BACKGROUND: Global health education has attracted significant attention in recent years from academic institutions in developed countries. In India however, a recent analysis found that delivery of global health education is fragmented and called for academic institutions to work towards closing the developing country/developed country dichotomy. Our study explored the understanding of global health in the Indian setting and opportunities for development of a global health education framework in Indian public health institutions. METHODS: The study involved semi-structured interviews with staff of Indian public health institutes and other key stakeholders in global health in India. The interview questions covered participants' interpretation of global health and their opinion about global health education in India. Thematic analysis was conducted. A theoretical framework developed by Smith and Shiffman to explain political priority for global health initiatives was adapted to guide our analysis to explore development of global health education in Indian public health institutions. RESULTS: A total of 17 semi-structured interviews were completed which involved 12 faculty members from five public health institutes and five stakeholders from national and multilateral organisations. Global health was viewed as the application of public health in real-world setting and at a broader, deeper and transnational scale. The understanding of global health was informed by participants' exposure to work experiences and interaction with overseas faculty. Most common view about the relationship between global health and public health was that public health has become more global and both are interconnected. Integration of global health education into public health curriculum was supported but there were concerns given public health was still a new discipline in India. Most participants felt that global health competencies are complementary to public health competencies and build on core public health skills. Employability, ...
Abstract Background Disparity in utilization of reproductive healthcare services between the urban poor and the urban non-poor households in the developing nations is well known. However, disparity may also exist within urban poor households. Our objective was to document the extent of disparity in reproductive healthcare utilization among the urban poor and to identify the socio-demographic determinants of underutilization with a view to characterizing this vulnerable subpopulation. Methods A survey of 16,221 households was conducted in 39 clusters from two large urban poor settlements in Delhi. From 13,451 consenting households, socio-demographic data and information on births, maternal and child deaths within the previous year was collected. Details of antenatal care (ANC) was collected from 597 pregnant women. Information on ANC and postnatal care was also obtained from 596 recently delivered (within six months) mothers. All data were captured electronically using a customized and validated smart phone application. Households were categorized into quintiles of socio-economic position (SEP) based on dwelling characteristics and possession of durable assets using principal component analysis. Potential socio-demographic determinants of reproductive healthcare utilization were examined using random effects logistic regression. Results The prevalence of facility based birthing was 77 % ( n = 596 mothers). Of the 596 recently delivered mothers only 70 % had an ANC registration card, 46.3 % had ANC in their first trimester, 46 % had visited a facility within 4 weeks post-delivery and 27 % were using modern contraceptive methods. Low socio-economic position was the most important predictor of underutilization with a clear gradient across SEP quintiles. Compared to the poorest, the least poor women were more likely to be registered for ANC (OR 1.96, 95 %CI 0.95-4.15) and more likely to have made ≥ 4 ANC visits (OR 5.86, 95 %CI 2.82-12.19). They were more likely to have given birth in a facility (OR 4.87, 95 %CI 2.12-11.16), to have visited a hospital within one month of childbirth (OR 3.18, 95 %CI 1.62-6.26). In general, government funded health insurance and conditional cash transfers schemes were underutilized in this community. Conclusion The poorest segment of the urban poor population utilizes reproductive healthcare facilities the least. Strategies to improve access and utilization of healthcare services among the poorest of the poor may be necessary to achieve universal health coverage.
