key: cord-0919549-o4ruio2m authors: nan title: Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019 date: 2021-09-04 journal: Lancet DOI: 10.1016/s0140-6736(21)01207-1 sha: 255ad428531d0e405eee294f7a64afe625f53f9b doc_id: 919549 cord_uid: o4ruio2m BACKGROUND: Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. METHODS: We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (U5MR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. FINDINGS: Global U5MR decreased from 71·2 deaths per 1000 livebirths (95% uncertainty interval [UI] 68·3–74·0) in 2000 to 37·1 (33·2–41·7) in 2019 while global NMR correspondingly declined more slowly from 28·0 deaths per 1000 live births (26·8–29·5) in 2000 to 17·9 (16·3–19·8) in 2019. In 2019, 136 (67%) of 204 countries had a U5MR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030, 154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9·65 million (95% UI 9·05–10·30) in 2000 and 5·05 million (4·27–6·02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3·76 million [95% UI 3·53–4·02]) in 2000 to 48% (2·42 million; 2·06–2·86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0·80 (95% UI 0·71–0·86) deaths per 1000 livebirths and U5MR to 1·44 (95% UI 1·27–1·58) deaths per 1000 livebirths, and in 2019, there were as many as 1·87 million (95% UI 1·35–2·58; 37% [95% UI 32–43]) of 5·05 million more deaths of children younger than 5 years than the survival potential frontier. INTERPRETATION: Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve U5MR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. FUNDING: Bill & Melinda Gates Foundation. Under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) are important indicators reflecting multiple aspects of societal wellbeing such as access to nutrition and food; basic infrastructure such as housing, water, and sanitation; education; agency; financial security; access to preventive and treatment health services; and future human capital. The UN Millennium Development Goals (MDGs) are credited with mobilising global action on child health, and manifested as an unprecedented, accelerated reduction in child mortality and resulted in 58 countries achieving the MDG 4 target of reducing U5MR by two-thirds. 1,2 Sustainable Development Goal (SDG) 3.2 specifically calls to, "By 2030, end preventable deaths of newborn babies and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1000 live births and under-5 mortality to at least as low as 25 per 1000 live births." 3 The SDG focus on equity was codified here in a shifting from relative global targets, that were mainstays in the MDG agenda, to absolute targets for each country. The SDG framework aims to build on the successes of the MDG era, albeit with a notably broader lens in which health (SDG 3) is one of several goals related to healthier lives, wellbeing, and equity. 3 Even within SDG 3, the SDG agenda is broader than the MDG agenda, reflecting a growing understanding of the intersectional nature of health outcomes with basic infrastructural considerations such as health system performance, sustainability, and environment. This intersectional perspective is illustrated in the language of initiatives such as the call from the UN Global Strategy for Women's, Children's and Adolescents' Health 2016-2030 to integrate survival, prevention, thriving, and enabling environ ments, 4 the Every Newborn Action Plan, the World Bank's Global Financing Facility for Women, Children and Adolescents, The Lancet Global Health Commission on High Quality Health Systems, and the Countdown to 2030. [5] [6] [7] Although this broader focus has not necessarily led to child and neonatal health receiving less investment in development assistance for health (DAH; which, for child and neonatal health, grew by 2·66% from 2015 to 2019 and remained the second largest DAH focus area in 2019), the growth in investment in this period was less than during the period between 2000 and 2015, when DAH for child and neonatal health increased by 314%. 8 Evidence before this study During the Millennium Development Goal (MDG) era , numerous organisations comprehensively described global progress in reducing child and neonatal mortality (MDG 4) , but the early Sustainable Development Goal (SDG) period has seen few comparable efforts to track progress and none to date have attempted to quantify the preventable portion of child mortality (SDG 3.2) . Past preventable mortality analyses have focused on health-care delivery, or were limited to high-income countries and adult populations. The most recent child mortality report from the UN Inter-agency Group for Child Mortality Estimation (UNIGME), published in 2017 for the year 2015, reports on all-cause mortality only. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is the only annual assessment of trends in all-cause mortality and causespecific mortality by detailed age groups for all locations with a population greater than 50 000 people from 1990 to the present that is compliant with the Guidelines for Accurate and Transparent Health Estimates Reporting. This analysis presents levels and trends in all-cause and causespecific neonatal and under-5 mortality from 2000 to 2019. Multiple future health scenarios for child mortality in 2030 were constructed to represent potential trajectories, including the potential impacts of the COVID-19 pandemic and scenarios with targeted improvements in neonatal survival. Additionally, this study presents for the first time all-cause mortality estimates for granular age groups of 0-6 days, 7-27 days, 1-5 months, 6-11 months, 12-23 months, and 2-4 years. SDG 3.2 explicitly prioritises ending preventable child deaths. Therefore, based on all-cause and cause-specific mortality estimates from GBD 2019, this study introduces a novel, reproducible, and holistic heuristic for quantifying optimal child survival. Within this framework are two complementary causespecific benchmarks: a global optimum, based on the lowest observed neonatal and under-5 mortality, and a survival potential frontier, based on stochastic frontier analysis of observed mortality and the Healthcare Access and Quality Index. The latter allows for comparing performance between similar countries, and specifically helps those countries with high mortality to establish intermediate goals. There has not yet been a comprehensive assessment of NMR and U5MR in the SDG era. Selected publications assessed interim progress towards part of SDG 3.2 or provided projections to 2030, [9] [10] [11] [12] [13] but none have been comprehensive with respect to cause, age, trends, geo graphy, and progress towards 2030 targets. The comprehensive nature of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 lends itself to a detailed analysis of levels, trends, and drivers of change for specific age groups, causes, and locations. Additionally, there has not been any previous effort, to our knowledge, to empirically explore the concept of preventable mortality in children. Although preventable death has been theoretically defined since the early 2000s, the definitions has usually been through a healthcare delivery lens 14, 15 rather than a more holistic lens of preventability that might be interpreted as the intended wording of SDG 3.2. Furthermore, although the Organisation for Economic Co-operation and Develop ment (OECD) and Eurostat convened to provide a more uniform approach to interpreting avoidable deaths in 2019, this was with a singular focus on highincome countries and the adult population. 