conducted a secondary analysis of data from HIV Prevention Trials Network 082 (HPTN 082), a multisite prospective study designed to assess oral PrEP adherence among AGYW in southern Africa. Methods: We estimated the relative prevalence of high PrEP adherence 3 and 6 months after initiation among AGYW 16–25 years who reported a history of any IPV in the past year at enrollment versus AGYW who did not, both overall and by age. High adherence was defined as an intracellular tenofovir-diphosphate concentration at least 700 fmol/punch or more dried blood spots. Results: Among 409 PrEP-initiating AGYW, half (49%) reported experiencing any IPV by a current/recent partner in the year prior to enrollment. Overall, a similar proportion of AGYW who reported IPV had high PrEP adherence at months 3 and 6 as AGYW who did not report IPV. There was, however, evidence of effect modification by age at month 3: among AGYW less than 21 years old, those who reported IPV were less than half as likely to have high adherence [adjusted PR (aPR) = 0.43, 95% confidence interval (CI) 0.22–0.86]; among AGYW aged 21 years or older, those who reported IPV were more than twice as likely to have high adherence (aPR = 2.21, 95% CI 1.34–3.66). At month 6, effect estimates within each age stratum were consistent in direction to those at month 3. Conclusion: IPV events may either impede or motivate PrEP adherence among African AGYW, with age appearing to be an important consideration for IPV-related adherence interventions.
In randomized trials of provider-focused clinical interventions, treatment allocation often cannot be blinded to participants, study staff, or providers. The choice of unit of randomization (patient, provider, or clinic) entails tradeoffs in cost, power, and bias. Provider- or clinic-level randomization can minimize contamination, but it incurs the equally problematic potential for referral bias; that is, because arm assignment of future participants generally cannot be concealed, differences between arms may arise in the types of patients enrolled. Pseudo-cluster randomization is a novel study design that balances these competing validity threats. Providers are randomly assigned to an imbalanced proportion of intervention-arm participants (e.g., 80% or 20%). Providers can be masked to the imbalance, avoiding referral bias. Contamination is reduced because only a minority of control-arm participants are treated by majority-intervention providers. Pseudo-cluster randomization was implemented in a randomized trial of a decision support intervention to manage depression among patients receiving human immunodeficiency virus care in the southern United States in 2010–2014. The design appears successful in avoiding referral bias (participants were comparable between arms on important characteristics) and contamination (key depression treatment indicators were comparable between usual care participants managed by majority-intervention and majority-usual care providers and were markedly different compared with intervention participants).
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)
'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(10)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(20)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(40)'/%3e%3c/g%3e%3cuse xlink:href='%23e' transform='rotate(-80)'/%3e%3c/g%3e%3cpath d='M-225-21.5h450v7.5h-450z'/%3e%3cpath fill='%23339E35' d='M-225 86h450v100h-450z'/%3e%3c/svg%3e)