On 2020-10-20 17:57:35, user Dinofelis wrote:

It is strange to conclude that one observes statistically significant "<br /> PCR negativity in intervention and control groups were (day 7, 182 (52.1%) vs. 54 (35.7%) (P value = 0.001)"and concludes that there is no effect.

Let us remember that statistical non-significance of rejection of H0 is not equivalent to proof of absence of effect. It simply means that the test didn't have enough power to prove anything.

In order to prove absence of effect, one needs to reject with statistical significance the hypothesis that the effect is larger than a given threshold.

I have seen many papers confusing "statistical absence of significance" with "proof of H0".

On 2020-10-31 12:07:38, user Scandinavian Journal wrote:

One issue not talked about much is that a normal HCQ dose as per on the package is not considered lethal, has been around for 50 years with good reliability and costs a few dollars for a package. If I caught the virus would I decide that this is useless because some study say so while others say it is effective ? I would of course put myself under this treatment.<br /> If it is useless well what damage did it do. If it was effective it may have saved my life or made the disease progression milder. For a few dollars. Easy choice.

On 2020-10-21 14:08:08, user Darren Brown; HIV Physiotherap wrote:

The EUROQoL EQ-5D-5L self-reported health related quality of life (HRQOL) measurement tool has been used for statistical purposes, however this baseline data of EQ-5D-5L scores across 5 domains (health status) and index value are not reported. This would be useful data to understand the HRQoL of the sample, with respect to population normative data (https://euroqol.org/eq-5d-i... "https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/population-norms/)").

On 2020-10-21 19:18:46, user Alan Wilson wrote:

I would recommend the authors to check other recently published ASRM abstracts in the topic:

https://www.fertstert.org/a...

https://www.fertstert.org/a...

On 2020-10-23 11:44:52, user Alexander Samuel wrote:

Dear authors,

I fully agree with your introduction, discussion, and everything is done correctly in this paper. After scientific misconducts from Gautret et al. in Didier Raoult's IHU Marseille, and its transfer to USA through J. Todaro followed by Zev Zelenko's strange comments, there is clearly a situation that went out of control about hydroxychloroquine.

My comment on your work is that Recovery + Solidarity weight almost for 90% of the results, In a meta-analysis, I expect a significant effect of all (or most) studies, here it seems like the results are a new read of Recovery + Solidary, with comments on very low weighted unpublished or published clinical trials. Of course, authors mention that there is still no effect in the absence of Recovery, indirectly (published vs unpublished, high dose vs low dose). I think it would be important to not just make a "second read of recovery data" (exagerated statement, sorry for the way it is said). The discussion on the difference between high / low dose is what interested me most in your paper, and would be worth more comments or even analysis.

I would suggest more theoretical molecular biology bibliography (molecular effects of HCQ might reduce the immune reaction more than affect viral cell entry), more introduction elements on in vitro data (which clearly did not favor HCQ that much) for the next effort mentioned in this paper !

Anyways, this is a good paper since it is very honest and shows data properly, congratulations for this work.

Best regards.

On 2020-10-26 00:13:04, user Mahdi Rezaei wrote:

The accepted and peer-reviewed version of the article is now available via open-access Journal of Applied Sciences. DOI: https://doi.org/10.3390/app...

On 2020-10-27 03:12:46, user Critical Dissection 2 wrote:

Dear authors,

First I just want to say I think that it was great you pursued such an important topic. There were a lot of good things about your article like your clear abstract that very well laid out the different parts of the paper and the main summary of each section. I also like that you laid out the limitations of your study and how they should be solved for in further investigation of this topic. However, there is still some room for improvement in this paper. I thought that the introduction could use more background to contextualize the issue and put some scope into it to explain why people should expand upon your results and see if the data is helpful in the future. I also think that the figures need more explanation in the results section, unless a highly experienced physician is reading it, it is a little hard to tell what we are supposed to be looking at and drawing from the figure that supports your hypothesis. There was also an emphasis drawn between the two patients whose ablation was done with a little more targeting of certain factors compared to patients who underwent standard ablations that was only mentioned in the discussion but is a great point that I think should be brought up earlier maybe somewhere in the results section. I think with these changes you will have a good paper.

On 2020-10-27 16:42:24, user Kamran Kadkhoda wrote:

Again no good panel of confirmed common CoVs to exclude cross-reactivity especially to an Ab like IgM with poor affinity maturation.

On 2020-10-28 08:35:30, user Rasmus Skov Husted wrote:

The final peer reviewed article is published open access - please follow this link: https://bit.ly/3mrLlvZ

On 2020-10-28 16:35:38, user Edsard wrote:

I think we have a chicken and egg issue here. Your pollen theory is pretty good but also the reason why scientist always say: Correlation is not causation. Your pollen is the result of the weather (temperature and humidity, which has explained seasonality of the flu for 10 years already). Here is our paper. https://www.medrxiv.org/con...

On 2020-10-28 17:53:21, user Sam Wheeler wrote:

It it so that non-vaccinated hospital personnel are forced to wear a mask almost all the time to prevent flu, so the protection of flu vaccine is even greater than this study tells?

On 2020-10-30 17:10:52, user gatwood wrote:

I suspect there could be a strong corellation between vaccination status and following a strict adherence to all COVID anti-infection guidelines, PPE etc... Experienced and medically trained Drs and nurses more likely have been vaccinated and also are more likely to follow PPE wearing and careful anti-infection routines. Support staff (food service, assistants and claening staff) with less formal medical training and understanding of infection are probably less likely to be vacinnated and also may be less likely to carefully employ all technical anti-infection measures. Would this account for the vaccinated folks having less COVID infection?

On 2020-10-31 07:52:03, user Robert Eibl wrote:

This looks interesting, although there are a few caveats mentioned in the paper. Nevertheless, it should be possible almost everywhere, and even restrospectively, to check the vaccination status of Covid-19 patients, not only for influenza - and compare this with the average vaccination status of a whole country. Then it should be immediately clear, if there is a major benefit.

On 2020-10-29 15:18:11, user bljog wrote:

In the results you mention "A cluster of sequences in clade 20A has an ad- ditional mutation S:A222V colored in blue" but the Figure 1 has an annotation in blue for S477N.

On 2020-11-03 23:04:46, user David Markun wrote:

Nice study. Copy edit: " If we instead look after September 1, 2002" should refer to 2020.

On 2020-11-04 14:41:47, user Rodrigo Quiroga wrote:

Are´t these results expected regardless of children´s proneness to infection and infectivity? Up until August, the time periods with open schools were also periods with low viral propagation in the UK.

Wouldn´t the interesting period to observe with such an analysis be precisely August-November, with open schools and increasing case numbers?

On 2020-11-05 12:26:14, user Sandra Chydé wrote:

Dear authors,

You are citing one of my papers (reference 15) in a misleading way here : " There are concerns that the use of e-cigarettes in never-smokers may increase the probability that they will try combustible tobacco cigarettes and go on to become regular smokers, particularly among youth and young adults [13-15].".

First, our methodology focused ONLY on ever-smokers aged 17 having experimented with e-cigarette.

Second, we found that in this population of 17 yo, among ever-smokers, those who declared having ever used e-cigarettes were LESS likely than those who did not to transition to daily smoking at 17: RR =0.62 95 %CI [0.60 – 0.64].

This analysis is strongly robust and relies on a sample of 21,401 respondents.

Best,

Sandra Chyderiotis, Pharm.D, MPH

On 2020-11-07 10:32:09, user Ivan Ivanov wrote:

They will never share the primer sequences as the test is being commercialized already. The idea is interesting however I cannot imagine the price for 500ul LAMP reaction. Also what's the point to put DNase and carrier DNA together in the mastermix.

On 2020-11-14 02:00:10, user Melimelo wrote:

Hi, very interesting article. Which software did you use for initial qualitative coding and subsequent text mining? are there particular commands or functions in a given software package that were useful? are you sharing your code anywhere (eg github?)

On 2020-11-14 04:23:20, user Rich Kibbee wrote:

Error, this pdf lists a Centricon 70 Plus 100 kDa filter ...the first version lists it at 10 kDa.

On 2020-11-15 21:48:01, user Ands Hofs wrote:

We in germany do re-testing of positives on a regular basis, and the result is that false-positive diagnostic findings that are actually filed to the patient are in the range of 0,001 %. Even if testing activity of healthy subject was high up to September, the number of people that had a wrong test result is something like a handful a week and totally acceptable in the face of the alternative. Especially since one does a second test some days later.

But right now we have positive testing of 25% of samples in Frankfurt (Main),e.g., just mentioning this to get the perspective right, water is rising above neck to the lips...

A few people (like 1-5%) mentally infect 30% insecure anxious people here, damaging our wakefulness to keep our viruses for ourselves, prohibiting smart distancing to be practice in private contexts, behind closed doors in companies and among friends and neighbors all the same, and this is making the 2nd lockdown necessary.

And causing thousands of deaths not necessary when they would obey the democratic decision: we do not want to do triage. We want to keep the numbers low. We want to keep our viruses to ourselves. We do not want to have unnecessary lockdowns burning away existences, jobs, money... But what choices do we have?

Since we wasted the summer where we had the chance to get incidence real low.

Now the only thing that can save our neck is a (pre-) test that is really free for everyone, and MIT has one: https://digitalreality.ieee...

Every one writing about false positives should weigh his words thoroughly.<br /> Not the rate of one single test method is what people want to know. <br /> They want to have approved quality testing and numbers for "their" lab.

These numbers are there in every German lab, since they are obliged to certify every test they offer and to take part in Ring Tests where labs and their certified tests are tested. This is done by sending a lab unknown but specially prepared samples that each lab has to let run through the lab on a regular basis. This also is done to get quantitative tests to comparable levels between labs.

Comparable Levels for Covid-19-Infected patients:<br /> It is a pity that we do not let some piece of human DNA normally found from throat swabs run together with the Sars-CoV2 Test on a regular basis, resulting in viral units per human DNA count, because this would enable us to estimate the viral load at the place where the sample was taken. It would outrun many variabilities that occur when taking samples that affect the amount of material gained in the sampling process, and one could monitor viral loads across the time line for each infection with high therapeutic value. <br /> I'm so curious if someone has done this with the gargling method for probing, since here the local variability in infection density is not playing any role any more, as is the case for the question how infectious one could be in a certain state of the infection.

