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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.

Abstract Background The study aims to assess two approaches that apply the empirical completeness method to generate age-specific mortality statistics from incomplete death registration systems. Methods We use the empirical completeness method to calculate all-age death registration completeness, which is used with a model life table to generate mortality statistics and age-specific completeness using (1) the conventional method and (2) the equivalent deaths method. The results are compared with a capture-recapture (C-RC) study and three alternative mortality estimates for Brazilian states, and C-RC studies in Thailand, Oman and Vietnam, which independently estimate the level and age pattern of mortality or completeness. Results The empirical completeness method produces similar estimates of all-age completeness of registration to the C-RC studies. Compared with C-RC studies, at 15-59 years, the conventional method’s estimates of mortality and completeness are more concordant, while at 60-84 years the equivalent death method’s estimates are closer. Estimates of life expectancy from the two approaches each have similar concordance with the C-RC studies. For male adult mortality in Brazilian states, there is relatively strong average correlation of this study's estimates with three alternative estimates. Conclusions The two approaches produce mortality statistics from incomplete data that are mostly concordant with C-RC studies, and can be most usefully applied to subnational populations.

Summary: 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

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.

Introduction The measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.Methods The integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.Results In Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.Conclusion This integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

BackgroundThe widely-used estimates of completeness of birth registration collected by Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) and published by UNICEF primarily rely on registration status of children as reported by respondents. However, these self-reported estimates may be inaccurate when compared with completeness as assessed from nationally-reported official birth registration statistics, for several reasons, including over-reporting of registration due to concern about penalties for non-registration. This study assesses the concordance of self-reported birth registration and certification completeness with completeness calculated from civil registration and vital statistics (CRVS) systems data for 57 countries.MethodsSelf-reported estimates of birth registration and certification completeness, at ages less than five years and 12-23 months, were compiled and calculated from the UNICEF birth registration database, DHS and MICS. CRVS birth registration completeness was calculated as birth registrations reported by a national authority divided by estimates of live births published in the United Nations (UN) World Population Prospects or the Global Burden of Disease (GBD) Study. Summary measures of concordance were used to compare completeness estimates.FindingsBirth registration completeness (based on ages less than five years) calculated from self-reported data is higher than that estimated from CRVS data in most of the 57 countries (31 countries according to UN estimated births, average six percentage points (p.p.) higher; 43 countries according to GBD, average eight p.p. higher). For countries with CRVS completeness less than 95%, self-reported completeness was higher in 26 of 28 countries, an average 13 p.p. and median 9-10 p.p. higher. Self-reported completeness is at least 30 p.p. higher than CRVS completeness in three countries. Self-reported birth certification completeness exhibits closer concordance with CRVS completeness. Similar results are found for self-reported completeness at 12-23 months.ConclusionsThese findings suggest that self-reported completeness figures over-estimate completeness when compared with CRVS data, especially at lower levels of completeness, partly due to over-reporting of registration by respondents. Estimates published by UNICEF should be viewed cautiously, especially given their wide usage.

BackgroundCorrect 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.MethodsA 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.FindingsThe 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.ConclusionsReporting 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.

Full notification of deaths and compilation of good quality cause of death data are core, sequential and essential components of a functional civil registration and vital statistics (CRVS) system. In collaboration with the Government of Papua New Guinea (PNG), trial mortality surveillance activities were established at sites in Alotau District in Milne Bay Province, Tambul-Nebilyer District in Western Highlands Province and Talasea District in West New Britain Province.Provincial Health Authorities trialled strategies to improve completeness of death notification and implement an automated verbal autopsy methodology, including use of different notification agents and paper or mobile phone methods. Completeness of death notification improved from virtually 0% to 20% in Talasea, 25% and 75% using mobile phone and paper notification strategies, respectively, in Alotau, and 69% in Tambul-Nebilyer. We discuss the challenges and lessons learnt with implementing these activities in PNG, including logistical considerations and incentives.Our experience indicates that strategies to maximise completeness of notification should be tailored to the local context, which in PNG includes significant geographical, cultural and political diversity. We report that health workers have great potential to improve the CRVS programme in PNG through managing the collection of notification and verbal autopsy data. In light of our findings, and in consultation with the main government CRVS stakeholders and the National CRVS Committee, we make recommendations regarding the requirements at each level of the health system to optimise mortality surveillance in order to generate the essential health intelligence required for policy and planning.

Background and objectiveMany countries have used the new ANACONDA (Analysis of Causes of National Death for Action) tool to assess the quality of their cause of death data (COD), but no cross-country analysis has been done to verify how different or similar patterns of diagnostic errors and data quality are in countries or how they are related to the local cultural or epidemiological environment or to levels of development. Our objective is to measure whether the usability of COD data and the patterns of unusable codes are related to a country's level of socio-economic development.MethodsWe have assessed the quality of 20 national COD datasets from the WHO Mortality Database by assessing their completeness of COD reporting and the extent, pattern and severity of garbage codes, i.e. codes that provide little or no information about the true underlying COD. Garbage codes were classified into four groups based on the severity of the error in the code. The Vital Statistics Performance Index for Quality (VSPI(Q)) was used to measure the overall quality of each country's mortality surveillance system.FindingsThe proportion of 'garbage codes' varied from 7 to 66% across the 20 countries. Countries with a high SDI generally had a lower proportion of high impact (i.e. more severe) garbage codes than countries with low SDI. While the magnitude and pattern of garbage codes differed among countries, the specific codes commonly used did not.ConclusionsThere is an inverse relationship between a country's socio-demographic development and the overall quality of its cause of death data, but with important exceptions. In particular, some low SDI countries have vital statistics systems that are as reliable as more developed countries. However, in low-income countries, where most people die at home, the proportion of unusable codes often exceeds 50%, implying that half of all cause-specific mortality data collected is of little or no use in guiding public policy. Moreover, the cause of death pattern identified from the data is likely to seriously under-represent the true extent of the leading causes of death in the population, with very significant consequences for health priority setting. Garbage codes are prevalent at all ages, contrary to expectations. Further research into effective strategies deployed in these countries to improve data quality can inform efforts elsewhere to improve COD reporting systems.

