Assessing the policy utility of routine mortality statistics: a global classification of countries.

Objective: To evaluate the utility and quality of death registration data across countries. Methods: We compiled routine death and cause of death statistics data from 2015-2019 from national authorities. We estimated completeness of death registration using the Adair-Lopez empirical method. The quality of cause of death data was assessed by evaluating the assignment of usable causes of death among people younger than 80 years. We grouped data into nine policy utility categories based on data availability, registration completeness and diagnostic precision. Findings: Of an estimated 55 million global deaths in 2019, 70% of deaths were registered across 156 countries, but only 52% had medically certified causes and 42% of deaths were assigned a usable cause. In 54 countries, which are mostly high-income, there is complete and high-quality mortality data. In a further 29 countries, located across different regions, death registration is complete, but cause of death data quality remains suboptimal. Additionally, 37 countries possess functional death registration systems with cause of death data of poor to moderate quality. In 30 countries, death registration ranges from limited to nascent completeness, accompanied by poor or unavailable cause of death data. Furthermore, 38 countries lack accessible data altogether. Conclusion: By implementing more proactive death notification processes, expanding the use of digitized data collection platforms, streamlining data compilation procedures and improving data quality assessment, governments could enhance the policy utility of mortality data. Encouraging the routine application of automated verbal autopsy methods is crucial for accurately determining the causes of deaths occurring at home.

Comparative performance of national civil registration and vital statistics systems: a global assessment.

Objective: To assess the current state of the world's civil registration and vital statistics systems based on publicly available data and to propose strategic development pathways, including priority interventions, for countries at different levels of civil registration and vital statistics performance. Methods: We applied a performance assessment framework to publicly available data, using a composite indicator highly correlated with civil registration and vital statistics performance which we then adjusted for data incomparability and missing values. Findings: Globally, civil registration and vital statistics systems score on average 0.70 (0-1 scale), with substantial variations across countries and regions. Scores ranged from less than 0.50 in emerging systems to nearly 1.00 in the most developed systems. Approximately one fifth of the world's population live in the 43 countries with low system performance (< 0.477). Irrespective of system development, health sector indicators consistently scored lower than other determinants of civil registration and vital statistics performance. Conclusion: From our assessment, we provide three main recommendations for how the health sector can contribute to improving civil registration and vital statistics systems: (i) enhanced health sector engagement in birth and death notification; (ii) a more systematic approach to training cause of death diagnostics; and (iii) leadership in the implementation of verbal autopsy methods. Four different civil registration and vital statistics improvement pathways for countries at different levels of system development are proposed, that can constitute a blueprint for regional civil registration and vital statistics strengthening activities that countries can adapt and refine to suit their capabilities, resources, and particular challenges.

Global analysis of birth statistics from civil registration and vital statistics systems.

Objective: To assess civil registration and vital statistics completeness for births in World Health Organization's Member States and identify data completeness gaps. Methods: For the 194 Member States, we sourced birth registration data from the United Nations Children's Fund database of national surveys, and, where available, vital registration reports. We acquired publicly available vital statistics compiled by national authorities. We determined civil registration completeness as the percentage of living children younger than five years whose births have been reported as registered. We evaluated vital statistics completeness against the United Nations World Population Prospects' live birth estimates, and grouped countries into seven categories based on their civil registration and vital statistics completeness. Findings: Globally, civil registration completeness for births was 77%, exceeding vital statistics completeness for births at 63%. Twenty countries had limited civil registration (25% to 74% completeness) and had nascent or no vital statistics data (completeness < 25%) for births. Five countries had nascent or no civil registration and vital statistics for births. Twenty countries had functional civil registration (75% to 94% completeness) but nascent or no available vital statistics. Approximately half (96) of the countries had complete civil registration and vital statistics for births, but contributed to only 22% of global births. Conclusion: The gap in completeness between civil registration data and vital statistics for births is most pronounced in countries with lower civil registration completeness. Enhancing data transfer processes for birth registration, along with targeted investments to elevate registration rates, is crucial for yielding comprehensive fertility statistics for governmental planning.

Estimating causes of community death of adults in Myanmar from a nationwide population sample: Application of verbal autopsy.

In Myanmar 84% of deaths occur in the community, of which half are unregistered and none have a reliable cause of death (COD) recorded. Since 2018, Myanmar has introduced improved registration practices and verbal autopsy (VA) to assess whether such methods can produce policy relevant information on community COD. Community health midwives and public health supervisors grade II collected VAs on over 80,000 deaths which occurred between January 2018 and December 2019 in a nationwide sample of 42 townships in Myanmar. Electronic methods were used to collect and consolidate data. The most probable COD was assigned using the SmartVA Analyze 2.0 computer algorithm. Completeness of VA death reporting increased to 71% in 2019. Most adult (12+ years) deaths (82%) were due to non-communicable diseases, primarily stroke, ischemic heart disease and chronic respiratory disease, for both men and women. VA results were consistent with Global Burden of Disease (GBD) Study estimates, except for cirrhosis in men, which was more common, and had a younger age distribution of death than the GBD. Large scale implementation of improved death registration practices and COD diagnosis using VA is feasible and provides plausible, timely, disaggregated and policy relevant information on the leading causes of community death. Addressing the burden of non-communicable diseases, particularly cirrhosis in young men, is an important public health priority in Myanmar. Improving completeness of VA death reporting in poorly performing townships and in neonates, children and women will further improve the policy utility of the VA data.

Assessing the Diagnostic Accuracy of Physicians for Home Death Certification in Shanghai: Application of SmartVA.

Approximately 30% of deaths in Shanghai either occur at home or are not medically attended. The recorded cause of death (COD) in these cases may not be reliable. We applied the Smart Verbal Autopsy (VA) tool to assign the COD for a representative sample of home deaths certified by 16 community health centers (CHCs) from three districts in Shanghai, from December 2017 to June 2018. The results were compared with diagnoses from routine practice to ascertain the added value of using SmartVA. Overall, cause-specific mortality fraction (CSMF) accuracy improved from 0.93 (93%) to 0.96 after the application of SmartVA. A comparison with a "gold standard (GS)" diagnoses obtained from a parallel medical record review investigation found that 86.3% of the initial diagnoses made by the CHCs were assigned the correct COD, increasing to 90.5% after the application of SmartVA. We conclude that routine application of SmartVA is not indicated for general use in CHCs, although the tool did improve diagnostic accuracy for residual causes, such as other or ill-defined cancers and non-communicable diseases.

Validation of physician certified verbal autopsy using conventional autopsy: a large study of adult non-external causes of death in a metropolitan area in Brazil.

BACKGROUND: Reliable mortality data are essential for the development of public health policies. In Brazil, although there is a well-consolidated universal system for mortality data, the quality of information on causes of death (CoD) is not even among Brazilian regions, with a high proportion of ill-defined CoD. Verbal autopsy (VA) is an alternative to improve mortality data. This study aimed to evaluate the performance of an adapted and reduced version of VA in identifying the underlying causes of non-forensic deaths, in São Paulo, Brazil. This is the first time that a version of the questionnaire has been validated considering the autopsy as the gold standard. METHODS: The performance of a physician-certified verbal autopsy (PCVA) was evaluated considering conventional autopsy (macroscopy plus microscopy) as gold standard, based on a sample of 2060 decedents that were sent to the Post-Mortem Verification Service (SVOC-USP). All CoD, from the underlying to the immediate, were listed by both parties, and ICD-10 attributed by a senior coder. For each cause, sensitivity and chance corrected concordance (CCC) were computed considering first the underlying causes attributed by the pathologist and PCVA, and then any CoD listed in the death certificate given by PCVA. Cause specific mortality fraction accuracy (CSMF-accuracy) and chance corrected CSMF-accuracy were computed to evaluate the PCVA performance at the populational level. RESULTS: There was substantial variability of the sensitivities and CCC across the causes. Well-known chronic diseases with accurate diagnoses that had been informed by physicians to family members, such as various cancers, had sensitivities above 40% or 50%. However, PCVA was not effective in attributing Pneumonia, Cardiomyopathy and Leukemia/Lymphoma as underlying CoD. At populational level, the PCVA estimated cause specific mortality fractions (CSMF) may be considered close to the fractions pointed by the gold standard. The CSMF-accuracy was 0.81 and the chance corrected CSMF-accuracy was 0.49. CONCLUSIONS: The PCVA was efficient in attributing some causes individually and proved effective in estimating the CSMF, which indicates that the method is useful to establish public health priorities.

