On 2021-09-12 05:30:50, user kdrl nakle wrote:

William Brooks talks nonsense. The increase in mg household secondary infections could easily be the result of prior infections (before lockdowns) as a source of infection. It could have easily happen, perhaps even worse without lockdown. And indeed the hospitals in NYC, Brkln and Qns were overflowing with patients. But when you have political slant it is hard to think, isn't it?

On 2020-04-07 10:15:29, user denverbears wrote:

Correct, but the bigger question is how did they get such low SD in temperature duration and cough duration. This is highly suspect. If you have 29 patients with an average of 2 days--and just one of those patients has 1 day and one has 3 day duration, you get a SD of .25. Their SD is 0.2--lower than that. Something doesn't smell right about the numbers here.

On 2021-09-24 11:34:07, user PsxMeUP wrote:

The denominator is Ottawa from June 1 through July 31, for mRNA vaccines ONLY. Not total of vaccines administered since the beginning of the pandemic. Did you even read the study?

On 2020-03-27 00:50:17, user Simon Brazendale wrote:

I read this paper quickly and feel that people need to keep an open mind either way, the question is 'can this finding be reproduced?'. Certainly meta analysis seems to have been achieved, but the I squared values are greater than 25% for blood groups A and AB, which suggests some heterogenity. Lets see if out this global tragedy other studies can reproduce this as well as the original finding needing further scrutiny. It may be part of a key to better understanding or just a red herring

On 2020-11-20 19:44:06, user StephenSela wrote:

Can I see a real MRI/Xray picture of the damage from someone who actually has this

On 2020-05-04 01:53:51, user TinHo Mak wrote:

This explained why Singapore has low infection rate among local residence but high infection rate among external workers. They are living within a tiny island and they do not have significant DNA or mask wearing difference. Their key difference is their jab history.

On 2020-04-03 08:14:51, user OregonMSN wrote:

Interesting...thank you for the time you put into this analysis. I have not found anywhere, at what age a child is vaccinated with this BCG. Is this a vaccine that needs a titre checked and/or a booster in later years?<br /> Are your figures based on the deaths or the actual diagnosis of the 100th "patient" ? "Other analyses are controlling that (for example, number of patients (deaths) 10 days after the 100th patients were detected, was used as a dependent measure) ? # of patient deaths 10 after the 100th patient with positive disease? OR of positive/confirmed COVID-19 10 days after the 100th confirmed patient? The "death" used in your wording has thrown me off! Thanks.

On 2020-04-07 00:42:03, user Oleg Gasul wrote:

It seems to me Tokyo-172 strain is most powerful.<br /> Please, take a look on the map<br /> https://pbs.twimg.com/media...

There are Japan, Thailand, South Korea and Oman with very low level of spread.

On 2021-08-31 17:35:12, user Jake David wrote:

Need some help interpreting this: "<br /> Assuming a conservative total of 10 days of school absence per 5 new <br /> infections, there will be an estimated 210 (510, 400) absent days for <br /> the school without any interventions or 140 (120, 76) days with masking <br /> and testing." This *per* school? Do they have any usable data such as *per* student estimates? Thx for any help!

On 2020-02-13 16:20:21, user Xiaolin Zhu wrote:

We are the authors. We have retrained our model with confirmed cases by Feb. 11. We updated our prediction results. The total infections in mainland China would be 72172 by March 12, 2020 under current trend. It will be 149774 in the worst situation.

On 2020-05-22 16:23:27, user Jim Parfitt wrote:

It is difficult to find any discussion on this issue. I am a person who has taken NO systemic antibiotics for over 40 years. And I basically never get sick. I have been wondering how many of the severe cases of Covid 19 are in people who regularly take systemic antibiotics, and so have messed up gut flora. This is what i suspect. I would like to read the whole study; if that is possible.

On 2021-10-24 14:21:45, user Paul McKeigue wrote:

The abstract shown on this page for version 2 is the abstract for version 1. This will be corrected as soon as possible. The PDF has the correct updated abstract.

On 2022-01-10 14:15:38, user Greg wrote:

Mazda, indeed, the findings do appear confusing, but let me try to help. They studied unvaxxed (not really, because they counted one dose jabbed as unvaxxed), double-jabbed, and double-jabbed and boosted households for primary and secondary (transmission) Omi cron and Delta infections. They found:

One, overall, the unvaxxed and double-vaxxed households had equal amount of primary Omicron cases, but the double-jabbed and boosted had less Omicron cases.

Second, within a household infected with Omicron, an unvaxxed household was most likely to have a secondary infection, a doube-vaxxed next likely, and a double-jabbed and boosted least likely.

Third, comparing households for the ratio of Delta to Omicron infections, unvaxxed households had relatively equal amount of Delta and Omicron infections, double-jabbed households had more Omicron infections relative to Delta, and the double-jabbed and boosted had the most Omicron cases relative to Delta. Mazda, I think you are getting confused here by reading this as suggesting there were more Omicron cases for the double-jabbed and boosted households.

PS: I will leave it to others to offer corrections if I made any mistakes.

On 2021-07-14 02:01:48, user Direk Limmathurotsakul wrote:

The manuscript has been peer-reviewed and is now published at PLoS NTD. https://doi.org/10.1371/jou...

On 2024-02-26 17:17:59, user Ciarán McInerney wrote:

The sensitivity analysis is<br /> commendable. If I understand your logic correctly, the 20% inaccuracy in<br /> clinical coding informs a random 20% reclassification of cases and controls. To<br /> commit to this logic, all +19-thousand clinical codes also need to be randomly<br /> reclassified because there is no reason to assume that only the clinical coding<br /> for cancer is inaccurate in 20% of your sample.

On 2021-08-23 13:04:39, user Eyal Oren wrote:

I don't see any mention of vaccination status. Were these patients vaccinated or unvaccinated? Also the study would be stronger if comparison done to other patients in your catchment area vs CDC data (I believe that dataset is across US and not limited to Georgia?).

On 2022-03-22 03:17:02, user ST wrote:

The scientific article was very intriguing, and the abstract sparked my interest when the link between detecting changes in the gut microbiome and concussion diagnosis was made. The introduction was informative and included different helpful statistics on football players and the number of concussions they may receive in a singular football season. <br /> The PCR target region was the full 16S gene (V1-V9). The reason why the authors sequenced the full gene rather than the more common use of one region (i.e. V3-V4) should be included. A strength of the paper is that the scientists included the number of PCR cycles, however, 35 cycles is quite high. The higher the cycle number, the more errors that can be produced (Sze & Schloss, The impact of DNA polymerase and number of rounds of amplification in PCR on 16S rRNA gene sequence data 2019). This should be listed as a potential study limitation. PCR primers were not specifically listed and should be included in the methods section to ensure replicability. IF part of the Barcoding Kit, that should be stated as well. The scientists did state that there were problems with the ONT primer but there should be follow-up discussion of Bifidobacteriaceae taxa found in this study, if any. No quality controls/filtering steps for the sequences (such as removing low quality sequences and chimeras) were included. The scientists do not analyze specifically dominant and rare taxa. Given that microbial communities are highly dominated and uneven, analysis of the dominant taxa alone can be revealing, since metrics using all taxa can be strongly affected by the very numerous but low abundant rare taxa. The rare and dominant taxa of environmental pathogens are mentioned but what does this mean for the microbes found in the oral cavity and the gut? I suggest that bioinformatics should be performed on dominant as well as all taxa. The scientists do include rare taxa abundance in three of their figures to show the abundance of the different microbes found in fecal samples and salivary samples. I thought that the description of the sampling was good but there could be more of a description of what was in the tubes for collection? Were buffers used? What specific tubes were used? Were the samples taken straight to the lab? It would also be helpful to say what kit the tubes were from before stating that a collection tube and funnel were used. The fecal sample and saliva sample collection were described well but I think that scientists should make saliva sample collection have its own paragraph. One flaw of the article is that the scientists never discussed variance in 16S copy number and genome size in bacteria, which affects abundance data of 16S profiles. Were sequences binned or clustered before identification with Kraken? A rarefaction curve would be beneficial to include, and also sequencing coverage measures, such as Good’s coverage and Chao1 compared to observed OTUs. The article should include internal standards for PCR, DNA extraction, and sequencing. These internal standards may include utilizing a negative control, a strain grown in the lab, running a gel, and utilizing a known DNA sequence. I would like to comment that DNA extraction and amplification should be in the same section as I was a tiny bit confused when I read amplification in the sequencing section. The best option for readers would be to list the methods performed in chronological order. The sampling strategy is very well described and figure 1 demonstrates the samples collected as well as a visual representation of the collection strategy. The scientists discuss the number of classified reads for the samples but the number of reads per sample is not stated. Additionally, the study does not include any methods that quantify total bacterial numbers (16S community sequencing is normalized and only contains relative abundance data, not absolute abundance). <br /> Authors should include the specific parameters that were utilized when the samples were vortexed for replicability. Additionally, the stool and the saliva samples were stored at room temperature, and this needs clarification as storing the samples at room temperature for a long period of time may invalidate the experiment. The amount of time that the samples were stored at room temperature needs to be added for clarification. The specific statistical test that is done in figure 2e should be clearly stated. Data that was collected in this experiment could be compared to The Human Microbiome Project.<br /> The optic nerve sheath should be better explained, and it would be beneficial to know what is normal without a concussion and with a concussion. The relationship between the optic nerve and concussions should be better explained so the reader understands its significance.

Overall an interesting study! Thank you!

-Sydney T.<br /> #SHSU5394

On 2022-01-30 23:47:58, user HereHere wrote:

I'm a registered massage therapist in Ontario. We received no clear advice from our regulatory college about ventilation. I was waiting and waiting and waiting. They were very slow with recommending N95s and KN95s, and to my knowledge, still have not acknowledged that surface transmission is exceedingly rare. I don't know how they coordinate with Public Health Ontario, but you would think that, given we work in close contact with patients in typically small, poorly ventilated rooms, ventilation would have been given greater consideration.

On 2021-11-14 16:21:34, user Isaac Núñez wrote:

This article has been published in the journal 'Medicina Intensiva' and is available at the following URL: https://www.sciencedirect.c...

