On 2021-01-15 12:19:29, user Kit Byatt wrote:

Given that:<br /> 1. Excess mortality for a year can't be known for several weeks into the following year <br /> 2. Especially in a year with Christmas & New Year's Day on Fridays, and a pandemic impeding the bureaucracy of collecting & collating mortality data - particularly in cases where the Coroner [or equivalent] is involved)<br /> 3. Different countries have exhibited different patterns (or none) of winter excess mortality peaks (as shown in Figure 1c)

a) Is it not premature to undertake a comparison before all the data are in (or alternatively, at least title as 'Preliminary observations on...'?

b) Might not the association end up significantly higher, the same, or lower, then?

On 2020-07-15 14:57:36, user Rhyothemis wrote:

The PDF 'heat map' figure is illegible.

On 2021-12-06 23:20:21, user rick wrote:

When one person chooses to get a shot and the other doesn't, it's not an "inequity." It's a different decision.

On 2021-08-27 13:14:22, user Ash Guirgues wrote:

To which journals is this article being submitted

On 2021-09-08 03:11:32, user TBonePickenz wrote:

Too much discussion for something that has ***not been peer reviewed*** <br /> Also bear in mind this is a retrospective study.<br /> The gist is vaccines < natural immunity < natural immunity + vaccine. It is unclear if the 3rd option is statistically significant in my read.

In the first part of the discussion, they say "Individuals who were previously infected with SARS-CoV-2 seem to gain additional protection from a subsequent single-dose vaccine regimen. Though this finding corresponds to previous reports, we could not demonstrate significance in our cohort." However, in the final paragraph of the discussion they say, "Notably, individuals who were previously infected with SARS-CoV-2 and given a single dose of the BNT162b2 vaccine gained additional protection against the Delta variant." <br /> This needs to be clarified in the peer review process.

What it does do (in the US which is swimming in unused vaccines) is open up the question of the necessity of vaccine mandates in those who have already had a natural infection.

• a vaccinated doctor

On 2021-08-30 22:42:54, user Chris Curry wrote:

You would think this would be common knowledge seeing as all a vaccine does is simulate a person getting infected in order to force their body into building immunity to the virus. If natural immunity wasn't a thing then vaccination wouldn't be a thing either, but for some reason the country has decided that you have to be either "pro vaccine" or "anti-vaccine" without entertaining any sort of nuance.

On 2021-09-10 08:00:24, user Jim Ayers wrote:

I tried to search this page for the word placebo and couldn't find it. Already this is blowing up on the internet.

On 2022-03-22 12:17:46, user panos101 wrote:

What's the status of this article. Has it been published?

On 2024-12-03 10:06:13, user Ssekitoleko Twaha wrote:

Wonderful! This is a good study, it shows Mbarara has the majority of the victims which calls for further studies "Why Mbarara?"

On 2021-06-05 15:33:22, user Scandinavian Journal wrote:

Imo the twelve (13·5%) patients that had comorbidities associated with risk for severe disease [17] made a courageous contribution by accepting the possibility of ending up receiving placebo in the trial.

On 2021-06-07 14:51:21, user Stephen Smith wrote:

No, that's not what happened. <br /> First, the cumulative was not, for most pts, a measure of length of stay or determined by death. The most commonly used cumulative dose of HCQ = 2,400 mg. This dose/regimen was recommended, as noted in the paper by Yao et al., based upon computer modeling. The 2,400 mg dose was given over 5 days, 800 mg on Day and 400 mg on Days 2-5. The treating or consulting ID physician chose the cumulative dose. <br /> In late March, the French data came out and some switched to the French regimen, 600 mg of HCQ x 10 days plus azithromycin x 5 days. Most pts received the 800 mg first day dose, which was started by the ER docs and was a click in the computer ordering system. The ID docs saw the pt the next morning. Many continued the pt on 400 mg per day for 4 more days. Others switched to 600 mg per day. So, by Day 5 on the latter regimen, the cumulative HCQ dose = 3,200 mg or > 3 gm or the cut-off used in our paper. In other words, it took just as long to get to > 3 gm and as it took to get to 2,400 mg.