# Background This study investigated healthcare decision-making surrounding terminal illnesses of adults and elderly persons (aged 15 years or more), who later died at home, hospitals, or in-transit, in a rural, low-income area of Bangladesh where out-of-pocket health expenditure is very high. # Methods There were 1330 adult and elderly deaths in Matlab Health and Demographic Surveillance site in 2013. To record how decisions were made and implemented when caring for terminal illness, and how treatment-related costs were managed, the main caregivers of 69 randomly selected persons who died at home, 74 who died in hospitals, and 11 who died in-transit were interviewed with a social autopsy questionnaire in 2014. Differences between groups were tested by χ^2^ for significance at *P* \

INTRODUCTION:Adult male and female mortality declines in Japan have been slower than in most high-income countries since the early 1990s. This study compares Japan's recent life expectancy trends with the more favourable trends in Australia, measures the contribution of age groups and causes of death to differences in these trends, and places the findings in the context of the countries' risk factor transitions. METHODS:The study utilises data on deaths by age, sex and cause in Australia and Japan from 1950-2016 from the Global Burden of Disease Study. A decomposition method measures the contributions of various ages and causes to the male and female life expectancy gap and changes over four distinct phases during this period. Mortality differences by cohort are also assessed. FINDINGS:Japan's two-year male life expectancy advantage over Australia in the 1980s closed in the following 20 years. The trend was driven by ages 45-64 and then 65-79 years, and the cohort born in the late 1940s. Over half of Australia's gains were from declines in ischaemic heart disease (IHD) mortality, with lung cancer, chronic respiratory disease and self-harm also contributing substantially. Since 2011 the trend has reversed again, and in 2016 Japan had a slightly higher male life expectancy. The advantage in Japanese female life expectancy widened over the period to 2.3 years in 2016. The 2016 gap was mostly from differential mortality at ages 65 years and over from IHD, chronic respiratory disease and cancers. CONCLUSIONS:The considerable gains in Australian male life expectancy from declining non-communicable disease mortality are attributable to a range of risk factors, including declining smoking prevalence due to strong public health interventions. A recent reversal in life expectancy trends could continue because Japan has greater scope for further falls in smoking and far lower levels of obesity. Japan's substantial female life expectancy advantage however could diminish in future because it is primarily due to lower mortality at old ages.

Many national and subnational governments need to routinely measure the completeness of death registration for monitoring and statistical purposes. Existing methods, such as death distribution and capture-recapture methods, have a number of limitations such as inaccuracy and complexity that prevent widespread application. This paper presents a novel empirical method to estimate completeness of death registration at the national and subnational level.Random-effects models to predict the logit of death registration completeness were developed from 2,451 country-years in 110 countries from 1970-2015 using the Global Burden of Disease 2015 database. Predictors include the registered crude death rate, under-five mortality rate, population age structure and under-five death registration completeness. Models were developed separately for males, females and both sexes.All variables are highly significant and reliably predict completeness of registration across a wide range of registered crude death rates (R-squared 0.85). Mean error is highest at medium levels of observed completeness. The models show quite close agreement between predicted and observed completeness for populations outside the dataset. There is high concordance with the Hybrid death distribution method in Brazilian states. Uncertainty in the under-five mortality rate, assessed using the dataset and in Colombian departmentos, has minimal impact on national level predicted completeness, but a larger effect at the subnational level.The method demonstrates sufficient flexibility to predict a wide range of completeness levels at a given registered crude death rate. The method can be applied utilising data readily available at the subnational level, and can be used to assess completeness of deaths reported from health facilities, censuses and surveys. Its utility is diminished where the adult mortality rate is unusually high for a given under-five mortality rate. The method overcomes the considerable limitations of existing methods and has considerable potential for widespread application by national and subnational governments.

More countries are using verbal autopsy as a part of routine mortality surveillance. The length of time required to complete a verbal autopsy interview is a key logistical consideration for planning large-scale surveillance.We use the PHMRC shortened questionnaire to conduct verbal autopsy interviews at three sites and collect data on the length of time required to complete the interview. This instrument uses a novel checklist of keywords to capture relevant information from the open response. The open response section is timed separately from the section consisting of closed questions.We found the median time to complete the entire interview was approximately 25 minutes and did not vary substantially by age-specific module. The median time for the open response section was approximately 4 minutes and 60% of interviewees mentioned at least one keyword within the open response section.The length of time required to complete the interview was short enough for large-scale routine use. The open-response section did not add a substantial amount of time and provided useful information which can be used to increase the accuracy of the predictions of the cause of death. The novel checklist approach further reduces the burden of transcribing and translating a large amount of free text. This makes the PHMRC instrument ideal for national mortality surveillance.