Engaging in partnerships is a strategic means of achieving objectives common to each partner. The Post Graduate Diploma in Public Health Management (PGDPHM) partners in consultation with the government and aims to strengthen the public health managerial capacity. This case study examines the PGDPHM program conducted jointly by the Public Health Foundation of India and the Government of Madhya Pradesh (GoMP) at the State Institute of Health Management and Communication, Gwalior, which is the apex training and research institute of the state government for health professionals. This is an example of collaborative partnership between an academic institution and the Department of Public Health and Family Welfare, GoMP. PGDPHM is a 1-year, fully residential course with a strong component of field-based project work, and aims to bridge the gap in public health managerial capacity of the health system through training of health professionals. The program is uniquely designed in the context of the National Rural Health Mission and uses a multidisciplinary approach with a focus on inter-professional education. The curriculum is competency driven and health systems connected and the pedagogy uses a problem-solving approach with multidisciplinary faculty from different programs and practice backgrounds that bring rich field experience to the classroom. This case study presents the successful example of the interface between academia and the health system and of common goals achieved through this partnership for building capacity of health professionals in the state of Madhya Pradesh over the past 3 years.
BACKGROUND: Disparity in utilization of reproductive healthcare services between the urban poor and the urban non-poor households in the developing nations is well known. However, disparity may also exist within urban poor households. Our objective was to document the extent of disparity in reproductive healthcare utilization among the urban poor and to identify the socio-demographic determinants of underutilization with a view to characterizing this vulnerable subpopulation. METHODS: A survey of 16,221 households was conducted in 39 clusters from two large urban poor settlements in Delhi. From 13,451 consenting households, socio-demographic data and information on births, maternal and child deaths within the previous year was collected. Details of antenatal care (ANC) was collected from 597 pregnant women. Information on ANC and postnatal care was also obtained from 596 recently delivered (within six months) mothers. All data were captured electronically using a customized and validated smart phone application. Households were categorized into quintiles of socio-economic position (SEP) based on dwelling characteristics and possession of durable assets using principal component analysis. Potential socio-demographic determinants of reproductive healthcare utilization were examined using random effects logistic regression. RESULTS: The prevalence of facility based birthing was 77% (n = 596 mothers). Of the 596 recently delivered mothers only 70% had an ANC registration card, 46.3% had ANC in their first trimester, 46% had visited a facility within 4 weeks post-delivery and 27% were using modern contraceptive methods. Low socio-economic position was the most important predictor of underutilization with a clear gradient across SEP quintiles. Compared to the poorest, the least poor women were more likely to be registered for ANC (OR 1.96, 95%CI 0.95-4.15) and more likely to have made ≥ 4 ANC visits (OR 5.86, 95%CI 2.82-12.19). They were more likely to have given birth in a facility (OR 4.87, 95%CI 2.12-11.16), to have visited a hospital within one month of childbirth (OR 3.18, 95%CI 1.62-6.26). In general, government funded health insurance and conditional cash transfers schemes were underutilized in this community. CONCLUSION: The poorest segment of the urban poor population utilizes reproductive healthcare facilities the least. Strategies to improve access and utilization of healthcare services among the poorest of the poor may be necessary to achieve universal health coverage.
BACKGROUND: Indian medical education system is on the brink of a massive reform. The government of India has recently passed the National Medical Commission Bill (NMC Bill). It seeks to eliminate the existing shortage and maldistribution of health professionals in India. It also encourages establishment of medical schools in underserved areas. Hence this study explores the geographic distribution of medical schools in India to identify such under and over served areas. Special emphasis has been given to the mapping of new medical schools opened in the last decade to identify the ongoing pattern of expansion of medical education sector in India. METHODS: All medical schools retrieved from the online database of Medical Council of India were plotted on the map of India using geographic information system. Their pattern of establishment was identified. Medical school density was calculated to analyse the effect of medical school distribution on health care indicators. RESULTS: Presence of medical schools had a positive influence on the public health profile. But medical schools were not evenly distributed in the country. The national average medical school density in India amounted to 4.08 per 10 million population. Medical school density of provinces revealed a wide range from 0 (Nagaland, Dadra and Nagar Haveli, Daman and Diu and Lakshadweep) to 72.12 (Puducherry). Medical schools were seen to be clustered in the vicinity of major cities as well as provincial capitals. Distance matrix revealed that the median distance of a new medical school from its nearest old medical school was just 22.81 Km with an IQR of 6.29 to 56.86 Km. CONCLUSIONS: This study revealed the mal-distribution of medical schools in India. The problem is further compounded by selective opening of new medical schools within the catchment area of already established medical schools. Considering that medical schools showed a positive influence on public health, further research is needed to guide formulation of rules for medical school ...
