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BackgroundTaxes on discretionary foods and sugar-sweetened beverages have emerged as a strategy for health promotion. Between 2018-2019, the Bermuda government introduced a phased sugar tax on imported sugar-sweetened beverages, confectionery, products containing cocoa and pure sugar. The aim of this study was to conduct a qualitative evaluation of perceptions of the tax among the general population and key stakeholders.MethodsWe conducted a survey of the general population (N = 400), and semi-structured interviews with key informants (N = 14) from the government, food and beverage, and health sectors to understand awareness, acceptability, and perceived impact of the tax after implementation. Summary statistics and thematic analysis were conducted for the general population survey data, and thematic analysis using the framework method was conducted for key informant interviews.ResultsGeneral population respondents had high awareness of the sugar tax (94%) but lower awareness of the healthy food subsidy (32%). Most respondents (67%) felt the tax was not an appropriate way to motivate healthier consumption behaviour largely due to perceptions the tax would not be effective (44%), and due to the high price of healthy food (20%). However, nearly half (48%) of respondents reported consuming fewer taxed products, primarily for health reasons but also motivated by price increases. Key informants indicated there was high awareness, but limited understanding of the tax policy. Most informants expressed support for taxation as a health promotion strategy, conditional on policy implementation. The tax was not believed to have had an impact on consumption. Factors include the lack of clear price differentiation and the absence of accompanying health education or health promotion. No informants were aware of use of tax revenues for health purposes and tax revenue was reportedly re-directed after implementation.ConclusionsThere was high awareness, but limited acceptability of the tax as implemented. Clarity in the tax policy, appropriateness of the tax mechanism, and use of revenue in alignment with the tax aim are critical components for acceptance. The absence of complementary education and health promotion further affected acceptance and may limit potential health impacts. The lessons learned in Bermuda can inform similar policies in other settings.

Introduction The Case Surveillance and Vital Registration (CSAVR) model within Spectrum estimates HIV incidence trends from surveillance data on numbers of new HIV diagnoses and HIV‐related deaths. This article describes developments of the CSAVR tool to more flexibly model diagnosis rates over time, estimate incidence patterns by sex and age group and by key population group. Methods We modelled HIV diagnosis rate trends as a mixture of three factors, including temporal and opportunistic infection components. The tool was expanded to estimate incidence rate ratios by sex and age for countries with disaggregated reporting of new HIV diagnoses and AIDS deaths, and to account for information on key populations such as men who have sex with men (MSM), males who inject drugs (MWID), female sex workers (FSW) and females who inject drugs (FWID). We used a Bayesian framework to calibrate the tool in 71 high‐income or low‐HIV burden countries. Results Across countries, an estimated median 89% (interquartile range [IQR]: 78%–96%) of HIV‐positive adults knew their status in 2019. Mean CD4 counts at diagnosis were stable over time, with a median of 456 cells/μl (IQR: 391–508) across countries in 2019. In European countries reporting new HIV diagnoses among key populations, median estimated proportions of males that are MSM and MWID was 1.3% (IQR: 0.9%–2.0%) and 0.56% (IQR: 0.51%–0.64%), respectively. The median estimated proportions of females that are FSW and FWID were 0.36% (IQR: 0.27%–0.45%) and 0.14 (IQR: 0.13%–0.15%), respectively. HIV incidence per 100 person‐years increased among MSM, with median estimates reaching 0.43 (IQR: 0.29–1.73) in 2019, but remained stable in MWID, FSW and FWID, at around 0.12 (IQR: 0.04–1.9), 0.09 (IQR: 0.06–0.69) and 0.13% (IQR: 0.08%–0.91%) in 2019, respectively. Knowledge of HIV status among HIV‐positive adults gradually increased since the early 1990s to exceed 75% in more than 75% of countries in 2019 among each key population. Conclusions CSAVR offers an approach to using routine surveillance and vital registration data to estimate and project trends in both HIV incidence and knowledge of HIV status.

International audience; UNAIDS and other partners provide support to countries to develop estimates of HIV and related indicators on an annual basis. These estimates are used to monitor epidemic trends, guide program planning and resource allocation, and inform policy decision-making. The collection of articles in this AIDS supplement provide the headline results for the 2019 UNAIDS estimates and describe the new developments in the methods used to produce these estimates.

Background In line with the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, Norway aims for at least 90% of people living with HIV (PLHIV) to know their HIV-status. We produced current estimates of the number of PLHIV and undiagnosed population in Norway, overall and for six key subpopulations: Norwegian-born men who have sex with men (MSM), migrant MSM, Norwegian-born heterosexuals, migrant Sub-Saharan Africa (SSA)-born heterosexuals, migrant non-SSA-born heterosexuals and people who inject drugs. Methods We used the European Centre for Disease Prevention and Control (ECDC) HIV Modelling Tool on Norwegian HIV surveillance data through 2018 to estimate incidence, time from infection to diagnosis, PLHIV, and the number and proportion undiagnosed. As surveillance data on CD4 count at diagnosis were not collected in Norway, we ran two models; using default model CD4 assumptions, or a proxy for CD4 distribution based on Danish national surveillance data. We also generated alternative overall PLHIV estimates using the Spectrum AIDS Impact Model, to compare with those obtained from the ECDC tool. Results Estimates of the overall number of PLHIV in 2018 using different modelling approaches aligned at approximately 5000. In both ECDC models, the overall number undiagnosed decreased continuously from 2008. The proportion undiagnosed in 2018 was lower using default model CD4 assumptions (7.1% [95%CI: 5.3–8.9%]), than the Danish CD4 proxy (10.2% [8.3–12.1%]). This difference was driven by results for heterosexual migrants. Estimates for Norwegian-born MSM, migrant MSM and Norwegian-born heterosexuals were similar in both models. In these three subpopulations, incidence in 2018 was Conclusions Results allow cautious confidence in concluding that Norway has achieved the first UNAIDS 90–90-90 target, and clearly highlight the success of prevention strategies among MSM. Estimates for subpopulations strongly influenced by migration remain less clear, and future modelling should appropriately account for all-cause mortality and out-migration, and adjust for time of in-migration.