Objective To systematically review the reliability of hospital data on cause of death and encourage periodic reviews of these data using a standard method. Methods We searched Google Scholar, Pubmed and Biblioteca Virtual de la Salud for articles in English, Spanish and Portuguese that reported validation studies of data on cause of death. We analysed the results of 199 studies that had used medical record reviews to validate the cause of death reported on death certificates or by the vital registration system. Findings The screened studies had been published between 1983 and 2013 and their results had been reported in English (n = 124), Portuguese (n = 25) or Spanish (n = 50). Only 29 of the studies met our inclusion criteria. Of these, 13 had examined cause of death patterns at the population level – with a view to correcting cause-specific mortality fractions – while the other 16 had been undertaken to identify discrepancies in the diagnosis for specific diseases before and after medical record review. Most of the selected studies reported substantial misdiagnosis of causes of death in hospitals. There was wide variation in study methodologies. Many studies did not describe the methods used in sufficient detail to be able to assess the reproducibility or comparability of their results. Conclusion The assumption that causes of death are being accurately reported in hospitals is unfounded. To improve the reliability and usefulness of reported causes of death, national governments should do periodic medical record reviews to validate the quality of their hospital cause of death data, using a standard.

Objective. To present the results of the burden of disease, injuries and risk factors in Mexico from 1990 to 2010 for the principal illnesses, injuries and risk factors by sex. Materials and methods. A secondary analysis of the study results published by the Global Burden of Disease 2010 for Mexico performed by IHME. Results. In 2010, Mexico lost 26.2 million of Disability adjusted live years (DALYs), 56 % were in male and 44 % in women. The main causes of DALYs in men are violence, ischemic heart disease and road traffic injuries. In the case of women the leading causes are diabetes, chronic kidney disease and ischemic heart diseases. The mental disorders and musculoskeletal conditions concentrate 18% of health lost. The risk factors that most affect men in Mexico are: alcohol consumption, overweight/obesity, high blood glucose levels and blood pressure and tobacco consumption (35.6 % of DALYs lost). In women, overweight and obesity, high blood sugar and blood pressure, lack of physical activity and consumption of alcohol are responsible for 40 % of DALYs lost. In both sexes the problems with diet contribute 12% of the burden. Conclusions. The epidemiological situation in Mexico, demands an urgent adaptation and modernization of the health system

OBJECTIVE: To assess the extent and pattern of misclassification of death from non-specific diagnoses emanating from the Iranian death registration system, and to correct the data for health policy and planning. METHODS: Detailed medical records for 1426 hospital deaths classified to seven ill-defined or vague causes of death were reviewed by trained physicians, who then completed standard death certificates. Underlying causes of death from the review were compared with the cause assigned in registration data. FINDINGS: The probable underlying pattern of causes of death in the Islamic Republic of Iran is substantially different to that suggested by the death registration system. About 88% of 582 cases with non-specific diagnoses at ages 15-69 years were reassigned to various specific causes including ischaemic heart disease (33%), stroke (13%) and injuries (10%). A similar pattern of misclassification is apparent for 738 deaths at older ages (70 years and over), with 46% being reassigned to ischaemic heart disease and stroke. CONCLUSION: A significant proportion of deaths in the Iranian death registration system are being classified to cause groups of little relevance to epidemiological research or health policy. Reassignment of these deaths would increase the proportion of deaths from ischaemic heart disease and cerebrovascular diseases each by 32%, diabetes mellitus by 68% and chronic lower respiratory diseases by 73%. Substantial changes to procedures for diagnosing causes of death are urgently required if registration data are to effectively guide health policies and programmes in the Islamic Republic of Iran.

OBJECTIVE: Reliable information on the pattern, level and trend of mortality is essential for evidence-based policy to improve health. Various sources of mortality data in the Islamic Republic of Iran have not been critically assessed. This paper aims to document and evaluate the completeness of the different data sources on mortality and to estimate the level and trends of mortality over the past 40 years according to various mortality indices such as child mortality, adult mortality and life expectancy. METHODS: We undertook a systematic review of all available studies on infant mortality from 1964 to 2004 and estimated the most probable trend in child mortality. Death registration data from between 1992 and 2004 were assessed for completeness to estimate the level of adult mortality. Life tables for 2004 were constructed for the Islamic Republic of Iran based on these data, corrected for underregistration of death. FINDINGS: Infant mortality decreased from an estimated 154 deaths per 1000 live births in 1964 to 26 in 2004. The risk of adult mortality in 2004 was estimated to be 0.124 and 0.175 for females and males respectively. According to adjusted death registration data, life expectancy at birth in 2004 was 71.2 for females and 68.7 for males. The average completeness of death registration for ages 5 years and older across all systems was 76% for the period 2001-2004. CONCLUSION: There has been a general decline in child mortality in the Islamic Republic of Iran over the past three decades. Adult mortality levels also have declined, but less substantially. Mortality information systems have improved, yet serious concerns remain regarding the completeness and quality of data.

