Mapping HIV prevalence in sub-Saharan Africa between 2000 and 2017.

HIV/AIDS is a leading cause of disease burden in sub-Saharan Africa. Existing evidence has demonstrated that there is substantial local variation in the prevalence of HIV; however, subnational variation has not been investigated at a high spatial resolution across the continent. Here we explore within-country variation at a 5 × 5-km resolution in sub-Saharan Africa by estimating the prevalence of HIV among adults (aged 15-49 years) and the corresponding number of people living with HIV from 2000 to 2017. Our analysis reveals substantial within-country variation in the prevalence of HIV throughout sub-Saharan Africa and local differences in both the direction and rate of change in HIV prevalence between 2000 and 2017, highlighting the degree to which important local differences are masked when examining trends at the country level. These fine-scale estimates of HIV prevalence across space and time provide an important tool for precisely targeting the interventions that are necessary to bringing HIV infections under control in sub-Saharan Africa.

Adolescence and the next generation.

Adolescent growth and social development shape the early development of offspring from preconception through to the post-partum period through distinct processes in males and females. At a time of great change in the forces shaping adolescence, including the timing of parenthood, investments in today's adolescents, the largest cohort in human history, will yield great dividends for future generations.

Publisher Correction: Adolescence and the next generation.

In Fig. 4a of this Analysis, owing to an error during the production process, the year in the header of the right column was '2016' rather than '2010'. In addition, in the HTML version of the Analysis, Table 1 was formatted incorrectly. These errors have been corrected online.

Mapping local variation in educational attainment across Africa.

Educational attainment for women of reproductive age is linked to reduced child and maternal mortality, lower fertility and improved reproductive health. Comparable analyses of attainment exist only at the national level, potentially obscuring patterns in subnational inequality. Evidence suggests that wide disparities between urban and rural populations exist, raising questions about where the majority of progress towards the education targets of the Sustainable Development Goals is occurring in African countries. Here we explore within-country inequalities by predicting years of schooling across five by five kilometre grids, generating estimates of average educational attainment by age and sex at subnational levels. Despite marked progress in attainment from 2000 to 2015 across Africa, substantial differences persist between locations and sexes. These differences have widened in many countries, particularly across the Sahel. These high-resolution, comparable estimates improve the ability of decision-makers to plan the precisely targeted interventions that will be necessary to deliver progress during the era of the Sustainable Development Goals.

Mapping child growth failure in Africa between 2000 and 2015.

Insufficient growth during childhood is associated with poor health outcomes and an increased risk of death. Between 2000 and 2015, nearly all African countries demonstrated improvements for children under 5 years old for stunting, wasting, and underweight, the core components of child growth failure. Here we show that striking subnational heterogeneity in levels and trends of child growth remains. If current rates of progress are sustained, many areas of Africa will meet the World Health Organization Global Targets 2025 to improve maternal, infant and young child nutrition, but high levels of growth failure will persist across the Sahel. At these rates, much, if not all of the continent will fail to meet the Sustainable Development Goal target-to end malnutrition by 2030. Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress.

Measuring contraceptive method mix, prevalence, and demand satisfied by age and marital status in 204 countries and territories, 1970-2019: a systematic analysis for the Global Burden of Disease Study 2019.

