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Introduction Since 2014, the global public health community has recognized a set of targets for human immunodeficiency virus (HIV) known as “90-90-90,” an ambitious plan that called for the diagnosis of 90% of people living with HIV (PLHIV), antiretroviral therapy(ART) for 90% of those diagnosed HIV–positive, and viral suppression in 90% of those receiving ART by 2020 [1]. Population-level control of HIV will remain out of reach if many people initiating treatment disengage from ART for long periods of time, as they will have increased opportunity for viral load failure, morbidity, mortality [7], development of drug resistance, and viral transmission [8–11]. Clinical outcomes, such as viral load suppression, are not explicitly included in the cascade as long-term retention in care, the fourth stage in our cascade, is highly correlated with suppressed viral load [7,27], and our intention is to better understand PLHIV behavior as it relates to patterns of engagement, not the biological results of treatment. [...]the proposed cascade does not identify the facility at which people return to care or indicate how long they were disengaged.

In public health HIV treatment programs in Africa, long-term retention remains a challenge. A number of improvement strategies exist (e.g., bring services closer to home, reduce visit frequency, expand hours of clinic operation, improve provider attitude), but implementers lack data about which to prioritize when resource constraints preclude implementing all. We used a discrete choice experiment (DCE) to quantify preferences for a number of potential clinic improvements to enhance retention. We sought a random sample of HIV patients who were lost to follow-up (defined as >90 days late for their last scheduled appointment) from treatment facilities in Lusaka Province, Zambia. Among those contacted, we asked patients to choose between 2 hypothetical clinics in which the following 5 attributes of those facilities were varied: waiting time at the clinic (1, 3, or 5 hours), distance from residence to clinic (5, 10, or 20 km), ART supply given at each refill (1, 3, or 5 months), hours of operation (morning only, morning and afternoon, or morning and Saturday), and staff attitude (\"rude\" or \"nice\"). We used mixed-effects logistic regression to estimate relative utility (i.e., preference) for each attribute level. We calculated how much additional waiting time or travel distance patients were willing to accept in order to obtain other desired features of care. Between December 9, 2015 and May 31, 2016, we offered the survey to 385 patients, and 280 participated (average age 35; 60% female). Patients exhibited a strong preference for nice as opposed to rude providers (relative utility of 2.66; 95% CI 1.9-3.42; p < 0.001). In a standard willingness to wait or willingness to travel analysis, patients were willing to wait 19 hours more or travel 45 km farther to see nice rather than rude providers. An alternative analysis, in which trade-offs were constrained to values actually posed to patients in the experiment, suggested that patients were willing to accept a facility located 10 km from home (as opposed to 5) that required 5 hours of waiting per visit (as opposed to 1 hour) and that dispensed 3 months of medications (instead of 5) in order to access nice (as opposed to rude) providers. This study was limited by the fact that attributes included in the experiment may not have captured additional important determinants of preference. In this study, patients were willing to expend considerable time and effort as well as accept substantial inconvenience in order to access providers with a nice attitude. In addition to service delivery redesign (e.g., differentiated service delivery models), current improvement strategies should also prioritize improving provider attitude and promoting patient centeredness-an area of limited policy attention to date.

The cessation of most pre-exposure prophylaxis (PrEP) programmes (except for pregnant and breastfeeding women), removal of earmarked funding for key populations and orphans and vulnerable children, and the elimination of HIV survey, surveillance and community-led monitoring activities underscore the magnitude of the shift. Data from the Coverage, Quality and Impact Network (CQUIN) network of 21 countries in Sub-Saharan Africa show that by 2023, a median of 76% of people on antiretroviral therapy (ART) accessed treatment through a less-intensive DSD model [4]. The potential savings from DSD include cost and resource savings from less frequent clinic visits, both for clients and the health system [6, 7], and can increase human resource capacity [8]. In the face of funding cuts, DSD provides not a fallback plan, but a forward-looking strategy. Since its articulation nearly a decade ago [12], DSD has focused on client-centredness, grounded in the assumption that those who are clinically stable and treatment literate can be seen less frequently and will seek care when needed.

Under the umbrella term of “differentiated service delivery” (DSD), health systems are evolving away from traditional models of care, in which encounters were both frequent and exclusively at the health facility, to models that vary the location (e.g., to venues in the community), reduce the frequency (e.g., quarterly, biannually), and expand the roles of pharmacists, nurses, lay healthcare workers, and patients themselves (e.g., for peer drug distribution) in service delivery [1]. [...]patients fared slightly better in clinic-based clubs than community-based clubs, but persistence in either club model was poor, and retention after return to usual care was high. [...]understanding the mechanism is as important as understanding effects because effects (in implementation science) are often contextual, and mechanisms inform generalizability or external validity. [...]the inflexibility of the study intervention (e.g., the strict rules guiding dismissal from group care) weakens the findings.