Boston children hospital has done this in their study on viral loads in children, where for the first time it was found that children, regardless if having symptoms or not, have viral loads like heavily ill adults. <br /> Since their lungs are smaller proportional to their age and development, of course the net amount of aerosols produced by a small child e.g. up to 8 or 10 years is smaller ( - but proportional to the loudness of their voices ;)) <br /> Still - starting with 11 or 12 years, it starts to reach adult levels, meaning we must do DIY patchwork air ventilation with heat recovery mechanisms out of vapor barrier film and 2 vents in schools or let the pupils sit in the cold of fresh air or 8hrs / day under some masks that muffle sound (many innovative ideas for DIY masks are asked here for).<br /> I like the nordic approach either to do home schooling or do classes under the trees for the younger ones, leaving a lot of space in the school for elderly pupils, especially in classes wanting to have their final exams ;)

Andi

On 2020-11-18 16:18:54, user LB wrote:

Please add, in the Limitations, a comment about the fact that, "The mean time between the onset of symptoms and randomization was 10.2 days." It is quite possible that by the time the vitamin D levels were raised, the "cytokine storm" was already well underway. Thank you!

On 2020-11-19 15:54:00, user Lorenzu Borsche wrote:

Hello, this sentence:

Subsequently, we calculated sample size assuming a 50% between-group difference in hospital length of stay (considering 7 days as a median time of stay, with an expected variability of 9 days).

to me is not quite clear: do you mean, that you preset a desired length of stay to 7 days and the grouped the data so that both groups fit these 7 days? Thus did you mean a 50:50 distribution wrt the 7 days? If so, this cannot be done without distorting the data. If not, please explain, TIA Lorenz Borsche

On 2020-11-28 13:16:44, user Angie wrote:

The description of the amount of vitamin D used doesn't account for the mistake made in calculating vitamin D needs, nor is that mistake discussed in the article. In addition, making active forms of VitD from what is ingested is not an instant magic process. A body under attack may lack the energy to carry it out. Maybe it's just giving something by a pill is ineffective right now. What if you did transdermal? That would avoid the stomach/gut which is a place we know the virus attacks. Also vitamin D doesn't act alone. A person in ICU may not get a lot of vitK and may even be on anti-K blood thinners if they are a stroke risk. How many patients were on Lovenox vs something that thins blood via the vitamin K route? A daily exposure to a UV lamp may be more efficient for providing Vitamin D.

Anyway, the point is, I am not convinced that this test was properly done with reference to vitamin D. It takes weeks to normalize vitamin D in tissues where it is needed. Just testing the blood level after you gave a bolus pill is lying to yourself. It's like adding dye to water and saying, look, the sand at the bottom of the river turned all blue, we can assume it goes deep. What's the vitamin D status of hepatocytes after the one pill you gave? How much enzyme activity was there in the kidney to activate the D you gave?

Giving someone a vitamin is not like giving them a drug. The vitamin has to go to the tissues and do its work. You're thinking far too simplistically. VitaD affects thousands of reactions in the body and is not actively excreted as if it were an invader. That's nothing like a drug. Vitamins aren't drugs, that goes double for the fat soluble ones.

On 2020-12-24 23:19:01, user Matthias Fax wrote:

By design, this study could only fail to meet its hypothesis. It only proves what was to be expected. They used inappropriate dosage in oral form. They accepted an inappropriate delay after onset of symptoms. They didn't mention the significance of 25OHD sufficiency for patient outcome, indicating that the oral dosage was given too late to be of any immunological use.

On 2020-11-18 12:16:47, user Robin Whittle wrote:

I did not see any mention about how long after supplementation the 25OHD levels were tested. D3 takes some days to be converted in the liver to circulating 25OHD.

Since the intervention was with already-hospitalised patients, on average 10 days after their symptoms began - and with 25OHD levels rising over a period days, with the average length of stay about 7 days, this intervention may have been too late, and perhaps too little.

In the Cordoba trial (Castillo et al. https://doi.org/10.1016/j.j... "https://doi.org/10.1016/j.jsbmb.2020.105751)") 0.532 mg 25OHD calcifediol would have raised 25OHD levels within a few hours, probably above 100ng/ml on average - if one extrapolates from the curve shown for 0.266mg (a single Hidroferol capsule, of which two were used in Cordoba) in this patent: https://patents.google.com/... This greatly reduced the need for intensive care and eliminated deaths.

Since hospitalised COVID-19 patients have an extremely urgent need for raised 25OHD levels, so the autocrine signaling systems of their immune cells and many other cell types can function properly (McGregor et al. https://www.biorxiv.org/con... "https://www.biorxiv.org/content/10.1101/2020.07.18.210161v1)"), a combination of 25OHD calcifediol with bolus D3 may prove more effective than either treatment alone. The bolus D3 would sustain 25OHD levels for weeks, and the D3 itself may protect the endothelium (Gibson et al. https://doi.org/10.1371/jou... "https://doi.org/10.1371/journal.pone.0140370)").

On 2020-11-20 16:49:15, user Jean Kaweskars wrote:

Hello,

Your figures are not consistent.<br /> If you have 11% IFR for 80-90-year-old subjects who represent 6,3% of France population (> 80 years old), it does translate into a minimum of 0,69% overall IFR. If you apply your IFR rates by age, you would actually get an overall 0,91% IFR at minimum.

Regards

On 2020-11-25 15:49:17, user James Wyatt wrote:

In the discussion of weaknesses, you failed to mention that you eliminated approximately 1/3 of the cases for lack of complete data. Did you study these cases to see if their exclusion could possibly have biased your results? What was the crude death rate among these cases?

In Table 1, the disparity between mortality rates per 100k population is solely a function of the difference in incidence rates. That's significant, for sure, but the fact that CFR is the same for whites and blacks is also significant. In its rawest state, that indicates that, once someone is sick, race seems not to matter in the outcome. Doesn't that bear some discussion?

How did you determine cause of death? Covid-19 is rarely the sole cause when death certificates are completed competently and there is some judgment required to clearly identify a covid death. As follow-ups, were there non-Covid-19 deaths in your data? How were they identified? If there were none, can you justify that?

In mortality studies, the key question often is: How did you calculate the exposure? That is, how did you determine the denominators for your ratios? You reference some models, but you give no details.

The paper needs a lot more work, don't you agree?

On 2020-11-25 19:54:26, user Puya Dehgani-Mobaraki wrote:

Interesting data, which are also seen on our study were the persistency of the antibodies were detected and persisted during 8 months.

https://www.medrxiv.org/con...

I do would like to have more informations in regards of the patients selection for the 8 months analysis.<br /> Our cohort was based in patients resulted positive for Sara-Cov-2 early days of March, Italy. As far as my knowledge, very few cases were reported in Australia at that time.<br /> Puya Dehgani-Mobaraki

On 2020-12-04 13:43:42, user Ben Finn wrote:

Why does the paper make no mention at all of the large risk differences between sexes & races? (Men, Black and most Asian people have 2+ times COVID mortality of others.) Straightforward to model. Without considering this it can’t claim to be an ‘optimal vaccination strategy’.

On 2020-12-04 20:45:12, user Sam Wheeler wrote:

Is the full text possible to read as HTML somewhere? I did find the PDF.

On 2020-12-08 09:28:26, user Neville Calleja wrote:

Obviously the people receiving the influenza vaccine are (a) the most at risk of dying with COVID-19, either as an underlying cause of death, or as a contributory cause, and (b) more likely to be coming from affluent countries wherein identification of deaths as a COVID-related death is much more likely due to enough resources permitting testing of all patients. The latter could have been corrected by using excess mortality figures rather than reported COVID-19 deaths, which is highly dependent on the countries' capacity to test. Nonetheless, the first clearly explains the findings completely wherein countries with high life expectancy and therefore high proportion of elderly population with co-morbidities who are typically protected in winter using the influenza vaccines, could not be protected from COVID-19. This could be considered a correlational study at best.

On 2020-12-08 11:30:27, user Abdur Rahman wrote:

This preprint is accepted for publication, and the new link is: <br /> https://onlinelibrary.wiley...

On 2020-12-09 12:20:53, user Vladimir Gusiatnikov wrote:

The authors appear to treat viral loads quantified in transfer media as viral concentrations in mucus, however there typically is a 1.5 to 2 order-of-magnitude dilution as material is eluted from swab into media. As a result, the authors' estimates for the copy generation rate and copies per infectious quantum may be 1.5 to 2 orders of magnitude too low.

On 2020-12-09 16:34:09, user Livia Dovigo wrote:

The elegebility criteria (that lead to only 5 studies to be included) has not be clearly described... Searches returned more than 90 entries, the authors needed to inform the methodology for studies selection. Otherwise, results may not be reliable.

On 2020-12-11 00:07:54, user Peter Novák wrote:

PARTICIPANT CONSENT?

Authors claim, cite: "All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived."

I find this proclamation highly dubious.

I'm not sure how many of the the mass tested people have signed a form of informed consent, and I'd like to see how would the authors prove that. I personally have asked several participants and they insist they did not sign anything. But even in the case some, or even the majority signed something, what weight would that have under circumstances?

The people subjected to the mass testing (that technically means biological material extraction) with consideration, that those who do not subject, will be quarantined for week or two - that means, forced to stay home under threat of penalty as high as 1650 EUR (average monthly income in Slovakia is 1100 EUR brut), with few exceptions (e.q. nearest grocery store, drugstore and necessary health care), but certainly denied the access to workplace with no lost worktime salary compensation at all, neither from state nor employer.[1] A proposition effectively resembling a home prison in my opinion, and what's even worse in situation of economical crisis - with published threats from some employers that untested employees may lose their job eventually, thus undermining the public confidence in freedom of choice furthermore.[2]

It is known that criminal complaints on the accounts of possible coercion, health care law violations, human rights violations etc have been filled to the public prosecutor office. These are yet to be resolved.<br /> I acknowledge that some of the people have attended the testing voluntarily indeed, probably a minority though, as indicated by low compliance (15%) to the third round of testing where quarantine threat was removed.

Nevertheless, I doubt anyone could assume the actions under such circumstances constitute a "participant consent" by standards of any possibly existing ethical guidelines.

