SummaryBackgroundAn adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends.MethodsWe estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development.FindingsBetween 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3·0%. The largest health spending growth rates were in upper-middle-income (5·9) and lower-middle-income groups (5·0), which both increased spending at more than 5% per year, and spent $914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4·6%, and health spending increased from $51 to $120 per capita. In 2014, 59·2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29·1% and 58·0% of spending was OOP spending and 35·7% and 3·0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1·8%, and reached US$37·6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount.InterpretationHealth spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.FundingThe Bill & Melinda Gates Foundation.

BackgroundThe amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending.MethodsWe extracted GDP, government spending in 184 countries from 1980–2015, and health spend data from 1995–2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted.FindingsWe estimated that global spending on health will increase from US$9·21 trillion in 2014 to $24·24 trillion (uncertainty interval [UI] 20·47–29·72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5·3% (UI 4·1–6·8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4·2% (3·8–4·9). High-income countries are expected to grow at 2·1% (UI 1·8–2·4) and low-income countries are expected to grow at 1·8% (1·0–2·8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133–181) per capita in 2030 and $195 (157–258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157–258) per capita was available for health in 2040 in low-income countries.InterpretationHealth spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.FundingBill & Melinda Gates Foundation.

ObjectiveTo compare the clinical outcomes and cost-effectiveness of routine HIV screening in Portugal to the current practice of targeted and on-demand screening.DesignWe used Portuguese national clinical and economic data to conduct a model-based assessment.MethodsWe compared current HIV detection practices to strategies of increasingly frequent routine HIV screening in Portuguese adults aged 18-69. We considered several subpopulations and geographic regions with varying levels of undetected HIV prevalence and incidence. Baseline inputs for the national case included undiagnosed HIV prevalence 0.16%, annual incidence 0.03%, mean population age 43 years, mean CD4 count at care initiation 292 cells/μL, 63% HIV test acceptance, 78% linkage to care, and HIV rapid test cost €6 under the proposed routine screening program. Outcomes included quality-adjusted survival, secondary HIV transmission, cost, and incremental cost-effectiveness. ResultsOne-time national HIV screening increased HIV-infected survival from 164.09 quality-adjusted life months (QALMs) to 166.83 QALMs compared to current practice and had an incremental cost-effectiveness ratio (ICER) of €28,000 per quality-adjusted life year (QALY). Screening more frequently in higher-risk groups was cost-effective: for example screening annually in men who have sex with men or screening every three years in regions with higher incidence and prevalence produced ICERs of €21,000/QALY and €34,000/QALY, respectively.ConclusionsOne-time HIV screening in the Portuguese national population will increase survival and is cost-effective by international standards. More frequent screening in higher-risk regions and subpopulations is also justified. Given Portugal’s challenging economic priorities, we recommend prioritizing screening in higher-risk populations and geographic settings.

BackgroundIn Western countries, smoking accounts for a large share of socio-economic inequalities in health. As smoking initiation occurs around the age of 13, it is likely that school context and social networks at school play a role in the origin of such inequalities. So far, there has been little generic explanation of how social ties at school contribute to socio-economic inequalities in smoking. The SILNE (Smoking Inequalities – Learning from Natural Experiments) survey was designed to test the hypothesis that a combination of peer effect, homophilous social ties, and school context may explain how smoking inequalities are magnified at school – a theory known as network-induced inequality. In this paper, the survey theory and design are presented.FindingsThe social network survey was carried out in 2013 in six medium-sized European cities with average incomes similar to the national average: Namur (Belgium), Tampere (Finland), Hannover (Germany), Latina (Italy), Amersfoort (The Netherlands), and Coimbra (Portugal). In each city, 6 to 8 schools were selected in a stratified sampling procedure. In each school, two grades in secondary education, corresponding to 14-16-year-olds, were selected. All adolescents in these two grades were invited to participate in the survey. Social ties were reported using the roster approach, in which each adolescent had to nominate up to 5 friends from a directory.The survey collected information from 11,015 adolescents in 50 schools, out of a total of 13,870 registered adolescents, yielding a participation rate of 79%. The SILNE survey yielded 57,094 social ties, 86.7% of which referred to friends who also participated in the survey.DiscussionThe SILNE survey was designed to measure the association between adolescents’ social ties at school, their socio-economic background, and their smoking behaviour. Two difficulties were encountered, however: legal privacy constraints made it impossible to apply the same parental consent procedure in all countries, leading to somewhat lower participation rates in two cities: Hannover and Latina. It was also difficult to match the 6 cities in terms of both age and type of education.The SILNE survey provided a comparable database for the study of smoking inequalities across European cities from a social network perspective.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1041-z) contains supplementary material, which is available to authorized users.

BackgroundMany risk behaviours in adolescence are socially patterned. However, it is unclear to what extent socioeconomic position (SEP) influences adolescent drinking in various parts of Europe. We examined how alcohol consumption is associated with parental SEP and adolescents’ own SEP among students aged 14–17 years.MethodsCross-sectional data were collected in the 2013 SILNE study. Participants were 8705 students aged 14–17 years from 6 European cities. The dependent variable was weekly binge drinking. Main independent variables were parental SEP (parental education level and family affluence) and adolescents’ own SEP (student weekly income and academic achievement). Multilevel Poisson regression models with robust variance and random intercept were fitted to estimate the association between adolescent drinking and SEP.ResultsPrevalence of weekly binge drinking was 4.2% (95%CI = 3.8–4.6). Weekly binge drinking was not associated with parental education or family affluence. However, weekly binge drinking was less prevalent in adolescents with high academic achievement than those with low achievement (PR = 0.34; 95%CI = 0.14–0.87), and more prevalent in adolescents with >€50 weekly income compared to those with ≤€5/week (PR = 3.14; 95%CI = 2.23–4.42). These associations were found to vary according to country, but not according to gender or age group.ConclusionsAcross the six European cities, adolescent drinking was associated with adolescents’ own SEP, but not with parental SEP. Socio-economic inequalities in adolescent drinking seem to stem from adolescents’ own situation rather than that of their family.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-017-4635-7) contains supplementary material, which is available to authorized users.