BACKGROUND: Meeting the contraceptive needs of women of reproductive age is beneficial for the health of women and children, and the economic and social empowerment of women. Higher rates of contraceptive coverage have been linked to the availability of a more diverse range of contraceptive methods. We present estimates of the contraceptive prevalence rate (CPR), modern contraceptive prevalence rate (mCPR), demand satisfied, and the method of contraception used for both partnered and unpartnered women for 5-year age groups in 204 countries and territories between 1970 and 2019. METHODS: We used 1162 population-based surveys capturing contraceptive use among women between 1970 and 2019, in which women of reproductive age (15-49 years) self-reported their, or their partner's, current use of contraception for family planning purposes. Spatiotemporal Gaussian process regression was used to generate estimates of the CPR, mCPR, demand satisfied, and method mix by age and marital status. We assessed how age-specific mCPR and demand satisfied changed with the Socio-demographic Index (SDI), a measure of social and economic development, using the meta-regression Bayesian, regularised, trimmed method from the Global Burden of Diseases, Injuries, and Risk Factors Study. FINDINGS: In 2019, 162·9 million (95% uncertainty interval [UI] 155·6-170·2) women had unmet need for contraception, of whom 29·3% (27·9-30·6) resided in sub-Saharan Africa and 27·2% (24·4-30·3) resided in south Asia. Women aged 15-19 years (64·8% [62·9-66·7]) and 20-24 years (71·9% [68·9-74·2]) had the lowest rates of demand satisfied, with 43·2 million (95% UI 39·3-48·0) women aged 15-24 years with unmet need in 2019. The mCPR and demand satisfied among women aged 15-19 years were substantially lower than among women aged 20-49 years at SDI values below 60 (on a 0-100 scale), but began to equalise as SDI increased above 60. Between 1970 and 2019, the global mCPR increased by 20·1 percentage points (95% UI 18·7-21·6). During this time, traditional methods declined as a proportion of all contraceptive methods, whereas the use of implants, injections, female sterilisation, and condoms increased. Method mix differs substantially depending on age and geography, with the share of female sterilisation increasing with age and comprising more than 50% of methods in use in south Asia. In 28 countries, one method was used by more than 50% of users in 2019. INTERPRETATION: The dominance of one contraceptive method in some locations raises the question of whether family planning policies should aim to expand method mix or invest in making existing methods more accessible. Lower rates of demand satisfied among women aged 15-24 years are also concerning because unintended pregnancies before age 25 years can forestall or eliminate education and employment opportunities that lead to social and economic empowerment. Policy makers should strive to tailor family planning programmes to the preferences of the groups with the most need, while maintaining the programmes used by existing users. FUNDING: Bill & Melinda Gates Foundation.

Quantifying the effects of the COVID-19 pandemic on gender equality on health, social, and economic indicators: a comprehensive review of data from March, 2020, to September, 2021.

BACKGROUND: Gender is emerging as a significant factor in the social, economic, and health effects of COVID-19. However, most existing studies have focused on its direct impact on health. Here, we aimed to explore the indirect effects of COVID-19 on gender disparities globally. METHODS: We reviewed publicly available datasets with information on indicators related to vaccine hesitancy and uptake, health care services, economic and work-related concerns, education, and safety at home and in the community. We used mixed effects regression, Gaussian process regression, and bootstrapping to synthesise all data sources. We accounted for uncertainty in the underlying data and modelling process. We then used mixed effects logistic regression to explore gender gaps globally and by region. FINDINGS: Between March, 2020, and September, 2021, women were more likely to report employment loss (26·0% [95% uncertainty interval 23·8-28·8, by September, 2021) than men (20·4% [18·2-22·9], by September, 2021), as well as forgoing work to care for others (ratio of women to men: 1·8 by March, 2020, and 2·4 by September, 2021). Women and girls were 1·21 times (1·20-1·21) more likely than men and boys to report dropping out of school for reasons other than school closures. Women were also 1·23 (1·22-1·23) times more likely than men to report that gender-based violence had increased during the pandemic. By September 2021, women and men did not differ significantly in vaccine hesitancy or uptake. INTERPRETATION: The most significant gender gaps identified in our study show intensified levels of pre-existing widespread inequalities between women and men during the COVID-19 pandemic. Political and social leaders should prioritise policies that enable and encourage women to participate in the labour force and continue their education, thereby equipping and enabling them with greater ability to overcome the barriers they face. FUNDING: The Bill & Melinda Gates Foundation.

Disease-specific health spending by age, sex, and type of care in Norway: a national health registry study.

BACKGROUND: Norway is a high-income nation with universal tax-financed health care and among the highest per person health spending in the world. This study estimates Norwegian health expenditures by health condition, age, and sex, and compares it with disability-adjusted life-years (DALYs). METHODS: Government budgets, reimbursement databases, patient registries, and prescription databases were combined to estimate spending for 144 health conditions, 38 age and sex groups, and eight types of care (GPs; physiotherapists & chiropractors; specialized outpatient; day patient; inpatient; prescription drugs; home-based care; and nursing homes) totaling 174,157,766 encounters. Diagnoses were in accordance with the Global Burden of Disease study (GBD). The spending estimates were adjusted, by redistributing excess spending associated with each comorbidity. Disease-specific DALYs were gathered from GBD 2019. RESULTS: The top five aggregate causes of Norwegian health spending in 2019 were mental and substance use disorders (20.7%), neurological disorders (15.4%), cardiovascular diseases (10.1%), diabetes, kidney, and urinary diseases (9.0%), and neoplasms (7.2%). Spending increased sharply with age. Among 144 health conditions, dementias had the highest health spending, with 10.2% of total spending, and 78% of this spending was incurred at nursing homes. The second largest was falls estimated at 4.6% of total spending. Spending in those aged 15-49 was dominated by mental and substance use disorders, with 46.0% of total spending. Accounting for longevity, spending per female was greater than spending per male, particularly for musculoskeletal disorders, dementias, and falls. Spending correlated well with DALYs (Correlation r = 0.77, 95% CI 0.67-0.87), and the correlation of spending with non-fatal disease burden (r = 0.83, 0.76-0.90) was more pronounced than with mortality (r = 0.58, 0.43-0.72). CONCLUSIONS: Health spending was high for long-term disabilities in older age groups. Research and development into more effective interventions for the disabling high-cost diseases is urgently needed.