In a simplistic way to control for length of stay (LOS), we analyzed the effect of >3gHCQ/ >1gAZM on outcome after removing those patients, who had a LOS <= 5 days. All 49 patients with a LOS <= 5 days expired; none took > 3,000 mg HCQ and > 1,000 mg AZM. <br /> The 169 remaining patients serve as the "untreated" group and had a survival rate = 21.3%. The >3gHCQ />1gAZM group’s survival rate = 48.6%. This difference = 27.3%, which is still large and highly statistically significant (difference = 27.3%; 95% C.I. = 10.1-43.7%; p = 0.0006). <br /> In other words, even after eliminating all patients who had a LOS <= 5 days from the “untreated” group, the survival rate of the HCQ/AZM was more than 2.2-fold that of the "untreated" group. BTW, this type of analysis is heavily biased against showing a difference between treatment with HCQ, because the treatment may have an effect before Day 5. <br /> Remember, most of the "untreated" group did receive HCQ, just <= 3 gm.

In other words, cumulative dose of HCQ was not a marker of survival. The cumulative HCQ dose was determined by the ID doctor seeing the pt. Different ID doctors interpreted the available data on HCQ differently. Essentially, they chose between the 2,400 mg without AZM or the 6,000 mg total HCQ dose with AZM or no HCQ at all. A few ID doctors split the middle and used ~3 gm of HCQ with AZM.

Many ID doctors did not use AZM with HCQ for fear or concern about prolonging the QTc interval on the ECG. We, instead, followed the QTc interval closely.

Weight-based HCQ cumulative dose was more strongly associated with survival and absolute cumulative dose. This fact essentially rules out HCQ cumulative dose being a marker of survival as well.<br /> Lighter pts reached a weight-based cumulative HCQ dose well before heavier pts. If a pt weighed 50% of another pt, it took 50% of the days to reach a given weight-based HCQ cumulative dose. <br /> These pts typically received 800 mg HCQ on Day 1 and then 600 mg per day.<br /> A 60 kg pt reached 40 mg/kg by Day 4, while a 120 kg pt, didn't reach 40 mg/kg until Day 8.

SMS

On 2021-06-11 05:23:39, user Sock Dollager wrote:

Did I read correctly that the patients in your observational study were not given Zinc?

My understanding is that while AZM was discovered to have some unsuspected anti-viral properties, it was in combination with Zinc, with the Hydroxychloroquine acting as a Zinc ionophor that has had the best results.

You mention the French doctor Raoult, I presume it’s this one?

https://duckduckgo.com/?q=d...

Between his work and the pioneering Dr. Vladimir Zelenko and all these studies at<br /> https://c19study.com and this one at American Journal of Medicine https://www.amjmed.com/arti... and now your study, let’s hope more and more physicians will prescribe the Hydroxychloroquine Protocol (Hydroxychloroquine plus azithromycin [or doxycycline] plus zinc) promptly for their infected patients.

On 2020-04-22 17:23:10, user Dr-Artaud wrote:

Nice Try, the Study isn't for Herd Immunity, the study shows that the infection is much more prevalent that previously believed, and the additional knowledge of those infected permits the Case Fatality Rates to be realistically calculated.

On the issue of Herd Immunity, though, why does Bill Gates want 7 Billion Vaccines to occur to wipe out the virus when the SARS went away in May of it's outbreak in China, the Bird flu went away, and the seasonal flu goes away. As you clearly understand, after a specific percentage of a population is vaccinated, the ability of the virus to be conveyed to others decreases, eventually stopping the virus entirely. So why 7 Billion Vaccines. I think Bill Gates tipped his poker hand a little too far this time.

On 2020-04-18 04:24:55, user Vasyl Zhabotynsky wrote:

The conclusion seems to heavily rely on the fact that specificity is really 99.5%<br /> If specificity is 98.5% (which is still in the confidence interval for the estimate of specificity), one would expect to get 50 positive tests from 3330 tests (as stated in second paragraph of page 7) in a completely disease free population.

