To summarize, we have (a) people who get COVID-19 and have reported; (b) people who get the SARS-CoV-2 virus and have reported, and who may not necessarily develop COVID-19 (although they are counted as if they have done so); (c) people who report because they fear they have the virus, but who test negative (so we assume they have not had the virus); (d) people who have the virus but do not report (meaning we can only estimate how many such people there are); and (e) people who have other conditions that could be mistaken for the virus and who do not report (meaning that counting them would skew our already uncertain estimate of virus cases that have gone unreported).
Trying to figure out an accurate fatality rate depends on how we count these different categories. It is a tricky business, rife with uncertainty. Yet it’s what must be done in order to grasp whether we are dealing with something that is just marginally worse than flu, or rather is significantly worse, even exponentially worse. Things appear deceptively dire if we calculate death rate solely by reference to reported COVID-19 cases; but the picture is deceptively benign if we measure deaths against an inflated conjecture about the non-reporting population.
I suspect that this explains the ostensible contradiction between Dr. Fauci’s two comments on the fatality rate.
Andrew C. McCarthy, “More Thoughts on Computing the COVID-19 Fatality Rate” at National Review