16 In this study, based on GBD 2019, we have three objectives. First, we aim to present a detailed, comprehensive numerical assessment of progress towards SDG 3.2 targets for all-cause NMR and U5MR at the global, regional, and national level, including a series of scenarios that reflect possible trends over the next decade including the potential effects of the COVID-19 pandemic on young children. Second, we aim to evaluate comparative progress in cause-specific mortality in neonates and children from 2000 to 2019 to highlight successes and potential focus areas for improvement. Third, we aim to better define a holistic focus of preventable mortality by exploring two different measures of optimal child survival that can both inform global progress and provide a benchmark for intermediate progress evaluation in high-mortality settings. In so doing, this study seeks to meet the needs of an expansive, integrative SDG agenda, and to highlight the locations, age groups, and causes of preventable deaths, to inform policy and public health priorities aiming to achieve SDG 3.2. This manuscript was produced as part of the GBD Collaborator Network and in accordance with the GBD Protocol. This study is compliant with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER; 17 appendix p 9). A brief summary of each component of our study is described below. Extensive methodological details are provided in the appendix (pp . GBD 2019 includes all-cause and cause-specific mortality by age and sex for 204 countries and territories, 21 of which were estimated at the subnational level from 1990 to 2019, inclusive. Results in this study are presented only for countries and territories. All-cause mortality estimation covers six under-5 age groups: 0-6 days (early neonatal), 7-27 days (late neonatal), 1-5 months, 6-11 months, 12-23 months, and 2-4 years. Causespecific mortality estimates cover four age groups: early neonatal, late neonatal, 28-364 days, and 1-4 years. Although we present all six age groups, we mainly focus on results for the aggregate neonatal age group (<28 days) and the under-5 age group (0-4 years), to best align with the SDG under-5 and neonatal targets. Similarly, we focus on the years 2000, which marks the establishment of the MDGs, 2015, which marks the establishment of the SDGs, and 2019, which is the most recent year of GBD estimates. All-cause mortality data were compiled from 203 of 204 countries and territories ranging from the years 2000 to 2019, for a total of 3097 location-years. Vital registration covered a total of 14 889 022 global under-5 deaths in this period (appendix p 119). A total of 8000 unique sources were used in estimating cause-specific mortality in GBD 2019. All input data sources for each component of analysis are available for download from the GBD 2019 Data Input Sources Tool. All-cause mortality estimation closely followed the estimation techniques as described for previous iterations of GBD, 2, 18, 19 detailed in the appendix (p 9). Progress towards SDG 3.2 was assessed by examining U5MR and NMR in 2019. NMR is calculated as the probability of death between birth and 28 days and U5MR is calculated as the probability of death between birth and 5 years, and each metric is expressed as the number of deaths per 1000 livebirths. Aggregate mortality probabilities were benchmarked against the SDG thresholds of 25 under-5 deaths per 1000 livebirths and 12 neonatal deaths per 1000 livebirths. To assess relative progress across age groups, we compared the proportion of under-5 deaths occurring in each age group with the ratio of change in age-specific deaths to change in total under-5 deaths, for the periods 2000-14 and 2015-19. If progress towards SDG 3.2 is equal across age groups, the percentage contribution to progress and the percentage of total deaths would be equal. If the percentage of deaths is greater than the percentage of progress for an age group, then that age group is making slower progress towards the target. Comprehensive methods for cause-specific mortality estimation for GBD have been previously described 20 and are detailed in the appendix (p 35). We present most results at level 3 because this level is sufficiently detailed to reflect important cause groupings for the age groups presented in this analysis (eg, neonatal disorders and congenital birth defects), but not so detailed as to obscure important groupings of related conditions. U5MR and NMR were projected for six scenarios, all computed at the national level, up to 2030 as previously described. 21 The first three scenarios represent the reference, better-than-reference, and worse-than-reference scenarios, while a fourth represents the 2030 NMR and U5MR in the absence of COVID-19. The remaining two scenarios are intended to assess outcomes for interventions that focus only on specific age groups, to evaluate if opportunity is greater in a particular age group than in others, and to show the limits of achievement when efforts do not consider distinct needs of different age groups. For the first of these age-specific scenarios, neonatal mortality is at the better-than-reference level and remaining under-5 mortality stays at reference level (neonatal scenario), and for the second, mortality for children aged 28-364 days is at the better-than-reference level and neonatal mortality stays at the reference level (child scenario). Many strategies to address neonatal mortality are fundamentally different from strategies targeting older infants and children, so these two scenarios are a broad representation of those differences. Our approach to inform an assessment of preventable mortality focused on the quantification of two different measures of optimal child survival based on historical trends. The first measure, what we term the global optimum, represents a universal level at which all additional mortality is theoretically avoidable given current medical knowledge and technology. This is analogous to the GBD method used for estimating global standard life expectancy. The second measure, what we term the survival potential frontier, aims to quantify the amount of mortality that is avoidable given the country's level of Healthcare Access and Quality (HAQ) Index, thereby accounting for the differential resources available for health investment in different locations. First, we calculated the global optimum for NMR and U5MR based on the aggregate of the lowest observed age-specific and cause-specific mortality rates in locations with populations higher than 10 000 children younger than 5 years (to remove noise associated with small numbers) between 2000 and 2019, scaling them to match an all-cause mortality minimum that was calculated using the same approach. The scaling step was added to account for potential differences due to small numbers in low-mortality settings or geographical differences in cause assignment that can occur between, for example, subcauses of neonatal disorders. This method is analogous to that used by GBD to calculate a global standard life