The Australian mortality data are a foundational health dataset which supports research, policy and planning. The COVID-19 pandemic necessitated the need for more timely mortality data that could assist in monitoring direct mortality from the virus as well as indirect mortality due to social and economic societal change. This paper discusses the evolution of mortality data in Australia during the pandemic and looks at emerging opportunities associated with electronic infrastructure such as electronic Medical Certificates of Cause of Death (eMCCDs), ICD-11 and automated coding tools that will form the foundations of a more responsive and comprehensive future mortality dataset.

Background: Socioeconomic inequalities in mortality are evident in all high-income countries and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons. Methods: Using Australian Census (2016) linked to 13-months of Death Registrations data (2016-17), we estimated relative rates (RR) and rate differences (RD, per100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high education (tertiary), for individual causes of death (among those 25-84y) and grouped according to preventability (25-74y), separately by sex and age group, adjusting for age, using negative binomial regression. Results: Among 13.9M people contributing 14 452 732 person-years, 84 743 deaths occurred. We observed inequalities in most causes of death for each age-sex group. Among men aged 25-44y, absolute and relative inequalities (low versus high education) were largest for injuries, e.g. transport accidents (RR=10.1 [95%CI: 5.4-18.7], RD=21.1 [15.9-26.3]). Among those aged 45-64y, inequalities were greatest for chronic diseases, e.g. lung cancer (men RR=6.6 [4.9-8.9], RD=55.6 [51.1-60.1]) and ischaemic heart disease (women RR=5.8 [3.7-9.1], RD=19.2 [17.0-21.5]), with similar patterns for people aged 65-84y. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men. Conclusions: Australian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population. Key messages: Using linked Australian Census (2016) and Death Registrations data (2016-17), we provide the first estimates of education-related inequalities in cause-specific mortality for Australia, broadly suitable for international comparisons. Among men aged 25-44 years, inequalities were largest for injuries, with mortality rates among those with low education six-to-ten times that of those with high education. Among the mid- and older-age groups, inequalities were largest for chronic diseases, where mortality rates among those with the lowest education were between two- and seven-times those with the highest education. In 2016-17, around half of all deaths for men and one-third of deaths for women aged 25-84 were associated with less than tertiary education. The majority of these excess deaths were attributable to leading causes. The substantial inequalities seen in preventable deaths highlight ongoing opportunities to reduce inequalities in mortality and to improve the overall health of the Australian population. Australian estimates are generally consistent with, but higher than, those for comparable countries and earlier time periods, but further standardisation of methods and reporting would enhance the validity of such comparisons