Read on Twitter
Data and statistics around the #coronavirus are riddled with problems and often create confusion. That's why I've written a short paper explaining the most common pitfalls, published open access by @Intereconomics_: (1/n) https://www.intereconomics.eu/contents/year/2020/number/3/article/common-pitfalls-in-the-interpretation-of-covid-19-data-and-statistics.html
Pitfall 1: Measurement of lethality. Case fatality rate (CFR), infection fatality rate (IFR), and mortality rate (MR) (or death rate) are different concepts. They shouldn't be mixed up. Rule of thumb regarding their magnitude: CFR>IFR>MR. (2/n)
Pitfall 2: Comparability: Demographics play a huge role for the lethality of COVID-19, so check the age distribution behind the cases. Some readers will notice the similarity of this graph to the one in my @Medium story from March ( https://medium.com/@andreasbackhausab/coronavirus-why-its-so-deadly-in-italy-c4200a15a7bf). (3/n)
Pitfall 3: Death count. Are we over-/undercounting COVID-19 deaths? Look at the deviation of all deaths in 2020 from the previous average. How much excess mortality is explained by COVID-19? @jburnmurdoch, @OurWorldInData, @TheEconomist have graphs. (4/n) https://www.ft.com/content/6bd88b7d-3386-4543-b2e9-0d5c6fac846c
Pitfall 4: Reporting lags. The newest public data releases are often incomplete and subject to major revisions. Don’t rely on them for far-fetched conclusions. Statistics Sweden is very transparent about this: (5/n)
Pitfall 5: Sample selection bias. Think about why a person is included in a sample. Often, we see the sample is not representative of the population. We can still compute statistics, but they don’t generalize. @CT_Bergstrom has threads and courses: (6/n) https://callingbullshit.org/
Pitfall 6: Endogeneity of policy interventions. Cross-country comparisons of lockdown effects are biased. Countries that locked down hard also had many COVID-19 deaths early on. This determined both the lockdown policy and the later death toll. More: (7/n) https://p-hunermund.com/2018/10/15/sample-selection-vs-selection-into-treatment/
Some of the great researchers whose works appear in the paper: @drjenndowd @c_dudel @HelenBranswell @AdamJKucharski @christianbaye13 @kuhnmo Many thanks also to @chris_breu @ZBW_news @Zeitschrift_WD @JifferBourg1 @CEPS_thinktank! (8/n)