Background An effective health workforce is essential for achieving health-related new Sustainable Development Goals. Odisha, one of the states in India with low health indicators, faces challenges in recruiting and retaining health staff in the public sector, especially doctors. Recruitment, deployment and career progression play an important role in attracting and retaining doctors. We examined the policies on recruitment, deployment and promotion for doctors in the state and how these policies were perceived to be implemented. Methods We undertook document review and four key informant interviews with senior state-level officials to delineate the policies for recruitment, deployment and promotion. We conducted 90 in-depth interviews, 86 with doctors from six districts and four at the state level to explore the perceptions of doctors about these policies. Results Despite the efforts by the Government of Odisha through regular recruitments, a quarter of the posts of doctors was vacant across all institutional levels in the state. The majority of doctors interviewed were unaware of existing government rules for placement, transfer and promotion. In addition, there were no explicit rules followed in placement and transfer. More than half (57%) of the doctors interviewed from well-accessible areas had never worked in the identified hard-to-reach areas in spite of having regulatory and incentive mechanisms. The average length of service before the first promotion was 26 (±3.5) years. The doctors expressed satisfaction with the recruitment process. They stated concerns over delayed first promotion, non-transparent deployment policies and ineffective incentive system. Almost all doctors suggested having time-bound and transparent policies. Conclusions Adequate and appropriate deployment of doctors is a challenge for the government as it has to align the individual aspirations of employees with organizational needs. Explicit rules for human resource management coupled with transparency in implementation can improve governance and build trust among doctors which would encourage them to work in the public sector.
In: Bulletin of the World Health Organization: the international journal of public health = Bulletin de l'Organisation Mondiale de la Santé, Band 94, Heft 5, S. 370-375
In: Bulletin of the World Health Organization: the international journal of public health = Bulletin de l'Organisation Mondiale de la Santé, Band 91, Heft 11, S. 847-852
BACKGROUND: Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. METHODS: Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0-100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target-1 billion more people benefiting from UHC by 2023-we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. FINDINGS: Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2-47·5) in 1990 to 60·3 (58·7-61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9-3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6-421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0-3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5-1040·3]) residing in south Asia. INTERPRETATION: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close-or how far-all populations are in benefiting from UHC. ; For complete list of authors see http://dx.doi.org/10.1016/S0140-6736(20)30750-9
Background India has made substantial progress in improving child survival over the past few decades, but a comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality. Methods We assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in 5 × 5 km grids across India, and for the districts and states of India, using all accessible data from various sources including surveys with subnational geographical information. The 31 states and groups of union territories were categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from 2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and 25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We assessed the causes of child death and the contribution of risk factors to child deaths at the state level. Findings U5MR in India decreased from 83·1 (95% uncertainty interval [UI] 76·7–90·1) in 2000 to 42·4 (36·5–50·0) per 1000 livebirths in 2017, and NMR from 38·0 (34·2–41·6) to 23·5 (20·1–27·8) per 1000 livebirths. U5MR varied 5·7 times between the states of India and 10·5 times between the 723 districts of India in 2017, whereas NMR varied 4·5 times and 8·0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per 1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of change from 2010 to 2017 varied among the districts from a 9·02% (95% UI 6·30–11·63) reduction to no significant change for U5MR and from an 8·05% (95% UI 5·34–10·74) reduction to no significant change for NMR. Inequality between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to 2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate decline for neonatal disorders, and the smallest decline for congenital birth defects, although the magnitude of decline varied widely between the states. Child and maternal malnutrition was the predominant risk factor, to which 68·2% (65·8–70·7) of under-5 deaths and 83·0% (80·6–85·0) of neonatal deaths in India could be attributed in 2017; 10·8% (9·1–12·4) of under-5 deaths could be attributed to unsafe water and sanitation and 8·8% (7·0–10·3) to air pollution. Interpretation India has made gains in child survival, but there are substantial variations between the states in the magnitude and rate of decline in mortality, and even higher variations between the districts of India. Inequality between districts within states has increased for the majority of the states. The district-level trends presented here can provide crucial guidance for targeted efforts needed in India to reduce child mortality to meet the Indian and global child survival targets. District-level mortality trends along with state-level trends in causes of under-5 and neonatal death and the risk factors in this Article provide a comprehensive reference for further planning of child mortality reduction in India.