On 2020-03-22 04:52:08, user Juan B. Gutierrez wrote:

In summary, provided that our Ro is correct, and we are certain it is, as we reused very long results from our recent peer-reviewed result, https://doi.org/10.1007/s11... Bulletin of Mathematical Biology (the premier venue for the discipline), then with the information that we have today, Ro cannot be close to 3.

By a suggestion of Dr. Jeremy Faust, MD, Brigham and Women's Hospital, @jeremyfaust, I modified the most uncertain parameters to produce an Ro of 3.These parameters are the mean infectious periods for symptomatic (lambda_yr) and asymptomatic (lambda_ar) subjects. If we consider the median of the other parameters to be correct (there is more data), then the mean infectious period of a symptomatic patient should be 4.9 days, and the mean infectious period of an asymptomatic should be 4.1 days. These numbers do not match what is happening on the ground. If we reduce alpha, the probability of becoming asymptomatic upon infection, to something less than 0.86, e.g. alpha = 0.5, then the mean infectious period of a symptomatic patient should be 3.7 days, and the mean infectious period of an asymptomatic should be 3.1 days.

The reality is that patients are infectious before the onset of symptoms, and the disease lasts more than 3 days in symptomatic patients. The necessary conclusion is that via a computational reductio ad absurdum, and with the information we have today, Ro cannot be close to 3.

On 2021-05-26 09:43:39, user Laura Potts wrote:

Many thanks for this article. I appreciate this is a pre read but would be grateful for clarification as within the text it states “Age was significantly associated with Long-COVID (LC28) rising from 9.9% in 18-49 year olds to 21.9% in those aged >=70” using the data in table 1 looking at over 70s 24/96 gives 25% rather than 21.9% and the sums of the ages don’t add to the overall count for both overall and L28. It would great if these numbers could be updated.

On 2020-04-18 10:07:24, user Dean Karlen wrote:

Ignore this pre-print. They have insufficient evidence due to a weak measurement of the false positive rate. Consider that they saw 50/3330 in the test, and use the manufacturer false positive measurement of 2/371. I estimate the p-value (probability for seeing something as anomalous or more anomalous under the null hypothesis) to be about 0.08. There is weak evidence that even one of the 50 had COVID-19. And they are using that data to make an extraordinary claim?

It appears that none of the 26 comments below pick up on this point...

If you need help thinking about this problem, under the null hypothesis, ask yourself

Is it anomalous to see 50 or more positive tests in a sample of 3330 (all negative) when there was also an independent measurement of 2 positive tests in a sample of 371 (all negative)? Easiest to estimate by taking the first datum as a measure of false positive rate (50/3330) and the expected number of positives in the sample of 371 is therefore 5.6. Seeing 2 or fewer is not unlikely: p=0.08.

In fact the experiment was flawed in its design. With a poor false positive measurement they would have no chance to measure the expected small fraction of individuals with COVID antibodies. Why did they even embark on the study, when it was doomed to fail?

I hope this pre-print can be retracted somehow, and the community informed to not take this result seriously!

On 2020-04-19 00:10:56, user Joerg Stoye wrote:

Kudos to the authors for collecting very interesting data that arguably allow some cautiously optimistic conclusions. However, I am concerned that the statistical analysis might have been done in haste and that the rejection of 0% prevalence is an artifact of this. I would be more than happy to stand corrected! (Disclaimer: Jeffrey Spence posted very similar observations earlier. I post this anyway as I think I can marginally add value on exposition.)

The positive rate in the raw data is 50/3330=1.5%. The test’s false positive rate is estimated at 2/301=.5%, but with a 95% confidence interval extending upward to 1.9%. This means we cannot reject the hypothesis of zero prevalence. Note (this will become important): Because the binomial distribution is not well approximated by a normal here, the CI must be constructed as exact binomial, not by normal approximation. The authors do this and correctly report 1.9%. If they had mistakenly used a normal approximation combined with the sample variance, their CI would have extended only to 1.2% and zero prevalence would have been spuriously rejected.

Based on this, it is puzzling that the “headline” CI’s for prevalence do not include 0. Indeed, the authors state in their statistical appendix (bottom of page 2) that they need the positive rate to exceed 1-sensitivity. But then they move on to reject 0 anyway, in apparent violation of their own CI for sensitivity! What gives?

I conjecture that the problem is their subsequent use of the delta-method to analyze error propagation. This implicitly applies a normal approximation to all random variables under study. Indeed, the analysis culminates in providing standard errors, and these are only interpretable in the context of normal approximation. But recall that the normal approximation is inappropriate for the validation sample and furthermore that incorrectly using it would have yielded spurious rejection of zero prevalence. I conjecture that this is implicitly committed in the later part of the analysis. The earlier conclusion that 0 cannot be rejected seems appropriate to me.

Again, I’d be happy to stand corrected and also appreciate that the paper was put together under insane pressure.

On 2020-04-18 19:28:01, user Tomas Hull wrote:

What are the grounds for such a guess?

On 2020-04-24 07:31:44, user Dennis Menace wrote:

The children they tested were brought in by their parents. These are also not independent, is this a problem ?

On 2020-04-18 14:47:42, user Chris S wrote:

Were participants asked if they had been tested? If so, could the rate of actual COVID-19 testing among participants relative to the general population (at the time of survey) be used to assess ascertainment bias?

On 2020-04-23 14:43:46, user Jason Bayer wrote:

My question is this, in his interview he concluded that mortality rates in relation to this data (suggesting significantly more coronavirus cases then that being documented) is significantly lower, being in relation to this new higher estimate of cases....but how is he accounting for untested, undocumented coronavirus deaths? I do not see how one can claim anything on mortality in relation to undocumented cases but only count survivor data....am I missing something?

On 2020-04-23 18:41:00, user Young-In Kim wrote:

It’s not going to get peer reviewed well just like the studies on hydrochloroquine. That’s not a sample to apply to the whole population when we have data from all over the world. It’s picking and choosing data. I might well take my sample from worst hit parts of NYC n Italy to prove a point.

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

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

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

Natural immunity is highly effective against reinfection.

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

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

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

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

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

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

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

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

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

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

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

On 2020-05-12 20:31:26, user Erwan Gueguen wrote:

The methodology used raises several questions:

• Why were 6 patients with a negative PCR included in a study on Sars CoV2, which means we don't even know if they have the disease? They should have been excluded from the study.

• In Figure 1 describing the flowchart of the studied population, Patients were divided into 2 groups. A HCQ + AZI group (n = 45), and an "other regimen" group (n = 87). It is very strange to find in this "other regimen" group patients who have not all undergone the same treatment. For example, there are 9 patients who also took HCQ+AZ but for a shorter period of time before transfer to ICU or death, 14 patients who took lopinavir/ritonavir, and even 28 patients who took AZI alone. This group is therefore not a control group since patients who have taken the same drugs are in the two groups being compared.

• Following the description of these 2 groups, we discover figure 2 which compares not these 2 groups but 3 groups. The "other regimens" group was divided into 2 groups AZI (n=26) and SOC (n=61) (SOC = standard of care which includes no targeted therapy, or lopinavir/ritonavir or treatment received <48h until unfavorable outcome (transfer to ICU or death). Why 2 patients were removed from the AZI group? (figure 1 n=28, but n=26 in figure 2). Figures suggest that 2 patients from the AZI group were placed in the SOC group. This could change the statistical analysis of the data. It is essential that the authors clarify this point because the results are not publishable as they stand.

• Finally, table 1 shows 2 groups. Statistics are made on 2 groups but actually also on 3 groups for the therapeutic data (see table 2).

Conclusion: The study suffers from numerous methodological biases that make it difficult to interpret the data. The groups are not equivalent and the control group is made up of an agglomeration of patients who have undergone different treatments including HCQ+AZI treatment. It seems to me indispensable that the authors clarify the points raised before a submission to a peer-reviewed journal. I hope that the above comments will enable them to improve their study.

On 2024-02-02 01:52:27, user Alan Olan wrote:

The article has been published at Journal of Clinical Trials and available via - https://www.longdom.org/ope...

OR

at https://www.longdom.org/ope...

On 2021-10-02 22:04:46, user Eve Wurtele wrote:

What do the following abbreviations mean? (They are labels for SRA experimental description. I can't figure this out from reading the preprint. Thanks!!<br /> HCW_0184_FUP4<br /> HCW_0184_FUP3<br /> HCW_0184_FUP2<br /> HCW_0184_FUP14<br /> HCW_0184_FUP1<br /> HCW_0184_BL<br /> HCW_0180_BL<br /> HCW_0175_FUP4<br /> HCW_0175_FUP3<br /> HCW_0036_FUP14<br /> HCW_0017_FUP1<br /> HCW_0017_BL

On 2021-02-22 12:53:03, user joe gill wrote:

Thank you for this important report - is there a high resolution version of Table 1 - the linked version does not zoom in clearly to see the country figures. Like a PDF?

On 2021-09-12 13:38:28, user synchromystic wrote:

"As no vaccine is 100% effective".<br /> Really?<br /> I'd love to see the breakthrough cases of polio, small pox and many other viruses.

On 2021-08-22 13:37:42, user ingokeck wrote:

Dear authors,

Thanks for publicizing this research. I notice that the main point of your article, figure 1C, is purely based on a model you derived, however I was not able to find the data that went into it, i.e. positive and negative cell cultures plotted against the Ct values for the samples in each group.

I also notice that the probability for culture positivity you present in your model is vastly different from the source you quote for it (19. van Kampen et al. Duration and key determinants of infectious virus shedding in hospitalized patients with coronavirus disease-2019 (COVID-19)). To be more specific, the form of the curve you present for the non-vaccinated sample is vastly different from the one you cite, and your patients are vastly more infectious, with 50% positive cell culture probability already at 10^5.1 copies/ml, while van Kampen et al. writes 10^8.5 copies/ml. This corresponds to a difference in Ct-Values of 11! I cannot think of any sensible explanation for this difference.

To me, it looks like there must be errors in your model. It would help a lot if you revise your model and publish a scatter plot of positive/negative cell cultures per Ct/Values for both groups, as well as positivity against days of sample taken after symptom onset.