On 2020-04-28 19:35:41, user outdoorgirl0814 wrote:

What I mean by "pooled" is that of the 3330 patients included in the study, they counted 50 tests in which either IgG, IgM or both IgG and IgM were positive. However, they could have stated how many of the 50 positive tests were IgM, IgG or both. That would be important information. So, you're right "pooled" is the wrong term-it was how they scored the tests. But the end result is still pooling IgM and IgG positives. And the IgM specificity was not omitted; it was discussed in the paper. I am not sure why 2 people downvoted my question, which is just plain odd. It wasn't even a criticism or political or really anything other than a simple question about why those data were omitted. What is going on here?

On 2020-04-17 23:54:51, user David Hasenford wrote:

A lot of misguided comments here. 2.49% to 4.16% population prevalence is not "herd immunity"

On 2023-12-15 14:30:33, user Crambert wrote:

GDF15 has also a proliferative effect on renal cells in response to K restriction and acidosis via ErbB2 activation:See Acta Physiol (Oxf). 2023 Oct;239(2):e14046. doi: 10.1111/apha.14046 and Acta Physiol (Oxf). 2021 Jul;232(3):e13661. doi: 10.1111/apha.13661

On 2021-11-16 11:57:33, user disqus_aUdf6iYESf wrote:

This is an interesting study, and not an easy one to do. I congratulate the authors on their work.

I agree with the authors that the study is hypothesis generating.

A few questions/comments:

1) The authors describe no delay as being "score >2 SDs above the population mean". If no delay is the inverse of delay, I think this should be "a score higher than the cutoff for delay of 2 SD below population mean." A score >2 SD above population mean would include a very small proportion of children (about 2.5% in the population) of developmentally advanced children.

2) As the authors note, using a questionnaire (Age and Stages) by phone is not ideal for evaluation, and responses could be biased by parental knowledge of maternal SARS-CoV-2 infection.

3) The numbers with infection in the first trimester are small (only 5 children), but 4/5 (80%) had developmental delays, as compared to 6/20 in second trimester (30%), and 20/273 with infection in third trimester (7.3%). Those are striking differences, with a "dose-response" type pattern by trimester, but the numbers are small, so this study would need to be replicated by other groups, ideally with testing with the Bayley scales or other administered instrument.

4) A control group without SARS-CoV-2 infection would be important as an additional comparison group, and was not present. This would give a sense of whether in the population who responded and were assessed by phone questionnaire, the rate of developmental delay (score < mean - 2SD) was similar to that expected in the general population.

For all of these reasons, I think further studies are required to definitively state that maternal SARS-CoV-2 infection in the first or second trimester is associated with developmental delay, but this study provides preliminary data that this might be the case. It appears other studies in progress propose to prospectively address this question (e.g., PROUDEST study in Brazil), and such studies are required for a more definite answer as to whether SARS-CoV-2 infection early in pregnancy affects child neurodevelopment outcomes.

On 2020-08-21 19:06:14, user Heather Gray wrote:

I'm a layman but I want to express my appreciation for exploring the issue from this angle

On 2020-06-20 22:42:57, user many wrote:

Within the boundary of assumptions, the paper is mathematically accurate. I have a list of technical questions, which if addressed could make the paper noteworthy. See here: https://publons.com/publon/...

On 2020-03-26 00:03:02, user Your college professor wrote:

Some people suggest that the fact that COVID-19 binds to ACE2 receptors means there's a fertility risk involved, but we've had ACE2 binding corona viruses like HCoV-NL63 circulating for centuries and as far as I am aware nobody has ever observed any such harm from them.

We also have an autopsy of SARS fatalities, where no viral material was discovered in testicular tissues.

There's an argument to be made that the authors used an improper control group, as their control group apparently excludes men with fertility problems. The authors write:

The control group came from the population who previously received reproductive function evaluation and were classified as having normal fertility

In other words, rather than a normal distribution of the population, they're inevitably excluding a portion of subfertile men from their control group. One of the main symptoms commonly seen in subfertile men is the elevated LH levels they observed in COVID19 patients.