OBJECTIVE: To investigate the effect of immigration on life expectancy in Australia for the period from 1981 to 2003, and to compare life expectancy of the Australian-born population with that of other countries in the Organisation for Economic Cooperation and Development (OECD). METHODS: Standard life-table methods using age-specific all-cause mortality and population data from 1981 to 2003 were used to calculate life expectancy at birth (e0) for the total Australian population (including migrants) and for people born in Australia (excluding migrants). Mean differences in life expectancy for each sex were compared using paired t-tests. Rankings of life expectancy among OECD countries were reassessed, and rank changes measured using the Wilcoxon signed rank test. FINDINGS: Life expectancy of males and females was significantly lower in the Australian-born group than in the total Australian population. During 1981 to 2003, there was a mean difference in life expectancy of 0.41 years (95% confidence interval, CI: 0.37-0.44; t17 = 27.0; P < 0.0001) in males and 0.29 years (95% CI: 0.26-0.31; t17 = 27.6; P < 0.0001) in females between the Australian-born and the total population. After excluding migrant groups, Australia no longer ranked among the top five OECD countries with the highest life expectancy in the two most recent years examined. CONCLUSION: While Australia has one of the highest life expectancies in the industrialized world, this is partly attributable to immigration of populations with low rates of mortality. This effect needs to be considered in international comparative assessments of mortality levels.

ObjectiveThis paper aims to determine the cost of establishing and sustaining a verbal-autopsy based mortality surveillance system in rural India.Materials and methodsDeaths occurring in 45 villages (population 185,629) were documented over a 4-year period from 2003-2007 by 45 non-physician healthcare workers (NPHWs) trained in data collection using a verbal autopsy tool. Causes of death were assigned by 2 physicians for the first year and by one physician for the subsequent years. Costs were calculated for training of interviewers and physicians, data collection, verbal autopsy analysis, project management and infrastructure. Costs were divided by the number of deaths and the population covered in the year.ResultsVerbal-autopsies were completed for 96.7% (5786) of all deaths (5895) recorded. The annual cost in year 1 was INR 1,133,491 (USD 24,943) and the total cost per death was INR 757 (USD 16.66). These costs included training of NPHWs and physician reviewers Rs 67,025 (USD 1474), data collection INR 248,400 (USD 5466), dual physician review for cause of death assignment INR 375,000 (USD 8252), and project management INR 341,724 (USD 7520). The average annual cost to run the system each year was INR 822,717 (USD18104) and the cost per death was INR 549 (USD 12) for the next 3 years. Costs were reduced by using single physician review and shortened re-training sessions. The annual cost of running a surveillance system was INR 900,410 (USD 19814).DiscussionThis study provides detailed empirical evidence of the costs involved in running a mortality surveillance site using verbal-autopsy.

OBJECTIVE: To compare mortality burden estimates based on direct measurement of levels and causes in communities with indirect estimates based on combining health facility cause-specific mortality structures with community measurement of mortality levels. METHODS: Data from sentinel vital registration (SVR) with verbal autopsy (VA) were used to determine the cause-specific mortality burden at the community level in two areas of the United Republic of Tanzania. Proportional cause-specific mortality structures from health facilities were applied to counts of deaths obtained by SVR to produce modelled estimates. The burden was expressed in years of life lost. FINDINGS: A total of 2884 deaths were recorded from health facilities and 2167 recorded from SVR/VAs. In the perinatal and neonatal age group cause-specific mortality rates were dominated by perinatal conditions and stillbirths in both the community and the facility data. The modelled estimates for chronic causes were very similar to those from SVR/VA. Acute febrile illnesses were coded more specifically in the facility data than in the VA. Injuries were more prevalent in the SVR/VA data than in that from the facilities. CONCLUSION: In this setting, improved International classification of diseases and health related problems, tenth revision (ICD-10) coding practices and applying facility-based cause structures to counts of deaths from communities, derived from SVR, appears to produce reasonable estimates of the cause-specific mortality burden in those aged 5 years and older determined directly from VA. For the perinatal and neonatal age group, VA appears to be required. Use of this approach in a nationally representative sample of facilities may produce reliable national estimates of the cause-specific mortality burden for leading causes of death in adults.

Over recent years there has been a strong movement towards the improvement of vital statistics and other types of health data that inform evidence-based policies. Collecting such data is not cost free. To date there is no systematic framework to guide investment decisions on methods of data collection for vital statistics or health information in general. We developed a framework to systematically assess the comparative costs and outcomes/benefits of the various data methods for collecting vital statistics.The proposed framework is four-pronged and utilises two major economic approaches to systematically assess the available data collection methods: cost-effectiveness analysis and efficiency analysis. We built a stylised example of a hypothetical low-income country to perform a simulation exercise in order to illustrate an application of the framework.Using simulated data, the results from the stylised example show that the rankings of the data collection methods are not affected by the use of either cost-effectiveness or efficiency analysis. However, the rankings are affected by how quantities are measured.There have been several calls for global improvements in collecting useable data, including vital statistics, from health information systems to inform public health policies. Ours is the first study that proposes a systematic framework to assist countries undertake an economic evaluation of DCMs. Despite numerous challenges, we demonstrate that a systematic assessment of outputs and costs of DCMs is not only necessary, but also feasible. The proposed framework is general enough to be easily extended to other areas of health information.