Evolution of the global smoking epidemic over the past half century: strengthening the evidence base for policy action.

BACKGROUND: Despite compelling evidence on the health hazards of tobacco products accumulated over the past 70 years, smoking remains a leading cause of death worldwide. Policy action to control smoking requires timely, comprehensive, and comparable evidence on smoking levels within and across countries. This study provides a recent assessment of that evidence based on the methods used in the Global Burden of Disease (GBD) Study. METHODS: We estimated annual prevalence of, and mortality attributable to smoking any form of tobacco from 1970 to 2020 and 1990-2020, respectively, using the methods and data sources (including 3431 surveys and studies) from the GBD collaboration. We modelled annual prevalence of current and former smoking, distributions of cigarette-equivalents per smoker per day, pack-years for current smoking, years since cessation for former smokers and estimated population-attributable fractions due to smoking. RESULTS: Globally, adult smoking prevalence in 2020 was 32.6% (32.2% to 33.1%) and 6.5% (6.3% to 6.7%) among men and women, respectively. 1.18 (0.94 to 1.47) billion people regularly smoke tobacco, causing 7.0 (2.0 to 11.2) million deaths in 2020. Smoking prevalence has declined by 27.2% (26.0% to 28.3%) for men since 1990, and by 37.9% (35.3% to 40.1%) for women. Declines have been largest in the higher sociodemographic countries, falling by more than 40% in some high-income countries, and also in several Latin American countries, notably Brazil, where prevalence has fallen by 70% since 1990. Smoking prevalence for women has declined substantially in some countries, including Nepal, the Netherlands and Denmark, and remains low throughout Asia and Africa. Conversely, there has been little decline in smoking in most low- and middle-income countries (LMICs) with over half of all men continuing to smoke in large populations in Asia (China, Indonesia), as well as the Pacific Islands. IMPLICATIONS: While global smoking prevalence has fallen, smoking is still common and causes a significant health burden worldwide. The unequal pace of declines across the globe is shifting the epidemic progressively to LMICs. Smoking is likely to remain a leading cause of preventable death throughout this century unless smoking cessation efforts can significantly and rapidly reduce the number of smokers, particularly in Asia. FUNDING: XD and EG received funding through grant projects from Bloomberg Philanthropies (funding no. 66-9468) and the Bill & Melinda Gates Foundation (funding no. 63-3452).

Is the Rise in Reported Dementia Mortality Real? Analysis of Multiple-Cause-of-Death Data for Australia and the United States.

Official statistics in Australia and the United States show large recent increases in dementia mortality rates. In this study, we assessed whether these trends are biased by an increasing tendency of medical certifiers (predominantly physicians) to report on the death certificate that dementia was a direct cause of death. Regression models of multiple-cause-of-death data in Australia (2006-2016) and the United States (2006-2017) were constructed to adjust dementia mortality rates for changes in death certification practices. Compared with official statistics, the recent increase in adjusted age-standardized dementia death rates was less than half as large in Australia and about two-thirds as large in the United States. Further adjustment for changes in reporting of dementia anywhere on the death certificate implied even lower increases in dementia mortality. Declines in reporting of cardiovascular diseases as comorbid conditions also contributed to rises in dementia mortality rates. The increasing likelihood of dementia's being reported as directly leading to death largely explains recent increases in dementia mortality rates in both countries. However, studies have found that reported dementia on death certificates remains low compared with clinical evaluations of its prevalence. Improved guidance and training for certifiers in reporting of dementia on death certificates will help standardize mortality statistics within and between countries.

Are cause of death data for Shanghai fit for purpose? A retrospective study of medical records.

