IFR calculation for Italy
We focus on the area in Italy that experienced the initial outbreak of COVID-19 and estimated a Bayesian model fitting age-stratified mortality data from 2020 and previous years. We also assessed the sensitivity of our estimates to alternative assumptions on the proportion of population infected. Findings: We estimate an overall infection fatality rate of 1.29% (95% credible interval [CrI] 0.89 - 2.01), as well as large differences by age, with a low infection fatality rate of 0.05% for under 60 year old (CrI 0-.19) and a substantially higher 4.25% (CrI 3.01-6.39) for people above 60 years of age. In our sensitivity analysis, we found that even under extreme assumptions, our method delivered useful information. For instance, even if only 10% of the population were infected, the infection fatality rate would not rise above 0.2% for people under 60. Interpretation: Our empirical estimates based on population level data show a sharp difference in fatality rates between young and old people and firmly rule out overall fatality ratios below 0.5% in populations with more than 30% over 60 years old.
https://www.medrxiv.org/conten…101/2020.04.18.20070912v1
they are comparing mortality rates with previous years, which should deal with over-counting
In order to motivate the use of administrative death counts for our infection
fatality rate estimation, we begin by analysing patterns in overall mortality
in 2020 and previous years. In particular, on every day between February
21st (the beginning of the outbreak) and April 4th the difference between
the number of 2020 deaths and the 2015-2019 average has been computed for
total population and for different age groups.
Note that this is in line with the 0.66% IFR for Wuhan because of Italy's very old population.