BackgroundTwo World Health Organization comparative assessments rated the quality of South Africa's 1996 mortality data as low. Since then, focussed initiatives were introduced to improve civil registration and vital statistics. Furthermore, South African cause-of-death data are widely used by research and international development agencies as the basis for making estimates of cause-specific mortality in many African countries. It is hence important to assess the quality of more recent South African data.MethodsWe employed nine criteria to evaluate the quality of civil registration mortality data. Four criteria were assessed by analysing 5.38 million deaths that occurred nationally from 1997-2007. For the remaining five criteria, we reviewed relevant legislation, data repositories, and reports to highlight developments which shaped the current status of these criteria.FindingsNational mortality statistics from civil registration were rated satisfactory for coverage and completeness of death registration, temporal consistency, age/sex classification, timeliness, and sub-national availability. Epidemiological consistency could not be assessed conclusively as the model lacks the discriminatory power to enable an assessment for South Africa. Selected studies and the extent of ill-defined/non-specific codes suggest substantial shortcomings with single-cause data. The latter criterion and content validity were rated unsatisfactory.ConclusionIn a region marred by mortality data absences and deficiencies, this analysis signifies optimism by revealing considerable progress from a dysfunctional mortality data system to one that offers all-cause mortality data that can be adjusted for demographic and health analysis. Additionally, timely and disaggregated single-cause data are available, certified and coded according to international standards. However, without skillfully estimating adjustments for biases, a considerable confidence gap remains for single-cause data to inform local health planning, or to fill gaps in sparse-data countries on the continent. Improving the accuracy of single-cause data will be a critical contribution to the epidemiologic and population health evidence base in Africa.

BackgroundRecent assessments show continued decline in child mortality in Papua New Guinea (PNG), yet complete subnational analyses remain rare. This study aims to estimate under-five mortality in PNG at national and subnational levels to examine the importance of geographical inequities in health outcomes and track progress towards Millennium Development Goal (MDG) 4.MethodologyWe performed retrospective data validation of the Demographic and Health Survey (DHS) 2006 using 2000 Census data, then applied advanced indirect methods to estimate under-five mortality rates between 1976 and 2000.FindingsThe DHS 2006 was found to be unreliable. Hence we used the 2000 Census to estimate under-five mortality rates at national and subnational levels. During the period under study, PNG experienced a slow reduction in national under-five mortality from approximately 103 to 78 deaths per 1,000 live births. Subnational analyses revealed significant disparities between rural and urban populations as well as inter- and intra-regional variations. Some of the provinces that performed the best (worst) in terms of under-five mortality included the districts that performed worst (best), with district-level under-five mortality rates correlating strongly with poverty levels and access to services.ConclusionsThe evidence from PNG demonstrates substantial within-province heterogeneity, suggesting that under-five mortality needs to be addressed at subnational levels. This is especially relevant in countries, like PNG, where responsibility for health services is devolved to provinces and districts. This study presents the first comprehensive estimates of under-five mortality at the district level for PNG. The results demonstrate that for countries that rely on few data sources even greater importance must be given to the quality of future population surveys and to the exploration of alternative options of birth and death surveillance.

BackgroundOne of the fundamental building blocks for determining the burden of disease in populations is to reliably measure the level and pattern of mortality by age and sex. Where well-functioning registration systems exist, this task is relatively straightforward. Results from many civil registration systems, however, remain uncertain because of a lack of confidence in the completeness of death registration. Incomplete registration systems mean not all deaths are counted, and resulting estimates of death rates for the population are then underestimated. Death distribution methods (DDMs) are a suite of demographic methods that attempt to estimate the fraction of deaths that are registered and counted by the civil registration system. Although widely applied and used, the methods have at least three types of limitations. First, a wide range of variants of these methods has been applied in practice with little scientific literature to guide their selection. Second, the methods have not been extensively validated in real population conditions where violations of the assumptions of the methods most certainly occur. Third, DDMs do not generate uncertainty intervals.Methods and findingsIn this paper, we systematically evaluate the performance of 234 variants of DDM methods in three different validation environments where we know or have strong beliefs about the true level of completeness of death registration. Using these datasets, we identify three variants of the DDMs that generally perform the best. We also find that even these improved methods yield uncertainty intervals of roughly +/- one-quarter of the estimate. Finally, we demonstrate the application of the optimal variants in eight countries.ConclusionsThere continues to be a role for partial vital registration data in measuring adult mortality levels and trends, but such results should only be interpreted alongside all other data sources on adult mortality and the uncertainty of the resulting levels, trends, and age-patterns of adult death considered. Please see later in the article for the Editors' Summary.

BackgroundThere has been increasing interest in measuring under-five mortality as a health indicator and as a critical measure of human development. In countries with complete vital registration systems that capture all births and deaths, under-five mortality can be directly calculated. In the absence of a complete vital registration system, however, child mortality must be estimated using surveys that ask women to report the births and deaths of their children. Two survey methods exist for capturing this information: summary birth histories and complete birth histories. A summary birth history requires a minimum of only two questions: how many live births has each mother had and how many of them have survived. Indirect methods are then applied using the information from these two questions and the age of the mother to estimate under-five mortality going back in time prior to the survey. Estimates generated from complete birth histories are viewed as the most accurate when surveys are required to estimate under-five mortality, especially for the most recent time periods. However, it is much more costly and labor intensive to collect these detailed data, especially for the purpose of generating small area estimates. As a result, there is a demand for improvement of the methods employing summary birth history data to produce more accurate as well as subnational estimates of child mortality.Methods and findingsWe used data from 166 Demographic and Health Surveys (DHS) to develop new empirically based methods of estimating under-five mortality using children ever born and children dead data. We then validated them using both in- and out-of-sample analyses. We developed a range of methods on the basis of three dimensions of the problem: (1) approximating the average length of exposure to mortality from a mother's set of children using either maternal age or time since first birth; (2) using cohort and period measures of the fraction of children ever born that are dead; and (3) capturing country and regional variation in the age pattern of fertility and mortality. We focused on improving estimates in the most recent time periods prior to a survey where the traditional indirect methods fail. In addition, all of our methods incorporated uncertainty. Validated against under-five estimates generated from complete birth histories, our methods outperformed the standard indirect method by an average of 43.7% (95% confidence interval [CI] 41.2-45.2). In the 5 y prior to the survey, the new methods resulted in a 53.3% (95% CI 51.3-55.2) improvement. To illustrate the value of this method for local area estimation, we applied our new methods to an analysis of summary birth histories in the 1990, 2000, and 2005 Mexican censuses, generating subnational estimates of under-five mortality for each of 233 jurisdictions.ConclusionsThe new methods significantly improve the estimation of under-five mortality using summary birth history data. In areas without vital registration data, summary birth histories can provide accurate estimates of child mortality. Because only two questions are required of a female respondent to generate these data, they can easily be included in existing survey programs as well as routine censuses of the population. With the wider application of these methods to census data, countries now have the means to generate estimates for subnational areas and population subgroups, important for measuring and addressing health inequalities and developing local policy to improve child survival. Please see later in the article for the Editors' Summary.