On 2021-12-04 16:54:30, user Karl Krösus wrote:

Dear Sirs, dear Madams,

do you want to tell me that your findings are, that if you feed your simulation model with input parameters: contagiousness for unvaccinated = X and contagiousness for vaccinated = 0,25*X, infections by vaccinated are reduced by 75 %?!?! Bravo, I applaud you.<br /> And this effectiveness you derive from the RKI data despite those numbers being totally skewed because vaccinated persons need not to be regularly tested or at all.

Remembering the main reason behind the lockdown measures was to reduce <br /> contact between people because it was suspected that the majority of <br /> people were asymptomatic when infected and would not know that they were<br /> contagious. Now we have vaccines that effectively reduce symptoms and severity of the illness (60-80% depending on the vaccine, estimated), wouldn't that mean that the percentage of asymptomatic infected will rise? And since vaccinated people don't need mandatory tests to participate in social interaction/life it never will be detected?

Especially, since the hope that the vaccine could lower viral load and therefore contagiousness has died since the emergence of the delta variant?<br /> https://www.medrxiv.org/con...

Best regards,<br /> Karl

On 2021-11-28 03:32:41, user Alberto wrote:

With this modelling, what would be the situation in Germany if instead of 65% of the population being vaccinated it was 0%, as it was a year ago? Would the results of such model be compatible with reality?

On 2021-12-07 15:11:47, user MS wrote:

This paper describes a model, not reality. No actual factual figures are used. Weasel words include: "Elusive", "we assume", "we estimate", "under the assumption". Authors are from Humboldt U, known for political bias, many also work at RKI. This seems to be a contract work to justify German politics, as per RKI.

On 2021-07-13 14:29:41, user Larry berube wrote:

So I don't see where they checked the vaccine validity in India. https://www.cnn.com/2021/07...

On 2021-09-23 18:14:58, user kdrl nakle wrote:

n-28, n=29, n=106 and no significant difference between 2.4x10^5 and 3x10^4? That is because your samples are small. I think that 8 fold increase would be significant if you got bigger samples.

On 2021-08-31 16:53:43, user Dime wrote:

"We know that the antibody response wanes over about 8 months."

How do we "know" this is time-related and not variant-related? Studies have already shown that the vaxed are more susceptible to delta than the previous iterations of COVID. Perhaps, because of the nature of the vaxes targeting the spike protein, they are less effective against delta (and possibly subsequent variants).

On 2021-09-22 18:56:48, user Chewbacca wrote:

The health worker part is a good point, but I don't think different starting point changes anything to the real world applications of the study. If people who survived covid are proven to be statistically at least as safe as the vaccinated group, then we can conclude that they are protected well enough. If hospitalizations in the previously infected population start rising alarmingly, then the strategy could be reviewed, but for now I don't see the point in vaccinating them when the resources could be used more effectively elsewhere.

On 2021-09-01 03:40:09, user Ruff wrote:

It says that natural immunity is still bolstered by vaccination. And regardless, vaccination before infection is still better because this study only compared breakthrough vs recurrent infection, not the long term health of people who had those infections or that of people infected with no prior immunity. Data without context will cause more harm when used to make decisions like skipping vaccination or intentional contraction of a virus.

On 2021-09-08 21:54:03, user Liminal Circuits wrote:

That's not true of every country. I did the math on the source, and double checked it:

SARS-CoV-2 variants of concern and <br /> variants under investigation in <br /> England

‘Attendance to emergency care and deaths of confirmed and provisional Delta cases in England by vaccination status’<br /> ?February 1, 2021 to August 2, 2021:?

Deaths within 28 days of <br /> positive specimen date:?<br /> Total Vaccinated Cases: 148,956<br /> ?Total Vaccinated Deaths <50: 23 [Rate: 1.54/10,000]<br /> Total Vaccinated Deaths >=50: 465 [Rate: 31.21/10,000]<br /> Total Vaccinated Deaths: 488 [Percentage of all Deaths: 65.8%]<br /> _____________________________________________________

Total Unvaccinated Cases: 151,054

Total Unvaccinated Deaths <50: 48 [Rate: 3.17/10,000]<br /> Total Unvaccinated Deaths >=50: 205 [Rate: 13.57/10,000]<br /> Total Unvaccinated Deaths: 253 [Percentage of all Deaths: 34.1%]

https://assets.publishing.s...

On 2021-08-26 08:55:34, user William Richard Dubourg wrote:

Because of the voluntary nature of testing, testing rates as an outcome measure are on their own unreliable. There is reason to think the propensity to get tested is different between the vaccinated and infected groups. You need a model to predict testing propensity.

Your Table S1 does not match the text. Odds ratios and CIs are different.

My main concern relates to underlying health status. The infected group will exclude people who have previously died from COVID. The vaccinated group will not. Thus, there is reason to believe the infected group will have better underlying health status than the vaccinated group. This might explain why there were marginally more hospitalisations (a better and less biased outcome measure) in the vaccinated group than the infected group.

It should also be noted that there was no difference in deaths between the two groups.

Your conclusions about the beneficial effect of infection vs vaccination are therefore unwarranted.

On 2021-09-07 12:17:38, user Holger Lundstrom wrote:

Interesting take. The same however goes for the original study of the Pfizer vaccine.

Here, too, only 200 cases out of 40,000 people were used for the final analysis of vaccine efficacy.

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

On 2021-09-23 00:16:21, user 4qmmt wrote:

I'm confused by your concern for people with no symptoms. If they have no symptoms, is there an infection?

On 2021-09-09 15:10:17, user 4qmmt wrote:

I did not know that - could you please provide the reference? That makes their not counting the several thousand symptomatic subjects even more strange.

On 2021-08-27 19:26:07, user Jeremy R. Hammond wrote:

I am confused by the Model 3 analysis. The authors state that they found a significant 0.53-fold decreased risk for reinfection for "those who were both previously infected and received a single dose of the vaccine" compared to those who were previously infected and remained unvaccinated.

However, then they say they conducted a sub-analysis limiting subjects to those whose single dose of vaccine was "administered AFTER the positive RT-PCR test", which "represented 81% of the previously-infected-and-vaccinated study group." This analysis did NOT find a statistically significant decreased risk of reinfection among the previously-infected-and-vaccinated group.

Do I understand correctly, then, that in the main analysis, the immune systems of nearly 20% of "those who were both previously infected and received a single dose of the vaccine" were primed not with infection but with vaccination?

In other words, unless I am misunderstanding, they only saw a significant "benefit" for previously-infected-and-vaccinated individuals when the immunologic priming was with vaccination, with the significance being lost when narrowing the analysis to a true comparison between people whose immune systems were primed by infection. Which might suggest a phenomenon of original antigenic sin rather than a benefit of vaccination for those with preexisting natural immunity. The benefit in this case was not derived from vaccination after infection but from infection after vaccination.

Further, the authors state explicitly that they "could not demonstrate significance" for individuals with prior infection who SUBSEQUENTLY received a single dose of vaccine, which again suggests that their main analysis was NOT a comparison of people who were vaccinated after having acquired natural immunity and people who had natural immunity but were never vaccinated. This comparison was only made in the sub-analysis that did not reach statistical significance.

Confirmation or clarification from the authors would be appreciated.

On 2020-05-16 23:36:43, user PANAGIOTIS AMPATZIS wrote:

There is a hit piece from Buzz Feed news (I know lol) that says the Jet Blue founder (and anti lockdown proponent) gave 5000$ to the study to influence it. They make a huge deal out of it, so please release the full amount of the funding as an answer to show them that 5000 dollars is a small amount to make the study unreliable.

Keep up the good work

On 2021-03-23 17:22:24, user Nuno Sepúlveda wrote:

We are currently extending our analysis regarding the impact of misclassification on the detection of a putative association with ME/CFS.

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

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

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

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

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

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

Primary Outcome Measures :

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

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

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

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

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

Time between drug treatment and symptoms resolution

On 2022-02-04 12:27:17, user disqus_q5anFFpp6R wrote:

So wouldn't it be interesting to check neutralising IgG levels at a timepoint when IgG response is fully on. Unvaccinated were checked 12-17 days post testing. Isn't that a litte early?

https://www.nature.com/arti...

On 2025-03-07 03:42:49, user mehrdad alemi wrote:

The COVID-19 pandemic posed unprecedented challenges for countries worldwide. Despite international sanctions, Iran managed to respond effectively to this crisis by relying on its domestic capacities.

Among the actions taken by Iranian scientists, researchers, and physicians:

1. Production of Domestic Vaccines: Iran became one of the countries producing COVID-19 vaccines by developing domestic vaccines such as Noora.

2. Expansion of Diagnostic and Treatment Capacity: The development of diagnostic kits, the increase in the number of equipped laboratories, and the production of medical equipment, including ventilators, contributed to better crisis management.

3. Healthcare System Management: The establishment of field hospitals, the strengthening of medical infrastructure, and the implementation of health restrictions at critical times played a significant role in reducing infection and mortality rates.

4. Research and Innovation: The publication of reputable scientific articles and the conduction of clinical studies on Iranian vaccines strengthened Iran’s scientific standing in this field.

On 2020-06-10 09:40:43, user CC wrote:

are there any subtle clotting differences between A and O blood groups that could be relevant to the coagulopathy seen in CoVID19?

On 2020-04-27 19:53:17, user eldhose poulose wrote:

https://data.gov.in/catalog...

This is the link that I received from your paper

On 2021-07-06 10:59:10, user Princess Aakuti wrote:

Great Read, first vaccine reporting clinical efficacy on detla

On 2022-01-03 02:35:09, user Mike wrote:

This study shows that after three months the vaccine effectiveness of Pfizer & Moderna against Omicron is actually negative. Pfizer customers are 76.5% more likely and Moderna customers are 39.3% more likely to be infected than unvaxxed people.

On 2020-06-09 17:41:58, user Hamid Reza Marateb wrote:

This is a hospital-based cohort whose results could not be generalized to the population. Moreover, these patients usually have commorbidity, and thus avoid smoking. Here are justifications.

On 2020-11-07 10:52:37, user Jesper Kivelä wrote:

Ollila and coworkers have erroneously [based on their data and R code (1)] calculated standard errors (SE) for individual studies without first taking natural logarithm of upper and lower bound of confidence interval (CI) as would be appropriate in the case of ratio measures, like relative risk (RR).