OBJECTIVES: To assess the quality of cause of death reporting in Shanghai for both hospital and home deaths. DESIGN AND SETTING: Medical records review (MRR) to independently establish a reference data set against which to compare original and adjusted diagnoses from a sample of three tertiary hospitals, one secondary level hospital and nine community health centres in Shanghai. PARTICIPANTS: 1757 medical records (61% males, 39% females) of deaths that occurred in these sample sites in 2017 were reviewed using established diagnostic standards. INTERVENTIONS: None. PRIMARY OUTCOME: Original underlying cause of death (UCOD) from medical facilities. SECONDARY OUTCOME: Routine UCOD assigned from the Shanghai Civil Registration and Vital Statistics (CRVS) system and MRR UCODs from MRR. RESULTS: The original UCODs as assigned by doctors in the study facilities were of relatively low quality, reduced to 31% of deaths assigned to garbage codes, reduced to 2.3% following data quality and follow back procedures routinely applied by the Shanghai CRVS system. The original UCOD had lower chance-corrected concordance and cause-specific mortality fraction accuracy of 0.57 (0.44, 0.70) and 0.66, respectively, compared with 0.75 (0.66, 0.85) and 0.96, respectively, after routine data checking procedures had been applied. CONCLUSIONS: Training in correct death certification for clinical doctors, especially tertiary hospital doctors, is essential to improve UCOD quality in Shanghai. A routine quality control system should be established to actively track diagnostic performance and provide feedback to individual doctors or facilities as needed.

How advanced is the epidemiological transition in Papua New Guinea? New evidence from verbal autopsy.

BACKGROUND: Reliable cause of death (COD) data are not available for the majority of deaths in Papua New Guinea (PNG), despite their critical policy value. Automated verbal autopsy (VA) methods, involving an interview and automated analysis to diagnose causes of community deaths, have recently been trialled in PNG. Here, we report VA results from three sites and highlight the utility of these methods to generate information about the leading CODs in the country. METHODS: VA methods were introduced in one district in each of three provinces: Alotau in Milne Bay; Tambul-Nebilyer in Western Highlands; and Talasea in West New Britain. VA interviews were conducted using the Population Health Metrics Research Consortium (PHMRC) shortened questionnaire and analysed using the SmartVA automated diagnostic algorithm. RESULTS: A total of 1655 VAs were collected between June 2018 and November 2019, 87.0% of which related to deaths at age 12 years and over. Our findings suggest a continuing high proportion of deaths due to infectious diseases (27.0%) and a lower proportion of deaths due to non-communicable diseases (NCDs) (50.8%) than estimated by the Global Burden of Disease Study (GBD) 2017: 16.5% infectious diseases and 70.5% NCDs. The proportion of injury deaths was also high compared with GBD: 22.5% versus 13.0%. CONCLUSIONS: Health policy in PNG needs to address a 'triple burden' of high infectious mortality, rising NCDs and a high fraction of deaths due to injuries. This study demonstrates the potential of automated VA methods to generate timely, reliable and policy-relevant data on COD patterns in hard-to-reach populations in PNG.

Improving methods to measure comparable mortality cause (IMMCMC) gold standard verbal autopsy dataset.

OBJECTIVES: Gold standard cause of death data is critically important to improve verbal autopsy (VA) methods in diagnosing cause of death where civil and vital registration systems are inadequate or poor. As part of a three-country research study-Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) study-data were collected on clinicopathological criteria-based gold standard cause of death from hospital record reviews with matched VAs. The purpose of this data note is to make accessible a de-identified format of these gold standard VAs for interested researchers to improve the diagnostic accuracy of VA methods. DATA DESCRIPTION: The study was conducted between 2011 and 2014 in the Philippines, Bangladesh, and Papua New Guinea. Gold standard diagnoses of underlying causes of death for deaths occurring in hospital were matched to VAs conducted using a standardized VA questionnaire developed by the Population Health Metrics Consortium. 3512 deaths were collected in total, comprised of 2491 adults (12 years and older), 320 children (28 days to 12 years), and 702 neonates (0-27 days).

Generating cause of death information to inform health policy: implementation of an automated verbal autopsy system in the Solomon Islands.

