Suchergebnisse

AbstractIntroductionAchieving optimal HIV outcomes, as measured by global 90‐90‐90 targets, that is awareness of HIV‐positive status, receipt of antiretroviral (ARV) therapy among aware and viral load (VL) suppression among those on ARVs, respectively, is critical. However, few data from sub‐Saharan Africa (SSA) are available on older people (50+) living with HIV (OPLWH). We examined 90‐90‐90 progress by age, 15–49 (as a comparison) and 50+ years, with further analyses among 50+ (55–59, 60–64, 65+ vs. 50–54), in 13 countries (Cameroon, Cote d'Ivoire, Eswatini, Ethiopia, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia and Zimbabwe).MethodsUsing data from nationally representative Population‐based HIV Impact Assessments, conducted between 2015and 2019, participants from randomly selected households provided demographic and clinical information and whole blood specimens for HIV serology, VL and ARV testing. Survey weighted outcomes were estimated for 90‐90‐90 targets. Country‐specific Poisson regression models examined 90‐90‐90 variation among OPLWH age strata.ResultsAnalyses included 24,826 HIV‐positive individuals (15–49 years: 20,170; 50+ years: 4656). The first, second and third 90 outcomes were achieved in 1, 10 and 5 countries, respectively, by those aged 15–49, while OPLWH achieved outcomes in 3, 13 and 12 countries, respectively. Among those aged 15–49, women were more likely to achieve 90‐90‐90 targets than men; however, among OPLWH, men were more likely to achieve first and third 90 targets than women, with second 90 achievement being equivalent. Country‐specific 90‐90‐90 regression models among OPLWH demonstrated minimal variation by age stratum across 13 countries. Among OLPWH, no first 90 target differences were noted by age strata; three countries varied in the second 90 by older age strata but not in a consistent direction; one country showed higher achievement of the third 90 in an older age stratum.ConclusionsWhile OPLWH in these 13 countries were slightly more likely than younger people to be aware of their HIV‐positive status (first 90), this target was not achieved in most countries. However, OPLWH achieved treatment (second 90) and VL suppression (third 90) targets in more countries than PLWH <50. Findings support expanded HIV testing, prevention and treatment services to meet ongoing OPLWH health needs in SSA.

AbstractIntroductionThe global target for 2020 is that ≥90% of people living with HIV (PLHIV) receiving antiretroviral therapy (ART) will achieve viral load suppression (VLS). We examined VLS and its determinants among adults receiving ART for at least four months.MethodsWe analysed data from the population‐based HIV impact assessment (PHIA) surveys in Eswatini, Lesotho, Malawi, Zambia and Zimbabwe (2015 to 2017). PHIA surveys are nationally representative, cross‐sectional household surveys. Data collection included structured interviews, home‐based HIV testing and laboratory testing. Blood samples from PLHIV were analysed for HIV RNA, CD4 counts and recent exposure to antiretroviral drugs (ARVs). We calculated representative estimates for the prevalence of VLS (viral load <1000 copies/mL), nonsuppressed viral load (NVL; viral load ≥1000 copies/mL), virologic failure (VF; ARVs present and viral load ≥1000 copies/mL), interrupted ART (ARVs absent and viral load ≥1000 copies/mL) and rates of switching to second‐line ART (protease inhibitors present) among PLHIV aged 15 to 59 years who participated in the PHIA surveys in Eswatini, Lesotho, Malawi, Zambia and Zimbabwe, initiated ART at least four months before the survey and were receiving ART at the time of the survey (according to self‐report or ARV testing). We calculated odds ratios and incidence rate ratios for factors associated with NVL, VF, interrupted ART, and switching to second‐line ART.ResultsWe included 9200 adults receiving ART of whom 88.8% had VLS and 11.2% had NVL including 8.2% who experienced VF and 3.0% who interrupted ART. Younger age, male sex, less education, suboptimal adherence, receiving nevirapine, HIV non‐disclosure, never having married and residing in Zimbabwe, Lesotho or Zambia were associated with higher odds of NVL. Among people with NVL, marriage, female sex, shorter ART duration, higher CD4 count and alcohol use were associated with lower odds for VF and higher odds for interrupted ART. Many people with VF (44.8%) had CD4 counts <200 cells/µL, but few (0.31% per year) switched to second‐line ART.ConclusionsCountries are approaching global VLS targets for adults. Treatment support, in particular for younger adults, and people with higher CD4 counts, and switching of people to protease inhibitor‐ or integrase inhibitor‐based regimens may further reduce NVL prevalence.

HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. We reflect critically how the HIV modelling field might develop in future. We argue for HIV modelling to be more routinely aligned with national government and ministry of health priorities, recognizing their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. We also place importance on an environment existing in which collaboration between modellers, and joint approaches to addressing modelling questions, becomes the norm rather than exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritized for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection and analysis. We also argue the need for HIV modelling to increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another may lead to worse health overall. Such integration may also enhance partnership with national governments whose mandates extend beyond HIV and to all of health care. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal.