On 2021-09-12 21:59:19, user Swapnil Hiremath wrote:

<reposting with="" minor="" edits="" as="" disqus="" thought="" last="" one="" was="" spam="" for="" some="" reason=""><br /> The authors have undertaken an ambitious project: briefly, taking numerators from the VAERS database, denominators from vaccine numbers from elsewhere. They then perform a ‘harm-benefit’ analysis looking at COVID hospitalization as the only harm. The whole analysis is restricted to the 12-17 age group in whom the concern of myocarditis is admittedly higher.<br /> They report a risk which was anywhere from 1.5 to 6.1 times higher for vaccine associated myocarditis vs COVID causing hospitalization. Vaccines must be bad, surely.

However, several problems are quickly apparent.<br /> 1. The rate of myocarditis is much higher than the ones reported in Ontario: 160/million for 12-15 males compared to 72.5/million from Ontario (which includes Moderna as well - which has higher rates of myocarditis than the Pfizer/BioNTech). Why would this be so? There are many possible reasons, including the overestimation from VAERS being probable cause. On a perusal of the supplement, there are many which are other viral diseases which could be the reason; additionally many descriptions are quite vague (‘the doctor told us troponin was elevated’). It is very easy to submit cases to VAERS, so the numbers reported could be an overestimate - proper case ascertainment with source documents is necessary to be sure of the cases. Needless to say, simple arithmetic to derive 'rates' is also problematic. The VAERS website specifically suggests the numbers should *not* be used for estimating rates.

1. It was not clear why the authors chose Jan 1, when vaccines EUA for 16-17 started in March, and for 12-15 in May. In their database, there seems to be one case in March and most of the VAERS reports from May or later.

3.Next, the authors make many assumptions when it comes to who had comorbidities and who did not among the children, and multiply numbers to come up with some crude estimates. It would be useful for a pediatric diseases researcher to assess these assumptions. The 40% assumption of children hospitalized 'with COVID' and not due to COVID is a very crude untruth that the authors and others have needlessly perpetuated on social media with little foundation.

1. Most importantly, the authors assume that hospitalization is the only bad thing for children who develop COVID. Some 12-17 years olds have died due to COVID, and some may have had a 1 day hospital stay - their analysis treats these equally and incorrectly. Some teens developed MIS-C. Some developed longer term sequelae. To group them under ‘hospitalization’ seems overly simplistic. Similarly, from perusing some of the vaccine-myocarditis, many seem to have recovered with symptomatic care alone. The authors seem to be minimizing COVID and maximizing vaccine associated adverse events.

2. It should be noted that the involvement of children in the first two waves seems to be different than the one we have seen in the last 2 months with delta (for whatever reason - perhaps with lower immunization numbers in these).

3. Lastly, the pandemic is not yet done. Many more children are going to get COVID in the next few months and years. We are going to have many more hospitalization, morbidity and sadly many more deaths. There will be long term morbidity and sequalae. We do need better data to assess the risks and benefits. This study is not it.

Unfortunately this study has been picked up uncritically by media and will worsen vaccine hesitancy. This seems unwise in the face of an ongoing pandemic.

On 2021-09-14 18:45:10, user Nicole wrote:

Hey YOMAMA, I guess you didn't look at the publicly available information before questioning credentials:

Www.Ohri.ca/profile/shiremath

On 2021-09-12 01:57:32, user Swapnil Hiremath wrote:

The authors have undertaken an ambitious project: briefly, taking numerators from the VAERS database, denominators from vaccine numbers from elsewhere. They then perform a ‘harm-benefit’ analysis looking at COVID hospitalization as the only harm. The whole analysis is restricted to the 12-17 age group in whom the concern of myocarditis is admittedly higher. <br /> They report a risk which was anywhere from 1.5 to 6.1 times higher for vaccine associated myocarditis vs COVID causing hospitalization. Vaccines must be bad, surely.

However, several problems are quickly apparent. <br /> 1. The rate of myocarditis is much higher than the ones reported in Ontario: 160/million for 12-15 males compared to 72.5/million from Ontario (which includes Moderna as well - which has higher rates of myocarditis than the Pfizer/BioNTech). Why would this be so? There are many possible reasons, including the overestimation from VAERS being probable cause. On a perusal of the supplement, there are many which are other viral diseases which could be the reason; additionally many descriptions are quite vague (‘the doctor told us troponin was elevated’). It is very easy to submit cases to VAERS, so the numbers reported by the authors seem to be higher than the true value. The case ascertainment performed in Ontario seems a bit more reliable and trustworthy than user entered data in VAERS.

1. It was not clear why the authors chose Jan 1, when vaccines EUA for 16-17 started in March, and for 12-15 in May. In their database, there seems to be one case in March and most of the VAERS reports from May or later.

2. Secondly, the authors make many assumptions when it comes to who had comorbidities and who did not among the children, and multiply numbers to come up with some crude estimates. It would be useful for a pediatric diseases researcher to assess these assumptions. The 40% assumption of children hospitalized 'with COVID' and not due to COVID is a very crude untruth that the authors and others have needlessly perpetuated on social media with little foundation.

3. Most importantly, the authors assume that hospitalization is the only bad thing for children who develop COVID. 12-17 years olds have died due to COVID. Some developed MIS-C. Some developed longer term sequelae. To group them under ‘hospitalization’ seems overly simplistic. Similarly, from perusing some of the vaccine-myocarditis, many seem to have recovered with symptomatic care. The authors seem to be minimizing COVID and maximizing vaccine associated adverse events.

4. It should be noted that the involvement of children in the first two waves seems to be different than the one we have seen in the last 2 months with delta (for whatever reason - perhaps with lower immunization numbers in these).

5. Lastly, the pandemic is not yet done. Many more children are going to get COVID in the next few months and years. We are going to have many more hospitalization, morbidity and sadly many more deaths. There will be long term morbidity and sequalae. We do need better data to assess the risks and benefits. This study is not it.

On 2020-08-03 08:21:45, user Meead Saberi wrote:

The paper is now published here: https://doi.org/10.3389/fph...

On 2020-10-18 23:05:10, user Joe B wrote:

Would have been interesting to also examine use of fentanyl, dexmedetomidine and propofol in these patients. Also, since there is no IV formulation of melatonin available (we had the IND for it), presumable oral melatonin was used. The bioavailability of it is very low, about 15% (already published data years ago). So, the doses used would have been important to know also. Sort of shocking that P&S is using so much in terms a atypical antipsychotics in patients who presumably have ICU dementia, generally not recommended by SCCM guidelines.

On 2020-04-01 22:22:34, user Sui Huang wrote:

Nice, important work. Question: Mechanical ventilation has been associated with increase of ACE2 expression in the lung post-mortem. Do you find support for this previous finding in your data?

On 2021-08-25 12:07:48, user Prof. W Meier-Augenstein, FRSC wrote:

What other than the difference in antibody titer post-vaccination and post-infection is the take-home message of this study? Surely, the decline in antibody titer per se months after vaccination or primary infection is not a surprising finding but could be expected? Antibodies have a finite life-span given by their Ig specific half-life (for example 21 days for IgGs). In the absence of a subsequent challenge (e.g. by a secondary infection) antibodies formed in response to the challenge posed by vaccination or primary infection will have all but cleared from serum after 6+ months. Furthermore, the difference in antibody titer between mRNA vaccinated and SARS-CoV-2 infected could not have come as a big surprise either considering mRNA vaccination results in expression of spike-protein “only” which means in contrast to a viral infection host cells are actually not infected and do not reproduce copious amounts of the virus which will take longer to fight and clear from the body than the spike protein. For the same reason, macrophages (phagocytes) are unlikely to be involved in the mRNA vaccinated group to the same degree as they are in the group infected by the virus. The natural decline of IG antibodies produced in response to the mRNA vaccine does not offer an exclusive explanation for breakthrough infection. Instead, breakthrough infection occurring 146+ days post vaccination are most likely the result of a “perfect storm”, an unfortunate coincidence of the higher virulence of the Delta variant of <<7 days incubation time, the associated higher viral load produced, and the fact the production of neutralising antibodies by B-memory cells takes up to 4-5 days to reach its peak.

On 2021-08-26 17:27:19, user YT14 wrote:

At least the study is comparing apples with apples by looking at the titres of antibodies against the spike protein. And it is good to put a number in comparison between maximum titre of vaccinated to maximum titre in recovered. That it is lower in the recovered is probably due to their having antibodies against all the other components of the Wuhan coronavirus. And there is also the issue of the untested T-cell response, that is probably quite important too...

On 2025-03-09 21:02:55, user Dr. DP wrote:

Dear authors,<br /> Will this article be peer-reviewed/is there a path to peer-review being explored?

On 2020-11-06 10:28:28, user kdrl nakle wrote:

This is like saying that eating in rooms with more than two tables is associated with obesity. Absurd.

On 2025-05-28 15:43:41, user Peter Fino wrote:

This paper has now been published in the Journal of Neurotrauma with a slightly revised title. The citation for the peer-reviewed publication is below.

Fino PC, Antonellis P, Parrington L, Weightman MM, Dibble LE, Lester ME, Hoppes CW, King LA. Objective Turning Measures Improve Diagnostic Accuracy and Relate to Simulated Real-World Mobility/Combat Readiness in Chronic Mild Traumatic Brain Injury. J Neurotrauma. 2025 Mar 26. doi: 10.1089/neu.2024.0127. Epub ahead of print. PMID: 40135290.

On 2021-08-11 18:35:08, user UGApaul wrote:

So, should we therefore assume that by reducing mutations, that vaccines or immunity in general, reduces the potential for new variants of concern?

Such thinking would run counter to our many decades of understanding of flu.

It is not necessarily important that vaccines might reduce the numberof mutations, what is important, is whether there already exists, variants that can partially escape immunity and/or there exists a sufficient mutation rate within a partially immune population to generate future variants that can escape immunity.

Delta is most likely a classic benefactor of antigenic drift in a partially immune population.

On 2023-06-01 12:17:00, user Anne-Marthe Sanders wrote:

A peer-reviewed and published version of the article can be found at: https://www.ncbi.nlm.nih.go...

On 2022-01-27 00:09:31, user Autofan1 wrote:

Something seems to be fundamentally wrong with this study - because empirical observations tell exactly the opposite story: much more people have been infected in low relative humidity environments.

The best examples are...<br /> 1) ...the large Covid-19 outbreaks in meat producing companies in Germany (cold and dry air = very low RH).

2) ...the typical spread of the annual flu virus, where most people are infected in spaces with dry air (offices, public transport...) which is dominant indoors during European winter time.

And vice versa the rate of infections in high humidity environments has been negligible.

E.g. public swimming halls and SPAs are high RH and no mass infection events have been recorded in these areas at all, although people are not wearing masks and are regularly talking to each other with little distance.

So either the interpretation of the measurements are wrong - or there is a mechanism in human air intake that causes low RH environments to be more infectious.

Since this study has the potential to influence the behaviour of a large population (with potentially negative consequences) it would be a good idea of the authors to once again verify the interpretation of their findings.

On 2025-08-28 17:40:53, user gzuckier wrote:

Just a typo of some sort, I assume, but<br /> "-0.85 (95% Cl: [-0.48 --0.37]) for dose 3" can't be correct.

On a related note, however, I can't avoid a nagging suspicion of bias from the fact that some of the estimates used to support <br /> "concerning evidence of a higher-than-expected fetal loss rate" <br /> are not statistically significant is missing from the paper and must be intuited by the reader, as in <br /> "1.9 (95% CI: 0.39-3.42]) for dose 3";<br /> particularly when it's specifically noted with respect to estimates involving COVID infections <br /> "all the 95% CIs of the respective observed-to-expected differences included 0 (Table S8)."

The main findings, however, do not have this problem.

My humble suggestion is to include these other findings as "suggestive but not reaching statistical significance."

Or perhaps, since the results given for week 14 seem to be significant but are diluted by nonsignificant later results, that should be pointed out?

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 2021-02-16 06:28:51, user Robert Clark wrote:

I’m looking for the safety data specifically for senior citizens after the second dose. Pfizer hasn’t released it.

Robert Clark

On 2020-05-05 00:24:27, user Marc Imbert wrote:

The dosage is twice higher then the protocol raoult , without blood analysis to follow up toxicity apparently. The disparities between the groups are high with negative conclusion to be expected.

From figure 3 and 2, we can deduct that 56% (23/41) patient in the high dosage group and 35% (14/40) of the lower dosage group are in intensive care at enrolment. Not discussed in the study, although it has a clear impact on lethality, and CK.

A pertinent critera to look at, 51% hypertension profile in high dose CQ at enrolment, while the comparative group has less. To note, it is the exact figure ( and the highest) associated with the " poor clinical result outcome" in Roult's 1064 series ( with HCQ) and the "death outcome" the Chinese reference study without HCQ.

There are certainly more investigating data to explore out of this study,

On 2020-04-07 18:43:25, user Ethan Obie Romero-Severson wrote:

This article has been published in EID https://wwwnc.cdc.gov/eid/a...

On 2020-02-12 23:48:47, user StockShaman wrote:

What we need to know is how long out of the host does this virus last ?

On 2020-06-09 05:14:54, user Dewey wrote:

Why were they hospitalized if they were asymptomatic?

On 2020-05-03 00:49:59, user chess wrote:

Pr Raoult claimed that HCQ had an anti viral effect at the onset of the infection.<br /> So HCQ would also have an effect on cytokin storm later ?<br /> It's a fact that mortality rate 0.4% is very low at IHU_Maseille and someday we will discover why.

On 2024-03-25 10:04:24, user S wrote:

Interesting study, however, the authors failed to reference previous studies that externally validated the PCE and Framingham risk models among patients in the UAE. By not referencing such validation studies, the authors missed an opportunity to provide additional context and strengthen the evidence supporting the use of these risk models in their study population. It is important to acknowledge existing literature to ensure the robustness and reliability of the study's findings.

https://doi.org/10.1136/bmj...<br /> https://doi.org/10.1186/s12...

I extend my best wishes to the authors for a successful publication.

On 2020-04-19 06:07:39, user Shiva Kaul wrote:

The delta method is not the reason why the CIs don't include zero. (I did some numerical checks and the delta method actually seems fine here.)

The actual reason is their sampling model. They consider their sample of data as biased, since it does not match the known gender/zip/etc. statistics of Santa Clara. They reweight it to correct for this bias, boosting the number of positives considerably. In their model, it would be very unlikely to observe their actual dataset as a truly random sample. So (if you believe their dataset is biased, and that it should be corrected in the manner they propose) your sanity check does not invalidate their CIs.

That being said, while reviewing their statistical appendix, I found another issue, which I've written about in a separate comment.

On 2020-04-19 02:02:27, user defragmentingthecode wrote:

THe CDC's guidelines for reporting Covid19 deaths is "where the disease caused or isassumed to have caused or contributed to death".

I really don't know how accurate any studies are when we don't know how many Covid deaths were assumed, and how many deaths were due to the patient's co-morbidities rather than the presence of virus? Surely, we could have got this bit right?

Here is the CDC link. https://www.cdc.gov/nchs/da...

On 2020-04-22 16:02:11, user Stacy Johnson wrote:

How I wish Dr I were right! From March 1 to today, we have had 45k Covid-19 deaths. That is 30% more than during the entire 2018-2019 influenza season (12 months). My data suggest that before this is over (by mid-August, i.e., in 5.5 since the outbreak), we shall have about 245k Covid-19 deaths. That's the same number as the sum of influenza deaths between 2013 and 2019 (6 seasons, each of 12 months). How can anyone trust Dr I? If I'm wrong, I'll be celebrating, and I'll know by April 25, 2020, when my data suggest we'll exceed the 60k mark predicted by the "Chris Murray model" for the final death toll. Just wait 4 more days, please! Dr I is talking about Santa Clara (not nationwide), about infections detected (not deaths), and about discovering infection rates that are 85x worse than anticipated. Sadly, from that terrifying observation, he infers that mortality rates must be 85x better than anticipated, and, therefore, he finds them approximately equal to those from the flu. The maximum mortality from the flu for the period of 2010 to 2019 was 0.18%. In my Covid-19 model, I assume a mortality rate of 2.3%, i.e., 13x worse than the flu. Sadly, countries like Italy and Spain have reported Covid-19 mortality rates up to 10%, i.e., 4x worse than my assumption. Doubly sadly, my model has consistently predicted the death toll in the USA since 4/4/20; furthermore, it shows that by 4/24, our toll will exceed 60k, which the "Chris Murray model" provides as our ultimate count in early August. Trust me, I do not want to be right. This is not an argument I desire to win. It tears me up to think that I am the bearer of bad news. I want to rejoice in the Resurrection, not to wallow in death statistics. I check my numbers every day, and the same conclusion has been coming out for 17 days now. I shed tears over this, I pray to God to please let me be wrong. I don't want to be Jonah, preaching to the Ninevites: Another three days and the city will be destroyed. I want to flee to Tarshish! But the coffins are there, for everyone to see. If our mortality rate were equal to that of the flu, we should have had only 1400 deaths (=825k x .17%). But we actually have 40k coffins. Our actual mortality rate is 5.4% (=45k/825k). My assumption is barely half of that, Sorry, Dr I, I do not trust your inference, as much as I have high respect for your data and methods. The quality of data is always a problem. Analysis must include data from a variety of sources to minimize bias. On the other hand, coffins are coffins: 45k of them in the USA, and counting. No one can wish that figure away.

On 2020-04-19 22:12:07, user worldviewer wrote:

Yes, but how many had to die in NYC to achieve this? Would you mind extrapolating this to the entire country and estimate how many have to die to achieve herd immunity outside of NYC?

On 2020-06-24 18:01:45, user Nathan R. wrote:

Exactly. They do antibody tests after the flu season and extrapolate the data.

On 2020-04-24 23:35:40, user Jonathan G. Harris wrote:

This contradicts the Stanford study and does not vindicate it. Somewhere between .12 and .18% of NYC has died of covid. About 22% was infected . Even if this 22% is too low ant the correct were 33%, you would have fatality rates of .36 to .54, far more than the claimed .1 to .2%.

On 2020-04-24 05:58:27, user JM V wrote:

With 80 (1.7%) people dead in Castiglione d'Adda (Caveats: Old/Smoking/Unlucky/Collapse of Health care system/Some would have died anyway) this was already extremely unlikely. Now, with NYC 0.22% excess deaths and 21.2% of shoppers having antibodies, an IFR of 0.8% - 1.2% appears plausible.

On 2020-04-19 20:28:34, user Tick Tock wrote:

Can we see an example of a set of positives, negatives and samples from the lateral flow immuno-blot used?

On 2020-04-18 13:51:54, user Dr77Funkenstein wrote:

Excellent analysis. Very good. Once again the genius of bayes shines like a beacon to mankind. I read your entire analysis. I agree even if the likelihood ratio is around 5, the IFR is drastically reduced 0.5 to 1.0%

On 2020-04-21 20:17:21, user tom wrote:

The test kits were marketed under Policy D, i.e. no FDA validation or review, not even a EUA. It defies reason that they could be relied upon merely on the word of the foreign manufacturer (Hangzhou Biotest Biotech) and a perfunctory (and potentially skewed) in-house specificity validation run on a mere 30 control samples. The UK bought millions of £ worth of antibody tests from Hangzhou Alltest Biotech (maybe an affiliate of HBB, as there are curious similarities between the two tests' package inserts) and then shelved them due to inadequate specificity.

And how could a responsible researcher pre-print survey results based on unapproved rapid test kits without following up on the indicated positives by blood draw and ELISA, knowing full well the half-baked, incendiary results and conclusions would be picked up by media worldwide and potentially impact life-and-death decisions of massive scope by public health officials?

It is an extraordinary - indeed sensational - claim that the entire world has missed a silent, benign spread of SARS-CoV-2 that's 40x larger than recognized, and it runs counter to significant evidence of the virus having an asymptomatic fraction similar to influenza based on contained, fully-tested outbreaks in the Diamond Princess, Roosevelt, and Skagit Valley choir. Extraordinary claims require extraordinary evidence; this work is, to put it euphemistically, certainly not that. If these results do not bear out, Stanford has some serious explaining and housecleaning to do.

On 2020-06-23 19:20:17, user addie wrote:

The article states that patients receiving mechanical ventilation were ten years younger than those not receiving respiratory support - this implies that ventilators were being rationed? Can the authors speak to this.

Thank you.

On 2020-06-24 05:32:27, user Gavin Donaldson wrote:

Were patients ineligible to the dexamethasone arm excluded completely from the recovery trial or allocated to the other arms including the standard care arm?<br /> Could the reasons for the exclusions be included in a consort diagram of the participant flow.<br /> There was an imbalance between the two arms in age. Is there any data on obesity or hypertension since these are important risk factors for covid-19 mortality.

On 2020-04-19 21:44:48, user Paul Maxwell wrote:

It is not lax policy, the government has still introduced closures and set restrictions, it is just allowing the people to "do the right thing as adults"<br /> That is a cultural thing.

However, it seems their main goal of "protect" the vulnerable has been a huge failure as nursing homes have been doing nothing in terms of mitigation and now the very people their policies were targeted to protect are copping it.

On 2021-02-04 09:44:55, user Sepp271 wrote:

Taking into account the 7-day incidence of that region (Munich) and the number of tests taken, about 1 or 2 positive cases would have been expected when similar testing would have been done in general population. Taking dark number of incidence into concern this figure goes up to roughly 2 or 3.

Therefor within this study one can not state that the observed number of positive cases of 2 found in primary schools, kindergartens and nurseriesis is significantly different from the infection numbers in the general population.

It would have helped if the authors had made a strict comparison of both groups including statements about the confidence interval.

On 2020-02-12 18:53:53, user S.T wrote:

Table 2 has a typo(I presume). It states the time window is from 25th December 2010**

On 2020-06-18 23:37:52, user Florin wrote:

There was no mention of Japan, Taiwan, or Hong Kong, countries and territories which have successfully dealt with the pandemic without doing lockdowns. Taiwan didn't close its schools. Japan didn't do much testing or tracing. Hong Kong was late in imposing a complete travel ban. The only common and early responses to the pandemic in Japan, Taiwan, Hong Kong, and South Korea was universal mask wearing and a decrease in large gatherings.

On 2021-06-05 13:55:27, user Tim Winton wrote:

Would it be possible to see the code for this?

On 2021-12-09 20:54:49, user El Fabsterino wrote:

Interesting stuff. The sample sizes are very, very small, though. I'd refrain from using p-values here at all. I'm not sure the suggested statistical test (Student's t-test) to test for differences in the means is even applicable here. The original data is clearly not normally distributed and transformed into a 0/1 Bernoulli-variable by defining an arbitrary threshold.

On 2021-08-11 20:29:39, user S.O.S_1.20.17 wrote:

Me and my husband are both over age 60, (61 and 62) we both had the Moderna shots and we had a very strong response to the second shot, husband had a 102 degree fever, I had a 101 degree fever or possibly a little higher (my digital thermometer wasn't working right, it was flashing). Anyway we had a strong response. My son who is in his 20's also had the Moderna vaccine and works in a busy supermarket. He was exposed to 3 coworkers who had Covid (they were unvaxxed). My son wore an N95 mask to work. He was tested for Covid on July 21st. The tests, PCR and Rapid both came back negative. My husband travels to NYC on public transit wearing an N95 mask. He has not gotten Covid. Vaccines seem to be working well. We are still avoiding restaurants, my son did go out to restaurants a few times with his friends who are now vaccinated.

On 2021-08-11 20:10:04, user nullcodes wrote:

State of residence seems like too big of a geographic area to use as a match criteria. Cities and rural may have been a better criteria. The rollouts within states were quite varied.

On 2021-09-01 12:32:37, user Anonymous wrote:

Probably not theoretically/logically, however, for the duration of the covid-19 pandemic it was said that asymptomatic people could spread covid hence social distancing etc so should that not also apply now to vaccinated people if asymptomatic spread is a thing?

On 2020-11-26 05:48:46, user Community Medicine with velz wrote:

Re-infection can be defined only by viral genome sequencing. The implication of these results can be mis-leading as re-infection has been defined by RT-PCR in this study.

On 2020-06-18 07:05:58, user Anton De Spiegeleer wrote:

A revised version of this manuscript is available in pre-proof in the Journal of Post-Acute and Long-Term Care Medicine (JAMDA): https://doi.org/10.1016/j.j...<br /> This reference can be used for citations.

On 2020-07-18 18:45:51, user James Truscott wrote:

Hi, I think there is an error in the model as laid out in Supplementary Text File 1. The variable z represents all non-susceptibles, which includes the infectious-infected , y. The rate of loss of immunity term in equation 1 is gamma*z, but infectious individuals presumably don't have immunity to lose. They first recover (at rate sigma) and then can lose immunity. The term in equation 1 should therefore be gamma*(z-y). This change will affect the algebraic result, probably, and may change the dynamics significantly at some time points and/or parameter values.

On 2020-08-11 17:45:03, user Paul B wrote:

Re Jeremy’s post, I’m not sure the literal maths 18/82 8/92 is what is being explored. Rather, as with a graphite rod in a nuclear reactor, those blocks within the potential transmission chain serve to bring the R number down within the population even at lower percentages of prior infection.

On 2020-03-17 19:20:48, user RealConspiracy wrote:

And what about "-" Rh-factor?

On 2020-03-25 12:29:20, user jenniepoole wrote:

Hi were any of the patients with <br /> type A also checked for RH negative or were they all A + ?? This is important to me.

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 2021-10-01 02:28:35, user Clemens Hlauschek wrote:

Thanks for your response. Using terms such as 'life expectancy at birth for 2020' is highly misleading, regardless of your field's justification and history of such usage. I don't think the short clarification sentence in your Introduction section is appropriate, given the immense political and societal interest: With such work, as scientists, you are not only communicating to your field, but to a wider public, the mass media, and decision makers, which are all prone to use badly communicated science results to justify potentially detrimental policies. Communication throughout the paper, but especially in the abstract, while formally correct (from what I can tell), is nevertheless misleading with regard to a wider audience, and could easily be, from my perspective, be formulated much better, to deliver a more honest and objective message.

Also, I am missing references, discussion, and comparisions with important related work. I remember reading studies in the early weeks of the pandemic about estimates of life years lost due to Covid with results in the order of up to 2 digit numbers per Covid victim. Putting your results in perspective with prior, intuitively much more pessimistic results, would provide important insights, as far as I can tell.

The comparison with WW-II effects should either be left out, or clarified in detail / put into exact perspective. To what extent is the Covid-19 pandemic comparable with the losses of life in WW-II? How different exactly are the distances between WW-II effects and different pandemics compared to Covid-19? Is Covid-19 closer to previous pandemics of the last decades, or to WW-II? How much closer? We are speaking of the extermination of 6 million Jews (all age classes), countless Gypsies, Homosexuals, Handicapped, ... and the killing of many more, mainly young, soldiers; death of millions of other civilians due to starvation, diseases, mass-bombings, massacres. How do the demographic bumps in the population curves compare with the bumps created by WW-II? Drawing the WW-II comparison the way you do it, and thus implicitly communicating all these associations, sounds quite alarmist to me at best, and, at worst, puts you in the category of Holocaust deniers.

Thank you for considering and addressing these points.

On 2021-08-23 21:24:22, user Stuart wrote:

Published in JCI Insight, here: https://insight.jci.org/art...

On 2021-08-06 07:17:04, user disqus_UQJEvw3dWd wrote:

Dear Dr Austen El-Osta,

We read with interest this preprint article “What is the suitability of clinical vignettes in benchmarking the performance of online symptom checkers? An audit study”. Studies addressing the suitability of different evaluation methods are useful, and vignettes methods in particular have known advantages as well as known shortcomings (Fraser et al., 2018; Jungmann et al., 2019). Further detailed analysis into the overall utility of vignettes methodologies is certainly important. Whilst the approach taken for exploring vignette methodologies here is interesting and warrants reading and careful consideration, two aspects of the study conduct and reporting are deeply worrying.

We ask for the authors to correct aspects of the paper where there is unequal and unbalanced methodology applied to the funder symptom checker (Healthily), as compared to those applied to the symptom checkers of the funder’s competitors (Ada and Babylon).

We also ask that the authors report results in a balanced manner in the abstract. All outcome measures should be reported fairly, irrespective of whether the funder’s symptom checker performed well in any particular measure. Please see below for a detailed description of these aspects.