However, there is another problem that is more relevant than the above shortcomings. Luteinizing hormone is secreted in pulses, in a diurnal pattern. In contrast, FSH, which has no clean diurnal pattern, is not statistically significantly different between their control group and their COVID19 survivors.

What this diurnal LH pattern means is that you want to make sure that your control group is tested at the same time of day as your experimental group (ie COVID19 survivors). This explains for example why comparing different studies done on male fertility will lead to widely varying average levels of LH in different groups of subjects. The control group being measured at a different time of the day compared to the experimental group would also explain the prolactin differences seen in this particular study.

Unfortunately, the authors of this study don't mention when the control group had their values measured and when the survivors had their values measured. As a consequence, you can't consider this a proper control group, which means their results provide no evidence for their suggestion that COVID19 might cause fertility damage. Similarly, the 75th percentile they report for LH is not abnormally high, which would have been indicative of potential fertility problems.

Based on these problems, I don't see how this study would survive peer review.

On 2020-03-29 19:06:26, user MingXia Gao wrote:

Fever also can cause damage to the sperm, leading to a high LH. Most of your objects had a fever, so I don't think the increase of LH is because of COV-19. You should test the tissue or seminal fluid to make sure whether there are COV-19 exist in male reproductive organs.

On 2021-07-07 22:42:55, user Leo G. wrote:

That confirms that mass vaccination with spike-only antigen streamlines the coronavirus evolution.

On 2022-01-18 19:12:04, user Charles R. Twardy wrote:

This July 14 upload appears to be an inadvertent duplicate of the 8 June upload that links to the eventual publication in *Cancer*. (HTT LTran for noticing.)

Cancer pub doi: 10.1002/cncr.33130.

On 2021-08-09 18:06:43, user MJ wrote:

".....assuming that baseline mitigation measures of simple ventilation and handwashing reduce the second+ary attack rate by 40%".

Congress gave billions of dollars to upgrade schools, to properly fit them with the necessary equipment for proper ventilation/air purification. Schools have had a year to do it, yet it hasn't been done. Schools are going to be reopened in the next few weeks without proper mitigation strategies for airflow.. Schools will be a breeding ground for this virus, even scarier now that the transmission rate is triple what it was a year ago. Speaking as someone who was infected via classroom exposure, and still suffering effects from the virus, more needs to be done to protect and reduce the risk to the children and staff

On 2023-03-10 18:13:37, user Kirsten Wiens wrote:

This manuscript has now been published online at Lancet Microbe: https://doi.org/10.1016/S26...

On 2021-10-26 17:10:43, user Stephane wrote:

Could you please explain why the effectiveness is lower between fully vaccinated people ? "Effectiveness of full vaccination of the index against transmission to fully vaccinated household contacts was 40%"

On 2021-08-02 01:30:17, user Carter Clough wrote:

What was the date or time frame of this study? Was this prior Delta?

On 2021-06-22 21:23:31, user Jewbacca wrote:

FWIW, this was Israeli policy when we rolled out vaccines -- no vaccination for those previously infected and recovered --- as it was deemed both not needed and those that recovered from COVID were at somewhat higher risk of complications from the shot, such that the risk of side effects outweighed the risk of severe illness.

Glad you guys can catch up.

On 2021-08-04 07:40:19, user Philippe Meisburger wrote:

Question : should this finding be proven true, would it imply that someone who's got vaccinated (2 doses) before he/she ever got Covid 19 will benefit from the same level of protection convalescents have once they'll successfully fight a potential breakthrough infection ?

On 2021-06-30 13:51:55, user Adam Mercy wrote:

It is reassuring to some, but borderline insanity to others that we have to prove we have an immune system. We knew early in 2020, that prior T cell immunity was present in probably 50%+ of the population, from prior coronaviruses from as far back as 15y (or longer).

Covid likely is a patient-specific immune hypersensitivity. Some say MCAS, it may turn out to be. If that is the case, vaccines or not, those patients need drugs -- which implies drug therapies are the only way out.

And yet, the conclusion to this piece is about prioritizing vaccines. Scientists take a look at data from nation states like Mexico. Not small trials, massive interventions at scale. Or India. You are making a blunder which will meme''d about till the end of time. See our twitter on how to save your reputations.