Or maybe I just read the citation wrong and the authors did not mean the 3,6 million people undergoing the biologic material extraction to be the subject of the "necessary patient/participant consent"...?

[1] Public Health Office Edict No. 16 from 30.10.2020. Government Bulletin vol. 30 no. 12. http://www.minv.sk/swift_da...

[2] Dobrovolne nasilu? Niektorým ludom bez testovania hrozia výpovedou. Pravda, 26.10.2020. https://ekonomika.pravda.sk...

On 2021-02-01 21:30:19, user Igi Dano wrote:

As a Slovak citizen, I agree with most comments/notes presented here. I could as well add my own experience with "following testing procedure recommended by manufacturer..", where this testing procedure was conducted outside (of any premise, just an open tent) with temperature well below recommended range.

But that is not the point of my post here. The point is that Slovakia is currently (1.2.2021) ending the second round of another population-wide screening.<br /> I am desperately waiting for another study from the authors, confronting the newest results with original ones. <br /> Without that I would recommend potential readers of this study to use extreme carefulness with interpretations of it..

On 2021-02-02 12:13:10, user Miriam wrote:

Nobody in Slovakia was informed about this research. And it was not voluntary as they signed. There was and there is still strictly prohibited to go at work and to the nature if we are not tested. The final result of this mass testing is, that numbers of covid positive strongly increase. That is all. I am really afraid about my human rights in future.

On 2021-02-19 01:42:51, user Oliver Cudziš wrote:

Voluntary? "All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived - Yes" What is this, areu all blind or what. Slovak nation was like experimental rabbit without knowing, congratulations you just made stage for Slovak national uprising 2, good luck.

On 2020-12-13 13:26:48, user Sam Smith wrote:

A concern about the Córdoba study is that 25OHD serum levels were not measured, so we do not know if the treatment was associated with a benefit only in patients who were deficient. A randomized controlled trial will be needed to determine whether calcifediol will benefit hospitalized COVID-19 patients who are not deficient.

Sadly, calcifediol is sold in some European countries, including Finland?

On 2020-12-15 10:43:49, user NK wrote:

Re: article pre-published at https://www.medrxiv.org/con...

There are several methodological problems in this study.

1. Findings that suggest increased ORs among primary school teachers, child care workers and secondary education teachers are not properly presented and discussed

The summary states: "Teachers had no or only moderately increased odds of COVID-19". This finding is mentioned several places in the text of the article. Teachers are repeatedly referred to as having a low risk, even when the results for teachers show a significant increase in admissions and borderline significant increase in infection rates. Quotes: «First, our findings give no reason to believe that teachers are at higher risk of infection», and in the conclusion: “Teachers had no increased risk to only a moderate increased risk of COVID-19”. We wonder why the authors find it important to repeatedly mention this the result for teachers when the results for the last period does not exclude a substantial increased risk for teachers, whereas occupational groups with lower risk than teachers are not mentioned in the summary.

The part of “Supplementary table 1” shown below does not provide a basis for such a conclusion that teachers are a low risk group.

The OR (95% CI) for 1) primary school teachers 2), child care workers and 3) secondary education teachers were 1.142 (0.99-1.32), 1.145 (1.02-1.29) and 1.095 (0.82-1.47) respectively. The upper confidence limits are does not exclude 29 % to 47 % increased ORs, which represent substantial increases.

Concerning the results on the risk of admission, it is stated: «None of the included occupations had any particularly increased risk of severe COVID-19, indicated by hospitalization, when compared with all infected in their working age (Figure 3, S-table 2), apart from dentists, who had 7 ( 2-18) times increased odds ratio, and pre-school teachers, child care workers and taxi, bus and tram drivers who had 1-2 times increased odds ratio”.

This finding is not discussed or mentioned in the summary, even if the findings were statistically significant for pre-school teachers as well as for child care workers.

1. The study periods include periods when the schools were closed and include no period with high infection rate among children and youths.

It is not to be expected that teachers have higher infection rates than the average working population in periods when school are closed and when the infection rates are low in the age groups 0 - 9 and 10 -19 years. This problem is not discussed in the paper. Schools were closed from 12 March to 27 April. For a majority of the schools, holiday started from Friday 19 June.

The first study period lasted from February 27 to July 17. Thus, schools were closed for over 70 days of the first study period of 139 days. The infection rates in children at school age in the first study period were rather low (3.6 per 100 000 children per week between in the age group 10 -19 in week 19, 1.1 per 100 0000 children per week in week 25). In the last study period, the infection rates varied between 7 to 17 per 100 000 per week in the age group 10 - 19. Even if these rates are much lower than later weeks that were not studied (after week 42), the results from this second part of the study suggest an increased risk for teachers.

Thus, the infection rates among children started to increase from week 43, after the end of the study period. By not including this period, the study design excludes the possibility to detect if these high rates among pupils could be related to increase infection rates among teachers.

It is a problem that the results from this pre-published study has been quoted in the media and referred to as if teachers have no excess risk, or even possibly a reduced risk at the time that several municipalities were to decide what type of restrictions at schools should be introduced to reduce the risk of transmission among school children, see https://www.barnehage.no/korona/ny-forskning-nei-barnehagelaerere-har-ikke-okt-risiko-for-smitte/211143

On 2020-12-20 20:25:16, user Pablo Pablo wrote:

I can't explain why this result is in contradiction with this other one.eurosurveillance<br /> Could it be because of the Simpson paradox?

On 2021-01-05 09:55:32, user Disqus wrote:

In addition to the previuos comments I read, page 7 "SARS-CoV-2 positive incidence rates were calculated for staff and students attending an educational setting, irrespective of whether the infection was acquired within or outside the educational setting."

thus it is evident that if the incidence is higher among teachers than the general population, <br /> schools are not the safest places, with a perhaps low transmission rate among students but a <br /> greater transmission rate from students to teachers

On 2020-12-22 08:44:55, user Maxime Baud wrote:

Study published in Lancet Neurology, now available at https://www.thelancet.com/j...

On 2020-12-28 23:51:01, user ErikCarter wrote:

You really ought to test for infectious virus, rather than just RNA. Otherwise you can't truthfully claim that the variant results in higher "viral load"...you've not measure viral load, you've measured RNA load. These are not the same thing.

On 2021-01-08 15:09:29, user Kevin McKernan wrote:

Can the authors explain the mess in Table 2? This dilution series is non-linear and any student delivering such data would be told to repeat it. If it is in 6 replica's, you should share the dispersion in that data. There should a clear 3.3 Ct shift in each 10X dilution. If you dont have linearity in your dilution series how can you make a Ct cutoff? The non-linearity is non-concordant across different amplicons? It is frightening this is being used as a diagnostic test. Are there any internal controls in the test to ascertain the sample prep variance? Dahdouh et al demonstrates 10-16 Ct variance in RNaseP signals (human gene) suggesting tests that lack internal controls to normalize for swab and sample prep variance are random number generators. Table 2 also looks like a random number generator.

On 2020-12-29 01:55:20, user F Alexander Diaz-Quijano wrote:

This article is now published in the Journal of Clinical Epidemiology.

Share Link:<br /> https://authors.elsevier.co...

On 2020-12-31 14:23:25, user Don Wheeler wrote:

Interesting. Additional research with a larger sample size featuring a broader cross section of the population will be most beneficial. Let's see where this leads.. Great work! @ComaRecoveryLab #covid19

On 2021-01-05 03:55:19, user mahejibin khan wrote:

Though air transmission of the virus has been suspected , swab samples collected in unsterile conditions for RT-PCR screening of human subjects continues to be a practice in many regions/countries. <br /> Two mass scale nasopharyngeal swabs of employees of an establishment in Mysore, Karnataka, India, collected under unsterile conditions in their premises, by seating them in an open ground and screened for SARS-CoV-2 infection by RT-PCR, identified a large number of asymptomatic SARS-CoV-2 positive cases. Thus the establishment forced a two-day campus lockdown, on both the occasions, in order to sanitize and break the virus transmission chain. Since most of the infected subjects remained asymptomatic through their home quarantined period, they were certified for fitness to resume work. Since reports have shown patients fighting SARS-CoV2 infection developing IgM and IgG antibodies between 6–15 days after disease onset. Blood samples of two RT-PCR positive asymptomatic subjects after 17 day home quarantine were analysed for the presence of IgM and IgG antibodies. Absence of detectable titres of antibodies to SARS-CoV-2 virus in the two blood samples suggested lack of acquired immunity due to asymptomatic patients unexposed to the virus. Nasopharyngeal swabs positive for the virus by RT-PCR inferences establishment of the Covid-19 pathogen infection in the host. Absence of prodromal symptoms for the disease in these subjects and some of them testing negative in a second Rapid Antigen Detection Test (RAD) opinion, when swabs were sampled in designated hospital rooms, suggested occurrence of air borne virus and swab contamination during sample collection under unsterile conditions. <br /> Droplets that are sneezed or coughed behave differently in the open air, according to environmental conditions like temperature, humidity, ventilation, and the amount of virus deposited.<br /> My observations on plausibility of air borne SARS-CoV2, RT-PCR determining their fairly high numbers and prevalence of asymptomatic subjects living in that environment provides leads for studies with reference to herd immunity from the purview of viral attenuation due to environment and/or innate immunity initiation through pattern recognition receptors

On 2021-01-05 15:56:38, user Ti wrote:

You write that "the best performing method is XRAI (AUPRC = 0.224 ± 0.240)". Meaning that the AUPRC ranges from -0.016 to 0.464. Surely, you cannot have a negative area under the curve.

On 2021-01-05 16:49:15, user Ania Lorenc wrote:

Hi, I was wondering - have you excluded known factors contributing to severity - sex + age?

On 2021-01-09 15:11:56, user Derek Enlander, MD, MRCS, LRCP wrote:

The "long Haul Post Viral" SARS 2 Covid19 effects, Fatigue, Myalgia, Cognative defect, insomnia etc are reminiscent of the symptoms reported historically by Melvin Ramsay in 1955 when he reported these symptoms in a cohort of young doctors and nurses in the Royal Free Hospital in London. He termed the outbreak as Post Viral Fatigue, renamed Myalgic Encephalomyelitis (ME) and later Chronic Fatigue Syndrome (CFS).