We do not state that the selective application of methodology and the selective reporting of results has been deliberately conducted to bias the study to the benefit of the funder. However, the degree of different treatment of the funder’s symptom checker is so large, that an independent reader could draw that conclusion. We suggest rectifying the highlighted issues in the preprint, and, before submitting the manuscript for peer review.

Should these issues not be addressed in any future peer review process, we will in due course, also write to the editor of the publishing peer review journal.

Major concern 1 of bias towards study funder: The paper not only assesses the utility of a methodology, it also applies that methodology to report on relative performance of different symptom checkers (i.e. benchmarking).

This approach would be fair if the same methodology were applied to all the symptom checkers, however, the study presents a grossly unmatched analysis. One approach has been used for the funder’s symptom checker (Healthily) and a second for the symptom checkers of two main competitors of the funder. This gives the appearance of fundamental bias in testing and reporting based on study funding. Although some degree of bias may be introduced in studies for a multitude of reasons, deliberate application of fundamentally different testing methodologies to the products of the funder compared to those applied for their competitors is unacceptable. The Healthily symptom checker was tested with 6 inputters (4 professional non-doctor & 2 lay), whilst, for no rational justification, the Ada and Babylon symptom checker were tested with a testing group of fundamentally different make-up (not just the number of testers, but a systematic and deliberate choice to use a different type of tester population, i,e. 4 professional non-doctor inputters).

The number of tests also differed greatly (n=816 for Healthily, vs n=272 for Ada and Babylon). Additionally, only one professional non-doctor inputter recorded the consultation outcome and triage recommendation using Ada and Babylon symptom checkers, for all 139 vignettes, which is in contrast to the approach the authors adopted for Healthily.

Major concern 2 of bias towards study funder: There is also an important bias in selecting the results in the abstract. <br /> With respect to condition suggestion: In the results section, it is reported that “Ada consistently performed better than Healthily and Babylon in providing the correct consultation outcome in D1, D2 and D3” (i.e. in the provision of correct condition suggestions). The difference in performance was large: “The correct consultation outcome for Ada against the RCGP Standard at any disposition was 54.0% compared to 37.4% for Healthily and 28.1% for Babylon”. It is acknowledged in the abstract that condition suggestion (referred to as disposition/diagnosis) is a main outcome measure, however this measure is not reported in the abstract. This looks like selective reporting in the abstract to avoid negative messages about the funder’s symptom checker.

With respect to ‘triage recommendation’:<br /> It is reported in the results that “In benchmarking against the original RCGP standard, Healthily provided an appropriate triage recommendation 43.3% (95% CI 39.2%, 47.6%) of the time, whereas Ada and Babylon were correct 61.2% (95% CI 52.5%, 69.3%) and 57.6%, (95% CI 48.9%, 65.9%) of the time respectively (p<0.001). Again, this is omitted from the abstract, where only the aspects of the relatively positive performance of the funder’s symptom checker are reported.

We would welcome a change in this study to remove bias towards the funder in methodology and results reporting.

Yours faithfully

On behalf of Ada Health GmbH<br /> Dr. Stephen Gilbert<br /> Clinical Evaluation Director<br /> Ada Health GmbH<br /> Karl-Liebknecht-Str. 1<br /> 10178 Berlin, DE <br /> +49 (0) 152 0713 0836

REFERENCES

Fraser, H., Coiera, E., Wong, D., 2018. Safety of patient-facing digital symptom checkers. The Lancet 392, 2263–2264. https://doi.org/10.1016/S01...

Jungmann, S.M., Klan, T., Kuhn, S., Jungmann, F., 2019. Accuracy of a Chatbot (Ada) in the Diagnosis of Mental Disorders: Comparative Case Study With Lay and Expert Users. JMIR Formative Research 3, e13863. https://doi.org/10.2196/13863

On 2021-10-08 20:58:14, user AbsurdIdea wrote:

Referring to "However, if prior infection does not afford protection against some of the newer variants of concern, there is little reason to suppose that the currently available vaccines would either.": The mRNA vaccines are targeted specifically to the "spike". There appears to be no information as to what the infection used or uses to identify the virus, and thus while new variants have a "spike" and likelihood of maintained resistance there is zero evidence of what natural immunity would or would not recognise in a variant. Thus the argument provided has no substance.

On 2020-06-12 19:34:13, user Amr Sawalha, MD wrote:

Nice work. The lack of association in the HLA region is very interesting given the perceived exaggerated immune-mediated response in patients with severe COVID-19. Genetic studies looking at patients with confirmed cytokine storm will be of interest in this regard, and of course a closer look at the epigenetics of immune-response genes will be of interest.

On 2020-06-05 08:30:20, user Mohamed Abu-farha wrote:

The choice of the control population shows a serious limitation to this study. It technically assumes that people who were not infected are genetically different than those who were infected with the virus.

On 2020-06-04 18:17:08, user Fahd Al-Mulla wrote:

The Illumina arrays they used do not contain The ACE2 nor FURIN genes we have identified as the most possible cause of why Europeans are most affected by COVID-19. Our study was not mentioned!? <br /> https://www.biorxiv.org/con...

On 2020-06-11 12:16:07, user Desiree Sutton wrote:

Surely they are checking against genetic abnormalities like MTHFR or Factor V, right?

On 2021-10-29 17:15:41, user kdrl nakle wrote:

This is a very troubling report as we really need to differentiate "regular" deaths from the ones that are consequence of (and caused by) vaccination. This report is vague on that and it is going to be used against vaccination, no doubt.

On 2024-10-09 13:29:30, user disqus_foVd2sEK3I wrote:

Really nice work. Could you please share the accompanying code to reproduce these results? Thanks.

On 2020-12-27 18:54:51, user Travis Cesarone wrote:

This is odd, PN Medical has suggested cloth masks cause hyperventilation. <br /> This drastically lowers CO2, constricting blood vessels in the brain, leading to severe anxiety. N95s and surgical masks are associated with hypercapnia which can cause confusion and disorientation.

This should be interesting in peer-review.

https://www.pnmedical.com/b...

Individuals have a false sense of security that masks are protecting them. This 'security' has not been quantified in any study, so it is false. Therefore, there is a false increase in mental health due to a severe fear of the virus.

On 2023-06-21 18:28:21, user Wim van Drongelen wrote:

Now published in Communications Biology doi: 10.1038/s42003-023-04696-3

On 2022-05-10 08:12:41, user Zeng Zhiyu wrote:

Figure 2. All 1 dose vs none, the dot is way greater than 1, why the OR is still 0.566?

On 2021-06-10 23:22:29, user Don taylord wrote:

We know- from peer reviewed, randomized control trials, that HCQ does not help patients with mild or moderate disease.

On 2021-06-19 13:31:53, user globus999 wrote:

I read with interest the article. However, the conclusion does not seem<br /> to be supported by the evidence. If you look closely at all the plots, <br /> there seems to be no impact below 10 units. This would therefore <br /> indicate that yes indeed, there seems to be a safe level.

On 2024-10-21 23:26:17, user CDSL JHSPH wrote:

I think that the background behind your research is very important to the field of tuberculosis treatment. Treating the patients so that the bacteria is out of their body while also preventing antibiotic resistance and any toxicities that the medication may cause is an important balance when deciding duration and dosage of treatments. Utilizing the dose-finding methods, such as MCP-Mod, and applying it to studying duration-ranging of TB treatments seems like a very practical method to studying this topic.

I am curious about what you plan to do with the results of this study moving forward? You have identified a method to use in duration-ranging studies for TB antibiotics, but are you planning on using this information in your own studies? Is this a topic that many researchers in the field were looking for? I am just wondering about the practicality of this study and how it will actually be used moving forward.

On 2021-02-19 21:51:45, user Michael Verstraeten wrote:

Did you consider to imply Flaxman e.a., Estimating the effects of non-pharmaceutical interventions on Covid-19 in Europe, Nature, 584, 257 - 261 in your study, or didn't it meet the inclusion criteria?

On 2021-08-26 19:32:16, user Aubrey Bailey wrote:

A few problems:<br /> 1. The authors count single dose vaccine as "vaccinated". That's not anyone's accepted definition.

1. The authors include naturally infected individuals in the vaccinated group if <br /> they got vaccinated later. Why? Were there not 16K fully (double) vaccinated people<br /> in a giant medical database?

2. This is the big one - <br /> I admit to skimming, but I didn't see any control for time intervals since infection.<br /> This<br /> is absolutely critical because we know that the antibody response <br /> wanes over about 8 months. Since the vaccine has been around for more <br /> than 8 months, it makes sense that more people will be at the tail end <br /> of that. Thankfully many more people get vaccinated than infected.

In light of all of these and in light of the un-reproduced nature of these findings (which should have been observable since Februrary), we should consider the first sentence of the conclusions to be at best, strongly overreaching, and at worst irresponsible phrasing.

On 2021-09-01 10:08:16, user Jonh Peter wrote:

About Graphene’s health effects summarised in new guide (European Commission Feb.2015)<br /> At the level of the whole body, the authors indicate that there are two main safety factors to consider regarding exposure to CNTs and graphene. The first is their ability to generate a response by the body’s immune system; the second is their ability to cause inflammation and cancer.

On 2021-10-14 04:51:10, user gzuckier wrote:

That looks like a good correction. Thanks!

On 2021-09-08 14:30:11, user Texas wrote:

Not a typo. See antibody-dependent enhancement @ www.ncbi.nlm.nih.gov/pmc/ar...

On 2025-02-24 06:06:47, user Daniel Corcos wrote:

This work is a good start to appreciate the existence and organic nature of a post-vaccination syndrome. What worries me is the low number of control subjects. A much larger number of control subjects would allow adjustments to be made, particularly regarding the number of vaccine doses received.

