dataesr/scientific-paragraphs-categorization huggingface dataset:
HIV TESTING AND TREATMENT CASCADE IN EASTERN EUROPE AND CENTRAL ASIA Source: UNAIDS special analysis, 2017; see annex on methods for more details. 1  2016 measure derived from data reported by 12 countries, which accounted for 99% of people living with HIV in the region. 2 2016 measure derived from data reported by 13 countries. In the region, 93% of all people on antiretroviral therapy were reported to have received a viral load test during the reporting period. AIDS-related deaths <100 <100 <100 [<100-<100] [<100-<100] [<100-<100] People living with HIV Financial data are currently being validated and may be revised. For updates, please see http://aidsinfo. unaids. org. <500 <1000 1700 [<500-<500] [<1000-<1000] [1500-2000] <1000 47% [41%-53%] <1000 30% [26%-34%] 480 29% [24%-32%] <500 24% [21%-27%] 2010 2016.
INTRODUCTION UNAIDS annually provides revised global, regional and country-specific modelled estimates using the best available epidemiological and programmatic data to track the HIV epidemic. Modelled estimates are required because it is impossible to count the exact number of people living with HIV, people who are newly infected with HIV or people who have died from AIDS-related causes in any country: doing so would require regularly testing every person for HIV and investigating all deaths, which is logistically impossible and ethically problematic. Modelled estimates-and the lower and upper bounds around these estimates-provide a scientifically appropriate way of describing HIV epidemic levels and trends.
PARTNERSHIPS IN DEVELOPING METHODS FOR UNAIDS ESTIMATES Country teams use UNAIDS-supported software to develop estimates annually. The country teams are primarily comprised of demographers, epidemiologists, monitoring and evaluation specialists and technical partners working under the guidance of the national government's AIDS or health authority. The software used to produce the estimates is Spectrum, which is developed by Avenir Health, and the Estimates and Projections Package, which is developed by the East-West Center. 1  The UNAIDS Reference Group on Estimates, Modelling and Projections provides technical guidance on the development of the HIV component of the software. 2.
These methods also allow countries to take into account evidence of underreporting or reporting delays in HIV case report data, as well as the misclassification of deaths from AIDS-related causes. In all countries where UNAIDS supports the development of estimates, assumptions about the effectiveness of HIV programme scale-up and patterns of HIV transmission and disease progression are used to obtain age-and sex-specific estimates of people living with HIV, people newly infected with HIV, people dying from AIDS-related illnesses, and other important indicators (including treatment programme coverage statistics). These assumptions are based on systematic literature reviews and analyses of raw study data by scientific experts. Demographic population data, including fertility estimates, are derived from the United Nations Population Division's World Population Prospects 2015 data files.
In countries using HIV case reporting and AIDS-related mortality data, the number of years of data and the magnitude of the cases reported or AIDS-related deaths observed will contribute to determining the precision of the estimate. The assumptions required to arrive at the estimate also contribute to the extent of the ranges around the estimates: in brief, the more assumptions, the wider the uncertainty range, since each assumption introduces additional uncertainties. For example, the ranges around the estimates of adult HIV prevalence are smaller than those around the estimates of HIV incidence among children, which require additional data on prevalence among pregnant women and the probability of mother-to-child HIV transmission with their own additional uncertainty. UNAIDS is confident that the actual numbers of people living with HIV, people who are newly infected with HIV or people who have died from AIDS-related causes lie within the reported ranges.
IMPROVEMENTS TO THE 2017 UNAIDS ESTIMATES MODEL Country teams create new Spectrum files every year. The files may differ from one year to the next for two reasons. First, new surveillance and programme data are entered into the model; this can change HIV prevalence and incidence trends over time, including for past years. Second, improvements are incorporated into the model based on the latest available science and statistical methods that lead to the creation of more accurate trends in HIV incidence. Due to these improvements to the model and the addition of new data to create the estimates, the results from previous years cannot be compared with the results from this year. A full historical set of estimates are created each year, however, enabling a description of trends over time. Between the previous estimates and the 2017 estimates, the following changes were applied to the model under the guidance of the UNAIDS Reference Group on Estimates, Modelling and Projections and based on the latest scientific evidence.
METHODS FOR MEASURING THE 90-90-90 TREATMENT TARGET To describe country-level progress against the 90-90-90 targets, UNAIDS analysed data on the number of people who knew their HIV status, the number of people on treatment and the number of people virally suppressed among those tested, as reported through the GAM system. In 2015, 147 countries reported at least one measure; in 2016, that number increased to 163 countries. A description of the GAM system and the treatment target-related indicators that countries report against are provided in the UNAIDS GAM 2017 guidelines (1). All programme data submitted to UNAIDS-including the number of people reported to know their status, the number of people accessing treatment and the number of people on treatment who are virally suppressed-were validated by UNAIDS and its partners prior to publication.