On 2021-01-10 22:17:22, user Wayne Griff wrote:

Single dose vaccine efficacy is not 90%. It's less than 50%, and that's after only 3 weeks. It would be even less effective at 6, 9, 12 weeks or more. More importantly, at 3 weeks the neutralizing ability of 1 dose is only 1/5th as much as Convalescent Plasma (NEJM)

On 2021-01-11 23:14:43, user Chaitanya wrote:

Excited to read the paper since its amazing that the authors have both in vitro and patient sample data. I a curious to read more with regard to false positive/negative and the role of NASBA amplification

On 2021-01-13 11:39:34, user carina brehony wrote:

hopefully a full published paper will acknowledge the laboratories, public health departments and the Health Protection Surveillance Centre that collected, validated and provided the data which was then made available publicly

On 2021-01-15 16:00:23, user Martin Reijns wrote:

Congratulations on this work. One comment though: I know it's difficult (if not impossible) to keep up with all the literature on SARS-CoV-2, but I just wanted to say that the statement "Currently, no test combines detection of widely used SARS-CoV-2 E- and N-gene targets and a sample control in a single, multiplexed reaction" is incorrect. Our paper on this has been on medRxiv since June:

https://www.medrxiv.org/con...

and was recently published in PLoS Biology

https://journals.plos.org/p...

All the best, Martin

On 2021-01-18 05:38:05, user Benjamin Seng wrote:

This paper has been published in General Hospital Psychiatry (journal) and is available at the following link: https://doi.org/10.1016/j.g...

On 2021-01-21 09:05:28, user Dominik wrote:

The conclusion drawn here is simply wrong: "suggesting that current SARS-CoV-2 vaccines will protect against the 20B/501Y.V1 strain" when in fact they didn't check for all 17 epitope changes of mentioned strain but only N501Y which was never thought to be immune evasive. The same erroneous conclusion was drawn in the paper of Uni Texas which also only tested against N501Y but not all mutations.

On 2021-01-24 20:42:28, user Thomas Arend wrote:

Just some short remarks to table 5:

(35-5)/35 is 85.71% and not 82.86%

If you round 32/23 = 91.4285.. you get 91.43 not 91.42

Typo? 34/35 = 97.1428 ~ 97.14 ... not 97.12

And I agree with Michel Schrader comments to the presicion of 4 digits.

The hypothesis H0: specifity = 94% / Ha: specifity <> 94% you can only be rejected for AgPOCT V. p=0,0168.

H0: Specifiy = 92% cant be rejected for any AgPOCT.

You should calculate a CI for the specifity.

On 2021-01-26 23:19:50, user Janet Aisbett wrote:

The analysis as presented does not appear to support the conclusion that “individuals discharged from hospital following COVID-19 face elevated rates of multi-organ dysfunction…..”. We can conclude that these individuals have elevated rates of multi-organ dysfunction, but we have no way of knowing whether these were ‘new-onset’ events after discharge or were factors contributing to the severity of the individual’s COVID episode. This is because ‘new-onset’ events are defined with respect to HES APC and GDPPR extracts over the ten years prior to 2020. It would help if counts of ‘new-onset events’ were provided, broken into those which first appear in 2020 but before discharge (e.g., as secondary diagnostic codes alongside the COVID primary) and those which first appear post-discharge.

Forgive me if I have missed something, but I also have concerns about the 1:1 matching of the COVID cases to controls. Supplementary Table 1 suggests very coarse matching criteria. The use of an age category 70+ is particularly striking, given the comparative age distributions of COVID versus all hospitalisations. The matching of clinical characteristics also deserves further explanation. As presented, it appears that an episode of skin cancer eight years ago could allow a match to an individual with metastasised tumours requiring palliative care. Since more serious comorbidities may be a factor in COVID hospitalisation, matching on coarse clinical characteristics may tend to select a healthier control group. Presenting frequencies of selected sets of ICD-10 codes by age for the COVID cohort versus the control group would help resolve this question. Also worthy of explanation are the decisions not to include dementia in the matched histories, and not to consider previous hospitalisation.

Finally, the Supplementary Table 3 shows quite different outcomes for controls matched to ICU COVID cases compared with controls matched to non-ICU cases. These differences are not reflected in the COVID cohort. Although numbers are small for the ICU control group, the discrepancy is worthy of comment.

On 2021-01-27 14:15:18, user Antonio Beltrão Schütz wrote:

I think that this article is important, considering that in spite of does not proof by mean RT-PCR test that ivermectin can turn negative viral load in patients with increased viral load of Covid-19, it decreased the mortality (4/112) patients. This data extrapolated to 100.000 or 1,000.000 cases is significant.

On 2021-02-04 14:21:22, user Peter Ray wrote:

The suggested reason for the increased case rates for the first 10 days or so after injection is a possible change in behaviours to being less cautious.

Another possible reason is the dramatic increase in Covid prevalence occurring in Israel generally at the start of the vaccination program (late December). Given that the positive case data is available in public it might be worthwhile including a comparison of general population case rate on the daily incidence chart.

On 2021-02-04 21:24:38, user Charles wrote:

I am a bit unsettled by the days they decide to pick to get their best (around 90%) estimate.

They use the daily rate from day 1 to 12. Day 1 it's .028% and average until day 12 is around .041% (there is a spike in infection from day 1 to 12). Day 21 is .004%, day 22 is .011%, day 24 .006%, i.e. there is some standard-error. <br /> Now, it's all about which days one picks. <br /> - if one calculates Expected as being day 1, the best effectiveness rate is 86% on day 21, but on day 22 it dwindles at 61%...<br /> - if you use day 1 to 12 as Expected, effectiveness rate is around 85% on day 24 and 73% on day 22. <br /> - to get the 90% in the paper, you need to pick day 21 (the lowest incidence, that went up again the next days) and the Expected as days 1 to 12 (the highest incidence).

It seems that efficiency estimate does improve over time, but reaching 90% depends on which days one picks, both in term of "actual" and "expected". This choice might very well explain fluctuations between 60% and 90%, i.e. the estimate is very sensitive to small numbers and differences. Differences with previous estimate might be methodological (no proper control group).

On 2021-02-05 13:36:40, user Marie wrote:

Could you, as required by law, please declare your conflict of interest?

On 2021-02-06 02:50:56, user Crystal Sonia wrote:

How accurate and reliable is this SIR model? With the mco arent the cases still increasing? How are the beta and gamma estimated? What's the sensitivity and specificity of this model?

On 2021-02-15 15:10:33, user Paul Wolf wrote:

Near the end of the abstract, you say the data is "suggesting parallel evolution of a trait that may confer an advantage in spread or transmission." Why would this mutation be occuring in different parts of the US and nowhere else in the world? That doesn't suggest convergent evolution, but a common origin.

On 2021-02-16 20:47:03, user jiver wrote:

NHS are obsessed with over simplifying race. Why ask people to self report in only 3 categories? And two are skin colour but the other is geographical. Why on earth? What did you hope to achieve by only going this far? Already people are using this to discredit non whites. And NHSP have done it before, exactly the same, 3 categories allowed only.

On 2021-02-19 20:04:10, user Jacqueline J Clarke wrote:

Have you confused the symbols lesser than and greater than ? The occupying sentences don't make sense ?

On 2021-03-09 09:36:30, user Raph Ohuru wrote:

Published here https://doi.org/10.1093/cli...

On 2021-03-20 14:23:19, user Alexander Mathioudakis wrote:

This study has now been published here:

https://www.mdpi.com/2075-1...

On 2020-11-16 06:38:23, user whitecat31 wrote:

At the 39th replicant when the exponential phase is basically over? Am I understanding that correctly? Seriously? Did you guys run a comparison standard curve with 39 points? Something like the 39th replicant would be considered below the limit of detection and LOQ. So yeah.. your sample was contaminated.

On 2021-06-02 11:15:56, user Philip Ward wrote:

The authors of the paper have now published a second study that states their earliest positive sewage sample is from January 15th 2020 and does not make any reference to this preprint:

https://journals.asm.org/do...

On 2021-06-01 09:39:20, user Facundo Muñoz wrote:

Very nice paper.

I'd just like to point out a minor mistake in the text. At the top of page 6 it is stated that alpha_lockdown has a Gamma prior of mean 0.1667 and standard deviation 1.

This didn't match the stated 50/50 chance for decreasing/increasing effects. And indeed, thanks to your open-science approach to publishing I could verify that in the code [1] you used a Gamma prior with shape and rate parameters of values 0.1667 and 1 respectively.

Best wishes.

[1] https://gitlab.in2p3.fr/bou...

On 2021-08-15 11:06:56, user Dorian Dale wrote:

The most obvious flaw is depending on honest self-declarations of educational status. Go to LinkedIn for innumerable examples of resume inflation. The huge disparity between masters at 8.3% and PhDs at 23.9%. We are now seeing much analysis of how pervasive are dishonest responses to polling. If one is an anti-vaxxer, why not claim PhD status to add cred at the expense of over-educated elite?

On 2021-06-01 18:07:54, user japhetk wrote:

This research is problematic. <br /> First, this clinical trial's primary outcome measures were as attached below. And authors did not mention 2 out of 3 primary outcome measures. These are not good omissions apparently.

Second even the primary outcome measure they used was not specified before the study. Authors used ct cut value of 30, which was arbitrary. Authors explain why they did not use 40, but they must have used 40 if that leads to the good results. And that is not a clinical trial.

They did not correct for multiple comparisons across three primary endpoints, either, which they should have done as there are three primary endpoints.

Second as the figure 2 and the table shows the ct values of two groups before the intervention are close to statistically significant differences (p = 0.10).<br /> And as the figure 2 shows this group difference did not show even a hint of change at day 6! The two groups were almost statistically different from the beginning and that did not change visually at day 6 apparently. I can't see any hints of effects of IVM from this study.

Lay persons are watching this study, and they say they love IVM and hate vaccine and let's use IVM instead of vaccine based on this study's result. We hope authors do the proper research. They should provide three primary endpoints, correct the preexisting differences, and correct multiple comparisons, and should provide apparent conclusions.

Primary Outcome Measures :

Viral clearance at day 6 [ Time Frame: Outcome will be determined till 6 days post intervention ]

The primary outcome will be the viral clearance at day 6 in the intervention group compared to placebo.