On 2021-11-07 15:28:01, user DinCville wrote:

What can a study of 60+ year olds who had breakthrough infections tell us about the risk for all 60+ who are vaccinated? How representative are those 60+ with breakthrough infections? Could they be more likely to have pre-existing conditions that affected the effectiveness of their vax response? Concerned that these results be interpreted to mean all 60+ with vax are unprotected from long covid.

On 2024-05-19 16:23:05, user Millie Le wrote:

Five dermatologists and a referral to Johns Hopkins culminated into an informal diagnosis of “funky eczema”, launching my 12-year relationship with TCS and triamcinolone injections. No one could make sense of my eight biopsies. They all noted the same result - the possibility of a drug reaction. Because no one in the medical community equated TCS to this possibility, I continued to manage my misdiagnosis with the medication that started it all. Until it was unmanageable. From unknown hives to TSW, my journey is a familiar story. “Although no formal diagnostic criteria for TSW exist, reports of patients experiencing TSW are very common online.” Yes. Sadly, this. I am forever thankful to the Internet which led me to ITSAN and a global community who understood what I was experiencing. My entire world changed with this knowledge and four years later, I no longer have “funky eczema”. I am grateful to researchers who did not cast a whole community aside as overzealous medical sleuths quarterbacking the medical community from their desks. With continued research such as this, we are equipped with the tools to educate and prevent others from making the same unnecessary TSW journey where, “The only way out is through.” Thank you for your dedicated work which further validates and acknowledges the existence of TSW. More research to understand TSW, diagnose it, and treat it, please.

On 2024-05-09 14:39:59, user Ana Angel wrote:

Very important piece of research for the thousands of us suffering from this condition. More research is needed! <br /> I stopped all forms of steroids 4 years ago. I’m now much much better, but still flaring on my elbow creases. We need treatments to shorten these lo g recovery times

On 2021-05-14 21:23:13, user Kit Curtius wrote:

We acknowledge Dr. Adam Brentnall (QMUL) for helpful discussions on statistical prediction modeling!

On 2025-08-24 14:42:39, user Naoto T Ueno wrote:

We present a high-throughput assay that identifies a TRBJ1-6–derived TCR? pre-mRNA fragment as a potential blood-based biomarker for inflammatory breast cancer (IBC). Using a novel sequencing method (TGIRT-seq) for discovery and a scalable RT-PCR/Cas12a workflow for validation in peripheral blood mononuclear cells (PBMCs), we focused on a short RNA fragment (20–23 nt) spanning an exon–intron junction. This fragment likely originates from pre-mRNA and is stabilized by a 2´,3´-cyclic phosphate end, making it unusually detectable.

Our results show that this fragment is consistently different in PBMCs from IBC patients, with validation in larger follow-up cohorts. Importantly, the RT-PCR/Cas12a platform provides a path toward rapid, high-throughput screening—something that could make this approach practical in clinical settings.

That said, several challenges remain. Our current cohorts, while expanded, are still not large enough for definitive clinical conclusions. Independent replication across multiple centers will be essential. We also need broader comparisons to confirm whether this signal is specific to IBC and not just a marker of other inflammatory or cancer-related conditions. Finally, we see the importance of longitudinal studies to track whether this biomarker changes with treatment and outcomes.

Looking ahead, our priority is prospective, multicenter validation under standardized conditions. Direct comparisons with imaging and clinical features are also needed—though difficult, since IBC still lacks a definitive molecular diagnostic standard.

We welcome feedback and collaboration on validation studies, methodological improvements, and clinical translation. We are especially interested in exploring the biology of this RNA fragment and understanding why it might be unique to IBC.

On 2021-05-28 05:59:35, user ????? ????? wrote:

Hi, I'm Dr.Niaee and I was surprised that even basic data from our RCT is completely mispresented and is WRONG. We had 60 indivisuals in control groups and 120 in intervention groups and even this simple thing is mispresented.

On 2022-07-25 08:55:06, user Dr. D. Miyazawa MD wrote:

Explained for the general public<br /> https://note.com/miyazawane...

On 2022-11-07 06:03:04, user Daniel Corcos wrote:

I don't see any adjustment for the date of infection. There is a high probability that nirmatrelvir treatment was used on average at a different time, against infections with a different ratio of viral variants.

On 2021-10-18 18:05:16, user Francis Bascelli wrote:

How can I access this data on UK Biobank? The data/code section says the data can be accessed though UK Biobank, but I am having trouble finding it.

On 2022-01-14 03:44:42, user Mike B wrote:

Although your result shows that analytical sensitivity is similar for both variants, more critically it also echos by analytical evaluation (" 5 of 11 (45%) Omicron samples were negative despite having levels of virus above the LoD." ) the numerous clinical complaints that significant false negative results suggest that this test is unreliable as a screening tool to identify infected and contagious individuals or as a negative screening tool via serial testing in a specific populations. (travel, school, theatre arts, music, live performance). This study is significant because it's sample set comes from asymptomatic and almost entirely fully vaccinated donors. <br /> There is good concordance with a recent clinical study (Adamson, Sikka, https://doi.org/10.1101/202... ). In that study they confirm infectious transmission on day 1, with day 0 being Limit of Detection via RT-qPCR. In their study antigen tests did not turn positive until day 3 with viral loads via RT-qPCR somewhat lower than days 1 and 2. This study confirms a false negative issue and eliminates sampling technique as the source because RT-qPCR was run from the same sample as the antigen test. The clinical significance of this issue is of primary importance in context of the rapid rise in viral load and infectious transmission of Omicron as highlighted in the clinical study. The cause of the false negative issue needs urgent exploration. Thanks for a great job and continued hard work. Valuable information.

On 2020-08-15 17:53:14, user BannedbyN4stickingup4Marjolein wrote:

There isn't "T cell immunity" and "antibody immunity" as 2 different things. Nor when immunologists talk about "immunity" do they mean protection from catching a disease. They are talking about an immune response. You can be "immune" and catch the disease. Protective immunity to SARS-Cov-2 will involve both antibodies and T cells (also B cells, and a whole host of other things). But no-one knows how long it will last. Lets hope it IS a long time.

The world has just recently been spammed by a lot of bogus information about Covid-19 and cross-reactive T-cells so I refer anyone to this thread to put them straight:

https://twitter.com/profsha...

On 2020-05-03 15:40:02, user Charles Rosa wrote:

The WSJ, referencing this study, has the following quote in one of their article: "It suggests that the large majority of people who contract Covid-19 recover without ever knowing they were infected, and that the U.S. infection fatality rate may be more than an order of magnitude lower than authorities had assumed. Based on this seroprevalence data, the authors estimate that in Santa Clara County the true infection fatality rate is somewhere in the range of 0.12% to 0.2%—far closer to seasonal influenza than to the original, case-based estimates."

On 2025-12-01 22:35:37, user Mahalul Azam wrote:

Now published at https://www.doi.org/10.4103/ijpvm.ijpvm_242_24

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 2021-05-31 06:51:28, user Luca Prosperini wrote:

Where is the TABLE 1?<br /> Thank you

On 2021-08-04 04:29:21, user Abhishek Anand wrote:

most drugs require multiple year RCTs to prove longer-term safety and you are saying that not even having a control group is ok: Vioxx heart problems were only apparent after 18 months and if it was not an RCT, the problems would have most likely been explained away by confounding factors. <br /> without a control group, what would you compare against? deaths and other diseases vary due to so many other causes that it would be very hard to catch smaller safety signals.

On 2021-07-31 20:00:31, user I. Bokonon wrote:

In Table S5, among participants receiving placebo, why are the surveillance time (0.265) and n2 (736) for the positive baseline SARS-CoV-2 status group greater than the sum of those values shown for the 3 positive subgroups (0.264 and 735)?

On 2021-08-23 08:47:36, user Medhat Khattar wrote:

How is it correct to have used only saline as placebo injection, when the composition of the vaccine includes a range of compounds, most notably lipids?

On 2021-02-13 09:00:43, user Guy André Pelouze wrote:

Hello,<br /> May we have any explanation and evidence for the choice of this strategy: "Success will be declared if there is a 90% probability that the intervention arm is better than usual care in<br /> reducing CRP. "? Is it based on preliminary data or on a choice of efficacy which is lower than usual in order to catch small effects?<br /> Thank you,<br /> Guy-André Pelouze MD MSc

On 2020-09-22 17:38:28, user Laraine Abbey-Katzev wrote:

You started out talking deaths, but then switched to cases, which is a notoriously questionable statistic. So many blank tests and never actually performed tests reported as positive;, and then there is the story of asymptomatic positive tests being called cases. We should not accept that positive tests are cases. Many contend a case must be a person with some symptoms!<br /> In Tanzania a pawpaw fruit, monkey, and goat all tested positive! PCR testing was never designed for diagnosing disease, only for amplify viral snippets.

On 2020-04-23 17:09:17, user Sinai Immunol Review Project wrote:

Key findings:

Using clinical data of patients and statistical analysis, the authors wanted to explore the potential role of vitamin D in decreased cytokine levels which may lead to the reduction of disease severity in COVID-19 cases. The study shows that Spain and Italy present a severe vitamin D deficiency. Concerning COVID-19, the two countries have a higher mortality rate and a higher case fatality rate (CFR) for patients age >= 70. The authors have also shown that subjects with a severe deficiency of Vitamin D have 1.4 times higher risk for production of high C reactive protein (CRP), used to indirectly evaluate cytokine storm. They hypothesized that Vitamin D deficiency increases the risk for cytokine storm in COVID-19 patients and they estimated a 15% reduction in the number of severe COVID-19 cases after vitamin D deficiency elimination.

