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BACKGROUND: Mortality statistics are key inputs for evidence based health policy at national level. Little is known of the empirical basis for mortality statistics in China, which accounts for roughly one-fifth of the world's population. An adequate description of the evolution of mortality registration in China and its current situation is important to evaluate the usability of the statistics derived from it for international epidemiology and health policy. CURRENT SITUATION: The Chinese vital registration system currently covers 41 urban and 85 rural centres, accounting for roughly 8 % of the national population. Quality of registration is better in urban than in rural areas, and eastern than in western regions, resulting in significant biases in the overall statistics. The Ministry of Health introduced the Disease Surveillance Point System in 1980, to generate cause specific mortality statistics from a nationally representative sample of sites. Currently, the sample consists of 145 urban and rural sites, covering populations from 30,000 - 70,000, and a total of about 1 % of the national population. Causes of death are derived through a mix of medical certification and 'verbal autopsy' procedures, applied according to standard guidelines in all sites. Periodic evaluations for completeness of registration are conducted, with subsequent corrections for under reporting of deaths. CONCLUSION: Results from the DSP have been used to inform health policy at national, regional and global levels. There remains a need to critically validate the information on causes of death, and a detailed validation exercise on these aspects is currently underway. In general, such sample based mortality registration systems hold much promise as models for rapidly improving knowledge about levels and causes of mortality in other low-income populations.

There is considerable heterogeneity in the quality of cause-of-death statistics across Brazilian regions, especially for criteria such as completeness and ill-defined causes. These factors can influence generalizability and validity of reported causes of death, and must be considered in the interpretation and use of data for secondary descriptive analyses such as burden of disease estimation at regional level, with suitable adjustments to account for bias. The differences identified in this study could be a useful guide for defining measures and investments needed to improve data quality in Brazil.

VA is an imprecise tool for detecting leading causes of death among adults. However, much of the misclassification generally occurs within broad cause groups (e.g. CVD, respiratory diseases, and liver diseases). Moreover, compensating patterns of misclassification would appear to suggest that, in urban China at least, the method yields population-level cause-specific estimates that are reasonably reliable. These results suggest the possible utility of these methods in rural China, to back up the low coverage of medical certification of cause of death owing to poor access to health facilities there.

BackgroundVerbal autopsy (VA) is a practical method for determining probable causes of death at the population level in places where systems for medical certification of cause of death are weak. VA methods suitable for use in routine settings, such as civil registration and vital statistics (CRVS) systems, have developed rapidly in the last decade. These developments have been part of a growing global momentum to strengthen CRVS systems in low-income countries. With this momentum have come pressure for continued research and development of VA methods and the need for a single standard VA instrument on which multiple automated diagnostic methods can be developed.Methods and findingsIn 2016, partners harmonized a WHO VA standard instrument that fully incorporates the indicators necessary to run currently available automated diagnostic algorithms. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality. This VA instrument offers the opportunity to harmonize the automated diagnostic algorithms in the future.ConclusionsDespite all improvements in design and technology, VA is only recommended where medical certification of cause of death is not possible. The method can nevertheless provide sufficient information to guide public health priorities in communities in which physician certification of deaths is largely unavailable.The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality.

BackgroundAlmost 400,000 deaths are registered each year in Thailand. Their value for public health policy and planning is greatly diminished by incomplete registration of deaths and by concerns about the quality of cause-of-death information. This arises from misclassification of specified causes of death, particularly in hospitals, as well as from extensive use of ill-defined and vague codes to attribute the underlying cause of death. Detailed investigations of a sample of deaths in and out of hospital were carried out to identify misclassification of causes and thus derive a best estimate of national mortality patterns by age, sex, and cause of death.MethodsA nationally representative sample of 11,984 deaths in 2005 was selected, and verbal autopsy interviews were conducted for almost 10,000 deaths. Verbal autopsy procedures were validated against 2,558 cases for which medical record review was possible. Misclassification matrices for leading causes of death, including ill-defined causes, were developed separately for deaths inside and outside of hospitals and proportionate mortality distributions constructed. Estimates of mortality undercount were derived from "capture-recapture" methods applied to the 2005-06 Survey of Population Change. Proportionate mortality distributions were applied to this mortality "envelope" and ill-defined causes redistributed according to Global Burden of Disease methods to yield final estimates of mortality levels and patterns in 2005.ResultsEstimated life expectancy in Thailand in 2005 was 68.5 years for males and 75.6 years for females, two years lower than vital registration data suggest. Upon correction, stroke is the leading cause of death in Thailand (10.7%), followed by ischemic heart disease (7.8%) and HIV/AIDS (7.4%). Other leading causes are road traffic accidents (males) and diabetes mellitus (females). In many cases, estimated mortality is at least twice what is estimated in vital registration. Leading causes of death have remained stable since 1999, with the exception of a large decline in HIV/AIDS mortality.ConclusionsField research into the accuracy of cause-of-death data can result in substantially different patterns of mortality than suggested by routine death registration. Misclassification errors are likely to have very significant implications for health policy debates. Routine incorporation of validated verbal autopsy methods could significantly improve cause-of-death data quality in Thailand.

Although diagnostic misclassification is not uncommon in urban death registration data, they appear to balance each other at the population level. Compensating misclassification errors suggest that caution is required when drawing conclusions about particular chronic causes of adult death in China. Investment is required to improve the quality of cause attribution for health facility deaths, and to assess the validity of cause attribution for home deaths. Periodic assessments of the quality of cause of death statistics will enhance their usability for health policy and epidemiological research.