Background: The COVID-19 pandemic has caused major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shock at the sub-national level, rigorously accounting for the different sources of uncertainty.
Methods: Using death registration data from Belgium, we first assess the change in the heterogeneity of subnational standardized mortality ratios in 2020, when compared to previous years. We then measure the shock of the pandemic using district-level values of life expectancy, comparing the observed and projected districts life expectancy, accounting for all sources of uncertainty (related to the life-table construction at district level and to the projection methods at country and district level). The Bayesian modelling approach makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.
Results: The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial, with some districts barely showing any impact whereas the Bruxelles-Capital and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in mortality levels ' heterogeneity at a subnational level in comparison to past years measured by both the standardized mortality ratios and the life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.
Conclusion: Developing sub-national mortality estimates with their uncertainty is key to understanding why certain areas have been hard hit in comparison to others.