HIV self-testing (HIVST) is a novel approach designed to assist in achieving the goal of at least 90% of the population that learn their HIV status. A self-test user with a positive test is required to visit a clinic to link into HIV care, yet little is known about patient preferences for linkage strategies. We examined the intention to link to care amongst potential HIVST users and the suitability of three linkage to care strategies in Lusaka Province, Zambia. We conducted a representative cross sectional survey of 1,617 individuals aged 16-49 years old in Lusaka Province. Participants were shown a video of the HIVST. Data on intention to link to care and preferred linkage to care strategies-text message, phone call and home visits were collected. Eight focus group discussions were held concurrently with survey respondents to understand their preferences between the three linkage to care strategies. Of 1617 enrolled, 60% were women, 40% were men, with an average age of 27years (IQR = 22, 35). More men than women had at least secondary education (84% vs 77%) and were either employed or self-employed (67% vs. 41%). 85% (95%CI = 83 to 86) of participants said they would link to care within the first week of a positive self-test. Income >2,000 Kwacha (USD 200) per month versus income < 2,000 Kwacha (Adjusted odds ratio (AOR) = 0.59; 95%CI: 0.40 to 0.88; p = 0.009) and never versus prior HIV testers (AOR = 0.54; 95%CI: 0.32 to 0.91; p = 0.020) were associated with reduced odds of intention to link to care. 53% (95%CI = 50 to 55) preferred being prompted to link to care by home visits compared to phone call (30%) or SMS (17%). We found almost nine out of ten potential HIVST users in the general population intend to link to care shortly after a positive test, and preferred home visits or phone calls to facilitate linkage, rather than SMS. Also, higher income earners and those who never tested for HIV were associated with reduced odds of intention to link to care. Policy guidelines and implementation strategies for HIVST should be responsive to patient preferences for linkage to care strategies to achieve the continuum of HIV care.

Although the success of HIV treatment programs depends on retention and viral suppression, routine program monitoring of these outcomes may be incomplete. We used data from the national electronic medical record (EMR) system in Zambia to enumerate a large and regionally representative cohort of patients on treatment. We traced a random sample with unknown outcomes (lost to follow-up) to document true care status and HIV RNA levels. On 31 July 2015, we selected facilities from 4 provinces in 12 joint strata defined by facility type and province with probability proportional to size. In each facility, we enumerated adults with at least 1 clinical encounter after treatment initiation in the previous 24 months. From this cohort, we identified lost-to-follow-up patients (defined as 90 or more days late for their last appointment), selected a random sample, and intensively reviewed their records and traced them via phone calls and in-person visits in the community. In 1 of 4 provinces, we also collected dried blood spots (DBSs) for plasma HIV RNA testing. We used inverse probability weights to incorporate sampling outcomes into Aalen-Johansen and Cox proportional hazards regression to estimate retention and viremia. We used a bias analysis approach to correct for the known inaccuracy of plasma HIV RNA levels obtained from DBSs. From a total of 64 facilities with 165,464 adults on ART, we selected 32 facilities with 104,966 patients, of whom 17,602 (17%) were lost to follow-up: Those lost to follow-up had median age 36 years, 60% were female (N = 11,241), they had median enrollment CD4 count of 220 cells/μl, and 38% had WHO stage 1 clinical disease (N = 10,690). We traced 2,892 (16%) and found updated outcomes for 2,163 (75%): 412 (19%) had died, 836 (39%) were alive and in care at their original clinic, 457 (21%) had transferred to a new clinic, 255 (12%) were alive and out of care, and 203 (9%) were alive but we were unable to determine care status. Estimates using data from the EMR only suggested that 42.7% (95% CI 38.0%-47.1%) of new ART starters and 72.3% (95% CI 71.8%-73.0%) of all ART users were retained at 2 years. After incorporating updated data through tracing, we found that 77.3% (95% CI 70.5%-84.0%) of new initiates and 91.2% (95% CI 90.5%-91.8%) of all ART users were retained (at original clinic or transferred), indicating that routine program data underestimated retention in care markedly. In Lusaka Province, HIV RNA levels greater than or equal to 1,000 copies/ml were present in 18.1% (95% CI 14.0%-22.3%) of patients in care, 71.3% (95% CI 58.2%-84.4%) of lost patients, and 24.7% (95% CI 21.0%-29.3%). The main study limitations were imperfect response rates and the use of self-reported care status. In this region of Zambia, routine program data underestimated retention, and the point prevalence of unsuppressed HIV RNA was high when lost patients were accounted for. Viremia was prevalent among patients who unofficially transferred: Sustained engagement remains a challenge among HIV patients in Zambia, and targeted sampling is an effective strategy to identify such gaps in the care cascade and monitor programmatic progress.