Viral shedding duration [ Time Frame: Outcome will be determined till 14 days post intervention ]

Secondary outcomes: viral shedding duration (time between first positive PCR to last of two consecutive negative tests)

Symptoms clearance time [ Time Frame: Outcome will be determined till 14 days post intervention ]

Time between drug treatment and symptoms resolution

On 2021-06-02 13:20:34, user Robert Clark wrote:

Thank you for this report. In fact, several earlier studies on HCQ failed to report the effectiveness in their own data of HCQ specifically for the case of patients on mechanical ventilation.

Since this was one of the cases with the highest fatality rates, it was truly unfortunate that this option for treatment was not presented to doctors treating ventilated patients.

See discussion here:

Rapid identification of effective treatments for COVID-19.<br /> https://exoscientist.blogsp...

Robert Clark

On 2021-06-25 10:48:30, user ScottK wrote:

Since this was an observational study with a small number of survivors, the fear is that you draw conclusions that are tied to survival and not to treatments. Simply put...<br /> MDs won't prescribe HCQ/Zithro to certain risk pools.<br /> Cumulative dose may rise with survival, not the other way around.<br /> You've got 15% of the total population in the study on this regimen and 20% of the population survived. If the MDs picked 10-15 of the 'least contraindicated' patients to do anything with, chances are that you'd see higher survival.

Double blind, controlled or explain the heck out of the pooling and selection criteria.

On 2021-06-08 00:40:20, user Daniel Bastian wrote:

"The available pharmacokinetic data from clinically relevant and excessive dosing studies indicate that the SARS-CoV-2 inhibitory concentrations are not likely to be attainable in humans."

Say it with me now: cell culture studies != controlled clinical data.

On 2021-06-11 03:08:36, user Kel Sigmund wrote:

1. Do you know if the relative lack of severe manifestations among the vaccinees with breakthrough covid 19 was associated with the occurrence of prior Covid 19 infection before undergoing vaccination?
2. Do you have data on the demographics of the vaccinee recipients, especially risk factors for severe disease and age because it would be interesting to know if the vaccine truly mitigated the severity of disease or the vaccinated population is younger and healthier than most being health care workers.

On 2021-06-15 23:51:09, user Drew wrote:

Anyone know an estimate as to when the article will be peer-reviewed? Thanks in advance!

On 2021-06-16 18:24:27, user David McAllister wrote:

Given that randomisation to budesonide was stopped in March, are we expecting the updated findings soon?

On 2021-06-16 21:14:35, user Amanda wrote:

hi - i think there is a typo! This says 8/174 -- yet earlier it said 175.

The overall prevalence of persistent symptoms was 1.7% (80/4678 children; 95% CI 1.4%, 2.1%), and 4.6% (8/174 children; 95% CI 2.0%, 8.9%) in children who had a history of SARS-CoV-2 infection before persistent symptom onset.

Also ages 2-11 were overrepresented versus 12-17

On 2021-06-19 01:13:24, user suraj senjam wrote:

Now published in Indian Journal of Ophthalmology

On 2021-06-19 11:30:14, user Will Turner wrote:

Is this small changes in most subjects, or large changes in a smaller subset of subjects? You could get insight into this by showing the distribution (histogram) of (xbefore - xafter) where x is any brain measure found to significantly decrease. Figure 1 is very helpful, but it’s unclear what percent of subjects stay the same, increase slightly, decrease slightly, or decrease dramatically.

A second question your data should be able to address but the paper doesn’t: what are the % changes here? I get that fig 1 necessarily shows an index on the y axis for comparison purposes. But shouldn’t it be possible to construct this index with an absolute 0, because any length or volume measurement can be compared to 0. Then you could understand the difference in means in terms of not just statistical significance but magnitude, which is important for understanding what kind of effects this could have.

On 2021-06-22 13:45:29, user ibamvidivici wrote:

Both, age and BMI is highly correlated for the risk of Covid-19. Can you add the data about Median-age and Median-BMI for the groups:<br /> - positive SARS-Covid-19-Test<br /> - negative SARS-Covid-19-Test<br /> for both (LTCF and HCW) cohorts?<br /> This would be necessary to measure the margin of error for this study.

On 2021-06-22 21:24:02, user Noriaki Kurita (????), MD, PhD wrote:

This manuscript has now been available from Journal of General <br /> Internal Medicine. <br /> https://link.springer.com/a...

On 2021-06-23 10:31:57, user Otto von Ruggins wrote:

As a retired High School English Teacher, my concern with this Pre-print release is that at times it reads very poorly for a would be scientific paper. There are numerous errors in syntax and sentences that are not properly formatted. As much as I appreciate the findings of the researchers, I am disappointed in the lack of editing prior to the pre-print. I am willing to go through this paper and make corrections, but I can also imagine a simple Word document Spelling and Grammer check would also be a place to start. As an example, just try reading the paragraphs prior to the endnotes from "4. Muller’s ratchet, 'mutational meltdown' and fundamental principle of natural selection" on. You will encounter 'led' which should be spelled 'lead', two non-sentences in a row, the word 'where' which was probably supposed to be 'were', which would have made one of those phrases an actual sentence and more. Sadly, as I read this informative document, every time I came across these errors, I cringed at how it ever reached this stage with so many stumbling blocks to a proper English read!

On 2021-06-23 15:59:54, user Alain Tremblay wrote:

Do the authors have more information regarding the seropositive cases. Are these believed to be seropositive due to late phase of acute illness, prior SARS-Cov-2 infection, or prior vaccination? Since the trial recruited well into the vaccination effort in the UK, vaccination status of participants should be reported as well. Thanks for this great effort!

On 2021-06-29 08:20:33, user Max Pietsch wrote:

For the peer-reviewed updated version of this paper, please see: https://www.sciencedirect.c...

On 2021-06-30 07:39:55, user ViralPseudotypeUnit wrote:

This has now been published in The Lancet Microbe: https://www.thelancet.com/j...

On 2021-07-03 19:27:03, user Janet Cunningham wrote:

This paper is now published in The American Journal of Psychiatry:

https://doi.org/10.1176/app...

On 2021-07-08 13:48:55, user Eric wrote:

So is there a study that backs up 6 or 8 weeks for young and middle aged adults?

In Germany, the recommendation until last week was to hit exactly six weeks to stay within EMA licence but spread out the vaccine. Now, with more vaccine available and Delta looming, the allow 3 - 6 weeks but without any recommendation as to which end of that window to prefer.

EMA recommends 19 - 23 days but their reasoning is that 93% of trial participants fell into that bracket. So maybe they have simply no data to say that six weeks are better?

Unlike with the AZ vaccine, there is no vector immunity to overcome so it is not clear why a longer interval should be better.

Back to those seniors in this study here, is it even good for them to have more antibodies and less T-cells? My understanding is that they are typically T-cell challenged, so is it not better to boost T-cells?

On 2021-05-19 18:42:43, user Fred Bass wrote:

Were the patients randomized into those getting usual and those getting 12 week delay? Having 99 in one group and 73 in the other does not seem like a random split of 172 people! A bias toward giving healthier seniors the longer interval might account for some or even all of the results.

On 2021-07-08 22:19:15, user Michael Plank wrote:

This paper has now been published in the New Zealand Medical Journal and is available open access at:https://www.nzma.org.nz/jou...

On 2021-07-09 09:39:24, user Alice Ka wrote:

Another possible interpretation for hesitation/reluctance to get vaccinated could be that people who did not get Covid do not see the interest of getting vaccinated since they managed to avoid Covid by using masks, washing hands, etc. This could be even more relevant for workers who attended their work as usual during the three lockdowns. It could be worth to look into this if you have access to these information.

Other interpretation: poorer people tend to travel less frequently and may have less interest in the vaccine since it is not mandatory for conducting daily activities.

On 2021-07-10 16:09:38, user mzprx wrote:

I read in another study the rouleaux formation can be by created by in inflamation acute-phase proteins..

On 2021-07-10 21:46:46, user Merja Rantala wrote:

But you did not have a proper control group! You can't say anything about association of spectacles with covid based on this work.

On 2021-07-14 16:34:10, user Melissa Mallon wrote:

I was just doing research and found this article and this describes my nose sensation. It feels like I just used a nose spray and it is clear and dry. It is a little worrisome for sure. I was in Mexico and tested positive for Covid. Small cough, smell gone, headache that's it and now this nose spray feeling. I am about 7 days after test and probably about 10 days since first symptoms of cough and headache. By the way I was fully vaccinated.

On 2021-07-15 19:57:15, user Linsey Marr wrote:

The conclusions on cough samples, sputum, nasal secretions, hands, and high-touch surfaces seem sound, but I do not agree that this study can rule out speech as a source of virus because the sampling method was not appropriate for collecting aerosols (which might carry virus) generated by speech. Subjects spoke into a 18x19 cm or 27x27 cm polyethylene bag, to which "2 to 5 mL of DMEM+ was added and residual air was expelled." First, the ~1 L volume of air sampled, representing 1-2 breaths worth, is orders of magnitude too small to capture enough viruses to detect. Second, the act of expelling the air would push almost all aerosols out of the bag. An analogy is that it's like trying to catch a fish by dipping a hula hoop into the water. The authors should consider removing this portion of the study from the manuscript.

Linsey C. Marr, Ph.D.<br /> Charles P. Lunsford Professor<br /> Civil and Environmental Engineering<br /> Virginia Tech

On 2021-07-23 15:12:27, user mef wrote:

More corrections here: https://covid19criticalcare...

On 2021-07-29 08:59:44, user Johannes wrote:

"We obtained the baseline risks for selected U.S. counties from the Johns<br /> Hopkins University dashboard and for selected states of India from the <br /> New York Times dashboard"

JHU has received well in excess of $100,000,000 from the BMGF.

Is this a potential conflict of interest ?

Many Thanks.

On 2021-07-29 23:21:22, user eli_ot wrote:

https://www.nejm.org/doi/fu...

On 2021-07-31 22:45:18, user Matt Mauro wrote:

In Table S4 it lays out the causes of death. What's the difference between a COVID-19 pneumonia death and a COVID-19 death?