Drug-use disorders in the Eastern Mediterranean Region: a glance at GBD 2019 findings.

PURPOSE: The aim of this study is to investigate drug use disorders which are a major cause of Disability Adjusted Life Years (DALYs) in the Eastern Mediterranean Region (EMR). METHODS: This article is a part of the global burden of diseases (GBD), injuries, and risk factors 2019 study. The GBD modeling approach was used to estimate population-level prevalence of drug use disorders. We combined these estimates with disability weights to calculate years of life lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 1990-2019. RESULTS: It is estimated that in 2019 in EMR around 3.4 million people have drug use disorder which has increased by 137% compared to 1990. Also, in 2019, DALY number for drug use disorders was 1217.9 (95% UI: 940.4, 1528.9) thousand years and 7645 (95% UI: 6793.7, 8567.9) deaths occurred. The DALY rate increased 39.6% in the region since1990, whereas the global rate increased by 24.4%. United Arab Emirates, Libya, and Iran were most affected by drug use disorders with the highest rates of age-standardized DALY in EMR in 2019. The most prevalent drug use disorder in the region is opioid use which is accountable for 80% of all drug use disorders DALYs. CONCLUSION: Despite many interventions, drug use disorders are still responsible for high rates of DALY in the region which has increased since 1990 in both males and females; more comprehensive policies, better control measures and proper education could reduce the adverse effects.

Life Expectancy for White, Black, and Hispanic Race/Ethnicity in U.S. States: Trends and Disparities, 1990 to 2019.

BACKGROUND: Life expectancy (LE) differences within and between states by race/ethnicity have not been examined. OBJECTIVE: To estimate LE for selected race/ethnicity groups in states from 1990 to 2019. DESIGN: Cross-sectional time-series analysis. SETTING: United States. PARTICIPANTS: Deidentified death records and Census data were used to construct regression models with smoothed time series of mortality from 1990 to 2019. MEASUREMENTS: LE at birth, by sex and year, for subgroups of people reporting Hispanic, non-Hispanic Black, or non-Hispanic White race/ethnicity. RESULTS: Disparities in LE across states were 8.0 years for females and 12.2 years for males in 1990 and 7.9 years for females and 7.8 years for males in 2019. When race/ethnicity groups were accounted for, disparities across states were 20.7 years for females and 24.5 years for males in 1990, decreasing to 18.5 years for females and 23.7 years for males in 2019. Disparities across states increased within each race/ethnicity group between 1990 and 2019, with the largest increase for non-Hispanic White males and the smallest for Hispanic females. The disparity between race/ethnicity groups within states decreased for most of the 23 states with estimates for all 3 groups but increased for females in 7 states and males in 5 states. LIMITATION: Because of small sample size, LE was not estimated for 37 of 153 state-race/ethnicity groups. CONCLUSION: Disparity in LE across states was greater when race/ethnicity groups were considered. Disparities across all state-race/ethnicity groups in general have decreased over the past 3 decades. Within each race/ethnicity group, disparities across states have increased. Although racial/ethnic disparities decreased in most of the 23 states for which LE was estimated for all 3 groups, they increased for females in 7 states and males in 5 states. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute.

Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.