On 2021-05-28 18:07:40, user Craig Austin wrote:

Nobody wears masks properly, except professional staff in a clinical setting , nobody. Viruses didn't change sizes, mask' s pore size didn't change only human behavior changed.

On 2021-03-03 18:20:01, user LabMonkey wrote:

Eager to see the temporal distribution of some of these variants - any clue as to when they'll be visible in GISAID?

On 2021-03-04 14:34:51, user Paul McKeigue wrote:

Now published in BMC Medicine:

https://bmcmedicine.biomedc...

On 2020-06-29 13:45:28, user Algur wrote:

Is there a timeline when this will be peer-reviewed?

On 2021-02-23 12:35:42, user Marek J wrote:

Great. We need more trials like this. There is huge potential: https://www.medrxiv.org/con...

On 2020-03-21 19:23:25, user KnowItAll wrote:

For figure 1c, it would be useful to include the number of genomes sampled from each country. The figure makes it seem like there are large differences in the distribution of viruses between countries, but there is only 1 sequence from Sweden, 5 from Italy, 9 from south Korea, vs 25 from the US.

On 2020-12-13 04:57:43, user Haitham kussaibi wrote:

Dear valuable readers,

The current manuscript has been peer reviewed and published by <br /> Karger, Acta cytologica<br /> DOI:10.1159/000509669<br /> Thank you for your interest.<br /> The Authors

On 2021-05-14 01:56:12, user J.A. wrote:

In reviewing Tom Argoaic comment, I looked at the public dataset. In the dataset, the days from exposure to starting study drug or placebo are listed as 1 to 6 days. In the preprint tables 1 and 2, there are none listed for 1 day and 28 people listed for 7 days. It seems very clear that the authors of the preprint have altered the data. There is nothing in the methods explains that the data were altered. It looks like the authors chose to inflate the delay from exposure to starting medicine by +1 days for everyone. As this time from exposure to starting the study medicine is the primary focus of the preprint, this should be clear to readers and should be correct. Furthermore, not altering the data would seem to yield the same statistical analysis, yet have the benefit of being correct. This should be corrected.

Second, the authors should consider making a figure to visually show what the authors are trying to present. While there are many tables, visually showing the percentage with COVID-19 by day 1-6 would be a better way to present the data, with the mean +/- 95 confidence interval for the estimate.

Third, the authors should discuss why the placebo event rate varies over time. The placebo event rate is 10%, 15%, 19%, 12%, 13%, and 0% over the day 1-6, is there a biological reason for this variation or this random variation? The day 3 group has the highest event rate (18.9%), which then makes the statistical difference. Is this an artifact or is there biological plausibility for why taking placebo on day 2 or 4 is much better than day 3. Perhaps add this to the discussion to explain why this is not all just a post-hoc artifact of small subgroups.

On 2021-03-09 21:18:20, user Antonio Beltrão Schütz wrote:

In this meta-analisis, the I2 is very rise to be accept and CI to recovery time is, also, very big to be accept. Therefore, the results of this meta-analisis are not confiable. Is possible that personal interpretation of Grade parameters has contribute to increase I2

On 2023-02-07 08:39:11, user Frauke Mattner wrote:

Hi, congratulation to your very informative preprint. I am just looking for a figure comparing vaccinated with non-vaccinated persons. Could you still add it? You defined vaccination as at least one shot obtained. Could you also provide data for thoses being at least two-fold or triple-fold vaccinated ?

On 2020-04-23 13:10:03, user ABO FAN wrote:

The overwhelming majority of Japanese people who are positive for COVID-19 are seniors in their 60s or older (easily infected). On the other hand, many foreigners are in their 20s to 40s (not easily infected). Cruise ship passengers are mainly senior Japanese and foreign families. When you correct for age, the number of Japanese positives is overwhelmingly low.<br /> Now it is statistically clear that BCG is effective.<br /> Since the original data from the Japanese Ministry of Health, Labour and Welfare provide only the number of positive individuals, the age structure of all passengers, including non-infected ones, is unknown. I suspect that an opponent wrote this paper in bad faith even if he knows the truth. https://uploads.disquscdn.c...

