RESUMO
How deadly is an infection with SARS-CoV-2 worldwide over time? This information is critical for developing and assessing public health responses on the country and global levels. However, imperfect data have been the most limiting factor for estimating the COVID-19 infection fatality burden during the first year of the pandemic. Here we leverage recently emerged compelling data sources and broadly applicable modeling strategies to estimate the crude infection fatality rate (cIFR) in 77 countries from 28 March 2020 to 31 March 2021, using 2.4 million reported deaths and estimated 435 million infections by age, sex, country, and date. The global average of all cIFR estimates is 1.2% (10th to 90th percentile: 0.2% to 2.4%). The cIFR varies strongly across countries, but little within countries over time, and it is often lower for women than men. Cross-country differences in cIFR are largely driven by the age structures of both the general and the truly infected population. While the broad trends and patterns of the cIFR estimates are more robust, we show that their levels are uncertain and sensitive to input data and modeling choices. In consequence, increased efforts at collecting high-quality data are essential for accurately estimating the cIFR, which is a key indicator for better understanding the health and mortality consequences of this pandemic.
RESUMO
Understanding how widely COVID-19 has spread is critical for examining the pandemics progression. Despite efforts to carefully monitor the pandemic, the number of confirmed cases may underestimate the total number of infections. We introduce a demographic scaling model to estimate COVID-19 infections using an broadly applicable approach that is based on minimal data requirements: COVID-19 related deaths, infection fatality rates (IFRs), and life tables. As many countries lack reliable estimates of age-specific IFRs, we scale IFRs between countries using remaining life expectancy as a marker to account for differences in age structures, health conditions, and medical services. Across 10 countries with most COVID-19 deaths as of May 13, 2020, the number of infections is estimated to be four [95% prediction interval: 2-11] times higher than the number of confirmed cases. Cross-country variation is high. The estimated number of infections is 1.4 million (six times the number of confirmed cases) for Italy; 3.1 million (2.2 times the number of confirmed cases) for the U.S.; and 1.8 times the number of confirmed cases for Germany, where testing has been comparatively extensive. Our prevalence estimates, however, are markedly lower than most others based on local seroprevalence studies. We introduce formulas for quantifying the bias that is required in our data on deaths in order to reproduce estimates published elsewhere. This bias analysis shows that either COVID-19 deaths are severely underestimated, by a factor of two or more; or alternatively, the seroprevalence based results are overestimates and not representative for the total population.