Potential limitations:

The results of this study remain hypothetical. Future studies should assess vitamin D and pro-inflammatory cytokine levels in COVID-19 patients upon hospital admission and the role of vitamin D in decreasing cytokine levels should be evaluated. In addition, the authors did not take into account the medical history of COVID-19 patients in their analysis, as previous studies have shown that patients who have comorbidities (cardiovascular disease, hypertension, chronic pulmonary disease, hepatic disease, diabetes and other chronic disease) are more likely to develop a severe COVID-19 https://www.medrxiv.org/con... <br /> https://www.medrxiv.org/con...<br /> Furthermore, age has been reported to be a major factor that determines outcome for COVID-19 and it has been demonstrated that aging affects the formation of the active form of vitamin D.https://www.ncbi.nlm.nih.gov/pmc/ar... https://www.ncbi.nlm.nih.go... It would be interesting to see if vitamin D deficiency in the elderly associates with severe forms of COVID-19. Finally, the authors have chosen to use CRP to evaluate the intensity of cytokine storm which is an indirect approach. However, even if CRP has been regarded as a pro-inflammatory molecule, it has some anti-inflammatory functions (recruitment of complement inhibitors and release of anti-inflammatory cytokines such as IL-10 and IL-1ra) and could be replaced by more specific inflammatory markers. https://www.fasebj.org/doi/... https://www.sciencedirect.c...

Overall relevance for the field:

The study results did not demonstrate a direct and obvious link between vitamin D deficiency and severe cases of COVID-19 that feature cytokine storm. The study is based only on analysis of the reported clinical data from multiple studies, the results are therefore hypothetical and require a more direct demonstration to see if vitamin D supplementation could really suppress cytokine storm in COVID-19 patients.

Review by Meriem Belabed as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

On 2020-09-22 13:49:24, user Calvint33 wrote:

Useful data. But if a ~30% reduction is not significant, then study was underpowered, no? Because 30% would be enough to act upon. Evidently the infection rate in Manitoba was too low for a good test even with this very sizable sample.

On 2020-04-06 18:50:06, user Theodore Koukouvitis wrote:

Insightful and readily quantifiable. The author is confident enough to make specific, short-term predictions and warn against the danger of a full removal of social distancing measures.

This paper should be peer reviewed and evaluated ASAP.

On 2020-04-22 01:51:11, user fourierTF wrote:

On p. 14, the rate alpha of asymptomatic virus carriers is estimated quite low, and variated in simulations between 0.01 and 0.16. But why should manifestation indexes between 51% and 81% be irrelavant for this number? Because, "in a setting where contacts have been traced properly, thereby effectively isolating the exposed population in an early stage before they become asymptomatic carriers, and when extensive tests are performed, this fraction would be minimal"? But at present and in the near future, we don't have this setting of extensive testing.

An even more important problem of parameter estimation seems to me: By varying the bevahiour influenced parameter R1, data for Germany were fitted to the cumulative number of reported cases. But these strongly depend on the number of tests. Most importantly, from week 11 to 12 (march 7 to 20), both numbers increased about 3-fold, compare Table 4 of the situation report by Robert Koch institute (RKI), as of april 15. Since the observed reproductive number directly depends on the number of registered infected persons, the peak in this number at march 10 appears to be largely artificial. Even more, since certainly the number of tests also jumped up from week 10 to 11 - but data are not published.

Finally, a personal-political remark: In the appendix of page 14, the authors give the usual scientific disclaimer: "Currently, there is no reliable data available about the asymptomatic cases." This is only read by specialists. The apodictic abstract of this highly influencing paper, however, is noticed by the media, by a larger public and presumably by German chancellor Angela Merkel, according to her related public statements. "We strongly recommend to keep all NPIs in place and suggest to even strengthen the measures in order to accelerate reaching the state of full control, thus, also limiting collateral damage of the NPIs in time." Otherwise, the authors threaten with their horror scenario A (p. 8): "the health care system will in expectation need a peak capacity of 500,000 ICUs or more" (comparable to the falsified prediction of far more than 200.000 ICUs at march 21, by Deutsche Gesellschaft für Epidemiologie). At this place, no carefulness about the "collateral damages" of continuing the lockdown at all, for families, children, culture, (small) enterprises and many others. These countermeasures nead strong reasons - but no word about strong scientific counter-arguments!

Johannes Wollbold, Weimar / Germany

On 2021-09-15 03:22:12, user William Brooks wrote:

"The increase in mg household secondary infections could easily be the result of prior infections (before lockdowns) as a source of infection."

I agree. Once infections have become widespread, forcing infected people to stay at home increases the risk they'll infect other members of the household, especially in crowded living conditions.

"It could have easily happen, perhaps even worse without lockdown."

The results of this study suggest high-risk people in poorer areas of NYC would've actually been better off without lockdown.

Also, numerous states in the US have been through Covid waves while keeping schools and businesses open (Florida, Texas, South Dakota, Georgia, etc.), and in all cases, the curve flattened lower than in NY. Also, NY had large numbers of outbreaks in hospitals and care homes, which lockdowns don't prevent (see Belgium, Italy, Spain, UK, etc.)

"And indeed the hospitals in NYC, Brkln and Qns were overflowing with patients."

A few hospitals were very busy, but overall the hospital system never ran out of beds, which is why the hospital ship Trump pointlessly sent was hardly used.

"But when you have political slant it is hard to think, isn't it?"

Apparently so.

On 2021-05-26 14:43:55, user Donepudi Raviteja wrote:

Sorry Sir, but this article need so much more rigorous Multivariate statistics like PCS, MANOVA etc.,. The statistics are basic and also misleading to some extant. In correlation matrix (Figure 3) the correlation between deaths per million and sanitation parameters looks identical to correlation between age >65 years and sanitation parameters. This show that the confiding factor is age distribution. If a proper multivariate analysis is done this would have been easily identified and avoided as discussion point. A simple age adjusted death-rate correlation with sanitation parameters would also be sufficient.

On 2020-12-10 00:06:10, user Amandeep Goyal wrote:

What kind of scores or testing was used to diagnose polyneuropathy ?

What tests were used if polyneuropathy was due to Diabetes or Amyloidosis ?

On 2020-04-04 19:53:38, user VirusWar wrote:

It is interesting study, but I'm surprised you don't talk about level of Potassium in the blood ? Did you check it ? Was there any Magnesium given to correct level of Potassium. Especially, you noted heart troubles with people having renal disease, but it is well known they have excess of Potassium which creates such heart troubles. Also, was treatment H+A stopped when QTc >=500ms ?

On 2020-04-09 19:39:41, user Harold Smith wrote:

What dosages of the drugs were used (on a body weight basis)? How did the patients' QT intervals correlate with potassium levels?

On 2020-04-07 00:42:52, user Oleg Gasul wrote:

Posted my comment and then noticed yours)

On 2020-03-30 15:52:29, user Rosemary TATE wrote:

Hi, I have just performed a review of this preprint. I hope it is useful. I'm a medical statistician. I'd certainly like to see the next version, and it would be good if you could take my comments on board. I'd be happy to help with the stats if you need it.

On 2020-03-30 18:02:09, user MVianna wrote:

Thank you for your answer. I think your contribution is very relevant and glad you took that into consideration.

On 2021-02-22 08:12:43, user Leo Delibes wrote:

This article has now been published in The Lancet Public Health: https://doi.org/10.1016/S24...

On 2020-07-02 20:44:39, user Joel Silveira wrote:

All of this may be due to 5-HT (serotonin) resulting from platelet degranulation, including NET.

On 2021-10-07 08:31:47, user Emmanuel André wrote:

1) Considering that the risk of myocarditis exists during natural infection and after vaccination (altough the risk after vaccination is lower)

2) Considering that it has been shown by others (https://www.nejm.org/doi/fu... ) that the risk of myocarditis was higher after the second dose of vaccine than after the first dosis, suggesting a "boosting effect" for that risk

3) Considering that immunization among younger populations can be achieved after a combination of natural infection followed by one only dose of vaccine

-> Did you observe a higher risk of post-vaccination myocarditis among previously infected individuals?

Best regards,

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 2020-07-26 22:23:24, user Chris Barker wrote:

an editorial point. The citations numbering seems confusing. I finally found the citation to the principal components method for longitudinal data (Li). The major points. The data appears to be over a five day period. This seems to be a very artificial and inherently biased dataset . How much of an improvement are 5 days of data over say the last available measurement or first available measurement? . the inclusion of data in the analysis appears to be defined as "from disease onset until hospitalization or beginning of recovery". The authors should move the "subject selection" from the appendix to the main text. Do the authors require that using the method in current clinical practice that patients must present with precisely the identical "subject selection criteria" as the manuscript? The requirement for "imputation" seems may be especially difficult to implement in routine medical care of a covid19 patient. . How heterogenous are the "between patient" characteristics at time of disease onset? If the authors method were to be applied to actual clinical practice are future patients likely to have the same or similar values of patient characteristics at onset? For example is an elderly or adolescent or infant data applicable? A seriously concerning issue is the authors appear to "re-use" the validation set, rather than have a separate validation dataset for each re-use. if so that would guarantee a bias toward the authors preferred model and would not represent an independent validation. there are important multiplicity considerations for the analysis. the authors should account for multiplicity, using a method such as Bonferroni or false discovery rate. The authors need to define their criteria for claiming the model "validates". ONe option may be to use a mahalanobis distance between the test and training dataset outcomes (for example in table 1). The authors should also clarify whether the type or variable "numeric (ratio scale)", categorical, ordinal or binary may all be included in the method Mc2PCA.

