Objective To examine the loss to care and mortality rates before starting antiretroviral therapy (ART) among ART eligible HIV-infected patients in Durban, South Africa. Design Retrospective cohort study. Methods We reviewed data from ART eligible adults (≥18 years) at an urban HIV clinic that charges a monthly fee from July to December 2006. ART eligibility was based on CD4 count ≤200 cells per microliter or clinical criteria and a psychosocial assessment. Patients who did not start ART and were lost within 3 months were phoned. Correlates of loss to care were evaluated using logistic regression. Results During the study period, 501 patients registered for ART training. Mean time from initial CD4 count to first ART training was 3.6 months (interquartile range 2.3−3.9 months). Four hundred eight patients (81.4%) were in care and on ART at 3-month follow-up, and 11 (2.2%) were in care but had not initiated ART. Eighty-two ART eligible patients (16.4%) were lost before ART initiation. Of these, 28 (34.1%) had died; two thirds of deaths occurred before or within 2 months after the first ART training. Despite multiple attempts, 32 patients (39%) were unreachable by phone. Lower baseline CD4 counts (≤100 cells/μL) and unemployment were independently associated with being lost. Conclusions Loss to care and death occur frequently before starting ART at an HIV clinic in Durban, South Africa. This delay from CD4 count to ART training, even among those with the lowest CD4 counts, highlights the need for interventions that improve linkage to care and prioritize ART initiation for those with low baseline CD4 counts.

Background The World Health Organization (WHO) recommends cough as the trigger for tuberculosis (TB) screening in HIV-infected patients, with acid fast bacillus (AFB) smear as the initial diagnostic test. Our objective was to assess the yield and cost of a more intensive TB screening in HIV-infected patients starting antiretroviral therapy (ART) in Durban, South Africa. Methods We prospectively enrolled adults, regardless of TB signs/symptoms, undergoing pre-ART training from May ‘07–May ‘08. Following symptom screen, patients expectorated sputum for AFB smear, TB polymerase chain reaction (PCR), and mycobacterial culture. Sensitivity and specificity of different symptoms and tests, alone and in combination, were compared to a gold standard of 6-week TB culture results. Program costs included personnel, materials and cultures. Results Of 1,035 subjects, 487 (59%) were female; median CD4 count was 100/μl. Two-hundred and ten (20%) were receiving TB treatment and were excluded. Of the remaining 825 subjects, 158 (19%) had positive sputum cultures, of whom 14 (9%) had a positive AFB smear and 82 (52%) reported cough. The combination of cough, other symptoms, AFB smear, and chest x-ray had 93% (CI 88–97%) sensitivity and 15% (CI 13–18%) specificity. The incremental cost of intensive screening including culture was $360/additional TB case identified. Conclusions Nearly 20% of patients starting ART in Durban, South Africa had undiagnosed, culture-positive pulmonary TB. Despite WHO recommendations, neither cough nor AFB smear were adequately sensitive for screening. TB sputum cultures should be performed before ART initiation, regardless of symptoms, in areas of high HIV/TB prevalence.

Objective To assess prevalence, disease stage, and linkage to HIV care following diagnosis at a mobile HIV testing unit, compared to clinic-based testing, in a Durban township. Design Prospective cohort study. Methods We enrolled adults presenting for HIV testing at a community-based mobile testing unit (mobile testers) and at an HIV clinic (clinic testers) serving the same area. Testers diagnosed with HIV, regardless of testing site, were offered immediate CD4 testing and instructed to retrieve results at the clinic. We assessed rates of linkage to care, defined as CD4 result retrieval within 90 days of HIV diagnosis and/or completion of ART literacy training, for mobile versus clinic testers. Results : From July-November 2011, 6,957 subjects were HIV tested (4,703 mobile and 2,254 clinic); 55% were female. Mobile testers had a lower HIV prevalence than clinic testers (10% versus 36%), were younger (23 versus 27 years) and were more likely to live >5 km or >30 minutes from the clinic (64% versus 40%; all p< 0.001). Mobile testers were less likely to undergo CD4 testing (33% versus 83%) but more likely to have higher CD4 counts (median 416/μl, IQR 287-587 versus 285/μl, IQR 136-482) than clinic testers (both p<0.001). Of those who tested HIV positive, 10% of mobile testers linked to care, versus 72% of clinic testers (p <0.001). Conclusions Mobile HIV testing reaches people who are younger, more geographically remote, and with earlier disease compared to clinic-based testing. Fewer mobile testers underwent CD4 testing and linked to HIV care. Enhancing linkage efforts may improve the impact of mobile testing for those with early HIV.

Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers’ capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.

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Objectives: Serious infectious complications of opioid use disorder (OUD), and specifically endocarditis, are becoming more common in the US. Individuals with OUD-associated endocarditis require long periods of complex medical care, often face recurrent addiction- and infection-related complications, and have dismal clinical outcomes. The objective of this study was to perform journey mapping analysis to capture common trajectories and patterns of care for people with OUD-associated endocarditis. Methods: This was an analysis of qualitative semi-structured interviews of individuals who received care for OUD-associated endocarditis. Interviews were conducted among individuals receiving care at a single academic healthcare system in Boston, Massachusetts. Ten participants meeting DSM-5 criteria for at least mild OUD and a culture-positive diagnosis of endocarditis who had previously completed care for OUD-associated endocarditis were recruited from inpatient and ambulatory settings. Details of participant's care episodes were extracted and visualized in an iterative journey mapping process. A grounded theory approach was then used to identify shared themes and care patterns among participants’ journey maps. Results: Common patterns of care included early addiction treatment and intensive outpatient care preceding periods without rehospitalization, while leaving outpatient care and return to drug use often directly preceded rehospitalization. Participants frequently left care by choice and proactively reengaged with care. Conclusions: Journey mapping is a novel, patient-centered approach to capturing the care experiences and trajectories of a patient population experiencing significant stigma, who engage with the healthcare system in unexpected and fragmented ways. For individuals with OUD-associated endocarditis, we identified critical moments to support and engage patients to prevent return to drug use and rehospitalization.

Objectives: To determine how commonly medical inpatients with opioid use disorder (OUD) referred for postacute medical care were rejected due to substance use or treatment with opioid agonist therapy (OAT). Additionally, to assess for changes in rejection rates following the United States Attorney's May 2018 settlement with a Massachusetts nursing facility for violating anti-discrimination laws for such rejections. Methods: We linked electronic referrals to private Massachusetts postacute medical care facilities from Boston Medical Center in 2018 with clinical data. We included referrals with evidence of OUD using ICD-10 diagnosis codes or OAT receipt. We identified the frequency of referrals where the stated rejection reason was substance use or OAT and classified these as discriminatory. We used segmented regression to assess for changes in proportion of referrals with substance use and OAT-related rejections before and after the settlement. Results: In 2018, 219 OUD-associated hospitalizations resulted in 1648 referrals to 285 facilities; 81.8% (1348) were rejected. Among hospitalizations, 37.4% (82) received at least 1 discriminatory rejection. Among rejections, 15.1% (203) were discriminatory (105 for OAT and 98 for substance use). Among facilities, 29.1% (83) had at least one discriminatory rejection. We found no differences in proportion of discriminatory rejections before and after the settlement. Conclusions: Individuals hospitalized with OUD frequently experience explicit discrimination when rejected from postacute care despite federal and state protections. Efforts are needed to enhance enforcement of anti-discrimination laws, regulations, and policies to ensure access to postacute medical care for people with OUD and ongoing medical needs.

Mobile, community-based HIV testing may help achieve universal HIV testing in South Africa. We compared the yield, geographic distribution, and demographic characteristics of populations tested by mobile- and clinic-based HIV testing programs deployed by iThembalabantu Clinic in Durban, South Africa. From July–November 2011, 4,701 subjects were tested; HIV prevalence was 35% among IPHC testers and 10% among mobile testers (p<0.001). Mobile testers varied in mean age (22–37 years) and % males (26–67%). HIV prevalence at mobile sites ranged from 0% to 26%. Testers traveled further than the clinic closest to their home; mobile testers were more likely to test ≥ 5 km away from home. Mobile HIV testing can improve testing access and identify testing sites with high HIV prevalence. Individuals often access mobile testing sites farther from home than their nearest clinic. Geospatial techniques can help optimize deployment of mobile units to maximize yield in hard-to-reach populations.