For example, SE was 0.204 for one of the included studies [reference 17 in study by Ollila and coworkers (2)], which is smaller than correct SE of 0.643. Naturally, too small SE will produce too narrow CI, which is evident, for example, from the Figure 3A in their study (2).

I replicated result highlighted in the abstract (2) based on a maximum follow-up [RR 0.61 (95% CI 0.39 to 0.96)] using R meta package and its metagen function. Replicated RR was 0.77 (95% CI 0.57 to 1.05) across 5 studies based on random-effects model with the use DerSimonian-Laird estimator for between-study variance. In sensitivity analysis, RR was 0.72 (95% CI 0.39 to 1.33) using the recommended methods for random-effects modeling with a small number of studies (3).

I first pointed out calculation errors in the study by Ollila and coworkers at Twitter, and as of submitting this comment statistical code provided by the authors in (1) is still under review for possible changes and corrections.

References

1. https://github.com/OllilaLa... (first accessed 7 August)
2. Ollila HM, Partinen M, Koskela J, et al. medRxiv 2020.07.31.20166116
3. Langan D, Higgins JPT, Jackson D, et al. Res Synth Methods 2019;10:83-98

On 2021-07-10 02:06:06, user Marcus wrote:

No mention of strain or variant specific data, even in limitations discussion.

On 2020-12-12 17:48:59, user Patrick Karas wrote:

Congratulations on this excellent work. Molecular subtyping for meningioma is much needed to help develop future therapies, and your work pushes this forward. How do you think your subtypes A, B and C compare to the meningioma molecular types similarly labeled type A, B, and C published last year in PNAS by Patel et al (doi: 10.1073/pnas.1912858116)? It seems like there is a lot of overlap (group A with intact NF2; group B and C with NF2 loss; group C with increased FOXM1 expression and high copy number variation). This is a great step forward validating these subtypes through a different approach.

On 2021-03-01 19:08:36, user Rainald Koch wrote:

The model ignores delays. If tracing and testing is not much faster than the transmission itself, the effectiveness of backward contact tracing is largely overestimated. Compliance with quarantine is another weakness. What works in SE Asia won't work in most other cultures.

On 2020-07-21 11:21:52, user Hagai Perets wrote:

This study: https://arxiv.org/abs/2007.... might explain these results. If a preceding strain provided immunity and began elsewhere in China, one would expect a correletion with two positions - one direct (Wuhan) and one inverse with the origin of the preceding strain.

On 2020-05-18 14:28:17, user OxImmuno Literature Initiative wrote:

https://www.immunology.ox.a...

On 2020-04-14 21:44:58, user _str wrote:

Why did you not take into account the risks of infection using public transport e.g. busses, trains?

On 2022-01-23 21:31:37, user maa jdl wrote:

This paper is a total nonsense!<br /> Why applying the Benford law?<br /> There is no reason. And the paper does not contradict that!<br /> On the contrary.<br /> You just need to look at the data to understand WHY the Benford law doesn't apply!<br /> This is what I did and ONE simple picture can reveal it in a much clearer way than a long paper with a lot of references. This can be done with no references at all! The chi² test is useful there only to give numbers on what is obvious from the picture.

On 2023-06-20 09:28:49, user Matt Hodgkinson wrote:

The problem with this study, as others have noted on PubPeer, is that the authors are proposing a heuristic for identifying paper mill articles that fails under closer examination.

Prof Gigerenzer works on 'simple heuristics' and 'gut feelings' as a good approach to being smart: it seems that the authors thought this assessment was 'good enough' without thinking through the consequences of labelling so many authors as having committed misconduct with the wave of a hand.

It is possible that some journal editors will adopt such crude screening techniques and reject submissions that lack institutional email addresses and international authors, putting a further barrier in the way of authors from lower-income countries - and incentivising gift authorship. This would go against the spirit of the recent World Conferences on Research Integrity (WCRI) Cape Town Statement, including that "Barriers to ‘open science’ participation by researchers working in low-resource settings need to be identified and addressed by publishers, and other appropriate national and global stakeholders, such as science councils, funders, and similar institutions."

On 2020-08-14 18:40:49, user Stoney Huff wrote:

THIS should be under a Conclusions header in bold:<br /> "Wrist measurement is more stable than forehead measurement <br /> under different circumstance. Both measurements have great fever <br /> screening abilities for indoor patients."

On 2022-02-16 21:04:27, user Showme wrote:

How long is the peer review still going to take ... ?

On 2023-12-21 15:35:25, user OJ Watson wrote:

Now published at: https://www.science.org/doi...

On 2020-04-24 15:57:17, user Rajendra Kings Rayudoo wrote:

To<br /> Manisha mandal , shyamapada mandal

Every thing is ok but how come the analytics of asymptomatic carriers and presymptomatic carriers which are grave fmdanherous to spread

More over in india this is a stage which entering into community transmission

Regards<br /> ............................................. Rajendra

On 2022-02-27 04:15:03, user RonG wrote:

Dr. Bredesen most certainly does have a "conflict of interest". He uses this article to promote his company and sales of his "bestselling" book. For me, this lack of transparency casts grave suspicion on the results. Many scientists and doctors work with corporations to publish research, but they honestly acknowledge that association.

On 2020-03-18 08:25:22, user Alberto wrote:

Althought It could survive for some period of time, its title (concentration) maybe is constantaly descending as a negative exponential function. That means that in a shorter period of time the efective probability of transmisión is lower. I have studied bacteriophages, but I suppose that dynamics of inhabilitation shows the same dinamics.

On 2020-05-01 04:18:35, user Dr. Anthony Burnetti wrote:

The proposed mechanism is blocking the import of accessory proteins into the nucleus that suppress the innate immune response. The dose needed to block viral replication in vitro is possibly higher than a dose that could have a positive impact on the immune response. It is still quite possible that the approved dose could have stronger effects in animals than in tissue culture.

On 2022-02-17 21:29:51, user RT1C wrote:

You state, "For those boosted, the median time to being boosted was 16 days prior to the study start date (IQR -38 to 6 days)." Is that a typo or did you truly mean a positive 6? i.e., did you mean -38 to -6 days, or -38 to 6 days? If the latter, you actually included subjects who were vaccinated with boosters after the study period began? If that's the IQR, then I assume the full range extends much further into the study range. Those are VERY recently boosted. In your discussion, you should not say, "boosting with a vaccine designed for an<br /> earlier variant of COVID-19 still provides significant protection against infection with the Omicron variant." without also providing a time associated with that. For example, you might add to that sentence "for a period of at least 1 month" or whatever. It seems important to stress the limitation of the study in this manner, to avoid giving the impression that the booster provides long-lasting protection against infection when that is not shown by your study.

Finally, on a related matter, how did you treat individuals who tested positive before 7 days after their booster? If, as some research suggests, vaccination temporarily increases susceptibility to infection (for about 2 weeks), by including subjects who were vaccinated within the study period, you may have biased findings against those without boosters.

On 2021-12-07 15:37:50, user Wolfgang Messner wrote:

After peer review, the paper is published in the following journal:<br /> Messner, W (2021). The Institutional and Cultural Context of Cross-National Variation in Early COVID-19 Outbreaks. International Public Health Journal, Vol. 13 No. 2, pp 227-235

Links:<br /> https://www.proquest.com/do...<br /> http://www.novapublishers.o...

On 2021-10-27 18:43:08, user Gregory Armstrong wrote:

Excellent presentation at SPHERES today. Question: I may have missed something, but to compare relative transmissibility via logistic regression, why not simply limit the data to the two variants and run the regression using the calendar date as the independent variable (using a binary variable for the variant, and multiplying the beta by 5.2)?

On 2021-09-12 06:41:02, user kdrl nakle wrote:

Air outlets versus inlets. Very important though not surprising information. The rest of this paper is also important info.

On 2020-05-05 20:58:20, user japhetk wrote:

A brief comment. <br /> This study's conclusion that the proportion of asymptomatic patients among the infected is 99.99% is not consistent with the fact that 9 Japanese out of 300 infected Japanese passengers among 1341 total passengers in the diamond princess ship (where all passengers went through PCR testing) have died (half the infected (which was confirmed by PCR) showed the symptoms by the way). And their fatality rate was higher than the age-matched westerners. Although, they were mostly old, so are the 30 percent of Japanese.

On 2025-09-15 08:00:31, user Jean-Pierre Le Rouzic wrote:

Thanks for your kind answer but the link is still incorrect in the "An online simulator for genetic counselling" paragraph.

Here is what I see:<br /> "This tool, available free of charge online at https://lbbeshiny.univ-lyon1.fr/ftd-als/ , is designed to facilitate genetic counselling provided by professionals to consultands, with an interactive and intuitive way to compute the risk estimates. "

On 2020-12-20 22:06:38, user Sam Smith wrote:

Is it possible to begin this treatment too early or too late, or to continue for too long?

On 2020-07-25 13:01:40, user Matthias von Davier wrote:

Something is missing here. Country level correlations can be inverse to individual level correlation (and they may be in this case). There's a long history of ecological fallacies and other types of wrong conclusions when making inferences from group level association to the individual level.

Andrew Gelman wrote https://www.amazon.com/Red-...

And the original Robinson 1950 article is here:

https://www.jstor.org/stabl...

On 2021-03-20 15:21:28, user drmoienkhan wrote:

Published <br /> Khan MA, Menon P, Govender R, Samra A, Nauman J, Ostlundh L, Mustafa H, Allaham KK, Smith JEM, Al Kaabi JM. Systematic review of the effects of pandemic confinements on body weight and their determinants. Br J Nutr. 2021 Mar 12:1-74. doi: 10.1017/S0007114521000921. Epub ahead of print. PMID: 33706844.