On 2021-08-03 16:04:04, user Daniel Keyes wrote:

Overall the study seems strong and has tremendous impact potential. Many parts of the world could potentially prevent hospitalizations and save lives by proper allotment of vaccine resources based on evidence of prior infection if the conclusion is correct.<br /> I felt that the first diagram/flowchart could be improved: there should be vaccinated/unvaccinated for each of the two groups: previously infected, not previously infected. Would envision a branch/fork for each of the aforementioned groups rather than continuous across the same line in the diagram.<br /> Given the time being taken to review this article (it seems long, but actually is probably not that long!), the reviewers might consider extending the data to the end of June, which could provide implications with respect to delta variant. As it is, the Midwest, where the study is located, already has a very high percentage of delta variant. But this was probably not the case for the period up to May 15, the end date for the study. Delta started to be present in mid-March, but was not substantial for the ensuing 2 months.. But, of course, that might delay the review process even longer, and would not be likely to change the conclusion.

On 2021-09-11 13:44:07, user Don Schott wrote:

First off, I tested positive, quarantined and received two jabs.<br /> This fills in some of the blanks of the Pfizer-BioNTech-19 submitted to the FDA that was approved by their Scientific Advisory Committee for experimental use. Tens of millions of jabs later and more to follow, we apparently know less.

The FDA Reviewers expressed specific concerns that the 40,000 plus in each Pfizer experimental and control groups did not show much difference-- no one died, 6 hospitalized in one group 1 in other group. But, they claimed there focus was on safety. The authors should be applauded for calling for more study of the effects of vaccines.

Sadly, FDA and CDC have little or no research (consensus doesn't count) before and since these approvals. The dissent that calls for more research is met with derision and insults, never data.

On 2021-09-12 11:21:41, user Shih-Hao Yeh wrote:

Let me assume your approach and data you used are all valid without any problems. <br /> 2 questions for your calculation and comparison in Fig 6 & 7.

(1) I'm confused in 44.4+210.5=255 in your Fig. 6. According to your context, 70% of children hospitalized for COVID-19 having medical comorbidity, and 30% don't. And in general, you estimate 33% of children in this age group have comorbidity based upon current data. So the likelihood of a CMB(comorbidity) kid get to hospital for COVID is 4.7 times more than a H(healthy) kid. [(0.67/0.33) / (0.3/0.7) = (0.67*0.7) / (0.33*0.3) = 0.469 / 0.099 = 4.7] That is correct.

Yet, what is the risks to be hospitalized for COVID for a H kid and a CMB kid respectively?<br /> Ans: <br /> Suppose in an average US medical area with 1 million adolescents, by your data, there will be 255 kids/1M hospitalized for COVID in 12 weeks supposed median prevalence . <br /> So, how many of them are H kids? How many CMB kids?<br /> 255*30%=76.5 H kids/1M kids<br /> 255*70%=178.5 CMB kids/1M kids<br /> Not 44.4 and 210.5.<br /> Yet, there are 670k H kids and 330k CMB kids per 1M kids.<br /> So, if you're healthy, in 1M healthy kids, your risk to be hospitalized for COVID within 12-week is<br /> 76.5/0.67=114/1M H kids<br /> if you have CMB, in 1M CMB kids, your risk to be hospitalized for COVID within 12-week is<br /> 178.5/0.33=541/1M CMB kids<br /> And yes, 541/114=4.7.

The risks to be hospitalized for COVID are actually larger than 44.4 and 210.5. Same mistake in high or low prevalence in the table. Tip: conditional probability. You don't include adult in the denominator of kid's risk, right? Same here.

(2) Further stratifying numbers into healthy and comorbidity groups to make the number smaller (by miscalculation) is a cunning move. Yet, it make sense. Comorbidity do contribute the severity of COVID.

However, since you stratify data for risks being hospitalized for COVID, why don't you stratify data for risks of vaccine-associated myocarditis (VAM)? I suppose that some medical comorbidity may also contribute to the risk of VAM?

I don't think these comparison in your paper are fair, meaningful comparison: <br /> P(healthy AND hospitalized for COVID) vs P(VAM)<br /> P(CMB AND hospitalized for COVID) vs P(VAM)<br /> These are meaningful comparison given same conditions:<br /> (a) P(hospitalized for COVID) vs P(VAM)<br /> (b) P(healthy AND hospitalized for COVID) vs P(H AND VAM)<br /> (c) P(CMB AND hospitalized for COVID) vs P(CMB AND VAM)

Taking these 2 problems into consideration, I don't think you can hold your original conclusion. If 255/1M can become 114 and 541 respectively, 162/1M can also become some numbers less than 114 and 541.

On 2021-09-17 17:37:04, user kdrl nakle wrote:

Separate two different vaccines you have and then rewrite paper with separate conclusions, not just giving tables. You cannot jam them altogether, tables are not enough.

On 2021-08-21 06:05:58, user Dinofelis wrote:

Even though 10% is within the confidence interval 8.4% - 24.8%, what is hard to explain is that the number of severe cases per 100 cases decreases faster (16.6%) than the rate of vaccination increases (10%). It would actually mean that non-vaccinated people that do get covid, are less often severely ill because others got vaccinated. That's very hard to explain, unless several of them got infected by vaccinated people with a lower viral load, but that would then imply a lower effect on infection prevention than demonstrated in this article.

On 2021-08-23 08:57:48, user Isatou Sarr wrote:

Hi,

What is the self ''clearance efficacy'' of the immune attack complex as a result of re-infection after vaccination and is there a need for medication to boost up the clearance cycle? What is the half-life of the vaccine induced antibodies/immune cells? Most vaccine studies are majorly focused on immune end-points with little on debris clearance and it is important to understand the dynamics of immune ''mop up'' as well as not only the longevity of the generated antibodies/immune cells but their subsequent efficacy upon initial encounter with antigens. It is also critical to understand the clonal expansion pathway of immune cells generated as a result of specific vaccination both on an individual basis and on the wider population.

Thank you.

On 2021-08-24 10:14:29, user Mikaela Olsen wrote:

How I wish it was possible to contact the authors to ask a simple question. The study compares two groups but which groups? One group contains those who survived a SARS-cov-2 infection the second group contains vaccinated people who would and would not survive an in fection. Is it really possible to compare these two groups? What would waning of antibodies have looked like if it was possible to exclude those who would not survive an infection from the vaccinated group?

On 2021-08-23 13:36:18, user Leo G. wrote:

Oral and nasal hygiene with Povidone-Iodine is widely used in India & Bangladesh to prevent nosocomial transmission.

It is equally effective in community settings. This hygiene includes gargling, mouth rinsing, nasal drop or irrigation. They should be performed 2-5 times per day, and/or before visiting the clinical

Many Listerine & Crest mouthwash products can be used for gargling.

On 2021-08-24 15:12:55, user Maria Kozlova wrote:

Thank you for the research!<br /> But perhaps the descriptions for Figures 5 A and B in the text and in the picture are confused?

On 2021-08-25 10:47:17, user ibamvidivici wrote:

In Figure 1 c is a infectiouness profile startet ca. 10 days before symptoms onset. But Figure 3 shows, that the meassurement startet 4 days before symptoms onset. How is that possible?

The infectiousness profile is not the real infectivity, it is the viral load of the tested person, estimated from the Ct-Value. For real infectivity the viral load had to be transfered to another people. After symptoms onset this happens with cough and sneeze. I doubt, that this happens before symptoms onset, because the only possibility would be by breathing. But Aerosol size of breathing droplets ist smaller than 1 micron and is vaporized in less than 1 ms, so before it settles onto a desk or towards other people. It's not proofed, that the virus is still intact after vaporisation process of the aerosol droplet.

(only relatives could become infected from asymptomatic by kissing or shared cutlery.)

On 2021-08-26 20:37:24, user David Anfinrud wrote:

This is mostly common sense. But again to get people to understand that those that had COVID are better protected and do not need the vaccine you have to have a study. This information is just a repeat of science seen over the Decades. Vaccines help but the best protection is natural immunity

On 2021-08-27 06:06:45, user joseph harrison wrote:

I wonder how this study accounts for people who died from infection from covid, considering that people who die from covid may have some defect in immune response, which has been documented in serveral studies. These immunocompromised people are effectively removed from the infected pool but are still present in the vaccinated pool, where they may not have as strong of an immune response to the vaccine. Furthermore, we are talking about a relatively small increase in breakthrough infection rate 13%, or the difference between a 30% or a ~35% chance. While the study seems well done and interesting to evaluate, I am dissappointed to see it linked on drudge with a headline natural immunity is better than the vaccine, when there are many other ways to potentially explain the small increase in protection from breakthrough infections.

On 2021-08-27 16:48:32, user Edward wrote:

This study adds important previously unreported information comparing natural post-infection immunity to immunity after vaccination. Unfortunately, the study risks giving the false impression that it is better to go ahead and seek natural immunity over vaccine immunity. The study, for example, does not take into account covid-attributable excess deaths. Thus, by default, those with natural post-infection immunity considered in the study are covid survivors. Hence, they can be expected to have stronger immunity than those who died because of covid. While the basic premise that natural immunity is stronger than vaccine immunity in the abstract, I suspect it is better to get a milder case of breakthrough covid than to risk death in search of natural immunity. We need a much larger study, ideally prospective, and will have to measure the frequency of "long haul covid" cases between the vaccinated and unvaccinated.

On 2021-08-27 19:58:34, user Kryptos wrote:

Good research study. So is it necessary to risk vaccinating a billion children who have no underlying conditions, considering the risks of blood clots, vascular damage, etc.? Wouldn't it be better to let them acquire natural immunity?

On 2021-08-28 16:17:13, user Aaron Plummer wrote:

Doesn’t common sense already confirm this though. Natural immunity has already been proven to be the most effective in everything for hundreds and hundreds of years. The vaccine hasn’t even been around for a year yet. One is our natural survival instincts that have allowed humans to survive severe deadly and catastrophic events over hundreds of years, and one is man made in a lab based on hypothesis and trial and error experiments. Again common sense dictates that natural immunity will always win this debate. Too bad this administration doesn’t seem to recognize or acknowledge its effects.

On 2021-08-29 17:43:03, user Edison Wong wrote:

I looked at the raw #s. If you take model 1, the break thru infection rate for the twice vaccinated was 1.46%. This is actually a much higher rate of efficacy vs clinical trials abd other studies I have seen. When you look at breakthru infections for previously infected, this is 0.12%. I do not see this mentioned anywhere else. A 13-fold greater risk of infection does becomes less meaningful if the higher risk group is closer to 1% than 10%.

