Abstract

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. 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. 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). 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.

Highlights

  • It is of interest to evaluate the distributional inequality of key indicators representing COVID-19 effects: Incidence, mortality, and the infection fatality

  • The relative Gini as well as the Theil index support the interpretation of less inequality between European countries compared to other continents

  • The absolute and relative Gini index behave complementary and should be reported simultaneously in order to gain a meta-perspective on very complex dynamics

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Summary

Introduction

It is of interest to evaluate the distributional inequality (between regions, over time) of key indicators representing COVID-19 effects: Incidence (rates, IR), mortality (rates, MR), and the infection fatality (rate, IFR) These measures inform global as well as regional health policies. It is of interest to study inequality across regions with a common health policy framework, such as the European Union (EU) or the United States of America (U.S.) Such maps or listings are not accompanied by general purpose measures to quantify heterogeneity or inequality. 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.

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