Now, leaving aside some of the other issues with using these studies, let's look at the simple fact that only one was even remotely representative of the population of Wuhan
-
Show this thread
-
The blood donor study is enormously unrepresentative. The population is (as with most blood donors) MUCH younger than the general poppic.twitter.com/Kk4E5y2JCM
1 reply 0 retweets 29 likesShow this thread -
The larger single-site study literally says at the start that a major limitation is the biased samplepic.twitter.com/d834C8m5gT
1 reply 0 retweets 30 likesShow this thread -
The smaller single-site study includes hospitalized patients as well as people returning to work at a single location in a city of 11 million. Not even remotely representative of the populationpic.twitter.com/spWByih9lW
1 reply 0 retweets 26 likesShow this thread -
The final study was a large, carefully designed serosurvey that was representative not just of the city of Wuhan but also surrounding regionspic.twitter.com/g9bsNGFGWH
1 reply 0 retweets 31 likesShow this thread -
For the four serosurveys, using Professor Ioannidis' methodology, the inferred IFRs are: 1. 0.45% 2. 0.35% 3. 0.42% 4. 0.82% So the representative sample implies an IFR double that of the biased samples
1 reply 1 retweet 38 likesShow this thread -
Health Nerd Retweeted Health Nerd
This actually accords with published data. There is some fairly strong evidence that selection bias can double your estimate of seroprevalence (thus halving the estimate of IFR)https://twitter.com/GidMK/status/1381391856773197824?s=20 …
Health Nerd added,
Health NerdVerified account @GidMKFascinating study demonstrating the issues with selection bias in seroprevalence estimates Using a selected sample of participants, the estimated prevalence of past COVID-19 infection doubled (!) https://www.nature.com/articles/s41467-021-22351-5#Sec2 … pic.twitter.com/pqN5l1SA41Show this thread1 reply 0 retweets 33 likesShow this thread -
Now, the fourth seroprevalence sample was not published until after Prof Ioannidis' paper came out, but the point here is that the three samples included in the paper are not sufficient to infer infections in the population
1 reply 0 retweets 31 likesShow this thread -
Health Nerd Retweeted Atomsk's Sanakan
All 3 estimates of the IFR that use biased sampling and survey methodology are half the more rigorous data. This inclusion of inappropriate estimates is repeated numerous times in the IFR review
@AtomsksSanakan covered this in detailhttps://twitter.com/AtomsksSanakan/status/1341183815176364038?s=20 …Health Nerd added,
Atomsk's Sanakan @AtomsksSanakan1/ Many COVID-19 contrarians, including those behind the Great Barrington Declaration, *still* cite John Ioannidis' inaccurate estimate of SARS-CoV-2's fatality rate. So let's go over how atrocious Ioannidis' paper is. https://twitter.com/gbdeclaration/status/1340921089023733761 … https://web.archive.org/web/20201118093302/https://www.who.int/bulletin/online_first/BLT.20.265892.pdf … pic.twitter.com/MlCAJImkRbShow this thread2 replies 1 retweet 46 likesShow this thread -
Anyway, I always think it's quite telling when people choose to attack the qualifications of their critics rather than discussing the critique itself
2 replies 4 retweets 86 likesShow this thread
Apologies! Another sample has been recently published that I was not aware of. This is also a random citywide estimate that implies an IFR of 0.5% So a reasonable range might be 0.5-0.8% for the IFR of Wuhanhttps://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)00238-5/fulltext …
-
-
Thanks. Twitter will use this to make your timeline better. UndoUndo
-
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.