BACKGROUND: Traumatic brain injury (TBI) and spinal cord injury (SCI) are increasingly recognised as global health priorities in view of the preventability of most injuries and the complex and expensive medical care they necessitate. We aimed to measure the incidence, prevalence, and years of life lived with disability (YLDs) for TBI and SCI from all causes of injury in every country, to describe how these measures have changed between 1990 and 2016, and to estimate the proportion of TBI and SCI cases caused by different types of injury. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 to measure the global, regional, and national burden of TBI and SCI by age and sex. We measured the incidence and prevalence of all causes of injury requiring medical care in inpatient and outpatient records, literature studies, and survey data. By use of clinical record data, we estimated the proportion of each cause of injury that required medical care that would result in TBI or SCI being considered as the nature of injury. We used literature studies to establish standardised mortality ratios and applied differential equations to convert incidence to prevalence of long-term disability. Finally, we applied GBD disability weights to calculate YLDs. We used a Bayesian meta-regression tool for epidemiological modelling, used cause-specific mortality rates for non-fatal estimation, and adjusted our results for disability experienced with comorbid conditions. We also analysed results on the basis of the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, there were 27·08 million (95% uncertainty interval [UI] 24·30-30·30 million) new cases of TBI and 0·93 million (0·78-1·16 million) new cases of SCI, with age-standardised incidence rates of 369 (331-412) per 100 000 population for TBI and 13 (11-16) per 100 000 for SCI. In 2016, the number of prevalent cases of TBI was 55·50 million (53·40-57·62 million) and of SCI was 27·04 million (24·98-30·15 million). From 1990 to 2016, the age-standardised prevalence of TBI increased by 8·4% (95% UI 7·7 to 9·2), whereas that of SCI did not change significantly (-0·2% [-2·1 to 2·7]). Age-standardised incidence rates increased by 3·6% (1·8 to 5·5) for TBI, but did not change significantly for SCI (-3·6% [-7·4 to 4·0]). TBI caused 8·1 million (95% UI 6·0-10·4 million) YLDs and SCI caused 9·5 million (6·7-12·4 million) YLDs in 2016, corresponding to age-standardised rates of 111 (82-141) per 100 000 for TBI and 130 (90-170) per 100 000 for SCI. Falls and road injuries were the leading causes of new cases of TBI and SCI in most regions. INTERPRETATION: TBI and SCI constitute a considerable portion of the global injury burden and are caused primarily by falls and road injuries. The increase in incidence of TBI over time might continue in view of increases in population density, population ageing, and increasing use of motor vehicles, motorcycles, and bicycles. The number of individuals living with SCI is expected to increase in view of population growth, which is concerning because of the specialised care that people with SCI can require. Our study was limited by data sparsity in some regions, and it will be important to invest greater resources in collection of data for TBI and SCI to improve the accuracy of future assessments. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation ; We acknowledge the funding and support of the Bill & Melinda Gates Foundation. AK was supported by the Miguel Servet contract, which was financed by the CP13/00150 and PI15/00862 projects integrated into the National Research, Development, and Implementation,and funded by the Instituto de Salud Carlos III General Branch Evaluation and Promotion of Health Research and the European Regional Development Fund (ERDF-FEDER). AMS is supported by the Egyptian Fulbright Mission Program. AF acknowledges the Federal University of Sergipe (Sergipe, Brazil). AA received financial assistance from the Indian Department of Science and Technology (New Delhi, India) through the INSPIRE faculty programme. AS is supported by Health Data Research UK. DJS is supported by the South African Medical Research Council. AB is supported by the Public Health Agency of Canada. SMSI received a senior research fellowship from the Institute for Physical Activity and Nutrition, Deakin University (Waurn Ponds, VIC, Australia), and a career transition grant from the