9/n This means that the exposure in this paper makes no sense. By all indications, the use of ivermectin in Peru was widespread in EVERY region, not just the 'maximal' one
-
-
20/n For example, the graph from Puno is plotted on a different axis to the others, which means that the declines in movement (the coloured lines) are all at least ~10% different to the other placespic.twitter.com/GhGMIt4omb
Show this thread -
21/n Also, the "excess" mortality is wildly different between regions, peaking at different times in different places. That's not that similar imo!
Show this thread -
22/n The other fascinating thing about these graphs is that they appear to completely undercut the entire argument in the study You see, the program that they've used to delineate exposure started at the end of Julypic.twitter.com/NLqIR8srzS
Show this thread -
23/n As far as I can tell from the study and news reports, it consisted of first identifying high-risk people for a week or two, then going house-by-house to test them and deliver care packages over the next few weeks/months
Show this thread -
24/n This means that the EARLIEST that the program could've been delivering ivermectin is around the second week of August But look at the peaks of excess deaths in those graphspic.twitter.com/QjaXUNrslR
Show this thread -
25/n It appears that in most cases, the peak of deaths happened in August ~or earlier~, which means that this program wasn't even started until deaths had already peaked in most places. This is a pretty huge issue for the analysis!
Show this thread -
26/n Anyway, at a basic level there's absolutely no way to estimate from the data how many people were actually taking ivermectin in any of these places, so this analysis cannot possibly show that ivermectin is effective or ineffective
Show this thread
End of conversation
New conversation -
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.