BACKGROUND: Good quality cause of death (COD) information is fundamental for formulating and evaluating public health policy; yet most deaths in developing countries, including the Solomon Islands, occur at home without medical certification of cause of death (MCCOD). As a result, COD data in such contexts are often of limited use for policy and planning. Verbal autopsies (VAs) are a cost-effective way of generating reliable COD information in populations lacking comprehensive MCCOD coverage, but this method has not previously been applied in the Solomon Islands. This study describes the establishment of a VA system to estimate the cause specific mortality fractions (CSMFs) for community deaths that are not medically certified in the Solomon Islands. METHODS: Automated VA methods (SmartVA) were introduced into the Solomon Islands in 2016. Trained data collectors (nurses) conducted VAs on eligible deaths to December 2020 using electronic tablet devices and VA responses were analysed using the Tariff 2.0 automated diagnostic algorithm. CSMFs were generated for both non-inpatient deaths in hospitals (i.e. 'dead on/by arrival') and community deaths. RESULTS: VA was applied to 914 adolescent-and-adult deaths with a median (IQR) age of 62 (45-75) years, 61% of whom were males. A specific COD could be diagnosed for more than 85% of deaths. The leading causes of death for both sexes combined were: ischemic heart disease (16.3%), stroke (13.5%), diabetes (8.1%), pneumonia (5.7%) and chronic-respiratory disease (4.8%). Stroke was the top-ranked cause for females, and ischaemic heart disease the leading cause for males. The CSMFs from the VAs were similar to Global Burden of Disease (GBD) estimates. Overall, non-communicable diseases (NCDs) accounted for 73% of adult deaths; communicable, maternal and nutritional conditions 15%, and injuries 12%. Six of the ten leading causes reported for facility deaths in the Solomon Islands were also identified as leading causes of community deaths based on the VA diagnoses. CONCLUSIONS: NCDs are the leading cause of adult deaths in the Solomon Islands. Automated VA methods are an effective means of generating reliable COD information for community deaths in the Solomon Islands and should be routinely incorporated into the national mortality surveillance system.

Understanding longevity in Hong Kong: a comparative study with long-living, high-income countries.

BACKGROUND: Since 2013, Hong Kong has sustained the world's highest life expectancy at birth-a key indicator of population health. The reasons behind this achievement remain poorly understood but are of great relevance to both rapidly developing and high-income regions. Here, we aim to compare factors behind Hong Kong's survival advantage over long-living, high-income countries. METHODS: Life expectancy data from 1960-2020 were obtained for 18 high-income countries in the Organisation for Economic Co-operation and Development from the Human Mortality Database and for Hong Kong from Hong Kong's Census and Statistics Department. Causes of death data from 1950-2016 were obtained from WHO's Mortality Database. We used truncated cross-sectional average length of life (TCAL) to identify the contributions to survival differences based on 263 million deaths overall. As smoking is the leading cause of premature death, we also compared smoking-attributable mortality between Hong Kong and the high-income countries. FINDINGS: From 1979-2016, Hong Kong accumulated a substantial survival advantage over high-income countries, with a difference of 1·86 years (95% CI 1·83-1·89) for males and 2·50 years (2·47-2·53) for females. As mortality from infectious diseases declined, the main contributors to Hong Kong's survival advantage were lower mortality from cardiovascular diseases for both males (TCAL difference 1·22 years, 95% CI 1·21-1·23) and females (1·19 years, 1·18-1·21), cancer for females (0·47 years, 0·45-0·48), and transport accidents for males (0·27 years, 0·27-0·28). Among high-income populations, Hong Kong recorded the lowest cardiovascular mortality and one of the lowest cancer mortalities in women. These findings were underpinned by the lowest absolute smoking-attributable mortality in high-income regions (39·7 per 100 000 in 2016, 95% CI 34·4-45·0). Reduced smoking-attributable mortality contributed to 50·5% (0·94 years, 0·93-0·95) of Hong Kong's survival advantage over males in high-income countries and 34·8% (0·87 years, 0·87-0·88) of it in females. INTERPRETATION: Hong Kong's leading longevity is the result of fewer diseases of poverty while suppressing the diseases of affluence. A unique combination of economic prosperity and low levels of smoking with development contributed to this achievement. As such, it offers a framework that could be replicated through deliberate policies in developing and developed populations globally. FUNDING: Early Career Scheme (RGC ECS Grant #27602415), Research Grants Council, University Grants Committee of Hong Kong.