Country-submitted data that did not meet the required validation checks for quality either at the indicator level or across the treatment cascade were not published. The final set of country measures of progress against the 90-90-90 targets for 2015 and 2016 are available at http://aidsinfo. unaids. org. Not all countries were able to report against all three prongs of the 90-90-90 targets. Complete treatment cascades are available in 2016 for 60 countries; another 17 countries, primarily in western and central Europe and North America, have complete cascades for at least one year between 2012 and 2015. Upper and lower ranges of uncertainty for country-level estimates were calculated from the range of estimated numbers of people living with HIV. This range may not fully capture uncertainty in the reported programme data.
To estimate regional and global progress against the 90-90-90 targets, UNAIDS supplemented the country-supplied data submitted through GAM with data obtained from a review of other published and unpublished data sources, including grey literature and Demographic and Health Survey results. There were insufficient reported data (reported, published or unpublished) from countries in western Europe and North America in 2016 to present results for the region, although the country values that were available in the region were used to construct the global totals. Upper and lower ranges of uncertainty for global and regional estimates were calculated from the range of numbers of people living with HIV and the lower and upper ranges of the numbers of people on treatment in the region. This range may not fully capture uncertainty in the reported or missing programme data for the first and third indicators.
DATA SOURCES AND INDICATOR-SPECIFIC METHODS FOR DERIVING GLOBAL AND REGIONAL MEASURES Estimates of people living with HIV Unless otherwise stated, all progress measures in this report are based on UNAIDS global, regional and country-specific modelled estimates for 168 countries of the numbers of people living with HIV in 2015 and 2016. More details about how UNAIDS derives estimates and uncertainty bounds around the number of people living with HIV and those accessing antiretroviral therapy can be found earlier in the section "Measuring antiretroviral therapy coverage". Knowledge of HIV status among people living with HIV Global and regional measures of the number of people living with HIV who know their status were derived using the most recent HIV surveillance and nationally representative population-based survey data available for 109 countries in 2016.
Although HIV surveillance systems can be a reasonably robust source of data to estimate the number of people living with HIV who know their status, biases in the reported numbers may still exist. For example, a country's measure of the knowledge of status may be underestimated if not all people diagnosed are reported to the surveillance system in a timely manner; the measure also may be overestimated if people are reported to the system more than once and these duplicates are not detected. Similarly, if people die or emigrate but are not removed from the system, the number of people living with HIV who are reported to know their HIV status also will be overstated. The estimated numbers of people living with HIV who knew their status for 25 countries in sub-Saharan Africa in 2016 were derived from nationally representative populationbased surveys conducted since 2010 and from treatment data reported through GAM.
While it is impossible to measure the exact magnitude of this bias, in previous surveys in Kenya, Malawi and Uganda, anywhere from one tenth to one third of HIV-positive participants misreported their HIV status as negative (2). Underestimation of knowledge of status also can occur at the national level if people living with HIV learn their status either as a result of-or subsequent to-the survey. For 27 countries without case surveillance data submitted through GAM or survey measures, UNAIDS used published and unpublished grey literature or modelled estimates to inform the 2015 and 2016 regional and global values. A similar method used to adjust knowledge of status for indirect surveys was applied to estimates from such countries before 2016 (most of them in western and central Europe). For 59 countries without any estimate of the number of people living with HIV who know their status, which are home to just 4% of the total estimated number of people living with HIV worldwide, the regional average of the ratio of the number of people who know their status and the number on treatment was calculated from available data submitted by countries in the region and weighted according to the number of people living with HIV by country.
People accessing antiretroviral therapy Global and regional measures of antiretroviral therapy numbers are calculated from country-reported programme data through GAM and the UNAIDS-supported Spectrum software. For a small number of countries where reported numbers of people on treatment are not available-primarily in western and central Europe and North Americaestimates of the number of people on treatment are developed either in consultation with the public health agency responsible for monitoring the national treatment programme or based on published sources. In partnership with UNICEF, WHO and other partners that support treatment service delivery in countries, UNAIDS reviews and validates treatment numbers reported through GAM and Spectrum on an annual basis. UNAIDS staff also provide technical assistance and training to country public health and clinical officers to ensure the quality of the treatment data that are reported.