expectancy for the purposes of calculating years of life lost and therefore can be interpreted to represent the optimum potential for reductions in child mortality based on current technology and health delivery systems. Second, to help with developing intermediate goals and to evaluate progress in higher-mortality settings, we calculated a survival potential frontier using stochastic frontier analysis 22 to evaluate the historical relationship between cause-specific neonatal and under-5 mortality rates and HAQ Index, 23 which is an aggregate metric of health system per formance across all age groups combined. The specific formulation of the stochastic frontier analysis is described in detail in the appendix (p 70), but briefly, it uses a spline to estimate the expected lower bound of mortality for a given value of HAQ Index. Stochastic frontier analysis was chosen to quantify system inefficiency because of its flexibility in shape, its assumption of performance possibilities given static system inputs, and the fact that it allows for random effects in the model rather than assuming uniformity of inputs across locations. All components of the analysis are based on 1000 draws of the posterior distribution of the quantity of interest by age, sex, location, and year. Point estimates are the mean of the draws, and 95% uncertainty intervals (UIs) represent the 2·5th and 97·5th percentiles. Results are presented by country, GBD super-region, and Socio-demographic Index (SDI) 24 quintile. SDI is a composite index of income per capita, educational attain ment, and inverse fertility, and it is used to categorise countries into SDI quintiles: low SDI (ie, low income per capita, low educational attainment, high fertility), low-middle SDI, middle SDI, high-middle SDI, and high SDI. Full results for GBD 2019 are available in an online visualisation at GBD Compare and for download from the GBD Results Tool. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Over the past two decades, there has been a substantial decrease in global deaths of children younger than 5 years, from 9·65 million (95% UI 9·05-10·30) in 2000, The Bahamas Saint Vincent and the Grenadines 1·98 (Table continues on (table) . The countries with the highest U5MR in 2019 were Central African Republic, Mali, and Chad, whereas Andorra, Singapore, and Slovenia were found to have the lowest U5MR. As for 2019 neonatal mortality, the highest rate was observed in Pakistan, followed by Mali and Central African Republic. The countries with the lowest 2019 NMR were Andorra, Japan, and Singapore. U5MR and NMR declined in every country between 2000 and 2019, apart from Dominica, Guam, and Northern Mariana Islands (appendix p 311). We found evidence of accelerated reduction in global U5MR, but the largest number of deaths, as well as the slowest progress, occurred in the early neonatal age group ( figure 1A, B) . In all SDI quintiles, decline in NMR lagged behind mortality declines in other age groups ( figure 1C, D) . There is evidence of relative progress in neonatal mortality in the time period between 2015 and 2019, compared with between 2000 and 2015, but early neonatal progress in this more recent time period is still slower than overall under-5 progress in low SDI settings ( figure 1D ). The proportion of neonatal death broadly increases as SDI increases: in 2019, in the low SDI quintile, 1·11 million (41%) of 2·67 million deaths in children younger than 5 years were neonatal deaths, and in the high SDI quintile 26 800 (55%) of 48 600 deaths in children younger than 5 years were neonatal deaths (appendix p 120). In 2015, 128 (63%) of 204 countries already had an U5MR below the SDG 3.2 threshold of 25 deaths of children younger than 5 years per 1000 livebirths (figure 2A). By 2019, eight additional countries-Syria, Uzbekistan, Guatemala, Philippines, Guyana, Nauru, Vanuatu, and Solomon Islands-had a U5MR below this threshold, making a total of 136 (67%; table). In 2015, 126 (62%) of 204 countries had an NMR below the SDG 3.2 threshold of 12 neonatal deaths per 1000 livebirths (figure 2B). By 2019, an additional seven countries-Syria, Iraq, Kyrgyzstan, Uzbekistan, Morocco, Solomon Islands, and Vanuatu-had achieved an NMR below this threshold, making a total of 133 (65%). Under-5 mortality in each analysed year was somewhat higher in males than in females, although this difference was not statistically significant at the global level (appendix p 99). U5MR declined in both males and females in the periods between 2000 and 2015, and between 2015 and 2019 (appendix p 99). The 2019 male-to-female ratio of U5MR does not change meaningfully with SDI; this ratio ranges from 1·08 in low-middle SDI to 1·18 in high SDI in 2019 (appendix p 99). The shaded areas in panels A and B represent 95% uncertainty intervals. The black line in panels C and D represents line of equivalence, such that points above the line indicate age and SDI groups in which change outpaces overall under-5 mortality change and points below the line indicate age and SDI groups in which change underperforms relative to overall under-5 mortality change. ARC=annualised rate of change. qx=probability of death. SDI=Sociodemographic Index. The leading level 3 causes of global under-5 mortality in 2019 were neonatal disorders, which accounted for 37·3% (95% UI 35·6-38·8) of deaths in children younger than 5 years, followed by lower respiratory infections (13·3% [12·1-14·4]), diarrhoeal diseases (9·9% [8·3-11·6]), congenital birth defects (9·4% [8·0-11·8]), and malaria (7·1% [3·5-12·0]; figure 3; appendix p 100). Leading subcauses of neonatal disorders and congenital birth defects and leading global aetiologies of lower respiratory infections and diarrhoeal disease can be found in the appendix (pp 106, 121). Of the 15 level 3 causes that accounted for more than 30 000 global under-5 deaths in 2019, the greatest reduction in deaths between 2000 and 2015 was observed in measles, which saw a -9·2% (95% UI -10·4 to -8·0) mean annual percentage change (appendix p 129). Measles was followed by proteinenergy malnutrition (-6·5% [-8·2 to -4·7]) and HIV/ AIDS (-6·0% [-6·9 to -5·0]). Among these same 15 highmortality causes, and for the period 2015-19, the three with the greatest reduction in deaths were mea sles (-11·3% [95% UI -13·7 to -9·0]), HIV/AIDS (-10·2% [-12·3 to -7·8]), and tuber culosis (-7·8 [-9·9 to -5·6]). In 2019, causes of death varied by age, sex, and SDI (figure 3; appendix p 100). The most common level 3 causes of death in children younger than 5 years were neonatal disorders, lower respiratory infections, and diarrhoeal diseases in the low SDI quintile, and neonatal disorders, congenital birth defects, and sudden infant death syndrome in the high SDI quintile (appendix p 100). The level 3 causes with the largest male-to-female ratio of mortality in the under-5 age group at the global level in 2019 were vascular intestinal disorders (5·99) and inguinal, femoral, and abdominal hernia (2·90), and those with the lowest ratio were gallbladder and biliary diseases (0·29) and pancreatitis (0·29; appendix p 100). In our reference scenario, by 2030, 154 (75%) of 204 countries are projected to have a U5MR lower than the SDG threshold of 25 under-5 deaths per 1000 livebirths, and 139 (68%) are expected to have an NMR lower than the SDG threshold of 12 neonatal deaths per 1000 livebirths ( figure 2, appendix p 93 ). In the better-than-reference Values presented are cause fractions: the proportion of total age-specific deaths with a particular underlying cause of death. Causes are presented at Level 2 in the hierarchy, with other non-communicable diseases disaggregated to include congenital birth defects, sudden infant death syndrome, haemoglobinopathies and haemolytic anaemias, endocrine, metabolic, blood, and immune disorders, and urinary diseases and male infertility separately. Total under-5 mortality is split at 28 days to include neonatal (<28 days) separately from children between 28 days and 5 years of age. SDI=Socio-demographic Index. the global optimum U5MR is 1·44 (95% UI 1·27-1·58). Sex differences in mortality are similar below the global optimum as compared to overall mortality, with an NMR male-to-female ratio of 1·05 (95% UI 1·00-1·09) and a U5MR male-to-female ratio of 1·12 (95% UI 1·05-1·18). 