On 2020-12-07 04:14:29, user Luis Ricardo Illescas wrote:

I think it would be important to separate the group that died in the street from the rest of the group that includes dying in houses, accommodations, shelters. They reflect a different level of tragedy

On 2020-04-11 08:17:28, user Xavier de Roquemaurel wrote:

Great work. Thanks.<br /> Can i suggest to please run a similar study concept, yet this time identifying countries according to the different BCG strains:<br /> BCG Japan (Tokyo)<br /> BCG Brazil / Moreau<br /> BCG Denmark<br /> ...<br /> This is also an hypothesis to test.<br /> Thanks<br /> Xavier

On 2021-07-06 17:47:47, user Stephen Smith wrote:

Hello John,

Thank you for your post. A few things -<br /> First, Cox and Kaplan-Meier analyses really do not make sense when looking at mortality in a single hospital admission for an acute illness. Doctors and, presumably, their pts don't care when during the hospital the pt died, so much as we care IF the pt died. Cox and KM curves are much better for long-term studies and for situations which allow removal of a pt from the numerator and denominator, such as lost to follow pts and a pt in a medical studies dies from a non-related event, such as trauma. Every pt who died is considered an event in this and similar studies. But the big thing is that the rate of death per day or week isn't important; the rate of death per entire hospitalization is important. <br /> Second, I have tried to explain this several times. The decisions to use HCQ with or without AZM and the regimen of HCQ used were decided by different Infectious Diseases doctors or Infectious Diseases practices. The hospital is a community-based teaching hospital. Most physicians, including all ID doctors, are private practitioners. There were several ID groups, each in private practice, who saw these pts at this one hospital. In general, within an ID group, their opinions on HCQ were consistent. The most commonly used HCQ regimen was 2,400 mg over 5 days. This regimen was recommended by a PK study in Clinical Infectious Diseases published in early March 2020. In other words, for the vast majority of pts who received HCQ, the cumulative dose of HCQ was determined by the ID doctor seeing the pt, not pt issues. <br /> Third, I have carved out pts by length of stay. For instance, 130 pts received < 3 gm of HCQ and had a LOS > 8 days. Their survival rate = 26.92%. Comparatively the majority of the HCQ/AZM pts had received > 3 gm of HCQ before Day 8. Their survival rate = 53.57%. This difference in survival rates, 26.65%, is statistically significant with p = 0.006. Eliminating pts with shorter length of stays assumes that therapy HAS NO effect until that threshold is crossed. That's most likely an incorrect assumption. Therefore, this type of analysis biases these data towards not showing a difference. Still, the difference in survival rates was great and highly statistically significant. <br /> Fourth, the median LOS = 13.1 days. That's plenty of time to be given > 3 gm of HCQ. <br /> Fifth, my point about weight-based dosing is that it moves older people up relative to younger pts.. So, when one divides the HCQ cumulative dose by the pt's weight, older pts moved up the relative list and younger ones moved down. For those with LOS > 8, the ave age for pts who received a cumulative, weight-based dose >= median = 63.4 yrs, while for pts who received the >= median absolute dose, the ave age = 60.3 yrs. <br /> Sixth, the weight range of this cohort was nearly 7-fold. Many pts weighed twice as much as many others. For a pt who weighed 50% of another, it took 50% of the time to reach a weight-based dose. For instance, consider two patients, X and Y. X weighs = 65 kg and Y weighs 130 kg. Let's choose a target cumulative weight-based dose = 40 mg/kg. The total HCQ dose for Pt X = 65 kg x 40 mg/kg = 2,600 mg total. The total HCQ dose for Pt Y = 135 kg x 40 mg/kg = 5,200 mg. The daily dose was the same, 600 mg per day. Obviously, it takes on 4.3 days for Pt X to reach 40 mg/kg and it takes 8.6 days for pt Y to reach that weight-based dose. <br /> So, weight-based cumulative HCQ dose was associated with survival, according to our statisticians, more so that absolute cumulative HCQ dose. That is strong evidence that HCQ is the reason for that increase in survival. Importantly, remember this group also received > 1 g AZM. <br /> Conversely, what is the alternative explanation for those observations and data? <br /> Why would weight-based cumulative HCQ dose be associated more with survival than absolute cumulative HCQ dose, if absolute cumulative dose was simply a marker of survival and when using weight-based HCQ cumulative dose increases average age of those who received >= median dose?

Stephen

On 2022-02-01 02:14:51, user Sulev Koks wrote:

The manuscript has been accepted for publication in Experimental Biology and Medicine.

On 2020-11-25 15:43:07, user Jayebird58 wrote:

The Danish masks study proves masks don’t work!

On 2020-08-28 07:43:07, user Hilda Bastian wrote:

At several points, the authors rely on what's described as the "historical efficacy of passive antibody therapy for infectious diseases". This is based on a small amount of data, much of it from the pre-intensive care era, and none from a publication later than 2010. As a result, no randomized trial is included, as they were published after 2010: 2 NIH randomized trials of convalescent plasma in influenza and 2 randomized trials of IVIG for influenza. Meta-analysis shows no benefit. [1] This also fails to consider the post-2010 ebola outbreak, and the failure of convalescent plasma to improve mortality from that disease. [1] Thus, there is no historically proof of efficacy of convalescent plasma, and what randomized data exists, does not suggest there has been important benefit in the past.

In addition to relying on this biased assessment of historical evidence to support a conclusion of effectiveness in this study, the authors cite this claim as a reason for not conducting a randomized trial: "Many COVID-19 patients would likely have been distrustful of being randomized to a placebo based on historical precedent". However, if they were accurately informed, prospective participants would be told there was no evidence of benefit. In a randomized trial in the Netherlands stopped because it was determined no benefit was likely in the study as designed, the authors reported that only 1 in 4 eligible patients declined, and that was typically because of fear of adverse events. [2] The requirement for adequate trial recruitment has more to do with doctors and patients in outbreaks not being misled about the state of uncertainty of this treatment.

The authors argue that the patients in the Expanded Access Program are diverse. However, it is important to point out that their diversity is not representative of the people severely ill with Covid-19 and at risk of dying. For example, 19% of the group are Black, whereas the CDC reports that they are over 30% of those hospitalized with Covid-19 and twice as likely to die. [3,4]

In respect of the representativeness of the small non-random sample described as "pseudo-randomized" in this preprint, no data is provided on the hospitals providing those samples.

In addition, as others have already pointed out in a discussion linked here, [5] critical information on timing of deaths is not provided. Those transfused earlier in the "epochs" have far longer follow-up for deaths than the larger number more recently. Given that since early in the outbreak, it's been observed that deaths occur across 2 to 8 weeks from the onset of symptoms, [6] the impact of this could be substantial, as participation in the EAP was higher later. In the group on the Diamond Princess cruise, for example, per Wikipedia's tallying, half the deaths may have occurred in that second month [7], and assessment of mortality appropriately included censoring for this. [8] Case series in the US typically report substantial proportions of people still in intensive care at study's end.

The authors' interpretation of their subgroup analysis based on a non-random set of blood samples preserved for blood bank quality assurance proceeds as though the safety of convalescent plasma for Covid-19 has been established, based on the data of their own uncontrolled study. However, controlled study is required to be certain, for example, whether plasma with lower levels of antibodies trigger antibody dependent disease enhancement. [5] As the FDA's memorandum reports that the results are also dependent on which assay results are used, this should be reported in any discussion of this subgroup analysis. [9]

In the absence of adequate controlled study of convalescent plasma establishing that it does more good than harm in infectious respiratory disease generally in contemporary medical settings, and Covid-19 in particular, the authors' claim that their uncontrolled study provides "strong evidence" is unjustified.

Disclosure: I have written about this study for the general public at WIRED, and am in the process of doing so at PLOS Blogs.

[1] Devasenapathy (2020). https://www.cmaj.ca/content...

[2] Gharbharan (2020). https://www.medrxiv.org/con...

[3] CDC COVID-Net (2020). https://gis.cdc.gov/grasp/C...

[4] CDC surveillance data (2020). https://www.cdc.gov/coronav...

[5] Harrell (2020). https://discourse.datametho...

[6] WHO (2020). https://www.who.int/docs/de...

[7] Wikipedia (2020). https://en.wikipedia.org/wi...

[8] Russell (2020). https://www.medrxiv.org/con...

[9] FDA Clinical Memorandum (2020). https://www.fda.gov/media/1...

On 2021-07-12 08:17:01, user Pablo wrote:

Dear authors, there is a small typo in page 5: Supplementary Table S1.

B.1.429 (EPISLON) -> B.1.429 (EPSILON)

On 2019-10-10 12:58:07, user GuyguyKabundi Tshima wrote:

EPIDEMIOLOGICAL SITUATION

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT OCTOBER 07, 2019<br /> Tuesday, October 08, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,206, of which 3,092 are confirmed and 114 are probable. In total, there were 2,143 deaths (2029 confirmed and 114 probable) and 1006 people healed.<br /> 443 suspected cases under investigation;<br /> 1 new case confirmed at CTE in Ituri in Mandima;<br /> 1 new confirmed death in North Kivu in Mabalako;<br /> 10 people were cured from the CTE, including 7 in Ituri in Komanda and 3 in North Kivu, including Beni, 1 in Katwa and 1 in Mabalako;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

No more confirmed cases of EVD at Butembo CTE<br /> - The Butembo Ebola Treatment Center (CTE) in North Kivu no longer has a confirmed case of Ebola Virus Disease;<br /> - The last two confirmed cases supported in this CTE have been released since Sunday, October 07, 2019 and have been reintegrated this Tuesday, October 08, 2019 in their respective communities by the teams of the response to the Virus Disease #Ebola of the psychosocial care. These cases are respectively health zones of Biena and Kayna;<br /> - Miss Ornella Bwira Zawadi, psychosocial supervisor at Butembo CTC, explains the psychosocial care at the Treatment Center. The Butembo CTE uses 17 psychologists subdivided into four blocks of tasks. These are triage supervisors, suspected cases, confirmed cases and accompanying village;<br /> - In the triage center, the psychologist ensures the awareness of newly admitted CTE cases. These new cases are normally 72 hours in the ETC and are taken on the 1st and the last day;<br /> - From the first day, the psychologist announces the result to the patients, its clinical evolution and its state. The patient who is positive is moved from the suspect's room to the confirmed block, while the patient who is negative until the third day remains in the suspected cases;<br /> - When the person is confirmed Ebola case, the psychologist is responsible for announcing his result, to make him aware of its evolution and life at the CTE. He asks him questions about his career in order to facilitate the follow-up of contacts;<br /> - It also monitors the confirmed case daily and ensures the relay between the patient and his family;<br /> - The accompanying person allows the good collaboration between the other CTE provider teams with the patient. It transmits various information of the patient, as well as its evolution to the other teams of the CTE;<br /> - Thereafter, intervenes the reintegration of suspected or confirmed cases cured and removed from the CTE. The psychiatrist accompanies him in his community. He educates his community and his family, explaining that the person who has been cured of Ebola is not dangerous and can not infect anyone else with the Ebola Virus Disease;<br /> - This Tuesday, October 08, 2019, Butembo CTE also released non Ebola people who were admitted to CTE as suspected cases.