Nevertheless, this measure may overestimate the number of people on treatment if people who transfer from one facility to another are reported by both facilities. Similarly, coverage may be overestimated if people who have died, have disengaged from care or have emigrated are not identified and removed from treatment registries. Treatment numbers also may be underestimated if not all clinics report the numbers on treatment completely or in a timely manner. UNAIDS recently completed a triangulation of data to verify the UNAIDS global estimate of people accessing antiretroviral therapy at the end of 2015. For more details about how confident UNAIDS is in reported treatment numbers, please see How many people living with HIV access treatment? 4.
People who have achieved viral suppression Progress towards the viral suppression target among people on treatment and as a proportion of all people living with HIV was derived from data reported to GAM. For the purposes of reporting, the threshold for suppression is a viral load of less than 1000 copies per ml, although some countries may set lower thresholds or require persons to achieve an undetectable viral load. UNAIDS GAM 2017 guidelines state that countries should only report viral load test results that were done as part of routine service delivery (i. e. not as a result of suspected treatment failure). This guidance also specifies only a person's last test result from the reporting year be submitted, so the reported number suppressed among those tested should represent people and not tests performed.
Across the regions, 88 countries reported viral load suppression data from case-based surveillance or laboratory-based reporting systems in 2016. Three countries reported survey data for 2016 from nationally representative population-based surveys, where viral load testing was done only among those who self-reported that they were on treatment. Through a review of the published and unpublished literature, UNAIDS identified nationally representative estimates of viral load suppression for an additional five countries. Where more recent data were not available from countries in western and central Europe and North America in 2016, it was assumed to be the same as the viral suppression estimate for 2015. For the 72 countries in 2016 with no nationally representative estimate of viral suppression among those tested, which represent 58% of the people on treatment worldwide, the regional average number of people on antiretroviral therapy who are virally suppressed was calculated using data submitted by countries in the region, weighted according to the number of people on treatment in a country.
By assuming that the percentage of people suppressed among those accessing viral load testing is representative of all people on treatment in the country, the measure may be either overor underestimated depending on the characteristics of the reporting clinics. Second, reported access to viral load testing varies considerably across each region, and it is difficult to know whether the experience in countries that reported data to UNAIDS is similar to that of countries without data in the region. In western and central Africa, viral load testing data submitted to UNAIDS in 2015 accounted for just 2% of all people on treatment in the region. As a result, viral suppression levels for the region were not published for 2015. UNAIDS assumes that all people on treatment in western and central Europe and North America received an annual viral load test in both 2015 and 2016.
Distribution of new HIV infections by subpopulation The distribution of new HIV infections by region was estimated based on data for 163 countries using five data sources. For countries that model their HIV epidemic based on data from subpopulations, including key populations, the numbers of new infections were extracted from Spectrum 2016 files. This source provided data from 63 countries for sex workers, 37 countries for people who inject drugs, 57 countries for men who have sex with men and 13 countriesonly in Latin America and Asia-for transgender people. The second source was mode of transmission studies conducted in countries between 2006 and 2012. The proportions of new infections estimated for each subpopulation, calculated by modes of transmission analyses, were multiplied by the number of total new adult (15-49) infections, by relevant gender, to derive an estimated number of new infections by subpopulation.
This source provided data from 18 countries for sex workers, 25 countries for people who inject drugs and 22 countries for men who have sex with men. New HIV infections for European countries with neither of the aforementioned data were derived from the European Centre for Disease Prevention and Control (ECDC) HIV Surveillance Report 2014. The proportions of new diagnoses for each region in Europe (West, central and East) were applied to UNAIDS estimates of new infections in each country for people who inject drugs and men who have sex with men. Data for sex workers were not available from the ECDC report. New HIV infections in China, Russia and the United States of America were taken from available national reports of new diagnoses. New HIV infections among countries without a direct data source were calculated from regional benchmarks.
UNAIDS does not present estimates of mother-to-child HIV transmission, including estimates related to children, in some countries that have concentrated epidemics unless adequate data are available to validate these estimates. UNAIDS also does not publish these estimates for countries where the estimated number of pregnant women living with HIV is less than 50. With regard to reporting incidence trends, if there are not enough historical data to state with confidence whether a decline in incidence has occurred, UNAIDS does not publish earlier data in order to prevent users from making inaccurate inferences about trends. Specifically, incidence trends are not published if there are fewer than four data points for the key population or if there have been no data for the past four years for countries using repeated survey or routine testing data.
