Crude infection fatality rate is a key indicator in understanding COVID-19 mortality

By Saurabh ChaturvediReviewed by Aimee MolineuxDec 21 2021

In a recent study posted to the medRxiv* preprint server, researchers leveraged recent data sources and broadly applicable modeling strategies to calculate the crude infection fatality rate (cIFR) in 77 countries from 28 March 2020 to 31 March 2021.

They used data on cumulative numbers of reported deaths by age from the COVerAGE database and a demographic scaling model to estimate cumulative numbers of infections by age.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Information on global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related mortality over time is critical for developing and assessing public health responses on both country and global levels. Estimating and analyzing the cIFR in many countries over time is essential for managing and learning from this global health crisis.

Understanding the need and role of cIFR

The cIFR is defined as a total number of deaths over a total number of infections, and limited data is a major challenge in estimating global cIFR over time. Other factors affecting cIFR estimation included inadequate testing coverage and test sensitivity, cause-of-death misclassification, and errors and delays in reporting coronavirus disease 2019 (COVID-19)-related deaths and cases.

Also, the numbers of reported deaths have often not been harmonized by age and sex over time; and the number of positive cases underestimates the total numbers of infected individuals. The case fatality rate for some countries can be estimated based on early but limited data on COVID-19; however, estimating cIFR in many countries over time has been difficult because of the unknown size of the truly infected population.

The study

The approach employed by this study to estimate cumulative numbers of infections by age used age-specific IFRs from China as the baseline which scales them to other countries by assuming that age-specific IFRs vary across countries proportionally to remaining life expectancy. The remaining life expectancy captures vulnerability to COVID-19 due to age, pre-existing conditions, and inadequate medical services. The researchers also assumed that the scaled baseline IFRs by age is constant within countries over time. Improvement in medical treatment, shortages of critical medical equipment, or spread of deadlier SARS-CoV-2 variants may also change the age-specific IFRs. The researchers also explored the sensitivity of cIFR estimates to deviations from these key assumptions.

This study used the best available data and advanced methods that avoid biases in the infected population to estimate the cIFR. Since the data was imperfect and modeling assumptions were strong, the researchers emphasized interpreting the broad patterns and trends of the cIFR that are likely to withstand systematic bias. They also analyzed the sensitivity of cIFR estimates to input data from various sources using (i) three different baseline IFRs by age, (ii) reported or estimated excess deaths, and (iii) estimated or confirmed cases. These sensitivity analyses suggested that the broad patterns were resistant to changes; however, the overall estimated level of cIFR varies depending on the data and modeling choice.

Conclusion

The study data helped to draw a landscape of the level, global variation, and temporal development of the COVID-19 infection fatality burden during the first year of the coronavirus pandemic. The cIFR varies strongly across countries, but little within countries over time, and it is often lower for women than men.

The analysis suggested that the age structures of both the general and the truly infected population are key drivers of the level and global variation of the cIFR. Consequently, increased efforts at collecting high-quality data are important for accurately estimating the cIFR, which is a key indicator for understanding the health and mortality consequences of this pandemic better.

Estimating and analyzing the cIFR in many countries over time is important for managing and learning from this global health crisis.”

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.