BACKGROUND: Associations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done. Therefore, we aimed to estimate the global and regional burden due to non-optimal temperature exposure. METHODS: In part 1 of this study, we linked deaths to daily temperature estimates from the ERA5 reanalysis dataset. We modelled the cause-specific relative risks for 176 individual causes of death along daily temperature and 23 mean temperature zones using a two-dimensional spline within a Bayesian meta-regression framework. We then calculated the cause-specific and total temperature-attributable burden for the countries for which daily mortality data were available. In part 2, we applied cause-specific relative risks from part 1 to all locations globally. We combined exposure-response curves with daily gridded temperature and calculated the cause-specific burden based on the underlying burden of disease from the Global Burden of Diseases, Injuries, and Risk Factors Study, for the years 1990-2019. Uncertainty from all components of the modelling chain, including risks, temperature exposure, and theoretical minimum risk exposure levels, defined as the temperature of minimum mortality across all included causes, was propagated using posterior simulation of 1000 draws. FINDINGS: We included 64·9 million individual International Classification of Diseases-coded deaths from nine different countries, occurring between Jan 1, 1980, and Dec 31, 2016. 17 causes of death met the inclusion criteria. Ischaemic heart disease, stroke, cardiomyopathy and myocarditis, hypertensive heart disease, diabetes, chronic kidney disease, lower respiratory infection, and chronic obstructive pulmonary disease showed J-shaped relationships with daily temperature, whereas the risk of external causes (eg, homicide, suicide, drowning, and related to disasters, mechanical, transport, and other unintentional injuries) increased monotonically with temperature. The theoretical minimum risk exposure levels varied by location and year as a function of the underlying cause of death composition. Estimates for non-optimal temperature ranged from 7·98 deaths (95% uncertainty interval 7·10-8·85) per 100 000 and a population attributable fraction (PAF) of 1·2% (1·1-1·4) in Brazil to 35·1 deaths (29·9-40·3) per 100 000 and a PAF of 4·7% (4·3-5·1) in China. In 2019, the average cold-attributable mortality exceeded heat-attributable mortality in all countries for which data were available. Cold effects were most pronounced in China with PAFs of 4·3% (3·9-4·7) and attributable rates of 32·0 deaths (27·2-36·8) per 100 000 and in New Zealand with 3·4% (2·9-3·9) and 26·4 deaths (22·1-30·2). Heat effects were most pronounced in China with PAFs of 0·4% (0·3-0·6) and attributable rates of 3·25 deaths (2·39-4·24) per 100 000 and in Brazil with 0·4% (0·3-0·5) and 2·71 deaths (2·15-3·37). When applying our framework to all countries globally, we estimated that 1·69 million (1·52-1·83) deaths were attributable to non-optimal temperature globally in 2019. The highest heat-attributable burdens were observed in south and southeast Asia, sub-Saharan Africa, and North Africa and the Middle East, and the highest cold-attributable burdens in eastern and central Europe, and central Asia. INTERPRETATION: Acute heat and cold exposure can increase or decrease the risk of mortality for a diverse set of causes of death. Although in most regions cold effects dominate, locations with high prevailing temperatures can exhibit substantial heat effects far exceeding cold-attributable burden. Particularly, a high burden of external causes of death contributed to strong heat impacts, but cardiorespiratory diseases and metabolic diseases could also be substantial contributors. Changes in both exposures and the composition of causes of death drove changes in risk over time. Steady increases in exposure to the risk of high temperature are of increasing concern for health. FUNDING: Bill & Melinda Gates Foundation.

BSAC Vanguard Series: Tracking the global rise of antimicrobial resistance.

One of the major challenges for tackling antimicrobial resistance (AMR) is understanding the true burden of resistance and its impact on human health, particularly in locations where surveillance is minimal and data are sparse. The Global Research on AntiMicrobial resistance (GRAM) Project was launched to address these gaps. The scale of the challenge was considerable, but after 4 years of developing a stringent methodological approach and collecting/analysing data from many different sources, the capstone GRAM paper was published in January 2022. This article discusses the key findings and reviews the challenges in scaling-up AMR surveillance systems in a One Health framework. The GRAM Project represents a critical first-step in obtaining the accurate data that are needed to correctly target actions to control AMR.

Trends and patterns of disparities in diabetes and chronic kidney disease mortality among US counties, 1980-2014.

