is an excellent scientist and a responsible professional. She likely read the paper more carefully than most. She grasped some of its strengths and weaknesses that are not apparent from a cursory glance. Below, I will mention a few points some may have missed.
1/

The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
It is challenging to estimate the effect of interventions in the absence of a counterfactual. This difficulty is compounded by likely confounders, such as climate (not mentioned in the paper). Territories that implemented similar interventions might share comparable climate.
6/
This is a sophisticated piece of work, with both strengths and weaknesses. Though, to me, its primary value is the proposed methodological framework rather than its estimates of the efficacy of individual interventions, which efficacy remain debatable.
7/
There is room for scientific discussion about how solid the estimates presented in the paper may be. Though, accusing colleagues expressing reservations about the robustness of some of the findings of 'spreading disinformation' feels inadequate, to say the least.
8/
This paper has generated endless conflict. One intriguing feature is that all the spats are around 'educational settings'. Interestingly, the paper also claims that T&T and isolation of cases, among other measures, are completely ineffective, yet no one seems to care ... 🤔
9/

More from Science

https://t.co/hXlo8qgkD0
Look like that they got a classical case of PCR Cross-Contamination.
They had 2 fabricated samples (SRX9714436 and SRX9714921) on the same PCR run. Alongside with Lung07. They did not perform metagenomic sequencing on the “feces” and they did not get


A positive oral or anal swab from anywhere in their sampling. Feces came from anus and if these were positive the anal swabs must also be positive. Clearly it got there after the NA have been extracted and were from the very low-level degraded RNA which were mutagenized from

The Taq.
https://t.co/yKXCgiT29w to see SRX9714921 and SRX9714436.
Human+Mouse in the positive SRA, human in both of them. Seeing human+mouse in identical proportions across 3 different sequencers (PRJNA573298, A22, SEX9714436) are pretty straight indication that the originals

Were already contaminated with Human and mouse from the very beginning, and that this contamination is due to dishonesty in the sample handling process which prescribe a spiking of samples in ACE2-HEK293T/A549, VERO E6 and Human lung xenograft mouse.

The “lineages” they claimed to have found aren’t mutational lineages at all—all the mutations they see on these sequences were unique to that specific sequence, and are the result of RNA degradation and from the Taq polymerase errors accumulated from the nested PCR process
💥and so it begins..💥
It's time, my friends 🤩🤩

[Thread] #ProjectOdin


https://t.co/fO90N78fta


new quantum-based internet #ElonMusk #QVS #QFS

Political justification ⏬⏬
#ProjectOdin


#ProjectOdin #Starlink #ElonMusk #QuantumInternet

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