While demography plays a confounding role, the demographic structure of the world contradicts the patterns of COVID-19 mortality observed thus far. Poorer countries will generally have younger age structures, but their collective weight in the global elderly population is nevertheless very large (Figure 8.B). This is because the developing world is very populous and has registered significant population aging as well (World Bank, 2016). As a result, it counts many more people in the older age cohorts than the HICs combined: the developing world’s 70+ population is 1.8 times bigger than that of HICs; its 60+ population is 2.4 times larger.

# **The Share of the Developing World Could Be Three Times Larger**

To crystalize this line of reasoning further, we conduct a two-step thought experiment. First, what share in global COVID-19 mortality would developing countries claim if we were to apply a common set of assumptions of infectivity and fatality to the age distributions of the countries of the world? Second, how would such counterfactual simulations be affected if we relax the requirement that common infectivity and fatality parameters are applied across the world?

The infection prevalence ratio (IPR) and the infection fatality ratio (IFR) are the two key epidemiological parameters needed for the first step of this thought experiment. It is well recognized that at this still-early stage of the pandemic, there is considerable uncertainty about the true or eventual values for the IPR and IFR parameters. This uncertainty will have huge implications for the absolute count of fatalities, but it does not affect the distribution of the death toll across countries if we assume that the same parameters apply to all countries (Dowd and others, 2020). First-order changes in the levels of the IPR and the IFR will produce multiplicative changes to both the numerator and denominator that wash out as we calculate the global shares.

We assume that the infection prevalence ratio is independent of age. As argued by Verity and others (2020), this is a reasonable assumption consistent with previous studies of respiratory infections. Following Dowd and others (2020), we apply a common IPR, which we set at an arbitrary 10 percent of the population. Again, this number may be off by a wide margin, but as long as we treat all countries the same for the purpose of this thought experiment, the exact level of this parameter does not matter for the calculation of the shares.

We use the age-stratified IFR estimates for different age cohorts by Verity and others (2020), which are corrected for censoring and ascertainment bias.<sup>9</sup> Censoring bias occurs because during the early stage of an epidemic the distribution of observed time lags between the onset of symptoms and the outcome of death or recovery is censored. Ascertainment bias arises from the fact that surveillance of a newly emerged pathogen is typically biased towards detecting clinically severe cases, especially at the start of an epidemic when diagnostic capacity is low.

> 9 The corrected IFR estimates of Verity and others (2020) are based on a synthesis of data from a range of surveillance settings in Wuhan and elsewhere in China. The average IFR is 0.66 percent, with an increasing profile for age: 0.6 percent for those 50-60, 1.9 percent for those 60-70, 4.3 percent for those 70-80 and 7.8 percent for the 80+ population (see also Figure 10).

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