Global health organizations frequently set disease-specific targets with the goal of eliciting adoption at the national-level; consideration of the influence of target setting on national policies, programme and health budgets is of benefit to those setting targets and those intended to respond. In 2014, the Joint United Nations Programme on HIV/AIDS set ‘ambitious’ treatment targets for country adoption: 90% of HIV-positive persons should know their status; 90% of those on treatment; 90% of those achieving viral suppression. Using case studies from Ghana and Uganda, we explore how the target and its associated policy content have been adopted at the national level. That is whether adoption is in rhetoric only or supported by programme, policy or budgetary changes. We review 23 (14 from Ghana, 9 from Uganda) national policy, operational and strategic documents for the HIV response and assess commitments to ‘90–90–90’. In-person semi-structured interviews were conducted with purposively sampled key informants (17 in Ghana, 20 in Uganda) involved in programme-planning and resource allocation within HIV to gain insight into factors facilitating adoption of 90–90–90. Interviews were transcribed and analysed thematically, inductively and deductively, guided by pre-existing policy theories, including Dolowitz and Marsh’s policy transfer framework to describe features of the transfer and the Global Health Advocacy and Policy Project framework to explain observations. Regardless of notable resource constraints, transfer of the 90–90–90 targets was evident beyond rhetoric with substantial shifts in policy and programme activities. In both countries, there was evidence of attempts to minimize resource constraints by seeking programme efficiencies, prioritization of programme activities and devising domestic financing mechanisms; however, significant resource gaps persist. An effective health network, comprised of global and local actors, mediated the adoption and adaptation, facilitating a shift in the HIV programme from ‘business as usual’ to approaches targeting geographies and populations.

The Joint United Nations Programme on HIV/AIDS (UNAIDS) publishes estimates of the HIV epidemic every year [1]. For 2016, estimates are available for 160 countries representing 98% of the global population. These estimates are produced by countries with guidance from UNAIDS. The methods used in this process continue to evolve over time under the stewardship of the UNAIDS Reference Group on Estimates, Modelling and Projections [2]. In 2014, the WHO convened the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) Working Group with the aim to define and promote good practice in reporting global health estimates [3]. The GATHER Statement is the outcome produced by this group. It defines a list of reporting requirements to allow for the accurate interpretation, and facilitate the appropriate use, of global health estimates [4]. UNAIDS fully endorses and supports the GATHER Statement. The current special supplement, which details the methods used to produce the 2016 UNAIDS estimates, further supports the routine publication of data sources and methods used as part of an open and transparent process. It provides updates of the evolving understanding of the data on which the estimates are based, the methods used to derive the estimates, justification of changes in these methods, and the sources of new data available to inform these modifications. It follows a series of such collections [5–10] which have documented and described the evolving methods used to produce the UNAIDS Global AIDS estimates since 2004.

Background Truck drivers have unique health needs, and by virtue of their continuous travel, experience difficulty in accessing healthcare. Currently, planning for effective care is hindered by lack of knowledge about their health needs and about the impact of on-going programmes on this population’s health outcomes. We reviewed healthcare programmes implemented for sub-Saharan African truck drivers, assessed the evaluation methods, and examined impact on health outcomes. Methods We searched scientific and institutional databases, and online search engines to include all publications describing a healthcare programme in sub-Saharan Africa where the main clients were truck drivers. We consulted experts and organisations working with mobile populations to identify unpublished reports. Forest plots of impact and outcome indicators with unadjusted risk ratios and 95% confidence intervals were created to map the impact of these programmes. We performed a subgroup analysis by type of indicator using a random-effects model to assess between-study heterogeneity. We conducted a sensitivity analysis to examine both the summary effect estimate chosen (risk difference vs. risk ratio) and model to summarise results (fixed vs. random effects). Results Thirty-seven publications describing 22 healthcare programmes across 30 countries were included from 5,599 unique records. All programmes had an HIV-prevention focus with only three expanding their services to cover conditions other primary healthcare services. Twelve programmes were evaluated and most evaluations assessed changes in input, output, and outcome indicators. Absence of comparison groups, preventing attribution of the effect observed to the programme and lack of biologically confirmed outcomes were the main limitations. Four programmes estimated a quantitative change in HIV prevalence or reported STI incidence, with mixed results, and one provided anecdotal evidence of changes in AIDS-related mortality and social norms. Most programmes showed positive changes in risk behaviours, knowledge, and attitudes. Our conclusions were robust in sensitivity analyses. Conclusion Diverse healthcare programmes tailored to the needs of truck drivers implemented in 30 sub-Saharan African countries have shown potential benefits. However, information gaps about availability of services and their effects impede further planning and implementation of effective healthcare programmes for truck drivers.