16 causes of death have a global optimum of zero deaths and are therefore classified as 100% preventable by this framework. With the exceptions of exposure to forces of nature and conflict and terrorism, all of these preventable deaths are infectious conditions. If all countries reduced mortality to the global optimum, the leading level 3 global under-5 causes of death would be neonatal disorders; congenital birth defects; lower respiratory infections; sudden infant death syndrome; and endocrine, metabolic, blood, and immune disorders. When looking at mortality along the spectrum of HAQ Index, our analysis suggests that in 2000, as many as 1·50 million (95% UI 1·31-1·72) neonatal deaths were above the survival potential frontier, accounting for 40% (95% UI 37-43) of 3·76 million neonatal deaths. In the same year, analysis suggests that 3·94 million (95% UI 3·49-4·40) under-5 deaths were above the survival potential frontier: 41% (95% UI 39-43) of 9·65 million under-5 deaths). In 2019, the number of deaths occurring Figure 4 : 2019 NMR and U5MR by HAQ Index at the national level 204 countries were analysed, and the colour of each point indicates the SDI quintile that the country belongs to. HAQ Index ranges from 0 (worst) to 100 (best). The survival potential frontier, global optimum, and SDG targets are indicated as lines on the graph. Grey shaded bands represent 95% UIs. Countries are labelled with their ISO3 country code in bold when their ratio to the survival potential frontier is in the highest 10% of all countries and in italics when their ratio to the survival potential frontier is in the lowest 10% of all countries. ISO3 codes and corresponding location names are listed in the appendix (p 11). NMR=neonatal mortality rate. HAQ=Healthcare Access and Quality. SDG=Sustainable Development Goal. SDI=Socio-demographic Index. U5MR=under-5 mortality rate. UI=uncertainty interval. 4) . Global under-5 mortality above the survival potential frontier in 2019 consisted of 1·56 million (95% UI 1·11-2·17; 83%) deaths due to communicable, maternal, neonatal, and nutritional (CMNN) diseases, 0·23 million (0·15-0·33; 12%) deaths due to non-communicable diseases, and 0·08 million (0·06-0·11; 5%) deaths due to injuries (appendix p 130). If all regions had mortality rates at their survival potential frontier levels in 2019, the distribution of under-5 deaths would skew slightly towards non-communicable diseases but would not fundamentally change; 2·58 million (95% UI 2·35-2·81; 81%) deaths would be due to CMNN diseases, 0·46 million (0·40-0·52; 15%) deaths would be due to non-communicable diseases, and 0·13 million (0·11-0·15; 4%) deaths would be due to injuries (appendix p 130). Of the 48 level 3 causes that were accountable for more than 5000 global under-5 deaths in 2019, those with the lowest proportion of cause-specific deaths above the survival potential frontier were sudden infant death syndrome (27% [95% of SIDS deaths above the survival potential frontier), other malignant neoplasms (28% [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] ), varicella and herpes zoster (29% [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] ), and congenital birth defects (30% [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] ; appendix p 94). Of the same 48 causes, those with the highest proportion of cause-specific deaths above the survival potential frontier were invasive non-typhoidal salmonella, other neglected tropical diseases, haemoglobinopathies and haemolytic anaemias, and malaria, all with over 50% above the survival potential frontier. The leading causes of death overall were also those with the highest above-survival potential frontier mortality rates, and the rank order would remain similar even if all regions had cause-specific mortality rates at their survival potential frontier levels in 2019: 33% of each of neonatal disorders and lower respiratory infections deaths were above the survival frontier (neonatal disorders ranked first and lower respiratory infections ranked second in both observed and expected), while 40% of diarrhoea deaths were above the frontier (ranked third in observed and fourth in expected; appendix p 94). Declines of U5MR and NMR have continued to accelerate worldwide. Of 204 countries, our reference scenario suggests that, by 2030, 154 (75%) are likely to meet the U5MR SDG target and 139 (68%) the NMR SDG target. However, the concomitant findings of growing relative inequity and a large remaining proportion of preventable deaths shows there is much more work to be done. If every country were at the global optimum in 2019, global U5MR would have been 1·44 (95% UI 1·27-1·58) deaths per 1000 livebirths and NMR would have been 0·80 (95% UI 0·71-0·86) deaths per 1000 livebirths. Thankfully, although children have been found to be at risk of developing multisystem inflammatory syndrome 25 as result of COVID-19, they appear to be less at risk of severe illness and death. It is important to reiterate, however, how the complex, multisector determinants of health that substantially affect child survival could be negatively affected by COVID-19, an understanding that is likely to continue to evolve in the coming months and years. Risks include, 26 but are not limited to, the potential disruption of routine perinatal and clinical care for children, worsened in-facility outcomes due to over burdened medical systems, loss of caretakers from the pandemic impacting child health and wellbeing, suspended vaccination campaigns, financial and economic pressures leading to food insecurity and malnutrition, disruption of supply chains leading to decreased availability of highly active antiretroviral therapy medications for HIV/AIDS, interrupted prevention of mother-to-child transmission programmes, decreased malaria prevention and treatment, and disruption of domestic economies and education systems. Mitigating these risks will require even more focus and attention on an equilibrium strategy for neonatal and child health. Our analysis suggests the need for a five-pronged strategy to optimise child survival in the SDG era that augments community-based strategies and efforts to address social determinants of health (eg, education, family planning, financial security) that proved effective during the MDG era. The central theme is that, to achieve SDG targets by 2030, investments should strive for equilibrium and overall system strengthening, with a particular focus on inequality, rather than simply shifting attention to individual priorities. Neonatal deaths comprise an increasing share of global under-5 deaths, indicating a generalised need to improve neonatal programmes along the entire SDI spectrum. Although not explicitly stated in SDG targets or in our analysis, reductions in stillbirths should also be targeted through comprehensive maternal and neonatal care. Reducing early neonatal mortality, and stillbirth mortality, should start with expansion of community and facility-based strategies targeted towards pregnancy, labour, delivery, and the postnatal period. 