Global antibiotic consumption and usage in humans, 2000-18: a spatial modelling study.

BACKGROUND: Antimicrobial resistance (AMR) is a serious threat to global public health. WHO emphasises the need for countries to monitor antibiotic consumption to combat AMR. Many low-income and middle-income countries (LMICs) lack surveillance capacity; we aimed to use multiple data sources and statistical models to estimate global antibiotic consumption. METHODS: In this spatial modelling study, we used individual-level data from household surveys to inform a Bayesian geostatistical model of antibiotic usage in children (aged <5 years) with lower respiratory tract infections in LMICs. Antibiotic consumption data were obtained from multiple sources, including IQVIA, WHO, and the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). The estimates of the antibiotic usage model were used alongside sociodemographic and health covariates to inform a model of total antibiotic consumption in LMICs. This was combined with a single model of antibiotic consumption in high-income countries to produce estimates of antibiotic consumption covering 204 countries and 19 years. FINDINGS: We analysed 209 surveys done between 2000 and 2018, covering 284 045 children with lower respiratory tract infections. We identified large national and subnational variations of antibiotic usage in LMICs, with the lowest levels estimated in sub-Saharan Africa and the highest in eastern Europe and central Asia. We estimated a global antibiotic consumption rate of 14·3 (95% uncertainty interval 13·2-15·6) defined daily doses (DDD) per 1000 population per day in 2018 (40·2 [37·2-43·7] billion DDD), an increase of 46% from 9·8 (9·2-10·5) DDD per 1000 per day in 2000. We identified large spatial disparities, with antibiotic consumption rates varying from 5·0 (4·8-5·3) DDD per 1000 per day in the Philippines to 45·9 DDD per 1000 per day in Greece in 2018. Additionally, we present trends in consumption of different classes of antibiotics for selected Global Burden of Disease study regions using the IQVIA, WHO, and ESAC-net input data. We identified large increases in the consumption of fluoroquinolones and third-generation cephalosporins in North Africa and Middle East, and south Asia. INTERPRETATION: To our knowledge, this is the first study that incorporates antibiotic usage and consumption data and uses geostatistical modelling techniques to estimate antibiotic consumption for 204 countries from 2000 to 2018. Our analysis identifies both high rates of antibiotic consumption and a lack of access to antibiotics, providing a benchmark for future interventions. FUNDING: Fleming Fund, UK Department of Health and Social Care; Wellcome Trust; and Bill & Melinda Gates Foundation.

The impact of errors in medical certification on the accuracy of the underlying cause of death.

BACKGROUND: Correct certification of cause of death by physicians (i.e. completing the medical certificate of cause of death or MCCOD) and correct coding according to International Classification of Diseases (ICD) rules are essential to produce quality mortality statistics to inform health policy. Despite clear guidelines, errors in medical certification are common. This study objectively measures the impact of different medical certification errors upon the selection of the underlying cause of death. METHODS: A sample of 1592 error-free MCCODs were selected from the 2017 United States multiple cause of death data. The ten most common types of errors in completing the MCCOD (according to published studies) were individually simulated on the error-free MCCODs. After each simulation, the MCCODs were coded using Iris automated mortality coding software. Chance-corrected concordance (CCC) was used to measure the impact of certification errors on the underlying cause of death. Weights for each error type and Socio-demographic Index (SDI) group (representing different mortality conditions) were calculated from the CCC and categorised (very high, high, medium and low) to describe their effect on cause of death accuracy. FINDINGS: The only very high impact error type was reporting an ill-defined condition as the underlying cause of death. High impact errors were found to be reporting competing causes in Part 1 [of the death certificate] and illegibility, with medium impact errors being reporting underlying cause in Part 2 [of the death certificate], incorrect or absent time intervals and reporting contributory causes in Part 1, and low impact errors comprising multiple causes per line and incorrect sequence. There was only small difference in error importance between SDI groups. CONCLUSIONS: Reporting an ill-defined condition as the underlying cause of death can seriously affect the coding outcome, while other certification errors were mitigated through the correct application of mortality coding rules. Training of physicians in not reporting ill-defined conditions on the MCCOD and mortality coders in correct coding practices and using Iris should be important components of national strategies to improve cause of death data quality.