On 2020-03-25 22:43:03, user Sinai Immunol Review Project wrote:

Title: A serological assay to detect SARS-Cov-2 seroconversion in humans

Immunology keywords: specific serological assay - ELISA - seroconversion - antibody titers

Note: the authors of this review work in the same institution as the authors of the study<br /> Main findings: <br /> Production of recombinant whole Spike (S) protein and the smaller Receptor Binding Domain (RBD) based on the sequence of Wuhan-Hu-1 SARS-CoV-2 isolate. The S protein was modified to allow trimerization and increase stability. The authors compared the antibody reactivity of 59 banked human serum samples (non-exposed) and 3 serum samples from confirmed SARS-CoV-2 infected patients. All Covid-19 patient sera reacted to the S protein and RBD domain compared to the control sera.<br /> The authors also characterized the antibody isotypes from the Covid-19 patients, and observed stronger IgG3 response than IgG1. IgM and IgA responses were also prevalent.

Limitations of the study:The authors analyzed a total of 59 control human serum samples, and samples from only three different patients to test for reactivity against the RBD domain and full-length spike protein. It will be important to follow up with a larger number of patient samples to confirm the data obtained. Future studies will be required to assess how long after infection this assay allow to detect anti-CoV2 antibodies. Finally, while likely, the association of seroconversion with protective immunity against SARS-Cov-2 infection still needs to be fully established.

Relevance: <br /> This study has strong implications in the research against SARS-Cov-2. First, it is now possible to perform serosurveys and determine who has been infected, allowing a more accurate estimate of infection prevalence and death rate. Second, if it is confirmed that re-infection does not happen (or is rare), this assay can be used as a tool to screen healthcare workers and prioritize immune ones to work with infected patients. Third, potential convalescent plasma donors can now be screened to help treating currently infected patient. Finally, the recombinant proteins described in this study represent new tools that can be used for further applications, including vaccine development.

Review part of a project by students, postdocs and faculty at the Immunology Institut of the Icahn School of Medicine, Mount Sinai.

On 2020-05-29 08:49:02, user David Cadrecha wrote:

Similar study in Spain shows a 20% reduction in the number of deaths per day social distancing started earlier.

Looking at different countries and regions, a strong correlation between late intervention and number of fatalities is found.

It should work for any country and tells that every single day of anticipation reduces deaths by roughly 20-25% (in the absence of other preventive actions)

“LA PRÓXIMA VEZ DEBEMOS ACTUAR ANTES. Impacto de la precocidad de las intervenciones por Covid-19”

https://t.co/TWfpDklLfo

On 2021-12-29 00:53:32, user madmathemagician wrote:

The world (cfr. twitter references above) cites this article as evidence that "analysis concludes that, as a general tendency, the more a country vaccinates the less reliable the data it shares".

A conclusion not supported by its flawed analysis, used for political propaganda.

On 2022-01-20 17:38:31, user Saar Wilf wrote:

Thank you for this detailed response.

I would like to clarify I didn't intend to question your credentials. This is high quality work. I just believe there is a better explanation for the data than the one you propose. I of course may be wrong.

Allow me to explain what I meant by the hospitalizations pattern: I'm not denying there is a large effect that is very statistically significant. However, all of the effect and significance stem from a single drop on the day of PCR+. After that day, there is no further change between the groups.<br /> It is biologically implausible for a vaccine to have an effect on hospitalizations that occurs only on the day of diagnosis.<br /> However, it is a strong indication that there is some confounder, such as how the decision to hospitalize is taken.

If indeed that day is the day of swabbing, then it means the patient was hospitalized prior to the PCR result. They are therefore likely to have been hospitalized for a reason other than COVID, and tested upon admission. And that means the effect is not related to the vaccine, explaining why there is no difference in hospitalizations later on.

It is an interesting challenge to figure out what that confounder is, but before addressing that and other issues - Do you agree with this analysis? If not, why do you think all the hospitalization difference occurs on one day?