VACCINATION

• A vaccination ring was opened around the confirmed case of 06 October 2019 in the Oicha health zone in Tenambo, North Kivu;
• Continuation of vaccination around the last case of 04 October 2019 in Andindulu village in the Lolwa health zone in Ituri;
• Continuation of the vaccination of newly recruited front-line staff in the Reference Hospitals of Katwa and Kyondo Health Zones;
• Launch of Local Polio Immunization Days integrated with vitamin A supplementation and mebendazole deworming in 17 ZS of Butembo Antenna, most of which are Ebola virus-infected areas;
• Since vaccination began on 8 August 2018, 235,389 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 103,567,829 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2019-10-04 22:38:03, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 03 OCTOBER 2019

Friday, October 04, 2019

Since the beginning of the epidemic, the cumulative number of cases is 3,201, of which 3,087 are confirmed and 114 are probable. In total, there were 2.139 deaths (2025 confirmed and 114 probable) and 999 people cured.<br /> 451 suspected cases under investigation;<br /> 3 new confirmed cases, including:<br /> 1 in North Kivu in Beni;<br /> 2 in Ituri, including 1 in Mambasa and 1 in Mandima;<br /> 2 new confirmed deaths in North Kivu, including 1 in Beni and 1 in Mabalako;<br /> 4 people healed from the CTE in North Kivu in Beni;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.<br /> Day 18 without response activities in the Lwemba Health Area in Mandima, Ituri.

LEXICON<br /> • A community death is any death that occurs outside a Ebola Treatment Center.<br /> • A probable case is a death for which it was not possible to obtain biological samples for confirmation in the laboratory but where the investigations revealed an epidemiological link with a confirmed or probable case.

NEWS<br /> The 10th Ebola Virus Disease epidemic in the DRC reaches its 1000th cure<br /> - The thousandth cured of the Ebola Virus Disease came out Friday of the Mangina CTE in Mabalako in North Kivu Province;<br /> - Indeed, this 1000th cured is part of four healed Friday of this CTE. It is about a woman, quarantine gone, case contact of her nephew with the Air of Health of Lwemba with Mandima in Ituri. As soon as she felt the fever, she went to the Health Center, where she was detected as a suspected case and transferred directly to the CTE. She was confirmed and followed her treatment until recovery. She advises the population to go quickly to the Health Center and not fear the CTE to cure Ebola Virus Disease;<br /> - Among these four cures, there is also a health provider. This is an ambulance hygienist, the 1001 st healed, who was contaminated during the unloading of his personal protective equipment (PPE). He recommended a lot of protection and precautions to all hygienists when removing PPE. And in case of possible contamination, do not panic, but rather go quickly to the Health Center for appropriate treatment;<br /> - For the Ebola Epidemic Epidemic Response Coordinator, Dr. Faustin Bile Saka, these healers will be the ambassadors for the response in their respective communities and testify that when we arrive early we have the chance to come out healed like them. He handed out the certificates of release to the cured, with the various partners of the response, WHO and IMC to the 1000, 1001, 1002 and 1003 th cures of the Ebola Virus Disease in the DRC;<br /> - As a miracle, the 10th epidemic of the Ebola Virus Disease began around the end of July 2018 and declared in early August 2019 in Mangina and it is still in Mangina, where came the 1000th cured.

VACCINATION

• Since vaccination began on August 8, 2018, 232,725 people have been vaccinated;
• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 102,092,950 ;
• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:

1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.

On 2020-03-28 16:06:33, user Mark Dane wrote:

Thank you for this important study. Did you collect samples in patient rooms who were either known or expected to not have the virus so we can see the null data?

On 2022-01-10 21:55:28, user TMK wrote:

There is a theory that can back it up. "Original antigenic sin".

On 2021-08-15 17:21:01, user carbsane wrote:

Can someone PLEASE explain to me how there can be 850 cases of COVID among the placebo group through March 13th if most of that group was subsequently vaccinated?? <br /> According to Pfizer's website they began unblinding and vaccinating in December (pretty much after the EUA), as they reported that as of Jan 29th 3,624 placebos had been FULLY vaxxed. Their last reported numbers (before dropping the information from their weibsite) were on Feb 24th by which time 16,904 had received at least one dose of vaccine.

On 2025-11-17 02:35:18, user Charin Modchang wrote:

Now published in PLOS Neglected Tropical Diseases. DOI: https://doi.org/10.1371/journal.pntd.0013618

On 2021-05-26 12:04:01, user zega wrote:

Paper has valid conclusions, but uses "work around" method to make that conclusion, this paper compares ACTUAL blood levels with positivity rate https://journals.plos.org/p...

On 2020-10-15 08:32:49, user WOStavelot wrote:

Selling genetic testing is not the best formative domain for driving a clinical study. There should have been a broader base of information to permit placing symptomatology in a more useful perspective. Feels like this was patched on to an in-place system to get some additional funding. Nothing too wrong with that accept that thinking that large numbers of respondents will fix a poor design is an error. Disappointing.

On 2022-08-13 18:37:14, user Christian Fiala, MD, PhD wrote:

Is there any information as to the requirements and/or use of face masks by pregnant women during the pandemic in the region?

On 2021-12-25 04:08:33, user Nick Bauer wrote:

Figure 1 legend should explain the colors better because it's hard to interpret otherwise.

On 2020-05-28 23:39:32, user Gerard Pujadas Anguiano wrote:

We have found that Celecoxib is also an inhibitor of the main protease (M-pro) of the SARS-CoV-2 virus. This result is published at IJMS. Find the PDF for the paper here https://www.mdpi.com/1422-0067/21/11/3793

On 2023-01-02 13:22:01, user John Jacobs wrote:

A thread with some comments on this study. https://twitter.com/johnjlj...

https://unrollthread.com/t/...

On 2021-09-11 13:44:08, user Irl Smith wrote:

Arola et al. show that the incidence of myocarditis is in the vicinity of 140 per year per million boys aged 15 (in girls, and other boys, the incidence is roughly an order of magnitude smaller). By neglecting the prior probability of myocarditis in all persons, not just those being vaccinated, the authors render their conclusions completely untenable. In other words, while the risk of hospitalization from COVID in boys is arguably smaller than the risk from myocarditis, there is no evidence that vaccination status affects the myocarditis risk.

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

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

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

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

On 2021-09-10 16:30:40, user Roger Seheult wrote:

Why did you choose to compare vaccine related CAE with COVID hospitalizations? Why not compare Vaccine related CAE with COVID CAE? Are we comparing apples to apples? Hospitalizations in pediatric population (especially before delta) was rare from COVID-19 for any reason and most vaccine CAEs do not require hospitalization as I understand.

On 2021-09-22 20:35:49, user tooearly wrote:

What we don't know:How long is this effect? Months? Many months?<br /> Is MMR the best choice for LAV non specific immune boost? Would OPV not work even better? more details about the endpoints and how they were measured

On 2020-09-12 03:26:51, user SW wrote:

I'm confused by this comment: "In a clinical study, quantitative viral culture was ~25-fold lower<br /> than viral RNA measurement by PCR." I've looked at the study to which you link, but I don't see anything about 25, and I don't really see *quantitative* viral culture -- isn't it just about whether a viral culture ends up positive or negative, without quantifying it? This factor of 25 seems to work well, so I'd love to understand it. Thanks.

On 2020-07-12 18:43:47, user Mario Moisés Alvarez wrote:

Please share with us your opinion on this contribution. We really want to raise awareness on the importance of massive testing particularly in densely populated cities. <br /> Very Best. Stay safe.

On 2021-08-16 21:15:27, user Mike Ronnie wrote:

"While vaccines continue to provide outstanding protection against severe

disease and mortality, the durability of this protection cannot be

reliably predicted. Therefore, it is essential for public health policy

to encourage vaccination while also planning for contingencies,

including diminished long-term protection."

--> I strongly recommend deleting these last sentences, as your study did not investigate this issue at all. Therefore, based on yourstudy design, this statement has absolutely no justification.

On 2020-05-20 16:50:49, user Peter Ellis wrote:

Table 1 presents the data, showing 40 positive tests and 689 negative tests, i.e. an average prevalence of 5.49% across the course of the study. Elsewhere in the manuscript, the sensitivity is given as 100% (meaning none were missed) and the specificity as 98.3% (meaning there is a 1.7% false positive rate.

This being the case, can the authors please explain:

1) Why the caption for Table 1 reports 789 patients given that 40 + 689 = 729?

2) How they adjusted for false positives. 40 / 729 = 5.49%, which minus the 1.7% false positive rate leaves around 3.79% positive across the course of the whole study.<br /> [A Bayesian adjustment would be more accurate, this will suffice for now]

3) Given that the true positive rate in the samples they measured is around 3.79% across the whole study, how do they calculate a population prevalence of 4.6% at the start, rising to 7.1% at the end of the study. The methodology for this is entirely lacking.

On 2024-05-02 17:06:42, user Oliver wrote:

I am 44 months cold turkey. History includes class II ointment and cream use and one round of prednisone (25mg a day), and maybe even a steroid shot...but I'm not sure (I fell on my back once and went to the ER, they gave me a shot of something...this was a few months before I started my TSW). I am trying to get my records to confirm. When I used TCS, I never finished a prescription. I used small amounts. I even applied using a finger cot. I used very consistently for only about 2-3 years. In total, in my life, probably 4 years (on and off). I was pretty careful but very naive. I blame myself and my dermatologist. She always just prescribed me another TCS to use. She never mentioned avoiding long term use. So maybe I shouldn't blame myself. What I want to comment on here is that I truly believe the current situation with TSW is a systemic medical catastrophe. Just think about it, practicing physicians are not looking under the microscope in their clinics to distinguish TSW between other eczematous disorders. They are going by the eye, and that's if they are even cognizant of TSW. If you had to place a bet on the amount of people's skin on this earth that are addicted to TCS and actually have TSW symptoms rather other eczematous disorders, what is your over/under? Serious question. It's easily over tens of millions if you count every country. In North America? Millions. That might be underestimating it. You could get a clearer picture just by seeing how many TCS products are sold to end consumer. It's tens of millions. The situation is beyond complex. As a nonprofessional, I'd even go as far as saying most people that have a history of TCS that are walking into their doctors clinic, they have TSW and that person and their doctor don't even know it. How many of these people are there every day? Sure, use the TCS for long term. But if you use for 20+ years and TSW is still not recognized by most institutions...I won't say much more but my mind will always remember the late Eric 'Nim' Bjorklund. May his memory be a blessing. TSW is more than just a serious condition. It's a crisis. It's irreparable. It could be one of the greatest institutional failures of the century in medicine.