27 Nepal is an example of a country that explicitly prioritised the neonatal period and integrated community and facilitybased approaches, leading to accelerated improvements in neonatal and under-5 mortality. 28 The first step is encouraging and supporting facility-based delivery by skilled providers with the training and resources available to perform resuscitative efforts for women and neonates when needed. 5 Basic activities include skin-toskin contact, timely breathing assistance for intrapartum asphyxia, chlorhexidine umbilical cord cleansing for sepsis prevention, and early screening for congenital birth defects. 5 Improvements also need to be made to neonatal care after delivery. Advancements are needed for in-hospital activities such as intensive care for prematurity, advanced resuscitation for intrapartum asphyxia, full support for sepsis beyond antibiotics, breastfeeding education and support, and surgical care for neonatal emergencies and birth defects that have been shown to be associated with improved neonatal survival. 27, 29, 30 Postnatal check-ups are also required for prompt diagnosis and treatment of new illnesses that can be life-threatening in young neonates. Crosscutting, longitudinal neonatal care is not possible without augmenting hospital infrastructure, supply chains, and qualified health-care workers, and must be accounted for in national health plans. 5 Providing technology and supplies alone, without coordinated investment in the strengthening of health systems, will be insufficient for achieving the SDG targets. Moving beyond survival is the cornerstone of the SDGs, which requires enabling environments, as outlined in the UN Global Strategy for Women's, Children's and Adolescents' Health 2016-30 agenda. 4 Per our analysis, more than 90% of countries have the potential to achieve the SDG targets by optimising their current health systems. Efforts to counter shortages and retain skilled health-care workers, reinforce facility infrastructure and supplies including oxygen, 31 develop and strengthen referral networks, and expand integrated services 7 are needed to achieve access and quality of care for improving survival rates for children younger than 5 years, particularly around the time of birth. 27, 29 Liberia is an example of a country that has made important progress in health system strengthening. Despite the odds of civil war and the Ebola virus epidemic, Liberia heavily invested in paying and supervising community health workers, providing medical supply chains to remote areas, and creating a health information system, leading to better survival. 32 Community-based strategies such as primary health-care promotion and integrated management of childhood illness 33 are an important pillar of prevention. Successful community activities include vaccination campaigns, insecticide-treated bednets for malaria, and motherto-child HIV/AIDS transmission prevention. 34 Further efforts are required, however, to increase uptake and coverage of additional community-based activities such as ensuring optimal maternal nutrition and iron and folic acid supplementation 35 (to target low birthweight and neural tube defects), reducing household air pollution and second-hand smoke, Haemophilus influenzae type B and pneumococcal vaccination, and access to antibiotics 36 for lower respiratory infections. Similarly, treatment campaigns for diarrhoea such as oral rehydra tion solution, zinc, and rotavirus vaccines have been successful, but must be accompanied by reductions in malnutrition and improvements in clean water and sanitation to achieve more than 90% reduction in rates of diarrhoea from the 2015 levels. 37 Relative inequity has grown over the 29 years since the first GBD study, with the 51 countries in the Countdown to 2030 initiative in sub-Saharan Africa and south Asia now accounting for 80% of all child mortality and facing stark within-country disparities. 6, 38 Within-country disparities exist throughout the SDI spectrum and are related to race and ethnicity, urban-rural geography, mother's education, and income. 34 Global and national achievement of SDG 3.2 will hinge on our collective ability to target inequality both across and within countries. Progress for the countries in the Countdown to 2030 programme is monitored by key intervention coverage milestones, 6 but must be met with national ownership and effective international investment. On an international level, the World Bank's Global Financing Facility is an example of a performance-based, country-led mechanism to strengthen health systems and multisectoral approaches, 6 but the promise of this programme has not reached countries like Central African Republic and Chad, which are not only the furthest from achieving the SDG targets with lowest key intervention coverage, but are also cited as receiving the least development assistance funding. 39 These countries contrasts with countries like Rwanda and Bangladesh. In Rwanda, a revised national health policy successfully aligned international donors to nationally driven goals of comprehensive child health care and health system strengthening, and were associated with a dramatic reduction in under-5 mortality. 32 In Bangladesh, the government partnered with domestic and international non-governmental organisations to target areas of the country most in need with delivering known interventions, performing local effectiveness research, and prioritising women's empowerment. 28 Peru and Brazil are examples of middle and high-middle SDI countries that have targeted inequity internally. Peru substantially reduced under-5 mortality by adopting the 2002 Acuerdo Nacional, 28 a national health policy targeting extreme poverty that deployed health workers to impoverished communities, completed community-based intervention research to increase perinatal care coverage, and codified collective responsibility for improving health outcomes. Brazil sanctioned governmental conditional cash transfers targeting prenatal care, immunisation, child health check-ups, and nutritional education. 