Diversity of epidemiological transition in the Pacific: Findings from the application of verbal autopsy in Papua New Guinea and the Solomon Islands.

BACKGROUND: Cause of death data are essential for rational health planning yet are not routinely available in Papua New Guinea (PNG) and Solomon Islands. Indirect estimation of cause of death patterns suggests these populations are epidemiologically similar, but such assessments are not based on direct evidence. METHODS: Verbal autopsy (VA) interviews were conducted at three sites in PNG and nationwide in Solomon Islands. Training courses were also facilitated to improve data from medical certificates of cause of death (MCCODs) in both countries. Data were categorised into broad groups of endemic and emerging conditions to aid assessment of the epidemiological transition. FINDINGS: Between 2017 and 2020, VAs were collected for 1,814 adult deaths in PNG and 819 adult deaths in Solomon Islands. MCCODs were analysed for 662 deaths in PNG and 1,408 deaths in Solomon Islands. The VA data suggest lower NCD mortality (48.8% versus 70.3%); higher infectious mortality (27.0% versus 18.3%) and higher injury mortality (24.5% versus 11.4%) in PNG compared to Solomon Islands. Higher infectious mortality in PNG was evident for both endemic and emerging infections. Higher NCD mortality in Solomon Islands reflected much higher emerging NCDs (43.6% vs 21.4% in PNG). A similar pattern was evident from the MCCOD data. INTERPRETATION: The cause of death patterns suggested by VA and MCCOD indicate that PNG is earlier in its epidemiological transition than Solomon Islands, with relatively higher infectious mortality and lower NCD mortality. Injury mortality was also particularly high in PNG.This study was funded by Bloomberg Philanthropies.

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.

Improving the Policy Utility of Cause of Death Statistics in Sri Lanka: An Empirical Investigation of Causes of Out-of-Hospital Deaths Using Automated Verbal Autopsy Methods.

Background: Setting public health policies and effectively monitoring the impact of health interventions requires accurate, timely and complete cause of death (CoD) data for populations. In Sri Lanka, almost half of all deaths occur outside hospitals, with questionable diagnostic accuracy, thus limiting their information content for policy. Objectives: To ascertain whether SmartVA is applicable in improving the specificity of cause of death data for out-of-hospital deaths in Sri Lanka, and hence enhance the value of these routinely collected data for informing public policy debates. Methods: SmartVA was applied to 2610 VAs collected between January 2017 and March 2019 in 22 health-unit-areas clustered in six districts. Around 350 community-health-workers and 50 supervisory-staffs were trained. The resulting distribution of Cause-Specific-Mortality-Fractions (CSMFs) was compared to data from the Registrar-General's-Department (RGD) for out-of-hospital deaths for the same areas, and to the Global-Burden-of-Disease (GBD) estimates for Sri Lanka. Results: Using SmartVA, for only 15% of deaths could a specific-cause not be assigned, compared with around 40% of out-of-hospital deaths currently assigned garbage codes with "very high" or "high" severity. Stroke (M: 31.6%, F: 35.4%), Ischaemic Heart Disease (M: 13.5%, F: 13.0%) and Chronic Respiratory Diseases (M: 15.4%, F: 10.8%) were identified as the three leading causes of home deaths, consistent with the ranking of GBD-Study for Sri Lanka for all deaths, but with a notably higher CSMF for stroke. Conclusions: SmartVA showed greater diagnostic specificity, applicability, acceptability in the Sri Lankan context. Policy formulation in Sri Lanka would benefit substantially with national-wide implementation of VAs.