Building Capacity for Mortality Statistics Programs: Perspectives from the Indonesian Experience

Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic

BACKGROUND

Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civil Registration System (CRS) is affected by incompleteness of death recording that varies by sex, age and location.

METHODS

Under-reporting of CRS 2019 deaths was assessed for three age groups (< 5 years, 15-59 years and ≥60 years) at subnational level, through comparison with age-specific death rates from alternate sources. Age-specific corrections for under-reporting were applied to derive adjusted death counts by sex for each location. These were used to compute life expectancy (LE) at birth by sex in 2019, which were compared with subnational LEs from the Global Burden of Disease (GBD) 2019 Study.

RESULTS

A total of 9.92 million deaths (95% UI 9.70 to 10.02) were estimated across India in 2019, about 2.28 million more than CRS reports. Adjustments to under-five and elderly mortality accounted for 30% and 56% of additional deaths, respectively. Adjustments in Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh accounted for 75% of all additional deaths. Adjusted LEs were below corresponding GBD estimates by ≥2 years for males at national level and in 20 states, and by ≥1 year for females in 12 states.

CONCLUSIONS

These results represent the first-ever subnational mortality estimates for India derived from CRS reported deaths, and serve as a baseline for assessing excess mortality from the COVID-19 pandemic. Adjusted life expectancies indicate higher mortality patterns in India than previously perceived. Under-reporting of infant deaths and those among women and the elderly is evident in many locations. Further CRS strengthening is required to improve the empirical basis for local mortality measurement across the country.

Mortality estimates for WHO SEAR countries: problems and prospects

Cause-specific mortality estimates for 11 countries located in the WHO’s South East Asia Region (WHO SEAR) are generated periodically by the Global Burden of Disease (GBD) and the WHO Global Health Estimates (GHE) analyses. A comparison of GBD and GHE estimates for 2019 for 11 specific causes of epidemiological importance to South East Asia was undertaken. An index of relative difference (RD) between the estimated numbers of deaths by sex for each cause from the two sources for each country was calculated, and categorised as marginal (RD=±0%–9%), moderate (RD=±10%–19%), high (RD=±20%–39%) and extreme (RD>±40%). The comparison identified that the RD was >10% in two-thirds of all instances. The RD was ‘high’ or ‘extreme’ for deaths from tuberculosis, diarrhoea, road injuries and suicide for most SEAR countries, and for deaths from most of the 11 causes in Bangladesh, DPR Korea, Myanmar, Nepal and Sri Lanka. For all WHO SEAR countries, mortality estimates from both sources are based on statistical models developed from an international historical cause-specific mortality data series that included very limited empirical data from the region. Also, there is no scientific rationale available to justify the reliability of one set of estimates over the other. The characteristics of national mortality statistics systems for each WHO SEAR country were analysed, to understand the reasons for weaknesses in empirical data. The systems analysis identified specific limitations in structure, organisation and implementation that affect data completeness, validity of causes of death and vital statistics production, which vary across countries. Therefore, customised national strategies are required to strengthen mortality statistics systems to meet immediate and long-term data needs for health policy and research, and reduce dependence on current unreliable modelled estimates.

Empiricism in non-communicable disease mortality measurement for the Asia-Pacific: lost in translation

Control of non-communicable diseases (NCDs) is a key target for the United Nations Sustainable Development Goals (SDGs) for 2030. Available information indicates that countries in the Asia-Pacific Region accounted for 63% of the global NCD mortality burden in 2016. The United Nations Economic and Social Commission for the Asia Pacific (UNESCAP) Regional SDG progress report for 2020 included estimates of trends in NCD mortality rates from 2000 to 2016, which showed considerable variation in national NCD mortality by sex and location.

However, while the UNESCAP report states that there was sufficient primary data to derive these NCD mortality estimates for all countries, the critical gaps in availability of national data on causes of death in the Asia-Pacific region are well known. A closer review identified that the UNESCAP obtained these estimates from the United Nations Statistics Division, which in turn obtained the same estimates from WHO. Further analysis revealed that these organisations used varying and often inconsistent terms to describe estimation methodology as well as primary data availability for different countries, with substantial potential for misinterpretation.

The analysis also found that for countries without primary data, WHO reported NCD mortality estimates were based on complex epidemiological models developed for the Global Burden of Disease (GBD) Study, and this contradicts the UNESCAP rating of primary data sufficiency. The GBD Study also derives modelled cause of death estimates for countries with national data, but these were different from WHO estimates for these countries. This article discusses prevailing international practices in using modelled estimates as a substitute for empirical data, and the implications of these practices for health policy. In conclusion, a strategic approach to strengthen national mortality statistics programmes in data deficient countries is presented, to improve NCD mortality measurement in the Asia-Pacific Region.

The civil registration system is a potentially viable data source for reliable subnational mortality measurement in India

Introduction

The Indian national Civil Registration System (CRS) is the optimal data source for subnational mortality measurement, but is yet under development. As an alternative, data from the Sample Registration System (SRS), which covers less than 1% of the national population, is used. This article presents a comparison of mortality measures from the SRS and CRS in 2017, and explores the potential of the CRS to meet these subnational data needs.

Methods

Data on population and deaths by age and sex for 2017 from each source were used to compute national-level and state-level life tables. Sex-specific ratios of death probabilities in five age categories (0–4, 5–14, 15–29, 30–69, 70–84) were used to evaluate CRS data completeness using SRS probabilities as reference values. The quality of medically certified causes of death was assessed through hospital reporting coverage and proportions of deaths registered with ill-defined causes from each state.