Trends prior to 2000 are not published for countries if there is no early case surveillance or mortality data available. Finally, UNAIDS does not publish country estimates when further data or analyses are needed to produce valid estimates. More information on the UNAIDS estimates and the individual Spectrum files for most countries can be found in the aidsinfo section of the UNAIDS website (http://aidsinfo. unaids. org) More information on UNAIDS estimates-along with the individual Spectrum files for most countries-can be found on the UNAIDS website (www. unaids. org).
Data and methodology The present study draws on data from the European Union Labour Force Survey (EU-LFS). This data set makes it possible to describe the main changes that have affected job structure in around 12 countries between 1993 and 2013. Several arguments suggest that there has been a certain homogenisation of social structures among western countries over recent decades (global trade and the concomitant alignment of economic policies, technological change). However, we also know that these overall trends should not prevent us from observing potential national specificities linked, in particular, to the welfare regime in place  (Esping-Andersen, 1990). The latter influences the rate of growth in the service sector but also employment structure and the ethno-racial and gendered division of labour.
In this study, I use a more detailed level of the ESeG classification that distinguishes between clerks and skilled service employees  (Amar et al. , 2014). In the second section of this article, I use the proportion of workers in involuntary part-time jobs as an indicator to describe working conditions at the bottom of the social structure. The EU-LFS data set provides information about working time as well as the reasons for part-time work (person still undergoing training, for personal health reasons, need/choice to look after children or incapacitated adult, person could not find a full-time job, other personal reasons). It is therefore possible to calculate the proportion of part-time workers in each group of occupations who state they were unable to find a full-time job or contract.
With the decline in jobs at the interface of the upper working classes and lower middle classes, the middle classes are being undermined from the bottom up. Nevertheless, there are variations between national contexts. Some countries are not experiencing any clear decrease in administrative jobs and others, where the latter are in decline, have not experienced any real polarisation insofar as there has been no significant increase in the least-skilled jobs. In order to account for changes in social structures and look beyond common trends (i. e. the decreased proportion of industrial workers and increased proportion of highestskilled employees), several factors must be taken into consideration, and first and foremost public policies that shape the effects of technological change. The unequal decline in the proportion of administrative employees is partly linked to differences in structure according to sector of activity: in Germany, 25% of administrative workers are employed in industry as opposed to 14% in France, according to the EU-LFS data set.
O. D. was supported by PHC FASIC (Franco-Australian Hubert Curien Programme). S. C. D. , C. J. L. , J. L. P. and A. J. L. are funded by the National Health and Medical Research Council (NHMRC) of Australia. The 18-year Melbourne Atopy Cohort Study (MACS) follow-up was supported by the NHMRC (APP454856); Nestec Ltd. , a subsidiary of Nestlé Australia funded the first 6 years of the study.
Acknowledgments: MACS: We thank  John Thorburn , FRACP, for assistance in patient recruitment and administrative assistance and the  Mercy Maternity Hospital Department of Obstetrics  for participant recruitment, and  David Hill ,  Cliff Hosking  and  Christine Axelrad  for study leadership up to the 12-year follow-up. We thank  Anne Balloch  for assistance with data management,  Rida Asif ,  Carlie Dunford  and  Brittany Campbell  for cohort coordination, and  Jeeva Sanjeevan  for clinical testing, during the 18-year follow-up. We thank all of the MACS participants for their ongoing support for this study.
Funding: O. D. was supported by PHC FASIC (Franco-Australian Hubert Curien Programme). S. C. D. , C. J. L. , J. L. P. and A. J. L. are funded by the National Health and Medical Research Council (NHMRC) of Australia. The 18-year Melbourne Atopy Cohort Study (MACS) follow-up was supported by the NHMRC (APP454856); Nestec Ltd. , a subsidiary of Nestlé Australia funded the first 6 years of the study.
PAP involves the delivery of air under pressure to the pharynx via a well-fitting mask. This pressure acts as a pneumatic splint, holding the airway open and preventing its collapse. Although a highly efficacious treatment, patients are often uncomfortable using the device and adherence to therapy remains problematic  [3, 4]. For this reason, there is substantial interest in developing alternative treatments for OSA. These include hypoglossal nerve stimulation (HNS), which modulates upper airway collapsibility though neural stimulation of the genioglossus muscle  [5]. Since the first successful use of a HNS system to treat OSA was reported in 2001  [6] , three HNS systems have been CE-marked. Apnex Medical published the first feasibility study in 2011, reporting a significant decrease in OSA severity and symptoms following implantation with their system  [7] , but this device did not enter clinical practice because a pivotal study failed to show a between-group difference in the reduction of sleep apnoea, owing to unanticipated improvements in the control group (ClinicalTrials.