On 2021-08-03 22:35:32, user Gemma Hollie wrote:

Can you advise how many pregnant women / live births / still births there was during this period. Also, for moderate to severe disease, you report 45% for the delta variant. Can you advise, is this of the total 3371 women or the 1137 admitted due to symptoms of covid? <br /> Vaccine safety for pregnant women has not been well filtered down to health care professionals, therefore the uptake of women getting the vaccine has not high. Now more women are having the vaccine, i wonder if future results of women getting moderate to severe disease will continue to support recommending the vaccine. Will you be doing another study in the near futute to update the findings? Thank you

On 2021-08-25 01:30:14, user Lesley wrote:

The thing that's most concerning to me is the CDC Newsroom release title "Vaccination Offers Higher Protection than Previous COVID-19 Infection". This would lead those who only read the title of the release to believe that vaccination alone offers better immunity than natural infection immunity. <br /> If you read the study the CDC references it actually compares reinfection rates of those who have been vaccinated with reinfection rates of those who have not and concludes that among those who've been re-infected, those who were fully vaccinated had lower rate of reinfection. Did everyone really need a study to tell them that vaccination adds additional protection from reinfection??? That's all that this study showed. It did not show that vaccine immunity is superior to natural immunity.

On 2021-06-12 18:17:25, user Tracii Kunkel wrote:

Several factors weren't noted. And because of that, conclusions like yours are preposterous. By your logic, if I talked to a total of 3 people and they weren't re-infected, you would conclude that as absolute proof that surviving coronavirus makes vaccination meaningless. After all, 3 of 3 is 100% right? So 3 out of billions is a sufficient sample size. Couldn't POSSIBLY have randomly selected 3 people who made it 5 months without being infected. That would be impossible. That's your statement.

On 2021-04-15 21:01:27, user CY Liu wrote:

Did you control batch effect, position effect, covariates in the data analysis? I could not see it in the paper.

On 2021-07-30 05:59:31, user Raja Mugasimangalam wrote:

"Antibody responses did not correlate with overall protection against asymptomatic infection."<br /> This goes against any reasoning!

On 2020-06-11 23:05:21, user hoipoloi wrote:

Why was the famotidine given in to the patients? If it was solely for treatment of acid/indigestion etc, have you ruled out the patients' physiological(digestive) makeup as the relevant factor ..... as opposed to the treatment of it?

On 2022-01-07 14:35:45, user SurroundedByKnobs wrote:

Comparing households infected with the Omicron to Delta VOC, we found an 1.17 (95%-CI: 0.99-1.38) times higher SAR for unvaccinated, 2.61 times (95%-CI: 2.34-2.90) higher for fully vaccinated and 3.66 (95%-CI: 2.65-5.05) times higher for booster-vaccinated individuals, demonstrating strong evidence of immune evasiveness of the Omicron VOC.

Our findings confirm that the rapid spread of the Omicron VOC primarily can be ascribed to the immune evasiveness rather than an inherent increase in the basic transmissibility.

1.17 (95%-CI: 0.99-1.38) times higher SAR for unvaccinated<br /> 2.61 times (95%-CI: 2.34-2.90) higher for fully vaccinated<br /> 3.66 (95%-CI: 2.65-5.05) times higher for booster-vaccinated individuals

1.17 times higher is less than 2.61 and 3.66 times higher...

Am I reading this wrong? Or is this presented in a confusing way on purpose?

On 2020-09-25 12:20:05, user Svet wrote:

Please, can you analyse our samples from the surfaces, using this experimental, as a service or in collaboration? Can you measure kinetics of the virus on particular sample surfaces? What would be the price for 10 and 100 samples? Thanking you in advance, <br /> Dr. Katuscak

On 2020-03-12 14:56:17, user Reza Amini wrote:

This is great job! I've done something similar to this earlier but I have DATASET shortage.<br /> "imreza.ir" .<br /> This was really surprising

On 2023-02-04 12:23:54, user Lucija wrote:

Interested work based on the latest advances in ablation strategies. Nevertheless, there are a few things to note. PFA has now been successfully performed in humans in several clinical trials (and in regular clinical practice since the last year when Farapulse catheter got its CE mark) so the obvious disadvantage of this study is that it is not an in-human study. Follow-up for lesion reassessment has a wide range - 3 weeks to 3 months. Three weeks is too short of a period for any relevant conclusions as we aim for arrhythmia freedom in our patients - 3 weeks would not be satisfying in clinical surroundings. Longer follow-up is warranted - most studies now aim for at least 3 months and ideally 1 year. Also, single-shot catheters are repositioned during the ablation, so to replicate clinical conditions this should be taken into consideration. These findings confirm the safety of the PFA, which is the main strength of the study, especially when you consider brain MRI + histology findings (you can not do that in humans if you have successfully performed the procedure :) !). Finally, endoscopy for esophageal lesions should have been performed as it has been in most studies confirming PFA's safety for adjacent structures).

On 2021-08-18 15:53:47, user K Meijer wrote:

Does this assume the previously infected peeson still has antibodies left? What about someone who had Covid Beta variant middle December 2020, tested positive for IgG antibodies late in January with lab test, but showed hardly any antibodies remaining with rapid antibody test early August 2021?

On 2021-02-20 15:56:24, user Howard Gu wrote:

It is surprising that vaccination only reduces the viral load by 4 folds. However, this could be due to the research design. Only the high viral loads are detectable and thus included in the calculation of viral load reduction. Vaccinated people might get infected but have good immune responses effectively suppressing the viral replication. This could result in 400 or 4000 folds lower viral loads which may not be detectable and thus considered not infected and not included in the calculation of viral load reduction.

On 2021-02-13 17:05:48, user Harold Erickson wrote:

The question raised below seems much more important than the Qt estimate of viral load. What fraction of people tested positive after vaccination? What were their symptoms? Hopefully this will come soon

On 2020-04-25 22:57:46, user wbgrant wrote:

An additional article that supports the model study and should also be cited<br /> Prevalence and genetic diversity analysis of human coronaviruses among cross-border children.

Liu P, Shi L, Zhang W, He J, Liu C, Zhao C, Kong SK, Loo JFC, Gu D, Hu L.

Virol J. 2017 Nov 22;14(1):230. doi: 10.1186/s12985-017-0896-0.

On 2025-04-16 08:57:01, user Idan Menashe wrote:

This manuscript has now been published here: DOI: 10.1186/s11689-024-09573-6

On 2020-05-08 04:56:24, user Dan T.A. Eisenberg wrote:

This paper is very important. My lab is planning to implement an assay inspired by it. Can you elaborate on how long healthcare worker samples were stored at +4 for before testing?

On 2020-08-18 12:07:32, user Hagai Perets wrote:

A possible explanation for these results could be related to the following study:<br /> https://www.preprints.org/m...<br /> discussing possible immunity by prior virus infection.

Note the following quote from the paper:

"It is possible, and even likely that in a fraction of the cases the preceding low-virulence strain (LVS) only provides partial immunity, allowing for the SARS-CoV-2 high virulence strain (HVS) infection, but leading to a less virulent form of COVID-19. In such a case we might expect a higher fraction of newly identified COVID-19 patients to be, on average, more symptomatic during the early phases of the pandemic when it still spreads exponentially, before the LVS achieves her-immunity. At these early times the LVS has not yet infected the majority of the population and newly HVS-infected people are not likely to have been previously infected by the LVS, and be partially immunized. After the LVS infected a large fraction of the population, new HVS-infections are far more likely to be of previously LVS-infected people, who already acquired partial immunity.We might therefore expect a lower fraction of asymptomatic cases, and a higher morbidity rate during the early exponential growth of the HVS, in comparison with later times after sub-exponential-growth and later decay in the number of cases is observed."

On 2021-12-26 19:21:30, user Melani Turgeon Harmon wrote:

why worry so much about the unvaxxed IF Omicron's symptoms plays out [for the most] as a common cold? this would ultimately HELP our communities develop herd immunity and to quell the virus overall. we have much incidence now of influenza-- doesn't that seem a bit odd that there's very little breakouts of this now? wouldn't we worry MORE about an effective and proper treatment for folks with symptomatic covid to prevent hospitalizations rather than pushing a vaccine that does not provide 100% protection and folks can still transmit/acquire the virus-- especially IF vaccine effectiveness is waning with these variants?! something's amiss here. i mean, the flu vaccine--although different from covid viruses/vaxx-- loses its effectiveness each year when we try to cover the strands populated and people still can become sick after vaccination. who are we really fooling? we cannot keep racing after this virus b/c in the end it'll keep mutating for the win-- just like annual influenza viruses. have we learned nothing from the science, which is a process and NOT a product?

On 2022-01-02 14:47:58, user Nathi Mdladla wrote:

I hope the peer review process will be able to pick up the challenges and significant confounders of this study’s conclusions which are too overreaching in the context of Omicron.

The South African 3rd/Delta Wave ended in September 2021. Between that period and Mid-November South Africa was in between waves. Boosting and a major drive to vaccinate in SA, started at the same time in Mid-November. The 4th wave has been mild for everyone, whether vaccinated or unvaccinated.

