In most low- and middle-income countries (LMICs), data on all-cause mortality are deficient. In addition to public discussion, healthcare decision-making, and policy responses, this constrains scientific understanding of levels, trends, and distribution of mortality (by gender, socioeconomic status, or other key markers of heterogeneity). This project focused on improving mortality estimation in India, the most populous country in the world, and a country with poor population health. The focus was on methodological innovation, using novel data, and investigating inequalities. This research was even more urgent given the paucity of data during the pandemic in most LMICs.
This project provided an assessment of the impact of the COVID-19 pandemic in India, using data collected at regular intervals by the demographic and health surveys. It established that this data was high-quality, and helped provide the first empirical estimates of life expectancy declines during the pandemic in India. It found large impacts of the pandemic – overall life expectancy declined by 2.6 years between 2019 and 2020. The project was also the first to establish that these declines in life expectancy were unequally distributed – female life expectancy declined more than male life expectancy, and marginalized groups experienced greater reductions in mortality. These results point out that pandemics can worsen existing social inequalities in health and mortality in LMICs. They also point to the possibility of measuring mortality reliably in LMIC settings, and in particular highlight the strengths of large-scale surveys that include mortality questions.
In related goals, the project provided methods for mortality estimation using data that asks households to report on recent deaths of household members. The project also assessed if longitudional data collection efforts which track mortality of adults between survey waves can help measure mortality. The outcome for both exercises was yes. In the context of the pandemic, the project also helped assess the reliability and completeness of civil registration data.
These goals are important for society because reducing mortality and improving health are fundamental human objectives. They are included in the sustainable development goals. Similarly, advancing methodologies and data science approaches that can help monitor mortality in low and middle income countries can help guide policy priorities and public discussions.