BackgroundFor several decades, global public health efforts have focused on the development and application of disease control programs to improve child survival in developing populations. The need to reliably monitor the impact of such intervention programs in countries has led to significant advances in demographic methods and data sources, particularly with large-scale, cross-national survey programs such as the Demographic and Health Surveys (DHS). Although no comparable effort has been undertaken for adult mortality, the availability of large datasets with information on adult survival from censuses and household surveys offers an important opportunity to dramatically improve our knowledge about levels and trends in adult mortality in countries without good vital registration. To date, attempts to measure adult mortality from questions in censuses and surveys have generally led to implausibly low levels of adult mortality owing to biases inherent in survey data such as survival and recall bias. Recent methodological developments and the increasing availability of large surveys with information on sibling survival suggest that it may well be timely to reassess the pessimism that has prevailed around the use of sibling histories to measure adult mortality.Methods and findingsWe present the Corrected Sibling Survival (CSS) method, which addresses both the survival and recall biases that have plagued the use of survey data to estimate adult mortality. Using logistic regression, our method directly estimates the probability of dying in a given country, by age, sex, and time period from sibling history data. The logistic regression framework borrows strength across surveys and time periods for the estimation of the age patterns of mortality, and facilitates the implementation of solutions for the underrepresentation of high-mortality families and recall bias. We apply the method to generate estimates of and trends in adult mortality, using the summary measure (45)q(15)-the probability of a 15-y old dying before his or her 60th birthday-for 44 countries with DHS sibling survival data. Our findings suggest that levels of adult mortality prevailing in many developing countries are substantially higher than previously suggested by other analyses of sibling history data. Generally, our estimates show the risk of adult death between ages 15 and 60 y to be about 20%-35% for females and 25%-45% for males in sub-Saharan African populations largely unaffected by HIV. In countries of Southern Africa, where the HIV epidemic has been most pronounced, as many as eight out of ten men alive at age 15 y will be dead by age 60, as will six out of ten women. Adult mortality levels in populations of Asia and Latin America are generally lower than in Africa, particularly for women. The exceptions are Haiti and Cambodia, where mortality risks are comparable to many countries in Africa. In all other countries with data, the probability of dying between ages 15 and 60 y was typically around 10% for women and 20% for men, not much higher than the levels prevailing in several more developed countries.ConclusionsOur results represent an expansion of direct knowledge of levels and trends in adult mortality in the developing world. The CSS method provides grounds for renewed optimism in collecting sibling survival data. We suggest that all nationally representative survey programs with adequate sample size ought to implement this critical module for tracking adult mortality in order to more reliably understand the levels and patterns of adult mortality, and how they are changing. Please see later in the article for the Editors' Summary.

Background to the debateDemographic surveillance--the process of monitoring births, deaths, causes of deaths, and migration in a population over time--is one of the cornerstones of public health research, particularly in investigating and tackling health disparities. An international network of demographic surveillance systems (DSS) now operates, mostly in sub-Saharan Africa and Asia. Thirty-eight DSS sites are coordinated by the International Network for the Continuous Demographic Evaluation of Populations and Their Health (INDEPTH). In this debate, Daniel Chandramohan and colleagues argue that DSS data in the INDEPTH database should be made available to all researchers worldwide, not just to those within the INDEPTH Network. Basia Zaba and colleagues argue that the major obstacles to DSS sites sharing data are technical, managerial, and financial rather than proprietorial concerns about analysis and publication. This debate is further discussed in this month's Editorial.

