CDC Director Dr. Rochelle Walensky and Dr. Anthony Fauci have made more and more doomsday statements over the past few weeks, and with little evidence, they have finally reached their peak in the past few days. Their concerns and statements about the COVID-19 Delta variant, coupled with the reversal of health policies and guidance, were eventually asked to review the data that led to these conclusions. On Tuesday, Dr. Walensky issued a statement urging the restoration of mitigation measures through cover-ups, citing data—she did not cite or publish these data at the time—the Delta variant caused a higher viral load, more severe disease than the original strain, and The person who caused the vaccination is as contagious as the unvaccinated person.
Last night, inside CDC slide, Including these newly determined source materials, have all been leaked. Most of the slides focused on vaccine effectiveness, only seven slides examined new data on Delta variants—presumably the data that the CDC used to reverse the mitigation process. In these seven slides, on the one hand, the transmission ability between the Delta variant and the ancestor strain is compared, and on the other hand, various other infectious diseases of various types of widespread transmission are compared. Two of the slides cover an internal model generated by CDC that attempts to predict future delta transmission rates and the impact of masking and vaccines on these transmission rates.
In the remaining four slides, I will quickly review the sources and data of three of them: slides 16-18. For these three slides, five data sources are cited, and there are two data sources that seem to have not yet been cited-although we can infer at least one data source here. Of the five sources cited, one was peer-reviewed and published, one was a British government document that had been known for a week, two were preprints (not yet reviewed), and the last one was initially rejected for review.It’s important to note that preprints are useful in many ways, but since last year, there have been many pay attention to The speed at which they spread bad data and misinformation was pointed out.
CDC Slide 16, Statement 1：India reported that the Delta breakthrough cases in HCW (n=47, average Ct 16.5) had a lower cycle threshold (Ct) value compared with non-Delta breakthrough cases (n=22, average Ct 19); with the breakthrough of Delta, clusters Larger scale
This comes from a learn After being considered as one of the sources of participation in CDC decision-making, this has attracted a lot of attention in the past few days. The “India Report” marked by the CDC here has been-correctly-criticized for several damn failures: first it was rejected by peer review. It must also be the most complex, worst, and most confusing of all studies-this may even be what the CDC is counting on here to quote it. Upon review, the study appears to be not one, but three, all of which have been compressed into one paper. This includes a computational model, an epidemiological study on medical staff, and a biological study on neutralization potency. The CDC seems to care about the last two, so I will focus on that one. The study tracked a small sample of ChAdOx1 (AstraZeneca) and Pfizer/BioNTech vaccine recipients-it did not mention how small the sample was or the different vaccinations.
“We obtained similar data on breakthrough infections and ChadOx-1 [sic] The vaccination status of two other health institutions in Delhi has 4000 and 1100 medical staff respectively (Figure 2D). In the second hospital, there were 51 such sequences from 70 symptomatic infections, which were reconstructed from 57 phylogeny with high-quality genome-wide coverage; in the third hospital, 118 cases of symptomatic infections were recorded. 57 of them were used to rebuild phylogeny. “
Later, this paper compared Delta’s response to AstraZeneca and Pfizer (one-dose and two-dose) vaccines, and showed that Pfizer vaccines have a much better resistance to Delta than AstraZeneca. The CDC did not cite this information. The information they cited was related to the above-mentioned excerpt and only followed AstraZeneca’s results-a vaccine not used in the United States. Therefore, it is difficult to see how the information cited by the CDC infers the vaccination and health status in the United States. In addition, it is difficult to take a paper full of spelling errors and incredibly messy composition seriously as the basis for guiding the lives of about 330 million people half of the world.
CDC Slide 16, Statement 3: The risk of re-infection with Delta may be higher [aOR 1.46 (CI 1.03-2.05)] Compared to the Alpha variant, but only if the previous infection is ≥180 days
The third data point on this slide — don’t worry, I deliberately skipped the second data point — is a snippet of information from page 35 of Public Health Technology in England briefing From a week ago. This section is numbered 1.7.1 and covers national surveillance for reinfection. Its healthy sample size is 83,197, and the model has been adjusted based on “age, gender, area of residence, vaccination status (inoculated or not vaccinated in the past 14 days), race, and number of weeks of testing”. The model also includes variables that the CDC seems to be interested in—whether a person had a natural infection (confirmed by a positive test) 180 days ago, or more or less than 180 days ago. Of all people tested, 980 were identified as potentially reinfected (1.2%).
The above information uses odds ratios to determine the risk of Delta re-infection, and shows some evidence that those who have been infected with COVID-19 more than 180 days ago are slightly more likely to be re-infected (odds ratio, not included above), For previous infections under 179 days, it was 0.79, with 95% Cl 0.49 to 1.28. It is important to note: an odds ratio below 1 means that it is unlikely to happen, and an odds ratio above 1 means it is more likely to happen). It is also important to note that this information does not seem to explain the changes in vaccines-although mRNA vaccines dominate in the United States (the use of Johnson & Johnson is negligible), the United Kingdom has approved mRNA vaccines and two viral vector vaccines-Ah Sleecom and Jason. Therefore, it is not yet clear how this will affect the situation in the United States (mainly mRNA).
