By providing examples of outlier countries, we do not imply the data are wrong or misreported in specific countries. While country circumstances will differ, we do consider that inequality in data quality has a significant role to play in the aggregate. The recording of vital statistics was already prior to the pandemic subject to considerable variation in data quality, where WHO (2018a) contains a detailed description of the various challenges. We believe that the pandemic accentuates these pre-existing challenges. As a result, the tally of the developing world is likely significantly underestimated by a margin that will far exceed that of the HICs.

Data quality concerns are not the preserve of the developing world. Indeed, we observe that the HICs themselves are grappling with considerable data quality challenges. Total deaths may be measured with more precision than infections—a reasonable assumption, especially in HICs that have better registration methods for vital statistics. Yet, there is a growing realization that COVID19 fatalities are being misattributed to other causes of death (The Economist, 2020b). By some estimates, reported death rates in selected countries could be underestimated by 60 percent, which would of course imply a significant increase in the already considerable severity of the mortality burden in those countries (Burn-Murdoch and others, 2020).

Perhaps for this reason it is unsurprising that Belgium—the country with the highest severity ratio in the world—has reported such a high death toll. Belgium has corrective measures to aggressively include deaths occurring in elderly-care homes based on symptoms shown and contacts made even if there was not a confirmed infection (Bloomberg, 2020). As a result, excess all-cause deaths closely match COVID-19 deaths, which inspires confidence in the quality of the data. While this may help explain why Belgium has the highest level of severity globally, it at the same time raises suspicion on the data of many other countries.

# **Perspective 2: Unrealized**

While data quality may play a significant role, the vast discrepancies cannot be reasonably explained by data quality alone. The on-the-ground realities of many developing countries do not indicate acute health emergencies. The main reason for the excessive inequality must be different.

Gieseke (2020) argues that eventually everyone will be exposed to the coronavirus and most people will get infected. He notes that the real pandemic is the one that happens below the surface and spreads like wildfire between countries and almost always from younger people with no or weak symptoms to other people who will also have mild symptoms. While suppressive containment policies will be important to flatten the curve and decrease fatalities that way, they may result in flare-ups once restrictions are lifted. Our hopes are pinned on the development of effective drugs, but these take time to be developed and their effectiveness is not guaranteed.

This harrowing outlook will hopefully not materialize but we must consider that the most plausible explanation is that the pandemic still has to run its course through the age distributions of the world. This conclusion is certainly borne out in recent developments which show that the excessive concentration of the pandemic is de-compacting as the world’s epicenters are increasingly shifting from high-income countries to other locations in developing regions.

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