Cause of death data are a critical input to formulating good public health policy. In the absence of reliable vital registration data, information collected after death from household members, called verbal autopsy (VA), is commonly used to study causes of death. VA data are usually analyzed by physician-coded verbal autopsy (PCVA). PCVA is expensive and its comparability across regions is questionable. Nearly all validation studies of PCVA have allowed physicians access to information collected from the household members' recall of medical records or contact with health services, thus exaggerating accuracy of PCVA in communities where few deaths had any interaction with the health system. In this study we develop and validate a statistical strategy for analyzing VA data that overcomes the limitations of PCVA.We propose and validate a method that combines the advantages of methods proposed by King and Lu, and Byass, which we term the symptom pattern (SP) method. The SP method uses two sources of VA data. First, it requires a dataset for which we know the true cause of death, but which need not be representative of the population of interest; this dataset might come from deaths that occur in a hospital. The SP method can then be applied to a second VA sample that is representative of the population of interest. From the hospital data we compute the properties of each symptom; that is, the probability of responding yes to each symptom, given the true cause of death. These symptom properties allow us first to estimate the population-level cause-specific mortality fractions (CSMFs), and to then use the CSMFs as an input in assigning a cause of death to each individual VA response. Finally, we use our individual cause-of-death assignments to refine our population-level CSMF estimates. The results from applying our method to data collected in China are promising. At the population level, SP estimates the CSMFs with 16% average relative error and 0.7% average absolute error, while PCVA results in 27% average relative error and 1.1% average absolute error. At the individual level, SP assigns the correct cause of death in 83% of the cases, while PCVA does so for 69% of the cases. We also compare the results of SP and PCVA when both methods have restricted access to the information from the medical record recall section of the VA instrument. At the population level, without medical record recall, the SP method estimates the CSMFs with 14% average relative error and 0.6% average absolute error, while PCVA results in 70% average relative error and 3.2% average absolute error. For individual estimates without medical record recall, SP assigns the correct cause of death in 78% of cases, while PCVA does so for 38% of cases.Our results from the data collected in China suggest that the SP method outperforms PCVA, both at the population and especially at the individual level. Further study is needed on additional VA datasets in order to continue validation of the method, and to understand how the symptom properties vary as a function of culture, language, and other factors. Our results also suggest that PCVA relies heavily on household recall of medical records and related information, limiting its applicability in low-resource settings. SP does not require that additional information to adequately estimate causes of death.

Reliable, comparable information about the main causes of disease and injury in populations, and how these are changing, is a critical input for debates about priorities in the health sector. Traditional sources of information about the descriptive epidemiology of diseases, injuries, and risk factors are generally incomplete, fragmented, and of uncertain reliability and comparability. The Global Burden of Disease (GBD) study has provided a conceptual and methodological framework to quantify and compare the health of populations using a summary measure of both mortality and disability, the disability-adjusted life year (DALY).This paper describes key features of the Global Burden of Disease analytic approach, which provides a standardized measurement framework to permit comparisons across diseases and injuries, as well as risk factors, and a systematic approach to the evaluation of data. The paper describes the evolution of the GBD, starting from the first study for the year 1990, summarizes the methodological improvements incorporated into GBD revisions for the years 2000-2004 carried out by the World Health Organization, and examines priorities and issues for the next major GBD study, funded by the Bill & Melinda Gates Foundation, and commencing in 2007.The paper presents an overview of summary results from the Global Burden of Disease study 2002, with a particular focus on the neglected tropical diseases, and also an overview of the comparative risk assessment for 26 global risk factors. Taken together, trypanosomiasis, Chagas disease, schistosomiasis, leishmaniasis, lymphatic filariasis, onchocerciasis, intestinal nematode infections, Japanese encephalitis, dengue, and leprosy accounted for an estimated 177,000 deaths worldwide in 2002, mostly in sub-Saharan Africa, and about 20 million DALYs, or 1.3% of the global burden of disease and injuries. Further research is currently underway to revise and update these estimates.

Cause-of-death data for many developing countries are not available. Information on deaths in hospital by cause is available in many low- and middle-income countries but is not a representative sample of deaths in the population. We propose a method to estimate population cause-specific mortality fractions (CSMFs) using data already collected in many middle-income and some low-income developing nations, yet rarely used: in-hospital death records.For a given cause of death, a community's hospital deaths are equal to total community deaths multiplied by the proportion of deaths occurring in hospital. If we can estimate the proportion dying in hospital, we can estimate the proportion dying in the population using deaths in hospital. We propose to estimate the proportion of deaths for an age, sex, and cause group that die in hospital from the subset of the population where vital registration systems function or from another population. We evaluated our method using nearly complete vital registration (VR) data from Mexico 1998-2005, which records whether a death occurred in a hospital. In this validation test, we used 45 disease categories. We validated our method in two ways: nationally and between communities. First, we investigated how the method's accuracy changes as we decrease the amount of Mexican VR used to estimate the proportion of each age, sex, and cause group dying in hospital. Decreasing VR data used for this first step from 100% to 9% produces only a 12% maximum relative error between estimated and true CSMFs. Even if Mexico collected full VR information only in its capital city with 9% of its population, our estimation method would produce an average relative error in CSMFs across the 45 causes of just over 10%. Second, we used VR data for the capital zone (Distrito Federal and Estado de Mexico) and estimated CSMFs for the three lowest-development states. Our estimation method gave an average relative error of 20%, 23%, and 31% for Guerrero, Chiapas, and Oaxaca, respectively.Where accurate International Classification of Diseases (ICD)-coded cause-of-death data are available for deaths in hospital and for VR covering a subset of the population, we demonstrated that population CSMFs can be estimated with low average error. In addition, we showed in the case of Mexico that this method can substantially reduce error from biased hospital data, even when applied to areas with widely different levels of development. For countries with ICD-coded deaths in hospital, this method potentially allows the use of existing data to inform health policy.