Failure to keep people living with HIV engaged in life-long care and treatment has serious implications for individual and population-level health. Nested within a four-province study of HIV care and treatment outcomes, we explored the dynamic role of social and service-related factors influencing retention in HIV care in Zambia. From a stratified random sample of 31 facilities, eight clinics were selected, one urban and one rural from each province. Across these sites we conducted a total of 69 in-depth interviews, including with patients (including pregnant women) engaged in-care (n = 28), disengaged from care (n = 15), engaged facility transferee (n = 12), and friends/family of deceased patients (n = 14). At the same sites we conducted 24 focus group discussions with a total of 192 lay and professional healthcare workers (HCWs). Two-day observations in each of the eight facilities helped triangulate data on operational context, provider relations and patient-provider interactions. We ordered and analysed data using an adapted version of Ewart's Social Action Theory. Three overarching findings emerged. First, the experience of living with HIV and engaging in HIV care in Zambia is a social, not individual experience, influenced by social and gendered norms and life goals including financial stability, raising family and living stigma-free. Second, patients and their networks act collectively to negotiate and navigate HIV care. Anticipated responses from social network influenced patients' willingness to engage in care, while emotional and material support from those networks influenced individuals' capacity to remain in HIV care. Lastly, health system factors were most influential where they facilitated or undermined peoples' collective approach to health service use. Participants living with HIV reported facilitation of both their initial and continued engagement in care where services involved social networks, such as during couples testing and community outreach. Conversely, service features that were poorly aligned with respondents' social reality (e.g. workplace obligations) hindered long-term engagement. This study moves beyond listing barriers or socio-ecological groupings, to explain how social and health systems interact to produce HIV care outcomes. Our findings challenge the implicit assumption of individual agency underpinning many retention studies to highlight the social nature of illness and healthcare utilization for HIV in Zambia. This understanding of collective action for accessing and remaining in HIV care should underpin future efforts to revise and reform HIV and potentially other chronic service models and systems.

Survival represents the single most important indicator of successful HIV treatment. Routine monitoring fails to capture most deaths. As a result, both regional assessments of the impact of HIV services and identification of hotspots for improvement efforts are limited. We sought to assess true mortality on treatment, characterize the extent under-reporting of mortality in routine health information systems in Zambia, and identify drivers of mortality across sites and over time using a multistage, regionally representative sampling approach. We enumerated all HIV infected adults on antiretroviral therapy (ART) who visited any one of 64 facilities across 4 provinces in Zambia during the 24-month period from 1 August 2013 to 31 July 2015. We identified a probability sample of patients who were lost to follow-up through selecting facilities probability proportional to size and then a simple random sample of lost patients. Outcomes among patients lost to follow-up were incorporated into survival analysis and multivariate regression through probability weights. Of 165,464 individuals (64% female, median age 39 years (IQR 33-46), median CD4 201 cells/mm3 (IQR 111-312), the 2-year cumulative incidence of mortality increased from 1.9% (95% CI 1.7%-2.0%) to a corrected rate of 7.0% (95% CI 5.7%-8.4%) (all ART users) and from 2.1% (95% CI 1.8%-2.4%) to 8.3% (95% CI 6.1%-10.7%) (new ART users). Revised provincial mortality rates ranged from 3-9 times higher than naïve rates for new ART users and were lowest in Lusaka Province (4.6 per 100 person-years) and highest in Western Province (8.7 per 100 person-years) after correction. Corrected mortality rates varied markedly by clinic, with an IQR of 3.5 to 7.5 deaths per 100 person-years and a high of 13.4 deaths per 100 person-years among new ART users, even after adjustment for clinical (e.g., pretherapy CD4) and contextual (e.g., province and clinic size) factors. Mortality rates (all ART users) were highest year 1 after treatment at 4.6/100 person-years (95% CI 3.9-5.5), 2.9/100 person-years (95% CI 2.1-3.9) in year 2, and approximately 1.6% per year through 8 years on treatment. In multivariate analysis, patient-level factors including male sex and pretherapy CD4 levels and WHO stage were associated with higher mortality among new ART users, while male sex and HIV disclosure were associated with mortality among all ART users. In both cases, being late (>14 days late for appointment) or lost (>90 days late for an appointment) was associated with deaths. We were unable to ascertain the vital status of about one-quarter of those lost and selected for tracing and did not adjudicate causes of death. HIV treatment in Zambia is not optimally effective. The high and sustained mortality rates and marked under-reporting of mortality at the provincial-level and unexplained heterogeneity between regions and sites suggest opportunities for the use of corrected mortality rates for quality improvement. A regionally representative sampling-based approach can bring gaps and opportunities for programs into clear epidemiological focus for local and global decision makers.

In a Policy Forum, Peter Ehrenkranz and colleagues discuss the contribution of CD4 and viral load testing to outcomes for people with HIV in low- and middle-income countries.In a Policy Forum, Peter Ehrenkranz and colleagues discuss the contribution of CD4 and viral load testing to outcomes for people with HIV in low- and middle-income countries.