1) I've been irritated by this and a related thread which suggested very low IFRs even at higher age and some unexplored resistance to severe covid in India. So I'll just crunch some numbers to explain why these claims don't make much sense to me.
2) Clearly, everything hinges on the covid-19 death count in India being halfway accurate. Prof. Rajkumar suggests 'you cannot undercount ten times the death rate'. But can you? A look at the case undercounting might be helpful - if lots of people aren't tested, will bodies be?
3) A recent serosurvey suggests 21% of India's 1.353 billion people have had covid. This makes ~284 million true cases. In the past half year before the survey, India officially counted ~10 million cases. So cases were undercounted by a giant factor of 28! indianexpress.com/article/india/…
4) Similar to virtually all other countries, the case undercounting was even worse in the early stage of the pandemic - but the factor of undercounting was way larger than in western countries for which we have seroprevalence data. science.thewire.in/the-sciences/i…
5) Given this massive case undercounting, I find it questionable to just take covid-19 deaths as given and result at very low death rates. Simple sniff test: If testing was so constrained during the entire pandemic, wouldn't you start cutting corners in testing bodies?
6) Good news: India is scheduled to perform a population census in 2021. So at least overall mortality could soon be assessed: If there were fewer old people than there should be according to some modeling, something might have happened... en.wikipedia.org/wiki/2021_Cens…
7) However, even that will not be clear-cut. Ex.: 20% of 1 million people at age 75 catch covid and 5% of the infected die = 10,000 covid deaths or 1% of the 1M. But mortality is very high in India at that age in general, so in statistical terms, we might not find a difference.
8) In addition, can we be 100% certain that the population or death statistics won't be fixed a little bit here and there? I wouldn't be. blog.twitter.com/en_in/topics/c…
9) As questioning governmental statistics seems to trigger quite some people, which does not really speak in favor of the data reliability, another 'left-leaning' source. And a dose of Copium. thehindu.com/opinion/Reader…
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1) Wissenschaftlich schlechte Arbeiten haben die Angewohnheit, nicht einfach wieder in der Versenkung zu verschwinden, da sie oft geeignet sind, bestimmte Narrative zu bedienen. So taucht die Ioannidis-Studie zu Lockdowns im neuen Policy Paper von @iw_koeln@michael_huether auf.
2) Die Ioannidis-Studie, im Paper zitiert als Bendavid et al. 2021, behauptet, keine Evidenz für die Wirksamkeit restriktiverer Corona-Maßnahmen relativ zu weniger restriktiven gefunden zu haben. Ihre Methodik ist allerdings völlig unglaubwürdig und wurde vielfach kritisiert.
3) Hier von mir in einem Thread mit Verlinkungen zu Kritiken von Seiten anderer Forscher:
Im Interview mit der @NZZ äußert der von @Markus_Soeder aus dem Bayerischen Ethikrat geworfene Prof. Christoph Lütge allerlei dreiste Falschbehauptungen, die aus dem Paralleluniversum der Corona-Leugner/-Verharmloser stammen könnten. Ein Faktencheck. (1/n) nzz.ch/international/…
Die WHO hat nie gesagt, dass Lockdowns mehr schaden als nützen. Ein WHO-Mitarbeiter deutete lediglich die Möglichkeit an und auch das nur bezogen auf junge Menschen. Ein anderer WHO-Mitarbeiter wurde aus dem Kontext gerissen. (2/n) euro.who.int/en/media-centr… politifact.com/factchecks/202…
Ob eine Infektion mit einer mutierten Variante gefährlicher oder tödlicher verläuft, ist in der Tat noch offen. Da die Mutationen allerdings mehr Infektionen verursachen, werden sie allein durch ihrer höhere Ansteckungsfähigkeit "mehr Krankheit und Tod" verursachen. (3/n)
Weil es die mangelhafte #Ioannidis-Studie zur Effektivität verschiedener Corona-Maßnahmen jetzt sogar in die #Bundespressekonferenz geschafft hat, wiederhole ich die Kritik dieser Studie nochmal auf Deutsch. In Kürze: Die Studie ist nicht glaubwürdig. 1/n
Im Grunde regressiert die Studie Corona-Fälle in verschiedenen Staaten im Frühjahr auf Variablen, die die verschiedenen Corona-Maßnahmen zu verschiedenen Zeitpunkten widerspiegeln. Sie behauptet, restriktivere Maßnahmen hätten keinen stärkeren Effekt als weniger restriktive. 2/n
Die Vergleichsgruppe zu den restriktiveren Ländern, die die Studie nutzt, sind zwei Staaten (Südkorea und Schweden), die nach Auffassung der Studie kaum oder gar keine restriktive Maßnahmen gegen Corona erlassen hätten. 3/n
There's a new paper by John Ioannidis and co-authors that's intended to push their anti-lockdown message by performing a flimsy empirical analysis. Adding to @GidMK's thread, I will just highlight one flaw that should have prevented this paper from being published but hasn't.
What they basically do is regressing case growth in Spring (terrible data) on a bunch of NPIs. Then they're puzzled bc their results indicate a positive "effect" of some NPIs on case growth. Well, that's not puzzling at all, that's because NPIs and case growth are endogenous!
NPIs tend to get tougher the worse the case growth gets. But case growth might already be taking off when you've just tightened your NPIs, making cases further grow exponentially before the NPIs do anything. This results in a positive correlation between NPIs and case growth.
The idea that weak or absence of evidence for asymptomatic spread is making a case against lockdowns and other preventive measures is self-defeating in so many ways. So I'll just list a few:
If asymptomatic spread wasn't a thing, it would imply that all the cases must be the result of symptomatic spreaders. This would imply we would have to quarantine everyone with cold symptoms ultra-hard, not less, because apparently their distancing and mask-wearing isn't enough.
Further, the study that found only few 100 asymptomatic cases and no symptomatic cases among 10M people was done in Wuhan - the place that had locked down ultra-ultra-hard. Did the lockdown achieved the almost total suppression of the virus? Looks like it. nature.com/articles/s4146…
Many papers are now investigating whether YouTube is creating "echo chambers", mostly regarding the (far) right. In principle, an interesting topic. However, if one of the labels for "far right" is "IDW", it's starting from false premises. arxiv.org/pdf/2011.12843…@EricRWeinstein
How did this happen? The paper provides sources for the labels. So it's just repeating what others have already done, without checking whether it makes sense. Playing it safe, one may say.