Perspective is important to determine how much of a public health response is reasonable. If the risk is for 100 people vs 1000,000 in a nation of 6 million, that should figure into any decision for lockdown & mask mandates.

On 2021-08-30 20:34:53, user Jason Anderson wrote:

I am from the opinion that this type of article being available before being peer-reviewed is slightly irresponsible due to the amount of news coverage it is likely to receive. After reading the manuscript, if I were reviewing, it would be a strong reject or major revisions (depending on the opinion of the handling editor). My expertise is certainly not medicine, but it is on data science and advanced statistical/econometric methods - the precise methodology the authors used here. To keep it short, splitting the data and generating separate models is not appropriate in this context based on the discrete outcomes the authors are modeling. IF, and big if, the authors are going to defend having separate models, there are a series of tests that need to be done to show that this is the appropriate approach. This is lacking. Also quickly, the authors have done their best at controlling for what they can, but there are still numerous unobservables that are not accounted for. Why is this important - it can bias parameter estimates, which leads to ORs (calculated from parameter estimates) that are not true representations of the population parameters. ORs can also be misleading; hence, the preferred inference is based on marginal effects.

If anybody, including the authors, are interesting in additional, more detailed comments, I'd be happy to discuss.

On 2021-09-02 18:28:43, user Kostas Damdas wrote:

Who were the participants? people vaccinated in january vs people covid positive recently? immunocompromised vs healthy?

On 2021-11-09 10:52:01, user Harry Wood wrote:

The Israeli study is flawed on many levels. This dissects the errors.

https://www.quora.com/A-rec...

On 2021-08-27 02:02:02, user Alexis Hill wrote:

Nice search, I wonder will you provide sample collection time, information on transmission pair?

On 2021-08-27 02:16:17, user Tom Hennessy wrote:

Phlebotomy.

"Reduction of the body iron stores can improve hyperandrogenemia and insulin resistance"<br /> "phlebotomy with consecutive reduction of body iron stores lowered blood pressure and resulted in improvements of markers of cardiovascular risk and glycemic control."<br /> "blood donation may prevent not just diabetes but also cardiovascular disease"<br /> “Our findings suggest that lower-end normal Hb levels are favorable for and maintenance of healthy metabolism involving mild chronic activation of the hypoxia response. Therefore modulation of Hb levels could serve as a novel strategy towards treatment of metabolic syndrome”<br /> “Our findings suggest that an increased Hb level is a predictor of elevated serum ALT in adolescent girls with dyslipidaemia. Our study also highlights the importance of further research to establish cut-off points for Hb and its utility in diagnosing and preventing the onset of dyslipidaemia in adolescents. ”<br /> "Our findings provide in vivo evidence of a relation between hyperinsulinaemia/insulin resistance, the main variables of insulin resistance syndrome and erythropoiesis. Increased red blood cell count could be considered as a new aspect of the insulin resistance syndrome that could contribute to the increased risk of developing cardiovascular problems."

On 2021-08-29 20:22:01, user Holger Lundstrom wrote:

"PCM received funding from the Wellcome Trust [110110/Z/15/Z]."

To quote from:<br /> https://www.bmj.com/content...

"An increasingly clear feature of the covid-19 pandemic is that the public health response is being driven not only by governments and multilateral institutions, such as the World Health Organisation, but also by a welter of public-private partnerships involving drug companies and private foundations."

"These advisory and media activities seem to overlap with Wellcome’s £28bn endowment, which has at least £1.25bn invested in companies working on covid-19 vaccines, therapeutics, and diagnostics: Roche, Novartis, Abbott, Siemens, Johnson & Johnson, and—through its holdings in the investment company Berkshire Hathaway—Merck, AbbVie, Biogen, and Teva.11"

"Yet charities such as Gates and Wellcome—and even drug companies—have generally been praised in the news media during the pandemic for their efforts to solve the public health crisis, with relatively little attention paid to their financial interests and with few checks and balances put on their work."

“What the pandemic is doing is buffing the reputation of organisations like Gates and Wellcome and the drug companies, when I don’t think they really deserve that buffing up,” says Joel Lexchin, professor emeritus of York University’s school of health policy and management in Toronto. “I think they’re acting the way they always have, which is, from the drug companies’ point of view, looking after their own financial interests, and from the point of view of the foundations is pursuing their own privately developed objectives without being responsible to anybody but their own boards of directors.”

On 2021-08-30 04:59:27, user William Brooks wrote:

The authors estimate that if the UK government's hadn't extended restrictions for another month, daily hospital admissions would have reached 3400, whereas they peaked at only 1400 due to restrictions being extended. However, according to Our World in Data, peak weekly admissions in July were higher in the UK than all mainland European countries except for Spain and considerably higher than in countries with fewer restrictions and smaller percentages of population vaccinated such as Sweden and Croatia.

To better assess the results of the UK government's decisions, it would be more informative to compare England's outcomes to the real-world outcomes of other European countries instead of models that may overestimate the effects of government actions.

On 2021-08-31 14:22:02, user Shungo Y@JOJOLANDS(?)????????? wrote:

The standardized mean difference is the difference in proportions between groups divided by the standard deviation for a binary variable. <br /> https://handbook-5-1.cochrane.org/chapter_9/9_2_3_2_the_standardized_mean_difference.htm

The authors seem to use SMD simply as the difference in proportions. Therefore, we do not know if the two groups are well balanced.

On 2021-09-01 09:50:45, user Till Bruckner wrote:

This paper usefully highlights and quantifies the scarcity of randomised trials of NPIs. Providing a precise definition of NPIs and more details on inclusion/exclusion criteria might add value.

A potential weak point is the claim that "it is unlikely that we have been unaware of pertinent results of further NPI trials, given their substantial impact on current debates and scarcity of the evidence." This appears to assume that all NPI trials were either (a) registered in a trial registry or (b) reported in the academic literature.

There may have been experiments meeting the inclusion criteria that were run by government bodies and research units such as "nudge units" that were neither registered nor made public in academic formats.

Performing a grey literature search and/or reaching out to key informants outside academia who may be able to comment on the likelihood of such research having been performed would help to provide assurance that no relevant studies have been missed, and strengthen the conclusions of the paper.

Till Bruckner

On 2021-09-03 13:39:22, user rbrine@msn.com wrote:

Since “each mRNA-1273 dose provides three times more mRNA copies of the Spike protein than BNT162b2”, why do recipients of mRNA-1273 require two doses for “full vaccination”, like recipients of BNT162b2, especially if the first mRNA-1273 dose caused a prolonged adverse reaction?

On 2021-09-03 20:53:44, user Cal Research wrote:

This article has been published in Frontiers in Medicine: https://www.frontiersin.org...

On 2021-12-01 13:58:36, user Nudnik_de wrote:

I'm missing one parameter in the study. It seems there is no differentiation made under which condition people interact with each other. In other words, whats the impact of 3G and 2G rules? Vaccinated but not tested people meet Unvaccinated but tested folks... I'm concerned that the lack of considering such aspects could have a severe impact on the results and therefor lead to improper measures.

On 2021-12-01 21:40:48, user anedabei wrote:

The statement of the paper "unvacs drive it" ist not grounded in reality.

The weekly report of the RKI Report from Nov 25 compares vacs and unvacs in "Tabelle 3"

Unfortunately, it is in German, so some help: The row "Symptomatische COVID-19-Fälle¹ " shows symptomatic cases for the prior 4 weeks.<br /> Adding them up results in 289.953 cases for all age groups. 139.856 of them or 48 % are vac breakthru.

So both vacs und unvacs contribute about the same to drive the pandemia. However, vacs are of course somewhat better protected.

For VE, the vac rate needs to be considered. It is, taken from page 24, 12-17 years 43.0 %, 18-59 years 75.0 % and for 60+ years 87.8 %, resulting in an average rate of 68.1 % for the entire population.

On 2021-12-01 22:43:19, user Tom wrote:

Is the use of a 2005 Contact-Model feasable? It does not take the "2G"-Rules and the general fear of Covid into account. I Assume that stadiums full of vaccinated people thinking they are safe while the unvaccinated are not allowed to enter would skew the contact-matrix.

On 2021-12-02 08:51:52, user koen wrote:

This publication makes a number of hard claims, with a title that insinuates as such. These claims are based on a model that is proposed by the authors without proper validation and verification of the model. One of your claims is that your models shows that with a vaccination uptake of 80% of the total population the reproduction number r remains at 0.86 in the current situation in Germany. These claims could be verified by applying the model to the COVID situation in different countries (with higher and lower vaccination uptake). Furthermore, contact tracing results should be used in part to validate claims about the source of infection. Based on the comments above and the discussion in the article the subjective title seems inappropriate and suggestive to person viewpoints of the authors.The best of luck in publishing this article in the current state!

On 2021-12-02 13:52:27, user Thomas Binder wrote:

With all due respect, this modelling study is based on totally wrong assumptions thus is just GIGO: Garbage In, Garbage Out!

On 2021-12-08 20:50:16, user doc_fishoil wrote:

The theme of this paper is the poor attempt of turning absurd assumptions into golden scientific insights by algebraic mumbo-jumbo: <br /> Just take formula (7) to see that "base transmissibility" for the vaccinated and the unvaccinated (that represents their behaviour) produces any proportion of contributions of vaccinated and unvaccinated, as all other parameters are gauged somehow on data. <br /> However, the authors want to blame the unvaccinated, hence they chose to set them as equal although rather harsh testing rules only for unvaccinated were in place in Germany during the referred time ("3G"). Without any reason, comment, validation estimation of real word data, just by assumption in obvious and absurd contrast to everyday life experience. <br /> The result is delivery as ordered.

On 2021-12-01 22:20:28, user Kevin J. Black, M.D. wrote:

One more you may want to look at:<br /> Vitale C, Pellecchia MT, Grossi D, et al. Unawareness of dyskinesias in Parkinson's and Huntington's diseases. Neurol Sci. 2001;22(1):105-106.

On 2021-12-03 05:20:19, user Alberto wrote:

"see Figure 1(b). The plots show the dramatic situation that would have occurred in the case of the lack of vaccines. Indeed, by looking at Figure 1 (a) and (b), we observe an increase of a factor 10 in severe infections. This scary increase would have generated a serious crisis in the Israeli health system."