28 Although the specific solutions for targeting inequity and marginalised populations vary, the essential component is that the efforts to increase equity must be explicit, sustained, and universal because it is present throughout the world. Many of the leading causes of death are also the source of the most mortality above both the global optimum and the survival potential frontier, include neonatal disorders, congenital birth defects, sudden infant death syndrome, many childhood cancers, and important infections like lower respiratory infections, diarrhoea, and meningitis. These causes are prime targets for additional dedicated primary research on disease mechanisms for effective prevention, detection, and treatment. Sudden infant death syndrome is particularly notable as only 27% of the mortality burden is above the survival potential frontier, it is the top cause of death in older infants and children in the high SDI quintile, and comparatively little is known about its pathophysiology. This entire analysis draws on the overall strength and rigour of GBD 2019, the only comprehensive analysis of fertility, population, mortality, and outcomes for specific diseases and injuries that currently exists. The UN Inter-agency Group for Child Mortality Estimation last published estimates for 2017 11 but has not reported on causes of mortality since 2015, 12, 40 at which time there was broad agreement in the top causes of death globally, but some important differences existed in cause categories that limited our ability to make direct comparisons. Measuring preventable death with the intersection of HAQ Index and SDG targets has not been explored in previous literature and necessarily extends beyond the scope of the OECD and Eurostat taskforce that only focuses on adult health outcomes. 16 This method is more holistic than previous avertable mortality frameworks such as the Countdown to 2030 report that analysed only a composite coverage index of specific interventions, but did not measure the health system performance as a whole. 6 Uses of our preventable mortality analyses include being able to identify the causes with the most potential for improvement (largest proportion above the global optimum or stochastic frontier analysis), the regions with potential imbalances in health priorities (largest ratio above frontier or discrepancies in ratio between neonates and children aged 1-59 months), causes where there are needs for better distributional allocation of resources, expertise, or delivery (those where the frontier is largely flat until decreasing sharply in high HAQ Index settings), and the causes where there is the greatest need for basic research into prevention and treatment (largest proportion below the global optimum). This preventable death framework thus introduces a novel, useful, and potentially powerful tool for developing comprehensive, evidence-based strategies for advancing child survival on multiple fronts. This analysis has several limitations. First, it shares the limitations of the overall GBD analysis, 20, 24 including it being a descriptive study; limitations on data availability because of reporting lags or because of disruptions in settings with conflict, natural disasters, or domestic governance crises; variable data granularity with respect to age, sex, and cause detail; varying quality and completeness of mortality reporting systems; and the core GBD assumption of each death having only a single underlying cause, where, clinically, there is close interrelatedness of many causes, especially in the very young. Second, our future health scenario analyses are benchmarked against past trends and are ecological in nature. This limits the ability of the analysis to be used for causal inference, and also means it is limited in its ability to capture disruptions that could arise as a consequence of future crises, such as the COVID-19 pandemic. Third, although our framework for preventable mortality is conceptually simple, reproducible, and a powerful tool for tracking context-specific progress, it is also limited by its inherently retrospective nature, its inability to parse competing risks or factors that might influence geographical variability, and that it does not make special consideration for causes like vaccine-preventable diseases that some experts contend are entirely preventable. Finally, the definition of livebirth has varied in countries and over time. Although our study has utilised a large amount of empirical data on death in the under-5 age groups, directly or indirectly measured, such information is based on potentially different definitions of livebirths, thus affecting the accuracy of our results. Although we do account for source specific biases, difference in definitions of livebirths as one of them, in our U5MR estimation process, future model development should be done to explicitly account for the effect of definition of livebirths on the accurate estimation of mortality in the under-5 age groups. Future work is required to measure and understand the direct (severe illness and death) and indirect (determinants of health) effects of COVID-19 on child mortality. First, this work will include collecting data on disruptions in basic childhood health services (eg, vaccines, integrated management of childhood illness, well-child visits), nutritional status (eg, food supply and distribution), perinatal health (eg, maternal and neonatal care), and socioeconomic indicators such as fertility, education, and household income. A second direction is to work towards an integrated framework for women's, maternal, and child health because of the inherent links between the health of mothers and their children. Third, integrating information from prevention and intervention trials into developing future health scenarios is a priority in order to provide information to motivated policy makers as to what their most effective options might be. Fourth, following the momentum of the Institute for Health Metrics and Evaluation's Local Burden of Disease project, developing increasing local estimates of cause-specific and age-specific disease burden is crucial to guide local efforts at improving survival, and assess within-country disparities further. Achieving SDG 3.2 will require focus on equilibrium, which will involve balancing early newborn care with continuing prenatal and older child health initiatives, strengthening quality health systems, scaling up interventions, addressing within-country disparities, and pursuing integrative action on social determinants of health. All these steps forward promote the SDG agenda of moving beyond mere survival, for the wellbeing of young children worldwide. Department of Family and Community Medicine Department of Global Health and Social Medicine (A W Eagan MSW), Division of Cardiology (I Y Elgendy MD), Division of General Internal Medicine Department of Population Health Sciences (V Adekanmbi PhD), Faculty of Life Sciences and Medicine (M Molokhia PhD), School of Population Health and Environmental Sciences (Y Wang PhD), King's College London, London, UK; Centre of Excellence for Epidemiological Modelling and Analysis (O O Adetokunboh PhD) Department of Health Policy and Management (O O Akinyemi FWACP), Department of Health Promotion and Education Department of Nursing (A M Mersha MSc) Department of Veterans Affairs Department of Health Information Management and Technology (A K Alumran PhD), Environmental Health Department (S M A Dahlawi PhD), Forensic Medicine Division School of Nursing and Midwifery (A Desalew MSc) Department of Health Economics (V Alipour PhD), Preventive Medicine and Public