High Blood Pressure Research Council of Australia. FP and CF acknowledge support from the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e a Tecnologia, and Ministério da Educação e Ciência) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020 UID/QUI/50006/2013. TB acknowledges financial support from the Institute of Medical Research and Medicinal Plant Studies, Yaoundé, Cameroon. AM of Imperial College London is grateful for support from the Northwest London National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research andCare and the Imperial NIHR Biomedical Research Centre. KD is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (grant number 201900). PSA is supported by an Australian National Health and Medical Research Council Early Career Fellowship. RT-S was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. The Serbian part of this contribution (by MJ) has been co-financed with grant OI175014 from the Serbian Ministry of Education, Science and Technological Development; publication of results was not contingent upon the Ministry's approval. MMMSM acknowledges support from the Serbian Ministry of Education, Science and Technological Development (contract 175087). MM's research was supported by the NIHR Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust (London, UK) and King's College London. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the UK Department of Health. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt professor award, which was funded by the German Federal Ministry of Education and Research ; Sí
BACKGROUND: Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015. METHODS: For countries without high-quality vital registration data, we estimated prevalence and incidence with data from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4 cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS (UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for garbage coding and HIV misclassification. FINDINGS: Global HIV incidence reached its peak in 1997, at 3·3 million new infections (95% uncertainty interval [UI] 3·1-3·4 million). Annual incidence has stayed relatively constant at about 2·6 million per year (range 2·5-2·8 million) since 2005, after a period of fast decline between 1997 and 2005. The number of people living with HIV/AIDS has been steadily increasing and reached 38·8 million (95% UI 37·6-40·4 million) in 2015. At the same time, HIV/AIDS mortality has been declining at a steady pace, from a peak of 1·8 million deaths (95% UI 1·7-1·9 million) in 2005, to 1·2 million deaths (1·1-1·3 million) in 2015. We recorded substantial heterogeneity in the levels and trends of HIV/AIDS across countries. Although many countries have experienced decreases in HIV/AIDS mortality and in annual new infections, other countries have had slowdowns or increases in rates of change in annual new infections. INTERPRETATION: Scale-up of ART and prevention of mother-to-child transmission has been one of the great successes of global health in the past two decades. However, in the past decade, progress in reducing new infections has been slow, development assistance for health devoted to HIV has stagnated, and resources for health in low-income countries have grown slowly. Achievement of the new ambitious goals for HIV enshrined in Sustainable Development Goal 3 and the 90-90-90 UNAIDS targets will be challenging, and will need continued efforts from governments and international agencies in the next 15 years to end AIDS by 2030. ; Funding: We thank the countless individuals who have contributed to the Global Burden of Disease (GBD) Study 2015 in various capacities. We specifically thank Jeffrey Eaton and John Stover. HW and CJLM received funding for this study from the Bill & Melinda Gates Foundation; the National Institute of Mental Health, National Institutes of Health (NIH; R01MH110163); and the National Institute on Aging, NIH (P30AG047845). LJAR acknowledges the support of Qatar National Research Fund (NPRP 04-924-3-251) who provided the main funding for generating the data provided to the GBD-Institute for Health Metrics and Evaluation effort. BPAQ acknowledges institutional support from PRONABEC (National Program of Scholarship and Educational Loan), provided by the Peruvian government. DB is supported by the Bill & Melinda Gates Foundation (grant number OPP1068048). JDN was supported in his