Inequality indices to monitor geographic differences in incidence, mortality and fatality rates over time during the COVID-19 pandemic

Background It is of interest to explore the variability in how the COVID-19 pandemic evolved geographically during the first twelve months. To this end, we apply inequality indices over regions to incidences, infection related mortality, and infection fatality rates. If avoiding of inequality in health is an important political goal, a metric must be implemented to track geographical inequality over time. Methods The relative and absolute Gini index as well as the Theil index are used to quantify inequality. Data are taken from international data bases. Absolute counts are transformed to rates adjusted for population size. Results Comparing continents, the absolute Gini index shows an unfavorable development in four continents since February 2020. In contrast, the relative Gini as well as the Theil index support the interpretation of less inequality between European countries compared to other continents. Infection fatality rates within the EU as well as within the U.S. express comparable improvement towards more equality (as measured by both Gini indices). Conclusions The use of inequality indices to monitor changes in geographic inequality over time for key health indicators is a valuable tool to inform public health policies. The absolute and relative Gini index behave complementary and should be reported simultaneously in order to gain a meta-perspective on very complex dynamics.

Automated summary

This study explored the geographical evolution of the COVID-19 pandemic using inequality indices, finding less inequality between European countries compared to other continents. The absolute Gini index showed unfavorable development in four continents since February 2020. The use of inequality indices to monitor changes in geographic inequality over time for key health indicators is a valuable tool to inform public health policies.