Healthcare workers are a very difficult group to study in subsequent waves as the assumptions of an only vaccine benefit negate important confounders:<br /> 1. the at-risk individuals either stopped working in the first wave or were maximally affected in that wave already. <br /> 2. You can’t kill the same person twice - those at risk of mortality had either died in the last three waves of they were exposed and their survival could not be solely attributed to vaccines<br /> 3. A number of healthcare workers had been exposed in the prior two waves before delta and already had natural immunity which is known to have significant protection against re-infection and severe disease up to Omicron. Without accounting for healthcare workers with prior infection who received the vaccine, the vaccine effect can be over-exaggerated

Now coming to the most important confounder, making this study invalid and probably not worth publishing, is the fact that it stops on the 17th December, when a lot more has happened in South Africa beyond that date:<br /> - Omicron hospitalisations have been significantly lower compared to Delta or the 3rd wave in a country with <30% “full vaccination”. The benefit of the J&J vaccine should be done in this backdrop and not only based on the narrow healthcare group.<br /> - there’s an “observed” but yet undocumented significant breakthrough infection rate in the vaccinated healthcare workers who were recently boosted, leaving a question on the effectiveness of boosters against infection - a more important parameter for healthcare workers as it impacts ability to work…

This seems to be a rushed publication, without addressing the broader issues of the J&J vaccine:<br /> - when is the next booster dose, considering that it’s efficacy wanes within 2months and it should have been a double dose vaccine from the beginning (as realised in the US in April/May 2020)<br /> - what is the rate of breakthrough infections for this vaccine amongst healthcare workers<br /> - what is the benefit on severe disease and mortality outside the healthcare worker population which has many confounders?<br /> - and lastly, the benefits of the vaccine on any morbidity or mortality parameters cannot be de-coupled from the adverse events and mortalities that occurred before the “determined vaccinated period” of 4weeks whether they are proven to be associated or not. This is the reason the USA FDA is not considering J&J as it’s primary vaccine yet - efficacy and adverse events challenges/concerns.

On 2020-04-02 09:24:44, user Ákos Török wrote:

What do you think about this? If we pool an aliquot of e.g. 5 samples (collect swabs from 5 different persons in the same tube with transfer medium.) then extract RNA, then pool 10 such RNA samples? This would result in 50X pooling.

On 2021-12-18 02:12:44, user Peachyjenniekag21 wrote:

The main concern i have over the implications of this report are how this could impact conditions and protocols of prison inmates and populations. An unfortunate reflex seems to be rigid and stringent focus on isolation efforts as opposed to abundant supply of safe and effective treatment in congregate settings...

On 2021-09-30 10:22:03, user V Deepak Bamola wrote:

This preprint is under review at 'Experimental Biology and Medicine'<br /> @medrxivpreprint:Effect of Bacillus coagulans Unique IS-2 in Inflammatory Bowel Disease (IBD): A Randomized Controlled Trial https://t.co/hH32BrOdYT #medRxiv

On 2020-08-17 05:22:58, user Liz Halcomb wrote:

Please note that there are three errors in the preprint version of this paper. These are as follows;<br /> 1. Section 3.2.1 - The first three lines should read "Over three quarters of participants (77.2%) identified the need for access to an adequate supply of personal protective equipment to enable the provision of quality routine care during the pandemic. This accounted for some 29.3% of the overall statements."

1. Section 3.2.2 - The first three lines should read "Just over half of the participants (55.4%) referred to the need for high level communication supports in order to continue to provide quality nursing care."

2. Table 1 Key category Funding of services should read;<br /> Total 134 (11.0%)<br /> Nurse telehealth item 62<br /> Nurse billing 36<br /> Fund services 18<br /> Job security 15<br /> Nurse practitioner 3

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 2020-02-20 09:15:56, user Linh Ngoc Dinh wrote:

First off, I really appreciate this paper because it chose to fit time series of quarantined and recovered/death, which are less biased, to the model. However, I would like to be enlightened regarding some aspects:<br /> 1. w.r.t compartment P, based on what evidence do you think that a part of the population should be protected at alpha rate? We still have no vaccine yet.<br /> 2. w.r.t. the transition from compartment Q. Here I see there is only I (infectious/infective) can be moved to Q. However, if a person shows some symptoms but not become infectious yet (i.e. incubation period < serial interval), s/he is still considered as E (because not infectious), but might be quarantined. Should this one be included in your model?

Thanks much!

On 2021-02-06 06:12:34, user Scott Huffman wrote:

So what exactly was the n value in the non-vaccinated group, and what was the n value in the vaccinated group? How was a positive case defined? Was it merely a positive PCR test, or was it an actual symptomatic case where a person was sick? And importantly, what was the average cycle rate of the PCR testing? What is the Absolute Risk Reduction? What's the NNT? These are legitimate questions that must be asked. The answers should be very simple.

On 2021-02-19 08:12:14, user Philippe Marchal wrote:

• Concerning the first point, the data in https://www.math.univ-paris... gives the *cumulative* excess death, so the excess death from week 1 to week n. Looking at your graphs, it really seems that the total excess death from the beginning of 2020 up to the middle of the year is positive for France, whereas it is almost 0 by considering age-standardized rates at week 24.

• Neglecting autocorrelation for the noise will indeed affect the variance an not the mean. But this way you miss a major fact, which is that the severity of the flu epidemics greatly varies according to the year. If you compute the annual variance of the mortality rate according to your method, I suppose you will find a result much different from the empirical variance of the mortality rate as given by the real-world data. This is an important issue since typically, if you want to assess how bad the pandemic has been, you will divide the excess death by its standard deviation and underestimating the standard deviation will result in overestimating this ratio.

On 2025-07-01 18:15:13, user Yogev wrote:

This manuscript is now published in a peer reviewed journal, and can be found in: https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1593221/full

On 2021-08-10 21:39:41, user Paul Gordon wrote:

Hi,

Thanks for posting. I am trying to reconcile the text and Figure 1, but am having trouble. The B.1 graphs appear to be identical to the B graphs, even though the stated fold-changes at the top of each NT graph are different between B and B.1. Secondly, the text highlights a very large changes in Kappa neutralization efficacy, but it is marked in the Figure 1a B.1 graph as not statistically significant. Could you please clarify?

Cheers,

Paul

On 2021-08-21 12:15:04, user muhamad khairulbahri wrote:

This preprint is now published at:<br /> https://wjst.wu.ac.th/index...

On 2021-08-29 16:06:28, user Paul Wolf wrote:

I wonder if the infectiousness of the delta variant could be a blessing in disguise, if it dominates over other, potentially more dangerous variants.

On 2022-09-08 01:25:06, user Martin Hensher wrote:

Some people who have tweeted this article have taken your Long COVID prevalence estimates as being representative of Long COVID arising from Omicron / BA.5 infections. Yet my reading is that you have explicitly not counted Long COVID symptoms arising from the new COVID infections in your study period (June 2022); therefore people reporting Long COVID in this study do so from a prior infection, which could in fact have occurred at any time during the pandemic until June this year. Interpreting your Long COVID prevalence estimate as prevalence arising from recent BA.5 infection is therefore not correct - which some have done, but I hasten to add the authors have not! Would you agree that is a fair assessment?

On 2022-02-15 08:41:08, user Sylvia van der Woude wrote:

What a poor study with a far too small sample size!!! Was it cherry-picked from a much larger pool of patients? Also, symptoms were not taken into account, even though they are most important! ps: Isn't the funding by the B&M Gates foundation a conflict of interest?

On 2020-04-16 12:24:09, user Eric Zorrilla wrote:

Hi,

I tried to comment on the preprint, but I cant tell if my comment is going through. I noticed some sig/near-sig OR relations in your Suppl. Table 1 that I thought were potentially of interest to highlight in your paper in addition to those you highlighted?

NON-HOSPITALIZATION also associated with<br /> Oseltamivir (of interest to field imo?)

And sig or nearly sig with<br /> Atenolol<br /> Lisformin<br /> Metformin<br /> Rosuvastatin

The joint presence of these anti-metabolic syndrome drugs (hypertension, diabetes, dyslipidemia) seems of interest as may support the emerging hypothesis/view that UNTREATED obesity/metabolic syndrome disorders may be worse than TREATED obesity/metabolic syndrome disorders as COVID-19 comorbidities.

DECREASED VENTILATION was sig. associated with<br /> Cetirizine (Zyrtec)<br /> Diphenhydramine (Benadryl)<br /> Cholecalciferol (Vitamin D3)<br /> I’m not sure if the first two are an age confound or something interesting vis-à-vis immune reactivity/hypersensitivity, but may be of interest to deconvolute/deconfound?<br /> And the Vitamin D3 may be of interest given various other emerging preprints on it?

Nice work and best wishes,<br /> Eric

On 2020-08-09 17:02:50, user David Leidner wrote:

Article says all data fully available, but no link to the data is provided.

On 2020-06-05 20:23:05, user Steve S wrote:

It is good to see this strange weekly cycle being addressed by the research community. The hypothesis that contracting on the weekend because human behavior changes on these days—set by our arbitrary definition of time (a week)—sets the trend of the weekly cycles in viral metrics (cases reported and deaths) is appealing. However, it seems a tad odd to me that the explanation of the death rate being weekly is completely dependent on it having a cycle that is divisible by a week, i.e., 14 days is two weeks. If say the death rate peaked at 10 days instead, then you would expect interference patterns between previous weeks to create something analogous to beat frequency in sound, where there would be several irregular peaks within in a week and the weeks could look different from each other. 14 days would therefore have to be a perfect coincidence, which just seems unlikely... but still possible I guess. I'm a neuroscientist not an epidemiologist, so forgive my ignorance, but are there examples of other infectious diseases that have weekly trends. Are the cases reported and death rates also weekly in these cases?

On 2020-04-27 10:34:04, user Elena Sharova wrote:

They don't randomize health care workers to find an effect in comparable conditions (hospital, patients management, patient burden). Jan21 to Feb23 - incubation period before pneumonia detection is approximately 1-2 weeks. So how to compare pneumonias in the 1st week in control group with abcence in test group starting interferon - regurding the 1st week test group DO NOT infect a 1-2 week ago, not during the research. Are these groups equal?

On 2021-07-07 00:18:31, user itellu3times wrote:

For gosh sakes please mention the size of the current standard dose! Current standard for Moderna is 100 micrograms, study here is 25 micrograms? In both cases, two doses.