ObjectiveVerbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems.MethodsA literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification.FindingsA revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach.ConclusionsThe revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians.

SummaryBackgroundOver the past few decades, social and economic changes have had substantial effects on health and wellbeing in Russia. We aimed to use data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to evaluate trends in mortality, causes of death, years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and associated risk factors in Russia from 1980 to 2016.MethodsWe estimated all-cause mortality by use of a multistage modelling process that synthesised data from vital registration systems, surveys, and censuses. A composite measure of health loss due to both fatal and non-fatal disease burden (DALYs) was calculated as the sum of YLLs and YLDs for each age, sex, year, and location. Health progress was evaluated in comparison with patterns of change in similar countries by use of the Socio-demographic Index that was developed for GBD 2016.FindingsFollowing rapid decreases in life expectancy after the collapse of the Soviet Union, life expectancy at birth in Russia improved between 2006 and 2016. The all-cause mortality rate decreased by 16·6% (95% uncertainty interval 9·4–33·8) between 1980 and 2016. This overall decrease encompasses the cycles of sharp increases and plateaus in mortality that occurred before 2005. Child mortality decreased by 57·5% (53·5–61·1) between 2000 and 2016. However, compared with countries at similar Socio-demographic Index levels, rates of mortality and disability in Russia remain high and life expectancy is low. Russian men have a disproportionate burden of disease relative to women. In 2016, 59·2% (55·3–62·6) of mortality in men aged 15–49 years and 46·8% (44·5–49·5) of mortality in women were attributable to behavioural risk factors, including alcohol use, drug use, and smoking.InterpretationTrends in mortality in Russia from 1980 to 2016 might be related to complicated patterns of behavioural risk factors associated with economic and social change, to shifts in disease burden, and to changes in the capacity of and access to health care. Ongoing mortality and disability from causes and risks amenable to health-care interventions and behaviour modifications present opportunities to continue to improve the wellbeing of Russian citizens.FundingBill & Melinda Gates Foundation.

Measuring health inequalities is indispensable for progress in improving the health situation in the Region of the Americas, where the analysis of average values is no longer sufficient. Analyzing health inequalities is a fundamental tool for action that seeks greater equity in health. There are various measurement methods, with differing levels of complexity, and choosing one rather than another depends on the objective of the study. The purpose of this article is to familiarize health professionals and decision-making institutions with methodological aspects of the measurement and simple analysis of health inequalities, utilizing basic data that are regularly reported by geopolitical unit. The calculation method and the advantages and disadvantages of the following indicators are presented: the rate ratio and the rate difference, the effect index, the population attributable risk, the index of dissimilarity, the slope index of inequality and the relative index of inequality, the Gini coefficient, and the concentration index. The methods presented are applicable to measuring various types of inequalities and at different levels of analysis.

Over the past decade, according to several important indicators, health conditions have improved in the Region of health inequalities based on the use of various methods highlight the existence of important disparities among subregions and countries of the Americas that are not readily seen when using only the more-traditional methods for analyzing mortality and morbidity. There is also a need to incorporate the concepts of distribution and socioeconomic dimensions of health when interpreting a given situation. Using this approach will allow decisionmakers to target areas and populations that are in less-favorable conditions. A considerable body of aggregate data at the Regional and country levels from routine information systems is already availableóespecially on morbidity, mortality, and other health-related factorsóthat can be used on a regular basis to analyze health inequalities. These kinds of analyses may be regarded as a first step toward the identification of health inequities.Equity, health status, health status indicators, socioeconomic factors, Americas. ABSTRACTOver the past decade, health conditions have been steadily improving in the Region of the Americas, according to several indicators. This progress is the result of various social, environmental, cultural, and technological factors as well as the expanded coverage of health care services and public health programs. Nevertheless, these improvements have not shown the same intensity or momentum in every country or in every population group

With this type of epidemiologic study using GISs at the local level of health services, it is easy to see how a health event and its risk factors behave at a specific period in time. It is also possible to identify patterns in the spatial distribution of risk factors and in these factors' potential impact on health. Using GISs in an appropriate way will make it easier to deliver more effective, equitable public health services.