Geography, Not Lockdowns, Explains the Global Pattern of Excess Mortality

Throughout the pandemic, commentators have relied on ‘COVID-19 deaths per million people’ as a measure of the disease’s lethality. While this is not unreasonable for making comparisons within Europe, it is less justifiable for other parts of the world, where there has been substantial underreporting of COVID-19 deaths.

A better measure to use is excess mortality, i.e., the number of deaths in excess of what you’d expect based on previous years. This measure does not vary with factors like testing infrastructure or the criteria for assigning cause of death. (Though the best measure is age-adjusted excess mortality.)

In an unpublished study, the researchers Ariel Karlinsky and Dmitry Kobak have compiled all the available data on excess mortality. Their database – which they’ve termed the ‘World Mortality Dataset’ – allows us to make more meaningful comparisons across countries. 

Unfortunately, data are not yet available for most of the countries in Sub-Saharan Africa, Asia and the Middle East. However, the database does encompass Europe, much of Central Asia and the Americas, and parts of East Asia. Countries with available data are shown in blue in the map below:

Note that Karlinsky and Kobak did not take the usual approach of using the average of the last five years as the baseline. Rather, they took the superior approach of using a linear trend over the last five years. If deaths have been increasing year-on-year, their approach will yield a higher baseline, compared to using the five-year average. (See here for a visual explanation.)