INTRODUCTION: Diabetes and chronic kidney diseases are associated with a large health burden in the USA and globally. OBJECTIVE: To estimate age-standardized mortality rates by county from diabetes mellitus and chronic kidney disease. DESIGN AND SETTING: Validated small area estimation models were applied to de-identified death records from the National Center for Health Statistics (NCHS) and population counts from the census bureau, NCHS, and the Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 from diabetes mellitus and chronic kidney disease (CKD). EXPOSURES: County of residence. MAIN OUTCOMES AND MEASURES: Age-standardized mortality rates by county, year, sex, and cause. RESULTS: Between 1980 and 2014, 2,067,805 deaths due to diabetes were recorded in the USA. The mortality rate due to diabetes increased by 33.6% (95% UI: 26.5%-41.3%) between 1980 and 2000 and then declined by 26.4% (95% UI: 22.8%-30.0%) between 2000 and 2014. Counties with very high mortality rates were found along the southern half of the Mississippi river and in parts of South and North Dakota, while very low rates were observed in central Colorado, and select counties in the Midwest, California, and southern Florida. A total of 1,659,045 deaths due to CKD were recorded between 1980 and 2014 (477,332 due to diabetes mellitus, 1,056,150 due to hypertension, 122,795 due to glomerulonephritis, and 2,768 due to other causes). CKD mortality varied among counties with very low mortality rates observed in central Colorado as well as some counties in southern Florida, California, and Great Plains states. High mortality rates from CKD were observed in counties throughout much of the Deep South, and a cluster of counties with particularly high rates was observed around the Mississippi river. CONCLUSIONS AND RELEVANCE: This study found large inequalities in diabetes and CKD mortality among US counties. The findings provide insights into the root causes of this variation and call for improvements in risk factors, access to medical care, and quality of medical care.

The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India.

BACKGROUND: Tuberculosis (TB) is a major cause of death globally. India carries the highest share of the global TB burden. The COVID-19 pandemic has severely impacted diagnosis of TB in India, yet there is limited data on how TB case reporting has changed since the pandemic began and which factors determine differences in case notification. METHODS: We utilized publicly available data on TB case reporting through the Indian Central TB Division from January 2017 through April of 2021 (prior to the first COVID-19 related lockdown). Using a Poisson model, we estimated seasonal and yearly patterns in TB case notification in India from January 2017 through February 2020 and extended this estimate as the counterfactual expected TB cases notified from March 2020 through April 2021. We characterized the differences in case notification observed and those expected in the absence of the pandemic by State and Territory. We then performed a linear regression to examine the relationship between the logit ratio of reported TB to counterfactual cases and mask use, mobility, daily hospitalizations/100,000 population, and public/total TB case reporting. RESULTS: We found 1,320,203 expected cases of TB (95% uncertainty interval (UI) 1,309,612 to 1,330,693) were not reported during the period from March 2020 through April 2021. This represents a 63.3% difference (95% UI 62.8 to 63.8) in reporting. We found that mobility data and average hospital admissions per month per population were correlated with differences in TB case notification, compared to the counterfactual in the absence of the pandemic (p > 0.001). CONCLUSION: There was a large difference between reported TB cases in India and those expected in the absence of the pandemic. This information can help inform the Indian TB program as they consider interventions to accelerate case finding and notification once the pandemic related TB service disruptions improve. Mobility data and hospital admissions are surrogate measures that correlate with a greater difference in reported/expected TB cases and may correlate with a disruption in TB diagnostic services. However, further research is needed to clarify this association and identify other key contributors to gaps in TB case notifications in India.

Progress towards the 2020 milestones of the end TB strategy in Cambodia: estimates of age and sex specific TB incidence and mortality from the Global Burden of Disease Study 2019.

BACKGROUND: Cambodia was recently removed from the World Health Organization's (WHO's) top 30 high tuberculosis (TB) burden countries. However, Cambodia's TB burden remains substantial, and the country is on the WHO's new global TB watchlist. We aimed to examine the levels and trends in the fatal and non-fatal TB burden in Cambodia from 1990 to 2019, assessing progress towards the WHO End TB interim milestones, which aim to reduce TB incidence rate by 20% and TB deaths by 35% from 2015 to 2020. METHODS: We leveraged the Global Burden of Disease 2019 (GBD 2019) analytical framework to compute age- and sex-specific TB mortality and incidence by HIV status in Cambodia. We enumerated TB mortality utilizing a Bayesian hierarchical Cause of Death Ensemble modeling platform. We analyzed all available data sources, including prevalence surveys, population-based tuberculin surveys, and TB cause-specific mortality, to produce internally consistent estimates of incidence and mortality using a compartmental meta-regression tool (DisMod-MR 2.1). We further estimated the fraction of tuberculosis mortality among individuals without HIV coinfection attributable to the independent effects of alcohol use, smoking, and diabetes. RESULTS: In 2019, there were 6500 (95% uncertainty interval 4830-8680) deaths due to all-form TB and 50.0 (43.8-57.8) thousand all-form TB incident cases in Cambodia. The corresponding age-standardized rates were 53.3 (39.9-69.4) per 100,000 population for mortality and 330.5 (289.0-378.6) per 100,000 population for incidence. From 2015 to 2019, the number of all-form TB deaths decreased by 11.8% (2.3-21.1), while the age-standardized all-form TB incidence rate decreased by 11.1% (6.3-15.6). Among individuals without HIV coinfection in 2019, alcohol use accounted for 28.1% (18.2-37.9) of TB deaths, smoking accounted for 27.0% (20.2-33.3), and diabetes accounted for 12.5% (7.1-19.0). Removing the combined effects of these risk factors would reduce all-form TB deaths by 54.2% (44.2-62.2). DISCUSSION: Despite significant progress in reducing TB morbidity and mortality since 1990, Cambodia is not on track to achieve the 2020 WHO End TB interim milestones. Existing programs in Cambodia can benefit from liaising with risk factor control initiatives to accelerate progress toward eliminating TB in Cambodia.

Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study.

BACKGROUND: Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts. METHODS: We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions. FINDINGS: The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33-2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84-10·9) people and decline to 8·79 billion (6·83-11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion [0·72-1·71], Nigeria (791 million [594-1056]), China (732 million [456-1499]), the USA (336 million [248-456]), and Pakistan (248 million [151-427]). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91-2·87) individuals older than 65 years and 1·70 billion (1·11-2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (-6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82-8·73) in 2100 and a population of 6·88 billion (5·27-9·51) when assuming 99th percentile rates of change in these drivers. INTERPRETATION: Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come. FUNDING: Bill & Melinda Gates Foundation.

Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study.

BACKGROUND: Sepsis is life-threatening organ dysfunction due to a dysregulated host response to infection. It is considered a major cause of health loss, but data for the global burden of sepsis are limited. As a syndrome caused by underlying infection, sepsis is not part of standard Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) estimates. Accurate estimates are important to inform and monitor health policy interventions, allocation of resources, and clinical treatment initiatives. We estimated the global, regional, and national incidence of sepsis and mortality from this disorder using data from GBD 2017. METHODS: We used multiple cause-of-death data from 109 million individual death records to calculate mortality related to sepsis among each of the 282 underlying causes of death in GBD 2017. The percentage of sepsis-related deaths by underlying GBD cause in each location worldwide was modelled using mixed-effects linear regression. Sepsis-related mortality for each age group, sex, location, GBD cause, and year (1990-2017) was estimated by applying modelled cause-specific fractions to GBD 2017 cause-of-death estimates. We used data for 8·7 million individual hospital records to calculate in-hospital sepsis-associated case-fatality, stratified by underlying GBD cause. In-hospital sepsis-associated case-fatality was modelled for each location using linear regression, and sepsis incidence was estimated by applying modelled case-fatality to sepsis-related mortality estimates. FINDINGS: In 2017, an estimated 48·9 million (95% uncertainty interval [UI] 38·9-62·9) incident cases of sepsis were recorded worldwide and 11·0 million (10·1-12·0) sepsis-related deaths were reported, representing 19·7% (18·2-21·4) of all global deaths. Age-standardised sepsis incidence fell by 37·0% (95% UI 11·8-54·5) and mortality decreased by 52·8% (47·7-57·5) from 1990 to 2017. Sepsis incidence and mortality varied substantially across regions, with the highest burden in sub-Saharan Africa, Oceania, south Asia, east Asia, and southeast Asia. INTERPRETATION: Despite declining age-standardised incidence and mortality, sepsis remains a major cause of health loss worldwide and has an especially high health-related burden in sub-Saharan Africa. FUNDING: The Bill & Melinda Gates Foundation, the National Institutes of Health, the University of Pittsburgh, the British Columbia Children's Hospital Foundation, the Wellcome Trust, and the Fleming Fund.

Variation in Childhood Diarrheal Morbidity and Mortality in Africa, 2000-2015.