CDC Slide 16, Statement 2: Delta infection is associated with longer duration of Ct value ≤30 [median 18 days vs. 13 days for ancestral strains]
I initially skipped the second data point because the same research was used as a reference for slide 18, and I wanted to cover everything at once:
CDC Slide 18, Statement 2: Singapore: higher chance of needing oxygen, staying in ICU or dying [aOR 4.90 (CI 1.43-30.78)] And pneumonia [aOR 1.88 (CI 0.95-3.76)]2
This is a preprint Singapore learn. There are several questions about this study, and how it relates to US health policies and conditions. First, the sample size of the study was very small, monitoring only 829 patients—whether they had Alpha, Beta, or Delta infections (herein referred to as VOC). In addition, it is important to note that these are all VOC infections throughout Singapore during the study period. This cohort was compared with 846 other COVID-19 (non-VOC) patients who were admitted consecutively. Of the 829 people who tested positive for VOC, 157 were admitted. Then compare these 157 cases with 829 original COVID-19 cases to get the ratio of treatment type to death. I strongly recommend that you check Table 2 to see all treatments, admissions, and result comparisons between the data sets.
CDC Slide 18, Statement 1: Canada: Higher chance of being hospitalized [aOR 2.20 (CI 1.93-2.53)], ICU check-in [aOR 3.87 (CI 2.98-4.99)], And death [aOR 2.37 (CI 1.50-3.30)]1
This learn, May be the strongest of all cited data, from Canada, and also a preprint. The study has a strong sample size and controls various health-related demographic variables. The main limitation of this study is that although it models vaccination, it is general and is an indirect coverage of cumulative data. The study acknowledges a significant weakness:
“Canada is now one of the most widely vaccinated countries for SARS-CoV-2 in the world, and vaccination undoubtedly reduced the impact of these VOCs. A key limitation of our data set is its lack of data on the status of individual-level vaccination. We indirectly simulate the impact of vaccination on the prevention of serious diseases by adding a linear trend term to our model.”
Due to similarities in demographics, geography, lifestyle, and types of vaccines used in Canada and the United States, this may be the most relevant and powerful data set of all sources. It does show that there is evidence that this variant may hit young people more severely than the original variant.
CDC Slide 18, Statement 3: Scotland: higher chance of hospitalization [HR 1.85 (CI 1.39-2.47)]3
The final citation comes from Scotland and is the only one that has been peer reviewed and published sourceThis is also a good study, but the interesting part is the part that CDC chose not to include. The summary of the publication is as follows:
“In summary, we show that the Delta VOC in Scotland is mainly found in younger and more affluent groups. Compared with Alpha VOC, the COVID-19 hospitalization risk of Delta VOC patients has approximately doubled, and the hospitalization risk of patients with five or more related comorbidities is particularly increased. Both Oxford-AstraZeneca and Pfizer-BioNTech COVID-19 vaccines can effectively reduce the risk of hospitalization for patients with Delta VOC infected with SARS-CoV-2 and COVID-19, but with those with Alpha VOC. We do not have enough hospitalizations to compare vaccines in this area. The Oxford-AstraZeneca vaccine does not appear to be as effective as the Pfizer-BioNTech vaccine in preventing SARS-CoV-2 in patients with Delta VOC. “
Finally, I want to quickly comment on the two data points on slide 17. When reading the slide, neither of these two data points contains a data link.
The first statement probably comes from Novel Coronavirus Network The data is a very small sample. Only 19 cases of Delta breakthroughs have even been seen here, while Alpha and various other variants have more than 200.
The second data point comes from a small outbreak cluster in Massachusetts, located in Report CDC just released this morning. This report shows that the breakthrough case is more likely to be Delta, rather than Delta having a stronger tendency to break through. Since Delta is evolutionarily healthier than its competitors, it may appear more in the composition of cyclic variants, leading to more breakthrough cases. Similarly, the study lacks even the most basic statistical significance analysis—for example, it is noted that vaccinated individuals have a higher cycle threshold (hence lower viral load) than unvaccinated individuals, but the difference is very small, and No measure of statistical significance is given. If there is no significance test, it is difficult to determine the correlation of these simple findings.
I think of a different kind of life. A long time ago, a statistics professor of mine said that “statistics can’t lie, but statisticians can lie”. The CDC may not lie, but its exaggeration of the data and its relevance to the health of the United States is certainly close to disturbing deception. The picture CDC is trying to paint is that the U-turn that it caused the whiplash last week is the result of solid scientific evidence-but the evidence is neither extensive nor uniformly pointing to what the CDC selected from it (no, of course, mentioning this evidence as a warning) The reason may not apply to the current situation. Quite simply, the data does not support the bold assertion of the CDC. Perhaps there are two adults who found to support the increased risk of young people Delta with fewer or no comorbidities, and some evidence suggests that Delta may be slightly more infectious.
The data shows that, contrary to the clumsy information of the CDC, the vaccine is effective. Although this newly increased risk of young people should encourage people in this age group to be vaccinated, there is no need to advocate extreme mitigation based on exaggerated evidence and exaggerated risks.