On 2020-07-03 18:28:19, user Mark Pollington wrote:

Heterogeneous is clearly an important factor in determining herd immunity. However, in the developed counties discussed in this paper surely this will have been masked by the introduction of various non-pharmaceutical interventions.<br /> I was therefore fascinated to see how this problem could be tackled.

However, the equations outlining susceptibility do not appear to have been followed up to fit the parameters to data. Indeed, the discussion simply alludes to the authors fitting CVs which are an order of magnitude less than the susceptibility values used in the main paper!

Given the lack of evidence, then, why are arbitrarily susceptibility factors as high as 4 used? Why publish graphs which are so far removed from reasonable expectations? Unless politically motivated?

Clearly further research needs to be done to establish reasonable susceptibility factors, but I can't see any effective proposals in the paper. Computationaly intensive data fitting exercises with the inherent uncertainties in the data are certainly not the way to go!

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

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

On 2020-06-19 18:24:34, user ChrisdeZilcho wrote:

Apparently a new study from same team shows CoV2-positive samples from savage water stored in Dec last year. Would be interesting to see the phylogenetic sequence analysis. Did virus fizzle out in Dec/Jan or was there a "quiet" transmission activity? Have there been many independent intros into Italy? Looking forward to reading the publication.

On 2020-05-07 02:38:21, user Variant wrote:

In most cases, peak deaths and infections preceded the point at which any SAHO orders could have had impact. In fact, virus "curves" are nearly identical between states where there have been significant movement restrictions and those that haven't.

On 2022-01-23 21:56:36, user maa jdl wrote:

There is another published paper on this topic:<br /> https://journals.sagepub.co...<br /> The discussion is a bit deeper.<br /> But the conclusion is similarly naïve and wrong.<br /> This other paper also assumes the Benford law is a kind of data validation.<br /> Which it is not.<br /> And this paper -of course- conclude "germany did well", while actually this is pure chance!<br /> And also that Iran did the worst! Which is an obvious consequence of the lack of testing capacity. With this loaw capacity, the number of cases varies of less than two decades! Which makes it very improbable to "comply" with the Benford's law.<br /> The goodness of fit to the Benford law for the cases just represents the history of the epidemic in a country as well as the testing which are prformed.<br /> As I said previously, a simple picture of the data can explain why the Benford law is well or not well satisfied. There is even no need for a statistical test! It is obvious, we just need to make a good picture of the data and open our eyes!<br /> Unfortunately, there is no way to insert a picture here.

On 2025-12-04 16:45:16, user Richard wrote:

Does the data factor in the positioning of the formaldehyde sensors in relation to the dissection bench?

On 2020-09-13 17:03:48, user kdrl nakle wrote:

If you are comparing two groups without control group then you cannot say that both groups have improved outcomes. You can only compare the two. By the way, both samples are rather small, in particular the sample with Tocilizumab.

On 2020-10-28 19:15:20, user Dhurgham al-karawi wrote:

This paper is been published at World Academy of Science, Engineering and Technology<br /> International Journal of Computer and Information Engineering<br /> Vol:14, No:10, 2020 with new title ( Artificial Intelligence-Based Chest X-Ray Test of COVID-19 Patients )

On 2022-01-17 11:18:12, user Free Man in London wrote:

This is another Coke vs. Pepsi paper. There are only 2 conditions in this paper: vaccinated vs. unvaccinated. There are multiple conditions: vaccinated with supplements, unvaccinated with supplements Vitamin D, Quercetin, Melatonin, unvaccinated with supplements quercetin and zinc, etc. The paper prima facie is interesting but devoid of an answer to the real underlying question: are supplements more effective than the vaccines? Moderna and pfizer are more interested in keeping the question framed around simply 2 conditions. Until we force a re-framing to the way this effectiveness question is answered, we are not really solving the problem of stopping the virus. That said, omicron seems to be doing that quite well on its own.

On 2020-04-25 15:03:10, user David Ian Walker wrote:

You detected virus at 100 fold lower levels in treated effluent than in untreated influent. However, you do not specify what type of treatment the wastewater was subject to. This is important to know. Even if we could just have an idea of whether it was secondary or tertiary etc, that would be useful, but ideally a little more detail such as the type of treatment processes that are used at the Parisian WWTPs would be very helpful.

