BackgroundNyanza Province, Kenya, had the highest HIV prevalence in the country at 14.9% in 2007, more than twice the national HIV prevalence of 7.1%. Only 16% of HIV-infected adults in the country accurately knew their HIV status. Targeted strategies to reach and test individuals are urgently needed to curb the HIV epidemic. The family unit is one important portal.MethodsA family model of care was designed to build on the strengths of Kenyan families. Providers use a family information table (FIT) to guide index patients through the steps of identifying family members at HIV risk, address disclosure, facilitate family testing, and work to enrol HIV-positive members and to prevent new infections. Comprehensive family-centred clinical services are built around these steps. To assess the approach, a retrospective study of patients receiving HIV care between September 2007 and September 2009 at Lumumba Health Centre in Kisumu was conducted. A random sample of FITs was examined to assess family reach.ResultsThrough the family model of care, for each index patient, approximately 2.5 family members at risk were identified and 1.6 family members were tested. The approach was instrumental in reaching children; 61% of family members identified and tested were children. The approach also led to identifying and enrolling a high proportion of HIV- positive partners among those tested: 71% and 89%, respectively.ConclusionsThe family model of care is a feasible approach to broaden HIV case detection and service reach. The approach can be adapted for the local context and should continue to utilize index patient linkages, FIT adaption, and innovative methods to package services for families in a manner that builds on family support and enhances patient care and prevention efforts. Further efforts are needed to increase family member engagement.

HIV departments within Kenyan health facilities are usually better staffed and equipped than departments offering non-HIV services. Integration of HIV services into primary care may address this issue of skewed resource allocation. Between 2008 and 2010, we piloted a system of integrating HIV services into primary care in rural Kenya. Before integration, we conducted a survey among returning adults ≥18-year old attending the HIV clinic. We then integrated HIV and primary care services. Three and twelve months after integration, we administered the same questionnaires to a sample of returning adults attending the integrated clinic. Changes in patient responses were assessed using truncated linear regression and logistic regression. At 12 months after integration, respondents were more likely to be satisfied with reception services (adjusted odds ratio, aOR 2.71, 95% CI 1.32–5.56), HIV education (aOR 3.28, 95% CI 1.92–6.83), and wait time (aOR 1.97 95% CI 1.03–3.76). Men's comfort with receiving care at an integrated clinic did not change (aOR = 0.46 95% CI 0.06–3.86). Women were more likely to express discomfort after integration (aOR 3.37 95% CI 1.33–8.52). Integration of HIV services into primary care services was associated with significant increases in patient satisfaction in certain domains, with no negative effect on satisfaction.

Many gaps in care exist for provision of antiretroviral therapy (ART) in sub-Saharan Africa. Differentiated HIV care tailors provision of ART for patients based on their level of acuity, providing alternatives for where, by whom, and how often care occurs. We conducted a scoping review to assess novel differentiated care models for ART provision for stable HIV-infected adults in sub-Saharan Africa, and how these models can be used to guide differentiated care implementation in Kenya. A systematic search was conducted using PubMed, Embase, Web of Science, Popline, Cochrane Library, and African Index Medicus between January 2006 and January 2017. Grey literature searches and handsearching were also used. We included articles that quantitatively assessed the health, acceptability, and cost-effectiveness of differentiated HIV care. Two reviewers independently performed article screening, data extraction and determination of inclusion for analysis. We included 40 publications involving over 240,000 participants spanning nine countries in sub-Saharan Africa - 54.4% evaluated clinical outcomes, 23.5% evaluated acceptability outcomes, and 22.1% evaluated cost outcomes. Differentiated care models included: facility fast-track drug refills and appointment spacing, facility or community-based ART groups, community ART distribution points or home-based care, and task-shifting or decentralization of care. Studies suggest that these approaches had similar outcomes in viral load suppression and retention in care and were acceptable alternatives to standard HIV care. No clear results could be inferred for studies investigating task shifting and those reporting cost-effectiveness outcomes. Kenya has started to scale up differentiated care models, but further evaluation, quality improvement and research studies should be performed as different models are rolled out.

Youth are particularly vulnerable to acquiring HIV, yet reaching them with HIV prevention interventions and engaging and retaining those infected in care and treatment remains a challenge. We sought to determine the incidence rate of loss to follow-up (LTFU) and explore socio-demographic and clinical characteristics associated with LTFU among HIV-positive youth aged 15–21 years accessing outpatient care and treatment clinics in Kisumu, Kenya. Between July 2007 and September 2010, youth were enrolled into two different HIV care and treatment clinics, one youth specific and the other family oriented. An individual was defined as LTFU when absent from the HIV treatment clinic for ≥ 4 months regardless of their antiretroviral treatment status. The incidence rate of LTFU was calculated and Cox regression analysis used to identify factors associated with LTFU. A total of 924 youth (79% female) were enrolled, with a median age of 20 years (IQR 18-21). Over half, (529 (57%)), were documented as LTFU, of whom 139 (26%) were LTFU immediately after enrolment. The overall incidence rate of LTFU was 52.9 per 100 person-years (p-y). Factors associated with LTFU were pregnancy during the study period (crude HR 0.68, 95% CI 0.53–0.89); CD4 cell count ≥350 (adjusted hazard ratios (AHR) 0.59, 95% CI 0.39–0.90); not being on antiretroviral therapy (AHR 4.0, 95% CI 2.70–5.88); and nondisclosure of HIV infection status (AHR 1.43, 95% CI 1.10–1.89). The clinic of enrolment, age, marital status, employment status, WHO clinical disease stage and education level were not associated with LTFU. Interventions to identify and enrol youth into care earlier, support disclosure, and initiate ART earlier may improve retention of youth and need further investigation. Further research is also needed to explore the reasons for LTFU from care among HIV-infected youth and the true outcomes of these patients.