BackgroundCause-specific mortality statistics remain scarce for the majority of low-income countries, where the highest disease burdens are experienced. Neither facility-based information systems nor vital registration provide adequate or representative data. The expansion of sample vital registration with verbal autopsy procedures represents the most promising interim solution for this problem. The development and validation of core verbal autopsy forms and suitable coding and tabulation procedures are an essential first step to extending the benefits of this method.Methods and findingsCore forms for peri- and neonatal, child, and adult deaths were developed and revised over 12 y through a project of the Tanzanian Ministry of Health and were applied to over 50,000 deaths. The contents of the core forms draw upon and are generally comparable with previously proposed verbal autopsy procedures. The core forms and coding procedures based on the International Statistical Classification of Diseases (ICD) were further adapted for use in China. These forms, the ICD tabulation list, the summary validation protocol, and the summary validation results from Tanzania and China are presented here.ConclusionsThe procedures are capable of providing reasonable mortality estimates as adjudged against stated performance criteria for several common causes of death in two countries with radically different cause structures of mortality. However, the specific causes for which the procedures perform well varied between the two settings because of differences in the underlying prevalence of the main causes of death. These differences serve to emphasize the need to undertake validation studies of verbal autopsy procedures when they are applied in new epidemiological settings.

BackgroundCardiovascular diseases and their nutritional risk factors--including overweight and obesity, elevated blood pressure, and cholesterol--are among the leading causes of global mortality and morbidity, and have been predicted to rise with economic development.Methods and findingsWe examined age-standardized mean population levels of body mass index (BMI), systolic blood pressure, and total cholesterol in relation to national income, food share of household expenditure, and urbanization in a cross-country analysis. Data were from a total of over 100 countries and were obtained from systematic reviews of published literature, and from national and international health agencies. BMI and cholesterol increased rapidly in relation to national income, then flattened, and eventually declined. BMI increased most rapidly until an income of about ID 5,000 (international dollars) and peaked at about ID 12,500 for females and ID 17,000 for males. Cholesterol's point of inflection and peak were at higher income levels than those of BMI (about ID 8,000 and ID 18,000, respectively). There was an inverse relationship between BMI/cholesterol and the food share of household expenditure, and a positive relationship with proportion of population in urban areas. Mean population blood pressure was not correlated or only weakly correlated with the economic factors considered, or with cholesterol and BMI.ConclusionsWhen considered together with evidence on shifts in income-risk relationships within developed countries, the results indicate that cardiovascular disease risks are expected to systematically shift to low-income and middle-income countries and, together with the persistent burden of infectious diseases, further increase global health inequalities. Preventing obesity should be a priority from early stages of economic development, accompanied by population-level and personal interventions for blood pressure and cholesterol.

BackgroundMost analyses of risks to health focus on the total burden of their aggregate effects. The distribution of risk-factor-attributable disease burden, for example by age or exposure level, can inform the selection and targeting of specific interventions and programs, and increase cost-effectiveness.Methods and findingsFor 26 selected risk factors, expert working groups conducted comprehensive reviews of data on risk-factor exposure and hazard for 14 epidemiological subregions of the world, by age and sex. Age-sex-subregion-population attributable fractions were estimated and applied to the mortality and burden of disease estimates from the World Health Organization Global Burden of Disease database. Where possible, exposure levels were assessed as continuous measures, or as multiple categories. The proportion of risk-factor-attributable burden in different population subgroups, defined by age, sex, and exposure level, was estimated. For major cardiovascular risk factors (blood pressure, cholesterol, tobacco use, fruit and vegetable intake, body mass index, and physical inactivity) 43%-61% of attributable disease burden occurred between the ages of 15 and 59 y, and 87% of alcohol-attributable burden occurred in this age group. Most of the disease burden for continuous risks occurred in those with only moderately raised levels, not among those with levels above commonly used cut-points, such as those with hypertension or obesity. Of all disease burden attributable to being underweight during childhood, 55% occurred among children 1-3 standard deviations below the reference population median, and the remainder occurred among severely malnourished children, who were three or more standard deviations below median.ConclusionsMany major global risks are widely spread in a population, rather than restricted to a minority. Population-based strategies that seek to shift the whole distribution of risk factors often have the potential to produce substantial reductions in disease burden.

OBJECTIVE: To assess the impact on the reported cause-of-death patterns of a verbal autopsy coding strategy based on a review of every death by multiple coders versus a single coder. METHODS: Deaths in 45 villages (total population 180 162) in southern India were documented during 12 months in 2003-2004, and a standard verbal autopsy questionnaire was completed for each death. Two physician coders, each unaware of the other's decisions, assigned an underlying cause of death in accordance with the causes listed in the chapter headings of the International classification of diseases and related health problems, 10th revision (ICD-10). For the three chapter headings that applied to more than 100 of the deaths, agreement for subsets of causes of death within the chapter was also analysed. In the event of discrepancies, a third coder was used to finalize a cause of death. Cohen's kappa statistic (K) was used to measure levels of agreement between the two physician coders. FINDINGS: In total, 1354 deaths were documented, and a verbal autopsy was completed for 1329 (98%) of them. At the chapter heading level of the ICD-10, physician coders assigned the same cause to 1255 deaths (94%) (K = 0.93; 95% confidence interval: 0.92-0.94). The patterns of death derived from the causes assigned by each physician were all very similar to the patterns obtained through the consensus process, with the rank order of the 10 leading causes of death being the same for all three coding methods. CONCLUSION: Duplicate coding of verbal autopsy results has little advantage over a single-coder system for mortality surveillance or for identifying population patterns of death. Resources could be better diverted to other parts of the mortality surveillance process, such as validation.