On 2024-04-27 21:04:36, user Christopher Ho wrote:

I'm so glad that more research is being conducted on Tsw. As a TSW sufferer myself, it gives me hope to know that there may be better ways of diagnosing and treating the condition. I hope more studies come out of this and thank the authors very much for taking a big brave step forward towards publishing this for our community. It means a lot to us that this condition is acknowledged and medical guidance for use of TCS is properly updated by pharmaceutical companies and dermatologists.

On 2024-04-27 18:42:07, user Kim Brumfield wrote:

Thank you to Dr. Myles and his team for doing this research. My daughter has 20 years of prescribed steroid use for eczema without informed consent of the risk of topical steroid addiction and withdrawal. The dermatologists she saw used step therapy which eventually resulted in tachyphylaxis. The topical steroids stopped working after reaching hichest potency and now she is suffering from "eczema on steroids" which is really topical steroid withdrawal. Please help us find the cure for this horrible iatrogenic disease.

On 2024-05-03 17:29:02, user Jackie Kilpatrick wrote:

I have been through this hellish condition, experiencing all of the classic symptoms which differentiate it from eczema, including inability to control body temperature, bone deep incessant itch ( I slept in boxing gloves, ffs!), hair loss, insomnia, full red sleeve, oozing and flaking. I was told by doctors that the condition doesn’t exist. My consultant dermatologist said “if you don’t want my drugs, why are you here?” and when I said that I was hoping we could discuss other ways to maintain skin health like PH or microbiome issues she said scathingly that I and ‘my internet’ would know far more about that than she. <br /> For too long there has been a total disconnect between patients suffering a condition which not even medieval torture professionals could have dreamt up and a medical profession refusing to see the growing mountain of irrefutable even while anecdotal evidence emerging globally from social media. With the new video technology now available to all the number of brave selfless souls documenting in almost scientific detail what they are going through means that this, maybe one of the biggest medical scandals of all time, will soon be properly exposed for all to see. Proper research will support what all of us sufferers already know, the medical community will be forced to become as informed as their patients… imagine! … and maybe these horrendous drugs will be used as an absolute desperate measure of last resort rather than being doled out like sweeties for the most minor of complaints. More research and quickly please. Be the people who break this story properly and stand up for all the benighted souls burning in agony in their own skin.

On 2020-07-27 14:30:35, user Antonio Mattos wrote:

As most of countries have no testing, the best measurement would be death cases... Exemple like this, Brazil would just have coletive immunology when had approxiemely 2 milion deaths or hospitalizations... So, a tragetic cenarium. Seems that coletive immunology seens so far out of the reality.

On 2020-07-02 18:00:55, user Wouter wrote:

Same model, new simulations: https://academic.oup.com/ci...

On 2020-04-15 20:57:05, user Christian Smith wrote:

In the Discussion section, you write: "Should either those reported data or current global understanding of COVID-19 biology include substantial errors, those will become evident as a divergence between model predictions and Sweden’s public health situation"

Why did you then decide to not compare your predicted results to the real-world observations we have access to so far? Current (April 15) Covid19-induced ICU cases are reported at approximately 500, current hospitalized cases at 2100, accumulated deaths at 1200, and accumulated detected cases at 12000. There seems to be something off with your predicted numbers. Your plots are not easy to get exact numbers from, but as far as I can tell, the following numbers pop out for April 15 (today):

Figure 2A) ~20 000 hospitalized, 2B) ~10 000 hospitalized.<br /> Figure 3A) ~4000 ICU cases, 3B) 2500 ICU cases

Your predictions are an order of magnitude off from actual observations.

Minor point: Your assumptions on available ICU beds in Sweden are based on outdated sources. It is well known that the capacity has increased significantly in the last month.

On 2020-05-21 20:47:56, user Michael G Waldon wrote:

This paper represents a huge amount of effort and I am impressed with the apparent high quality of your work achieved in a short time. It will be instructive to now see if there is qualitative agreement between model predictions published here and future observations over coming weeks as restrictions are relaxed. <br /> Since I have been reading about the numerous and varied model predictions, I have been hoping to also see hindcasting and counterfactual simulations. These simulations provide information and guidance beyond that from simple predictions. I do ask that, in future reports, you include the added simulation in which actions are delayed beyond the factual case. This is important for a number of reasons. First, it gives balance to your analyses. Second, we need to know that the economic and social sacrifices that were made that we did (or did not) accomplished a purpose. In modeling I think it is important that we always estimate what has been achieved. <br /> If I were a peer reviewer, I would definitely support publication of this paper. Thank you.

On 2020-11-23 09:17:17, user Brenda Penton wrote:

I don't see how the data can be used if it only included 4 months of pandemic data? If Sweden had had a decreased mortality rate pre-pandemic and after the first wave, wouldn't that mean they would have had a decreased annual mortality rate otherwise or the assumed trajectory? I'm not sure if after wave data can be used since people still distanced, I'd assume. I can see if they used data next year comparing the two from March 2020 to March 2021. I still don't see the relevance of the study...even though Sweden had thousands of deaths from a pandemic..they would have died anyways, so no biggie? Is that it? It seems that people are using this data for proof that Sweden didn't do so bad or some kind of excuse? It's a little messed up to me.

On 2021-10-19 16:26:22, user Andy Bloch wrote:

There was a significant (and substantial) statistical difference that they brushed off, and they included the first 2 weeks after injection in the comparison. Pfizer is clearly more effective than AZ after 2 weeks against positive tests, as the Hazard Ratio chart in their Figure 2 shows.<br /> https://twitter.com/Andy_Bloch/status/1450397100341035021

On 2021-09-22 02:44:39, user orion9k wrote:

Then why are we quarantining people who test positive without symptoms? Because this is exactly what many experts have been saying, that asymptomatic people do not contaminate others ????

On 2020-07-01 18:36:55, user SPARK wrote:

Reference 10 typo in pdf

On 2021-11-09 23:59:36, user Jessica Grevis wrote:

Very interesting article. I'm curious if there is information on more specific professions, like an extended Table 2. I'm particularly interested in the construction trades.

On 2021-01-18 11:40:13, user Kit Byatt wrote:

Re Length of stay [LOS]

1. Was there a sex difference in LOS?

2. We know there are age differences in LOS (median & variance increasing with age). What were the LOSs for age brackets (e.g. each decade)?

3. Given the very skew LOS distributions in hospital in-patients usually, and especially here, mightn't it be helpful to put the inter-quartile range for the median LOS in 'Outcomes' para 2?

4. Could you calculate the 'decay' in in-patient numbers (i.e. the equation for the 'current number of inpatients' curve from time zero, for 1000 pts with the LOS distribution you know)? This could be invaluable for modelling bed occupancy.

Minor presentational points:

1. Figure 15 Middle (symptoms combination in ICU patients matrix) p 23

It is difficult to know the percentage figure for each bar in the symptom combinations and ICU admission matrix. Either putting the number over/in each column (as in Figure 15 Top), or at least showing minor tick marks at 0.01 intervals would greatly improve the clarity of this chart.

1. Is there a reason for presenting LOS data as a density plot and time from symptoms to admission as a Gamma distribution curve? They are essentially the same phenomena: time to an occurrence; why the different graphical representation?

On 2020-09-13 16:40:32, user kdrl nakle wrote:

One more non-randomized study where the selection of patients was obviously done with respect to their conditions. You can see that from age distributions of two groups. This repeats the same errors of previous non-randomized studies with roughly the same erroneous conclusions.

On 2021-08-22 14:07:20, user JB wrote:

have been approved for use in humans since December 2020<br />

They have been authorized, not approved.

On 2020-05-15 17:25:31, user Kom Mentar wrote:

I would be curious to learn more about your results of your assay validation. The Methods part describes how you were proceeding, but it would be great to see the resulting numbers for test sensitivity and selectivity. Any distributor-independent evidence for the key performance parameters of the EurImmune test would be highly welcome!

On 2020-09-07 11:05:36, user Raffaele Loffredo wrote:

Why not controlling for age distribution of cases (possibly of infected people)? In Italy and other countries the high mortality during the firs peak can be, at least partially, explained by the fact that the pandemic has been first and foremost an hospital-acquired infection. Consequently the pandemic during the firs peak has hurt the most vulnerable part of the population. This can explain the higher mortality and ICU occupacy rates during the first peak (also the harvesting effect can be at play).

On 2021-01-19 18:29:14, user Monika J. wrote:

As a Slovak citizen I can tell your that they are NOT telling the whole truth. Your can fact check my every single word.<br /> They claim that the testing was not obligatory... NOT TRUE<br /> People where forced to attend this mass testing. Prime minister admitted that they forced us to do this on the Press conference. Our Human rights where oppresed. Without negative test certificate your couldnt go to work, bank, post Office, all shops denied you to enter their premises. All services where denied to your without certificate. Even some doctors refused to treat patients without cerificate. You could only go to grocery store, pharmacy and drugstore without certificate. There were some exceptions, but not important. Some employers called the police on employees who wanted to go to work (they where healthy, had no symptoms) but didnt hlave the certificate. A lot of employees were fired, because they refused to get tested.

Lets talk about the study. They claim that they have participant conset.... NOT TRUE we havent sign anythig. Nobody informed people what kind of test they are using, who will hlave their samples afterwards, who will procesed their personal information..yes they hlave our personal numer and wrote some information from our ID....we dont know which information they collected.