contribution to this work by a Fellowship from Fundacao para a Ciencia e a Tecnologia, Portugal (SFRH/BPD/92934/2013). KD is supported by a Wellcome Trust Fellowship in Public Health and Tropical Medicine (grant number 099876). TF received financial support from the Swiss National Science Foundation (SNSF; project number P300P3-154634). AG acknowledges funding from Sistema Nacional de Investigadores de Panama-SNI. PJ is supported by Wellcome Trust-DBT India Alliance Clinical and Public Health Intermediate Fellowship. MK receives research support from the Academy of Finland, the Swedish Research Council, Alzheimerfonden, Alzheimer's Research & Prevention Foundation, Center for Innovative Medicine (CIMED) at Karolinska Institutet South Campus, AXA Research Fund, Wallenberg Clinical Scholars Award from the Knut och Alice Wallenbergs Foundation, and the Sheika Salama Bint Hamdan Al Nahyan Foundation. AK's work was supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R&D&I and funded by the ISCIII (General Branch Evaluation and Promotion of Health Research), and the European Regional Development Fund (ERDF-FEDER). SML is funded by a National Institute for Health Research (NIHR) Clinician Scientist Fellowship (grant number NIHR/CS/010/014). HJL reports grants from the NIHR, EU Innovative Medicines Initiative, Centre for Strategic & International Studies, and WHO. WM is Program analyst, Population and Development, in the Peru Country Office of the United Nations Population Fund, which does not necessarily endorse this study. For UOM, funding from the German National Cohort Consortium (O1ER1511D) is gratefully acknowledged. KR reports grants from NIHR Oxford Biomedical Research Centre, NIHR Career Development Fellowship, and Oxford Martin School during the conduct of the study. GR acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). ISS reports grants from FAPESP (Brazilian public agency). RSS receives institutional support from Universidad de Ciencias Aplicadas y Ambientales, UDCA, Bogota Colombia. SS receives postdoctoral funding from the Fonds de la recherche en sante du Quebec (FRSQ), including its renewal. RTS was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI14/00894 from ISCIII-FEDER. PY acknowledges support from Strategic Public Policy Research (HKU7003-SPPR-12).
Background: timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015. Methods: for countries without high-quality vital registration data, we estimated prevalence and incidence with data from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4 cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS (UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for garbage coding and HIV misclassification. Findings: global HIV incidence reached its peak in 1997, at 3·3 million new infections (95% uncertainty interval [UI] 3·1–3·4 million). Annual incidence has stayed relatively constant at about 2·6 million per year (range 2·5–2·8 million) since 2005, after a period of fast decline between 1997 and 2005. The number of people living with HIV/AIDS has been steadily increasing and reached 38·8 million (95% UI 37·6–40·4 million) in 2015. At the same time, HIV/AIDS mortality has been declining at a steady pace, from a peak of 1·8 million deaths (95% UI 1·7–1·9 million) in 2005, to 1·2 million deaths (1·1–1·3 million) in 2015. We recorded substantial heterogeneity in the levels and trends of HIV/AIDS across countries. Although many countries have experienced decreases in HIV/AIDS mortality and in annual new infections, other countries have had slowdowns or increases in rates of change in annual new infections. Interpretation: scale-up of ART and prevention of mother-to-child transmission has been one of the great successes of global health in the past two decades. However, in the past decade, progress in reducing new infections has been slow, development assistance for health devoted to HIV has stagnated, and resources for health in low-income countries have grown slowly. Achievement of the new ambitious goals for HIV enshrined in Sustainable Development Goal 3 and the 90-90-90 UNAIDS targets will be challenging, and will need continued efforts from governments and international agencies in the next 15 years to end AIDS by 2030. Funding Bill & Melinda Gates Foundation, and National Institute of Mental Health and National Institute on Aging, National Institutes of Health