Flaws and Uncertainties in Pandemic Global Excess Death Calculations
36 Pages Posted: 14 Feb 2023 Last revised: 13 Apr 2023
Date Written: January 30, 2023
Several teams have been publishing global estimates of excess deaths during the COVID-19 pandemic. Here, we examine potential flaws and underappreciated sources of uncertainty in global excess death calculations. Adjusting for changing population age structure is essential. Otherwise, excess deaths are markedly overestimated in countries that have increasingly aging populations. Adjusting for changes in other high-risk indicators, such as residence in long-term facilities, may also make a difference. Death registration is highly incomplete in most countries; completeness corrections should allow for substantial uncertainty and consider that completeness may have changed during pandemic years. Excess death estimates have high sensitivity to modeling choice. Therefore different options should be considered and the full range of results should be shown for different choices of pre-pandemic reference periods and imposed models. Any post-modeling corrections in specific countries should be guided by pre-specified rules. Modeling of all-cause mortality (ACM) in countries that have ACM data and extrapolating these models to other countries is precarious; models may lack transportability. Existing global excess death estimates underestimate the overall uncertainty that is multiplicative across diverse sources of uncertainty. Informative excess death estimates require risk stratification, including age groups and ethnic/racial strata. Data to-date suggest a death deficit among children during the pandemic and marked socioeconomic differences in deaths, widening inequalities. Finally, causal explanations require great caution. It is difficult to disentangle deaths attributed directly to SARS-CoV-2, indirect pandemic effects, and effects from measures taken. Globally, deaths directly due to SARS-CoV-2 may be the minority of calculated excess deaths.
Funding Information: NIH R35 GM122543 (Levitt).
Declaration of Interests: None.
Keywords: COVID-19, mortality, excess deaths, bias, demography
JEL Classification: C00
Suggested Citation: Suggested Citation