Comment on: A systematic review and meta-analysis of published research data on COVID-19 infection-fatality rates

TL;DR

This paper critically examines existing COVID-19 IFR studies, highlighting scientific flaws and misrepresentations that impact policy decisions during the pandemic.

Contribution

It identifies methodological flaws and inaccuracies in previous IFR research and critiques a widely cited meta-analysis for misrepresentation and duplication.

Findings

Many studies have flawed equations and unjustified assumptions.

Meta-analysis misrepresents original IFR values and duplicates data.

Research flaws significantly affect policy-making during COVID-19.

Abstract

The infection fatality rate (IFR) of COVID-19 is one of the measures of disease impact that can be of importance for policy making. Here we show that many of the studies on which these estimates are based are scientifically flawed for reasons which include: nonsensical equations, unjustified assumptions, small sample sizes, non-representative sampling (systematic biases), incorrect definitions of symptomatic and asymptomatic cases (identified and unidentified cases), typically assuming that cases which are asymptomatic at the time of testing are the same as completely asymptomatic (never symptomatic) cases. Moreover, a widely cited meta-analysis misrepresents some of the IFR values in the original studies, and makes inappropriate duplicate use of studies, or the information from studies, so that the results that are averaged are not independent from each other. The lack of validity of these research papers is of particular importance in view of their influence on policies that affect lives and well-being in confronting a worldwide pandemic.