Thay claim that tests where done ONLY by profesionals.. NOT TRUE. Tests where done by non medical personnel too - in some cities - those people braged about it on Facebook. There is NO name of person who tested you. You can not check if this person <br /> is profesionall or not.<br /> In some cities testing was done outside. People where forced to stand for multiple hours in lane just to get tested, in rain, and low tempersture...<br /> I could continue on and on and on....<br /> Now they are going to do the second round od this mass testing. They are again FORCING us to do it Once again. The second round is even worst than the first one. Now they want us to stand in lane to get tested in -10 to -15°C.<br /> Now the police will be controlling us if we have the certificate or not. If your will not have the certificate you will get a fine. And they will oppresed our human rights again. Segregstion od people to two categories is called apartheid and it is illegeal....this is what they are doing. They are creating second category people. First category Has certificate and Can live relatively normaly. Second category is treated like garbage.

On 2024-10-27 08:26:34, user Mohsen Ghanbari wrote:

This preprint has been published recently:

A comprehensive study of genetic regulation and disease associations of plasma circulatory microRNAs using population-level data.Genome Biology. 2024 Oc t 21;25(1):276. doi: 10.1186/s13059-024-03420-6.

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

Now published in Indian Journal of Ophthalmology

On 2020-05-18 23:17:11, user John N Wilson wrote:

Spencer, do you have a link to the Lupus data? I've been looking for it without much luck.

On 2021-01-26 15:10:16, user Hein De Waele wrote:

thanks, was the prophylactic use just the combo of Honey with Nigella Sativa or was there other drugs involved? Did you use for the prophylactic use the same dosage as in the treatment?

On 2021-08-18 19:05:43, user FABIO LIPIANI wrote:

Studies addressing immunosenescence in the immune system have expanded to focus on the innate as well as the adaptive responses. In particular, aging results in alterations in the function of Toll-like receptors (TLRs), the first described pattern recognition receptor family of the innate immune system. Recent studies have begun to elucidate the consequences of aging on TLR function in human cohorts and add to existing findings performed in animal models. In general, these studies show that human TLR function is impaired in the context of aging, and in addition there is evidence for inappropriate persistence of TLR activation in specific systems. These findings are consistent with an overarching theme of age-associated dysregulation of TLR signaling that likely contributes to the increased morbidity and mortality from infectious diseases found in geriatric patients.

On 2020-09-24 14:24:26, user Uri Goldsztejn wrote:

The source code is available on Github:<br /> https://github.com/uri-gold...

On 2020-06-13 07:13:04, user OxImmuno Literature Initiative wrote:

immunology.ox.ac.uk/covid-1...

On 2020-04-01 12:23:21, user Semper Explorans wrote:

Where is the exact methodology for the statistical model? What are the assumptions? What specific numbers and percentage rates for Ro, herd immunity are used? How is the data collected? While I do not doubt the exact gravity of the situation, and we must prepare for the worst, as both a doctor in the frontlines and as a researcher trained in evidence-based research, I need to establish whether a model is sound before I believe any of its conclusions. Incorrect data and/or incorrect assumptions or methodology leads to inaccurate numbers and conclusions.

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

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

On 2021-05-28 05:26:03, user Enzo wrote:

Other mistakes seem to weigh on the results and on the conclusions. Examples :<br /> In Figure 3, how could the mean length of stay in Niaee's control group be smaller than the one in ivermectin group, when Niaee finds a significant reduction of stay with IVM ?<br /> In Figure 2 (Mortality), how can RR for Chaccour be 1 when there's no event ? (Shouldn't it be "not calculatable" ?)<br /> In Figure 5, (severe adverse events), one is included despite Krolewiecki mentions the one reported "has not been reported in association to IVM"

On 2022-03-12 11:17:49, user Scott V. Nguyen, PhD wrote:

I am copying in the discussion from GitHub as the discussion is best here. Additionally, in GitHub, these comments are only visible to users who are signed in.

https://github.com/cov-line...

Thanks, in addition to the contributions from other folks here, I also want to point out an overlooked contribution that @corneliusroemer identified two recombination breakpoints which I think is wild!

According to this preprint, I guess these authors might not have discovered this potential recombinant independently?

I'll be more direct here. I don't think the authors of the preprint found it independently as the lead author is here in this thread (@PhilippeColson). What sits uneasily with me is that @Simon-LoriereLab and his colleagues checked the raw sequencing reads and kindly shared the raw fastq files publicly in GISAID over 3 weeks ago (~17 February, 2022). I did some digging and found that Santé Publique France and Institut Pasteur put out a statement on how they are monitoring it and how the EMERGEN consortium is working to characterize the recombinant: https://www.santepubliquefr... (publication dated 23/02/2022). I suspect @Simon-LoriereLab was the one who sent the alert to French efforts for increased surveillance of this recombinant.

This preprint has spread like wildfire through the news, such as this one from Reuters: https://www.reuters.com/bus...

This puts a chill in open ended efforts in public sequencing databases and open collaboration, especially as laboratories in Institut Pasteur put in the work to confirm the recombination. By rushing out a preprint to be "first" and using names like "Deltacron" or "Deltamicron", these unconventional names have stirred up a hornet's nest of conspiracy theories on social media. For example, I've seen claims that this validates the "Deltacron" from Cyprus that was the result of contamination or a conspiracy theory to detract attention from the current situation in Ukraine.

It isn't difficult to communicate any of this to any of the contributors here, especially since this is a public discussion. This highlights the fragility of trust in science and confidence from the public. By nature, I am not a confrontational person but this issue is worth pointing out. While this discourse is unrelated to what this repo is for (after all, we are here to identify and monitor any potential emerging lineages), I do think it is pertinent to discuss on what is done in a public forum.

The NY Times also discusses this issue: https://www.nytimes.com/202...

On 2020-03-31 10:25:53, user ortograf wrote:

difficult comparision of the control and treated groups at inclusion in the absence of PCR results.<br /> See <br /> https://annals.org/aim/full...<br /> for comments on influence of this parameter in the evolution of patients in a previously published study.

On 2020-03-30 22:23:50, user Sinai Immunol Review Project wrote:

Study Description

This is a randomized clinical trial of hydroxychloroquine (HCQ) efficacy in the treatment of COVID-19. From February 4 – February 28, 2020 142 COVID-19 positive patients were admitted to Renmin Hospital of Wuhan University. 62 patients met inclusion criteria and were enrolled in a double blind, randomized control trial, with 31 patients in each arm.

Inclusion criteria:<br /> 1. Age >= 18 years<br /> 2. Positive diagnosis COVID-19 by detection of SARS-CoV-2 by RT-PCR<br /> 3. Diagnosis of pneumonia on chest CT <br /> 4. Mild respiratory illness, defined by SaO2/SPO2 ratio > 93% or PaO2/FIO2 ratio > 300 mmHg in hospital room conditions (Note: relevant clinical references described below.)

a. Hypoxia is defined as an SpO2 of 85-94%; severe hypoxia < 85%. <br /> b. The PaO2/FIO2 (ratio of arterial oxygen tension to fraction of inspired oxygen) is used to classify the severity of acute respiratory distress syndrome (ARDS). Mild ARDS has a PaO2/FIO2 of 200-300 mmHg, moderate is 100-200, and severe < 100.

1. Willing to receive a random assignment to any designated treatment group; not participating in another study at the same time

Exclusion criteria: <br /> 1. Severe or critical respiratory illness (not explicitly defined, presumed to be respiratory function worse than outlined in inclusion criteria); or participation in trial does not meet patient’s maximum benefit or safe follow up criteria<br /> 2. Retinopathy or other retinal diseases<br /> 3. Conduction block or other arrhythmias<br /> 4. Severe liver disease, defined by Child-Pugh score >= C or AST > twice the upper limit<br /> 5. Pregnant or breastfeeding<br /> 6. Severe renal failure, defined by eGFR <= 30 mL/min/1.73m2, or on dialysis<br /> 7. Potential transfer to another hospital within 72h of enrollment<br /> 8. Received any trial treatment for COVID-19 within 30 days before the current study

All patients received the standard of care: oxygen therapy, antiviral agents, antibacterial agents, and immunoglobulin, with or without corticosteroids. Patients in the HCQ treatment group received additional oral HCQ 400 mg/day, given as 200 mg 2x/day. HCQ was administered from days 1-5 of the trial. The primary endpoint was 5 days post enrollment or a severe adverse reaction to HCQ. The primary outcome evaluated was time to clinical recovery (TTCR), defined as return to normal body temperature and cough cessation for > 72h. Chest CT were imaged on days 0 and 6 of the trial for both groups; body temperature and patient reports of cough were collected 3x/day from day 0 – 6. The mean age and sex distribution between the HCQ and control arms were comparable.

Findings

There were 2 patients showing mild secondary effects of HCQ treatment. More importantly, while 4 patients in the control group progressed to severe disease, none progressed in the treatment group.<br /> TTCR was significantly decreased in the HCQ treatment arm; recovery from fever was shortened by one day (3.2 days control vs. 2.2 days HCQ, p = 0.0008); time to cessation of cough was similarly reduced (3.1 days control vs. 2.0 days HCQ, p = 0.0016).<br /> Overall, it appears that HCQ treatment of patients with mild COVID-19 has a modest effect on clinical recovery (symptom relief on average 1 day earlier) but may be more potent in reducing the progression from mild to severe disease.

Study Limitations

This study is limited in its inclusion of only patients with mild disease, and exclusion of those on any treatment other than the standard of care. It would also have been important to include the laboratory values of positive RT-PCR detection of SARS-CoV-2 to compare the baseline and evolution of the patients’ viral load.

Significance

Despite its limitations, the study design has good rigor as a double blind RCT and consistent symptom checks on each day of the trail. Now that the FDA has approved HCQ for treatment of COVID-19 in the USA, this study supports the efficacy of HCQ use early in treatment of patients showing mild symptoms, to improve time to clinical recovery, and possibly reduce disease progression. However, most of the current applications of HCQ have been in patients with severe disease and for compassionate use, which are out of the scope of the findings presented in this trial. Several additional clinical trials to examine hydroxychloroquine are now undergoing; their results will be critical to further validate these findings.

Reviewed by Rachel Levantovsky as a part of a project by students, postdocs and faculty in the Immunology Institute at the Icahn school of Medicine at Mount Sinai.