A 10 times increase in severe cases and (therefor, presumably) deaths is indeed a scary scenario. So much so that it's incompatible with the reality we see everywhere (including, for example, Palestine), and incompatible with the previous year's numbers, when 0% of the population was vaccinated.

There is obviously a very strong confounding factor that must have not been taken into account in these calculations of vaccine efficacy. Finding that confounding factor would be essential for this and all other studies to give us correct estimations. Otherwise we're just speculating with unrealistic numbers.

On 2021-12-03 21:49:24, user gwern wrote:

An incorrect result from the first version of this paper (about PhDs being the most reluctant to get vaccines, when really they are probably the least) is still being very widely shared on social media (I can see several instances on Twitter today alone). The error should be discussed explicitly, in more detail, not buried in a vague throwaway comment about some categories being 'higher'; not just so people reading it will understand it, but as an instructive lesson to other researchers about the perils of mischievous responders in surveys, particularly online ones.

On 2021-12-06 07:07:21, user neil Muller wrote:

While this study may raise important questions it is being interpreted in ways that are not justified by the analysis. The paper answers a very narrow technical question as to whether there is an increase in the hazard ratio of primary infection versus reinfection compared to the first wave. Given that the risk profiles of the groups subject to the risk of primary infection and reinfection are so different (by definition the group at risk of primary infections now consists of only 30 to 40 percent of the population who have either adopted behaviour that is less risky, live in communities that were bypassed by the previous waves, or are in the 26 million people vaccinated so far) while the previously infected include the population at higher risk of infection by definition amounting to as much as 70 percent of the population) one would simply expect this.

As the study notes, to date of the possibly 42 million South Africans who have survived Covid infection 36 000 of these people have been identified as reinfections. Naturally as only 3 million infections have been identified by a test so this will be a dramatic under-estimate. But even if it is off by a factor of 15 which identified cases may be this is still only about 500 000 reinfections from 40 million infections.

Natural immunity is highly effective against reinfection.

It is unclear how the estimated change in the hazard ratio changes the projected number of reinfections.

In addition as no information is provided on the risks of hospitalisation and death based on the 36 000 identified reinfections to date we don’t even know whether this has any meaningful policy implication.

But it is the use of this paper in the framing of social and health policy that suggests that if these implications are not spelled out that makes this article misinformation.

The analysts cannot be naive about the debate on vaccine mandates in South Africa. There is clearly a concerted push to demonise the unvaccinated and to make the path to Vaccine Mandates for Covid Acceptable.

The headlines in the popular press focus on the apparent implications of this paper for natural immunity. The claim is that it will not hold up for infection under omicron.

This is clearly NOT what the paper says. The authors need to take responsibility for the way in which this research is being presented and clarify exactly what the paper says about the likely number of people who will be infected by omicron and if so, the number that are likely to require hospitalisation and run the risk of death.

The fact of the matter is that the authors can’t say anything about this as we don’t know about omicron. They admit this.

But they can indicate the number of 42 million South Africans that have natural immunity are likely to be reinfected. They can say the number of these people who are likely to be hospitalised. They can say the number of reinfected people who are likely to die.

They can say that there is no evidence that vaccination will provide any more immunity against infection than previous infection. They can say that there is no evidence that vaccination will lead to less hospitalisations or deaths than natural immunity.

Absent this they remain silent on the calla to reimpose apartheid era strategies such as the population registration act, separate amenities act, and all the hate speech and violation of rights guaranteed in our constitution. This time it is not based on race but on the equally socially constructed and unscientific concept of the unvaccinated.

To sensitise oneself simply replace the term unvaccinated with the k or n word and see if the statements that are made so easily are acceptable.

On 2021-12-06 15:18:05, user Jens Happel wrote:

Dear Robert,

thanks for the study. Is it possible to differentiate the group of the unvaccinated in unvaccinated and vaccinated between 1st dose and 2 weeks after infection?

In some studies they found the effect that between 1st and 2nd jab the likelihood of infection is significantly increased.

For example here

https://www.researchgate.ne...

see figure 2

Would be intressting to see what happens in this group.

Kind regards<br /> Jens Happel

On 2021-12-08 20:43:25, user Peka Bali wrote:

page 15 of the full text report reads: "Symptom probability time courses for participants with confirmed COVID-19 (n=1020, RT-PCR, antigen, or antibody tests) overlapped significantly with probability estimates from the whole population (Figure 7), except for “changes in sense of smell/taste."

How does this coincide with the conclusion of the report on the first page?!

"Conclusions. Patients with Long COVID report prolonged multisystem involvement and significant disability. Most had not returned to previous levels of work by 6 months. Many patients are not recovered by 7 months, and continue to experience significant symptom burden. "

I am simply flabbergasted by this pseudo-scientific conclusion, not to mention giving it a collective name!<br /> If anything, the only rational conclusion that can be drawn is that other than the altered sense of taste/smell there is NO correlation or causation whatsoever between Covid-19 and the other 65 symptoms as described!<br /> The insinuation as posed above in the publication, stating negative PCR and antibody tests as "suspected cases" is just absurd. What do you base this assumption on?!

This report makes no sense: when you have a control group and baptizing your control group to "suspected cases" to justify the conclusion, which is that these symptoms are Covid related when they are clearly not.

On 2021-12-13 14:29:16, user vepe wrote:

it looks like this study has a major flaw in the calculation of the covid cases

for example their data set contained 6846 cases in the cohort 12-17 (they applied the same logic for the other cohorts)

The 6846 number of covid cases for 12-17 was 2.5% of the total covid cases in their data set.<br /> Then they assumed the same infection rate as the adults at the time, 9.2% and normalized their total number of cases for 12-17 based on that:<br /> adjusted number covid cases = 6846*9.2/2.5 = 6846*3.7 = 25193

then they almost doubled the number of myocarditis cases on the premise that there would be cases that they would miss (e.g. people receiving care outside the TriNetX system)

so they end up with about ~12 myocarditis cases per 25193

so the biggest problem is that their estimated number of covid cases, is essentially the number of covid cases they were expecting to see in their data set and not the total number of covid cases associated with their data. Even if they were meant to estimate the number of covid cases they were expecting to see, this estimation is not accurate since the probability of a younger person ending up in the hospital is way smaller than adults.

In practice, based on that estimation of covid cases, the authors implicitly say that 2.5/9.2=27% of young people that get coronavirus, end up diagnosed/treated by health care provider. This looks like a big overestimation.

In practice, hospitalization rate for younger people looks like is closer to 2% as indicated below:<br /> https://www.aap.org/en/page...<br /> https://covid.cdc.gov/covid...

I think a more accurate estimation would have been to skip the normalization based on infection rates and estimate based on the probability a young person has to end up to a health care provider.<br /> example, covid cases = 6846*100/2 (instead of 6846*9.2/2.5)

Based on this estimation of covid cases, myocarditis risk would be higher in vaccination instead of infection for young people

On 2021-11-24 21:54:37, user Jens Happel wrote:

If the calculation and assumptions would be correct there would be a huge surge of Myocarditis during the Covid19 waves.

But that is clearly not tbe case.

https://jamanetwork.com/jou...

During the Covid19 waves the number of Myocarditis and Pericarditis was more or less constant.m, compared to 2019.

The surge started according to cited paper above in February, when most of the wave was over but vaccination rate started to pick up speed and was changing from elderly to the next younger groups where Myocarditis is more likely.

I guess your assumption about not detected Myocarditis is terrible over estimating that factor.

The charts in cited paper above show clearly that your paper has substantial flaws.

On 2021-12-13 19:29:22, user Surya wrote:

Dear researchers,

It's stated in the text that : "However, a 1-42 day risk interval was also used, since this interval is often used in vaccine safety studies of GB S and other outcome."; also the text states "Results were similar when excluding Brighton level 4 cases and when using a 42-day risk window, with incidence rates ranging from 1.1 t o 2.1."

I'm wondering why the results of SCRI are not shown for the 42 days window at risk and mRNA vaccines.

On 2021-12-13 19:29:49, user Joseph Psotka wrote:

The study fails a basic test of good design: the HCW were only described as over 18. That's ridiculous! Full age and gender details should have been provided. Seems like a crummy study.

On 2023-08-30 17:56:46, user Caroline Lima wrote:

This review resulted from the graduate-level course "How to Read and Evaluate Scientific Papers and Preprints" from the University of São Paulo, which aimed to provide students with the opportunity to review scientific articles, develop critical and constructive discussions on the endless frontiers of knowledge, and understand the peer review process.

In this pre-print, the authors discuss the growing demand for ultra-processed foods and their harmful effects on human health. The presence of different oxidized substances and the low nutritional value is associated with chronic cardiometabolic diseases such as cancer, diabetes, Parkinson's, and Alzheimer's. This makes ultra-processed foods a subject of great interest and widely studied. This observation reinforces how important it is to study possible causes for the development of the aforementioned diseases and how research should be conducted to identify and possibly prevent them. It is also important to emphasize that the specific description of what leads these foods to develop oxidized substances is necessary in order to make a correct judgment of the causes and not classify all foods that have undergone some processing as equally containing oxidative substances.

Comments and questions:<br /> The authors prove that oxidative dietary substances and phytosterols are found in ready-to-eat foods and fast foods including those of animal or vegetable origin if preservatives/dyes were used, when high temperatures during the preparation process were used, and in a manner related to forms of storage and distribution.<br /> The use of different biomarkers has been suggested for both ready-to-eat foods and fast foods. Why use brassicasterol biomarkers for ready-to-eat foods and biomarkers (7?-OH and 7?-OH) for fast foods? Is there any specific reason for using these biomarkers? Are there other biomarkers that could be used?<br /> The use of different biomarkers for each food category is reccomended: dairy products (brassicasterol), eggs and derivatives (stigmasterol and ?-sitosterol), meat and poultry (7?-OH), seafood and baby food (?-sitosterol) and others (campesterol). What can each biomarker reveal for each food?<br /> How can the assessment of exposure to oxidative substances be established and what criteria should be considered and disregarded in this assessment? Would these values/results be enough for possible preventions and diagnoses?<br /> For biomarkers, is there any factor that interferes with this measurement and evaluation?

On 2021-12-20 07:43:09, user A. Mesut Erzurumluoglu wrote:

Now published at: https://www.sciencedirect.c...