Health Research Center Research Group in Hospital Management and Health Policies (Prof N Alvis-Guzman PhD), Department of Economic Sciences Department of Health Policy and Management (L Doshmangir PhD), School of Nursing and Midwifery (H Hassankhani PhD), School of Management and Medical Informatics (L R Kalankesh PhD), Social Determinants of Health Department of Epidemiology (K D Artanti MSc, A Hargono Dr), Community Health Nursing (F Efendi PhD), Faculty of Public Health (S Martini PhD) Department of Health Policy Planning and Management (M A Ayanore PhD), University of Health and Allied Sciences Department of Health Information Management (B Reshmi PhD), Manipal Academy of Higher Education, Manipal, India (B Reshmi PhD); Department of Forensic Science (A D Badiye MSc, N Kapoor MSc), Government Institute of Forensic Science Department of Surgery and Cancer (Prof A C Davis PhD), Imperial College Business School (D Kusuma DSc), Department of Primary Care and Public Health (Prof A Majeed MD, R Palladino MD, Prof S Rawaf MD), WHO Collaborating Centre for Public Health Education and Training (D L Rawaf MD) Department of Community Medicine and Family Medicine (P Bhardwaj MD), School of Public Health (P Bhardwaj MD), Department of Pharmacology Department of Community Medicine (Prof S Burugina Nagaraja MD), Employee State Insurance Post Graduate Institute of Medical Sciences and Research Department of Health Education and Health Promotion (A Ziapour PhD Department of Health and Social Affairs (S V Gopalani MPH), Government of the Federated States of Micronesia, Palikir, Federated States of Micronesia; Department of Respiratory Medicine (H Goudarzi PhD Department of Zoology and Entomology (A I Hasaballah PhD Skaane County Council The Chinese University of Hong Kong, Hong Kong, China; Department of Public Health and Community Medicine (Prof A Humayun PhD), Shaikh Khalifa Bin Zayed Al-Nahyan Medical College Research and Development Center for Health Services (Prof K Yamagishi MD) Institute for Violence and Injury Prevention Global Health Research Center (C Wu PhD) Department of Forensic Medicine and Toxicology (Prof P Rastogi MD), Kasturba Medical College (Prof B Unnikrishnan MD), Manipal Academy of Higher Education, Mangalore, India; Department of Family Medicine and Public Health Julius Centre for Health Sciences and Primary Care (G A Kayode PhD Mymensingh, Bangladesh; Department of Health Policy and Management (Prof Y Khang MD), Institute of Health Policy and Management Department of Health Sciences (Prof D Kim DrPH), Cultures, Societies and Global Studies, & Integrated Initiative for Global Health School of Population and Public Health (J A Kopec PhD Department of Internal and Pulmonary Medicine (Prof P A Koul MD), Sheri Kashmir Institute of Medical Sciences Population Health Research Institute (T Sathish PhD) Melbourne School of Population and Global Health (Prof A D Lopez PhD), School of Health Sciences (A Meretoja MD), Department of Pediatrics Department of Forensic Medicine (Prof V Maled MD) Center for Translation Research and Implementation Science (G A Mensah MD) ); Woman-Mother-Child Department (I Michalek PhD) Ananthapuri Hospitals and Research Institute Department of Atherosclerosis and Coronary Heart Disease (Prof E M Mirrakhimov PhD) Department of Surgery (M A Tolani FWACS) University of Campinas (Unicamp), Campinas, Brazil; Department of Pediatric Medicine (Prof G Mustafa MD), The Children's Hospital & The Institute of Child Health Laboratory of Public Health Indicators Analysis and Health Digitalization Department of General Surgery (I Negoi PhD) Institute for Mental Health and Policy (Y T Nigatu PhD), Centre for Addiction and Mental Health Centre for Healthy Start Initiative National Institute of Mental Health and Neurosciences, Bengalore, India; Department of Health Metrics (A Pana MD), Center for Health Outcomes & Evaluation Dietary Supplements and Probiotic Research Center (H Pourjafar PhD), School of Medicine (M Shams-Beyranvand MSc) Centro de Investigaciones en Anomalías Congénitas y Enfermedades Raras Translational Health Research Institute (Prof A M N Renzaho PhD) Universal Scientific Education and Research Network (USERN) Department of Nutrition and Preventive Medicine Department of Geriatrics and Long Term Care (B Sathian PhD) Oral Diagnosis, Digital Health and Health Services Research (Prof F Schwendicke PhD) Department of Internal Medicine (M S Usman MB) Department of Health and Behavior Studies (Prof I D Sigfusdottir PhD), Graduate School of Architecture, Planning and Preservation (C B Swope MPH) School of Preventive Oncology Laboratory of Genetics and Genomics (Prof M S Zastrozhin PhD) Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES) (Center for Biomedical Research in Respiratory Diseases Network) Department of Population Science and Human Resource Development (Prof M I Tareque PhD) All India Institute of Medical Sciences Raffles Hospital Faculty of Information Technology Demographic Change and Aging Research Area (A Werdecker PhD Beijing Advanced Innovation Center for Big Data-based Precision Medicine Department of Health Policy and Management (Prof M Z Younis PhD) Technology Enabled Girl Ambassadors (TEGA) Programme (S S Yusuf MPH), Girl Effect, London, UK; Maternal and Child Health Division (S Zaman MPH), International Centre for Diarrhoeal Disease Research Amir Radfar reports payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing Medscape, WebMD, and Practice Point communications, and the National PI19/00588, PI19/00815, DTS18/00032, ERA-PerMed-JTC2018 (KIDNEY ATTACK AC18/00064 and PERSTIGAN AC18/00071, ISCIII-RETIC REDinREN RD016/0009), Sociedad Española de Nefrología, FRIAT, Comunidad de Madrid en Biomedicina B2017/BMD-3686 CIFRA2-CM. Jagadish Rao Padubidri acknowledges the Manipal Academy of Higher Education Mangalore, Mangalore, India for their constant support. George C Patton is supported by an NHMRC senior principal research fellowship. Alberto Raggi is supported by a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C. Besta, Linea 4 Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). Bhageerathy Reshmi acknowledges support from Manipal College of Health Professions, Manipal, India. Daniela Ribeiro acknowledges the financial support from the European Union Davide Sattin and Silvia Schiavolin acknowledge support by a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C Besta, Linea 4 Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). Francesca Giulia Magnani acknowledges support by a grant from the Italian Ministry of Health João Pedro Silva acknowledges support from grant number UIDB/04378/2020 from the Applied Molecular Biosciences Unit (UCIBIO), supported through Portuguese national funds via FCT/MCTES. David A Sleet acknowledges support from the James F and Sarah T Fries Foundation, The Bizzell Group. Mohammad Reza Sobhiyeh acknowledges support from the Clinical Research Development center of Imam Reza Hospital Kermanshah University of Medical Sciences Yunquan Zhang acknowledges the Science and Technology Research Project of Hubei Provincial Department of Education (grant number Q20201104) and Middle Aged Technology Innovation Team Project of Hubei Provincial Department of Education Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980-2015: a systematic analysis for the Global Burden of Disease Study Transforming Our World: the 2030 Agenda for Sustainable Development Every Woman Every Child. The global strategy for women's, children's and adolescents' health Reaching the every newborn national 2020 milestones: country progress, plans and moving forward. 