Results

The CRS operates through an extensive infrastructure with high reporting coverage, but child deaths are uniformly under-reported, as are female deaths in many states. However, at ages 30–69 years, CRS death probabilities are higher than the SRS values in 15 states for males and 10 states for females. SRS death probabilities are of limited precision for measuring mortality trends and differentials. Data on medically certified causes of death are of limited use due to low hospital reporting coverage.

Conclusions

The Indian CRS is more reliable than the SRS for measuring adult mortality in several states. Targeted initiatives to improve the recording of child and female deaths, to strengthen the reporting and quality of medically certified causes of death, and to promote use of verbal autopsy methods can establish the CRS as a reliable source of subnational mortality statistics in the near future.

Premature adult mortality in India: what is the size of the matter?

BACKGROUND

Reducing adult mortality by 2030 is a key component of the United Nations Sustainable Development Goals (UNSDGs). Monitoring progress towards these goals requires timely and reliable information on deaths by age, sex and cause. To estimate baseline measures for UNSDGs, this study aimed to use several different data sources to estimate subnational measures of premature adult mortality (between 30 and 70 years) for India in 2017.

METHODS

Age-specific population and mortality data were accessed for India and its 21 larger states from the Civil Registration System and Sample Registration System for 2017, and the most recent National Family and Health Survey. Similar data on population and deaths were also procured from the Global Burden of Disease Study 2016 and the National Burden of Disease Estimates Study for 2017. Life table methods were used to estimate life expectancy and age-specific mortality at national and state level from each source. An additional set of life tables were estimated using an international two-parameter model life table system. Three indicators of premature adult mortality were derived by sex for each location and from each data source, for comparative analysis RESULTS: Marked variations in mortality estimates from different sources were noted for each state. Assuming the highest mortality level from all sources as the potentially true value, premature adult mortality was estimated to cause a national total of 2.6 million male and 1.8 million female deaths in 2017, with Bihar, Maharashtra, Tamil Nadu, Uttar Pradesh and West Bengal accounting for half of these deaths. There was marked heterogeneity in risk of premature adult mortality, ranging from 351 per 1000 in Kerala to 558 per 1000 in Chhattisgarh among men, and from 198 per 1000 in Himachal Pradesh to 409 per 1000 in Assam among women.

CONCLUSIONS

Available data and estimates for mortality measurement in India are riddled with uncertainty. While the findings from this analysis may be useful for initial subnational health policy to address UNSDGs, more reliable empirical data is required for monitoring and evaluation. For this, strengthening death registration, improving methods for cause of death ascertainment and establishment of robust mortality statistics programs are a priority.

Mortality in India established through verbal autopsies (MINErVA): Strengthening national mortality surveillance system in India

Background

Following data access and storage concerns, Government of India transferred the management of its Sample Registration System (SRS) based mortality surveillance (formerly known as the Million Death Study) to an Indian agency. This paper introduces the new system, challenges it faced and its vision for future.

Methods

The All India Institute of Medical Sciences (AIIMS), New Delhi, the new nodal agency, established the “Mortality in India Established through Verbal Autopsy” (MINErVA) platform with state level partners across India in November 2017. The network in its first three years has undertaken capacity building of supervisors conducting verbal autopsy under the SRS, established a panel of trained physician reviewers and developed three IT-based platforms for training, quality control and coding. Coding of VA forms started from January 2015 onwards, and the cause specific mortality fractions (CSMF) of the first 14 185 adult verbal autopsy (VA) records for 2015 were compared with earlier published data for 2010-2013 to check for continuity of system performance.

Results

The network consists of 25 institutions and a panel of 676 trained physician reviewers. 916 supervisors have been trained in conducting verbal autopsies. More than 75 000 VA forms have been coded to date. The median time taken for finalizing cause of death on the coding platform is 37 days. The level of physician agreement (67%) and proportion of VA forms requiring adjudication (12%) are consistent with published literature. Preliminary CSMF estimates for 2015 were comparable with those for 2010-2013 and identified same top ten causes of death. In addition to the delay, two major challenges identified for coding were language proficiency of physician reviewers vis-à-vis language of narratives and quality of verbal autopsies. While an initial strategic decision was made to consolidate the system to ensure continuity, future vision of the network is to move towards technology-based solutions including electronic data capture of VAs and its analysis and improving the use of mortality data in decision making.

Conclusion

MINErVA network is now fully functional and is moving towards achieving global standards. It provides valuable lessons for other developing countries to establish their own mortality surveillance systems.

Elements of a strategic approach for strengthening national mortality statistics programmes

Information on cause-specific mortality from civil registration and vital statistics (CRVS) systems is essential for health policy and epidemiological research. Currently, there are critical gaps in the international availability of timely and reliable mortality data, which limits planned progress towards the UN Sustainable Development Goals. This article describes an evidence-based strategic approach for strengthening mortality data from CRVS systems. National mortality data availability scores from the Global Burden of Disease study were used to group countries into those with adequate, partial or negligible mortality data. These were further categorised by geographical region and population size, which showed that there were shortcomings in availability of mortality data in approximately two-thirds of all countries. Existing frameworks for evaluating design and functional status of mortality components of CRVS systems were reviewed to identify themes and topics for assessment. Detailed national programme assessments can be used to investigate systemic issues that are likely to affect death reporting, cause of death ascertainment and data management. Assessment findings can guide interventions to strengthen system performance. The strategic national approach should be customised according to data availability and population size and supported by human and institutional capacity building. Countries with larger populations should use an incremental sampling approach to strengthen CRVS systems and use interim data for mortality estimation. Periodic data quality evaluation is required to monitor system performance and scale up interventions. A comprehensive implementation and operations research programme should be concurrently launched to evaluate the feasibility, success and sustainability of system strengthening activities.