BACKGROUND: Diarrheal diseases are the third leading cause of disease and death in children younger than 5 years of age in Africa and were responsible for an estimated 30 million cases of severe diarrhea (95% credible interval, 27 million to 33 million) and 330,000 deaths (95% credible interval, 270,000 to 380,000) in 2015. The development of targeted approaches to address this burden has been hampered by a paucity of comprehensive, fine-scale estimates of diarrhea-related disease and death among and within countries. METHODS: We produced annual estimates of the prevalence and incidence of diarrhea and diarrhea-related mortality with high geographic detail (5 km2) across Africa from 2000 through 2015. Estimates were created with the use of Bayesian geostatistical techniques and were calibrated to the results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. RESULTS: The results revealed geographic inequality with regard to diarrhea risk in Africa. Of the estimated 330,000 childhood deaths that were attributable to diarrhea in 2015, more than 50% occurred in 55 of the 782 first-level administrative subdivisions (e.g., states). In 2015, mortality rates among first-level administrative subdivisions in Nigeria differed by up to a factor of 6. The case fatality rates were highly varied at the national level across Africa, with the highest values observed in Benin, Lesotho, Mali, Nigeria, and Sierra Leone. CONCLUSIONS: Our findings showed concentrated areas of diarrheal disease and diarrhea-related death in countries that had a consistently high burden as well as in countries that had considerable national-level reductions in diarrhea burden. (Funded by the Bill and Melinda Gates Foundation.).

Public health utility of cause of death data: applying empirical algorithms to improve data quality.

BACKGROUND: Accurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments. METHODS: We describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings. RESULTS: The proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD. CONCLUSIONS: We provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.

US Health Care Spending by Race and Ethnicity, 2002-2016.

Importance: Measuring health care spending by race and ethnicity is important for understanding patterns in utilization and treatment. Objective: To estimate, identify, and account for differences in health care spending by race and ethnicity from 2002 through 2016 in the US. Design, Setting, and Participants: This exploratory study included data from 7.3 million health system visits, admissions, or prescriptions captured in the Medical Expenditure Panel Survey (2002-2016) and the Medicare Current Beneficiary Survey (2002-2012), which were combined with the insured population and notified case estimates from the National Health Interview Survey (2002; 2016) and health care spending estimates from the Disease Expenditure project (1996-2016). Exposure: Six mutually exclusive self-reported race and ethnicity groups. Main Outcomes and Measures: Total and age-standardized health care spending per person by race and ethnicity for each year from 2002 through 2016 by type of care. Health care spending per notified case by race and ethnicity for key diseases in 2016. Differences in health care spending across race and ethnicity groups were decomposed into differences in utilization rate vs differences in price and intensity of care. Results: In 2016, an estimated $2.4 trillion (95% uncertainty interval [UI], $2.4 trillion-$2.4 trillion) was spent on health care across the 6 types of care included in this study. The estimated age-standardized total health care spending per person in 2016 was $7649 (95% UI, $6129-$8814) for American Indian and Alaska Native (non-Hispanic) individuals; $4692 (95% UI, $4068-$5202) for Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals; $7361 (95% UI, $6917-$7797) for Black (non-Hispanic) individuals; $6025 (95% UI, $5703-$6373) for Hispanic individuals; $9276 (95% UI, $8066-$10 601) for individuals categorized as multiple races (non-Hispanic); and $8141 (95% UI, $8038-$8258) for White (non-Hispanic) individuals, who accounted for an estimated 72% (95% UI, 71%-73%) of health care spending. After adjusting for population size and age, White individuals received an estimated 15% (95% UI, 13%-17%; P < .001) more spending on ambulatory care than the all-population mean. Black (non-Hispanic) individuals received an estimated 26% (95% UI, 19%-32%; P < .001) less spending than the all-population mean on ambulatory care but received 19% (95% UI, 3%-32%; P = .02) more on inpatient and 12% (95% UI, 4%-24%; P = .04) more on emergency department care. Hispanic individuals received an estimated 33% (95% UI, 26%-37%; P < .001) less spending per person on ambulatory care than the all-population mean. Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals received less spending than the all-population mean on all types of care except dental (all P < .001), while American Indian and Alaska Native (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 90% more; 95% UI, 11%-165%; P = .04), and multiple-race (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 40% more; 95% UI, 19%-63%; P = .006). All 18 of the statistically significant race and ethnicity spending differences by type of care corresponded with differences in utilization. These differences persisted when controlling for underlying disease burden. Conclusions and Relevance: In the US from 2002 through 2016, health care spending varied by race and ethnicity across different types of care even after adjusting for age and health conditions. Further research is needed to determine current health care spending by race and ethnicity, including spending related to the COVID-19 pandemic.