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Geneva: World Health Organization Child health and survival in a changing world Urgent global opportunities to prevent birth defects Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study Drivers of the reduction in childhood diarrhea mortality 1980-2015 and interventions to eliminate preventable diarrhea deaths by 2030 Mapping 123 million neonatal, infant and child deaths between 2000 and 2017 Mapping under-5 and neonatal mortality in Africa, 2000-15: a baseline analysis for the Sustainable Development Goals Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the Sustainable Development Goals Robert Ancuceanu reports consulting fees from AbbVie and AstraZeneca; payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events from Sandoz and AbbVie; support for attending meetings and/or travel from AbbVie and AstraZeneca, all outside the submitted work. Marcel Ausloos reports grants or contracts from Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084, outside the submitted work. Ettore Beghi reports grants or contracts paid to their institutions from ALSA, the Italian Ministry of Health and SOBI; payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events from Arvell Therapeutics; support for attending meetings and/or travel from ILAE and EAN, all outside the submitted work. Reinhard Busse reports leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid with the Robert Koch Institute as member of the scientific advisory committee, German Burden 2020 project, all outside the submitted work. Jacek Jerzy Jozwiak reports payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events from Teva, Amgen, Synexus, Boehringer Ingelheim, ALAB Laboratories, and Zentiva, all outside the submitted work. Nicholas J Kassebaum reports support for the present manuscript from the Bill & Melinda Gates Foundation as grant funding for the GBD. Kewal Krishan reports non-financial support from UGC Centre of Advanced Study, CAS II, Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. Morteza Mahmoudi reports payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events for his published books, plenary lectures, and licensed patent to Seer; leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid with the Academic Parity Movement, a non-profit organisation dedicated to addressing academic discrimination, violence, and incivility, as a cofounder, all outside the submitted work. Shuhei Nomura reports support for the present manuscript from Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) as grant funding. Adrian Pana reports grants or contracts from Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084, research grant (October, 2018, to September, 2022, understanding and modelling time-space patterns of psychology-related inequalities and polarisation, and project number PN-III-P2-2.1-SOL-2020-2-0351, research grant (June, 2021, to October, 2021, approaches within public health management in the context of COVID-19 pandemic, all outside the submitted work. Seithikurippu R Pandi-Perumal reports payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events for the volumes he edited; leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid, with Somnogen Canada, Toronto, Canada, as the President and Chief Executive Officer, all outside the submitted work. Thomas Pilgrim reports grants or contracts from Biotronik, Boston Scientific, and Edwards Lifesciences; payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events from Biotronik, Boston Scientific, and HighLifeSAS; and being proctor for Medtronic and Boston Scientific, all outside the submitted work. GR-2013-02354960). Jonathan F Mosser acknowledges funding from BMGF (OPP1182474). Bruno Ramos Nascimento was supported in part by CNPq (Bolsa de produtividade em pesquisa, 312382/2019-7), by the Edwards Lifesciences Foundation (Every Heartbeat Matters programme 2020), and by . Shuhei Nomura acknowledges support from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT). Oluwakemi Ololade Odukoya was supported by the Fogarty International Center of the National Institutes of Health under award number K43TW010704. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Alberto Ortiz was supported by FIS/Fondos FEDER (PI18/01366, Institutes of Health and the American College of Rheumatology; payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events from Simply Speaking; support for attending meetings and travel from OMERACT, an international organisation that develops measures for clinical trials and receives arm's length funding from 12 pharmaceutical companies, when travelling biannually to OMERACT meetings; leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid, with OMERACT as a member of the steering committee, with the US Food and Drug Administration (FDA) Arthritis Advisory Committee, with the Veterans Affairs Rheumatology Field Advisory Committee as a member, and with the UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis as a director and editor; stock or stock options in TPT Global Tech, Vaxart pharmaceuticals, Charlotte's Web Holdings, and previously owned stock options in Amarin, Viking, and Moderna pharmaceuticals, all outside the submitted work. Mark A Stokes reports payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events at the Autism Teaching Institute (Victoria, Australia); unpaid participation on a data safety monitoring board or advisory board with the Deakin University Human Research Ethics Committee; leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid, with the Australasian Society for Autism Research as a past president, with the Australasian Society for Autism Research as a board member, with Kidsafe (Victoria, Australia) as vice president, with Mindful as a member of the research advisory board, and with Autism Teaching Institute as chair of the research advisory board; stock or stock options in Cochlear and Medical Developments, all outside the submitted work. Stefan Stortecky reports grants or contracts to their institute from Edwards Lifesciences, Medtronic, Boston Scientific, and Abbott; consulting fees from BTG and Teleflex; payment or honoraria for lectures, presentations, speakers' bureaus, manuscript writing, or educational events from BTG and Boston Scientific; support for attending meetings and/or travel from BTG, all outside the submitted work. Carolyn B Swope reports support for the present manuscript from Delos Living as a former employee; and consulting fees from Delos Living, outside the submitted work. Riaz Uddin reports grants or contracts from Alfred Deakin Postdoctoral Research Fellowship, Deakin University, Australia; support for attending meetings and/or travel from Deakin University Institute for Physical Activity and Nutrition, all outside the submitted work. To download the data used in these analyses, please visit the Global Health Data Exchange at http://ghdx.healthdata.org/gbd-2019.