  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.