On 2020-05-20 17:22:05, user Omari wrote:

Anybody know the false positive rate of the test used?

On 2020-10-05 02:17:51, user Kiran Bhaganagar wrote:

I would like to bring to your attention a recent peer reviewed work in Environmental Research Journal on outdoor transmission, which will be very relevant to your work.

https://www.ksat.com/news/l...

On 2021-04-27 05:35:58, user SSS wrote:

Ok so there are at least 100 articles showing vaccines cause thrombosis. you can start by looking at the references in this article. youre welcome. https://www.ncbi.nlm.nih.go...

On 2021-05-16 20:45:44, user vinu arumugham wrote:

Vaccine content can vary widely. So to understand the relevance of your observed effects, we need to know where the studied product characteristics fall compared to the entire space of product characteristics.<br /> https://www.regulations.gov...<br /> www.sciencedirect.com/scien...

Further, T cells induced by injected vaccines home to the skin. T cells induced by natural infection, home to the lungs.

On 2020-10-26 13:59:51, user Chen Yanover wrote:

This preprint has been published in JMIR Public Health Surveillance here.

On 2025-07-30 10:53:20, user Esther van Kleef wrote:

This preprint has been accepted for publication in Eurosurveillance and is awaiting final editing.

On 2020-04-01 16:36:48, user japhetk wrote:

The study seems interesting.

However, the problems of this study's analyses, are as mentioned in the comments, <br /> they are not controlling when the infection spread in the country.

Other analyses are controlling that (for example, number of patients (or

deaths) 10 days after the 100th patients were detected, was used as a dependent measure).

Also, probably, the most accurate available BCG measure is "how long the country has advanced the BCG vaccination measure" (the year when the country stopped the BCG vaccination (or now, when the BCG vaccination is currently conducted in the country) - the <br /> year when the country started it). The current measure is not indicative as authors indicated.

I controlled these measures and have done the analyses.

The results were as follows.<br /> The partial correlation between "how long the country has advanced the BCG vaccination measure" and number of patients in the 10th day (when 1st day is 100th patients were detected in the country) after controlling the population of the country. P = 0.455, partial correlation coefficient = -0.116

The partial correlation between "how long the country has advanced the BCG vaccination measure" and number of deaths in the 10th day (when 1st day is the 100th patients were <br /> detected in the country) after controlling the population of the country. P = 0.111, partial correlation coefficient = -0.243

But the partial correlation between "how long the country has advanced the BCG vaccination measure" and when the 100th patients were detected in the country after controlling the population of the country was P = 0.078, partial correlation coefficient = 0.281.

Also "how long the country has advanced the BCG vaccination measure" is <br /> robustly and negatively correlated with GDP of the country after controlling the population of the country (p = 0.019, partial correlation coefficient: -0.292).

Also "how long the country has advanced the BCG vaccination measure" is robustly and negatively correlated with how fast the 100th patients were detected in the country (p = 0.078, partial correlation coefficient: 0.281).

But the correlation between GDP of the country and when the 100th patients were detected in the country after controlling population of the country was more robust (P = 0.001, partial correlation coefficient = -0.438).

And the correlation between "how long the country has advanced the BCG vaccination measure" and when the 100th patients were detected in the country disappeared when the population and GDP is also controlled (p = 0.322).

The partial correlation between "how long the country has advanced the BCG vaccination measure" and number of deaths in the 10th day after controlling the population and GDP of the country was P = 0.178, partial correlation coefficient = -0.210.

So, my guess is probably, there are number of spurious correlations happening in authors' analyses due to lack of important control variables, even if there are real correlations, they apparently should not be that strong (studies of the BCG's universal effects have not <br /> indicated such things either).

In Korea, China, Japan (diamond princess), the virus infected a lot of people in some regions or situations, too.

The countries of higher GDP can do more tests, they are more popular to the tourists from Asia, but they were perhaps less inclined to use masks, they were confident of their medical system and less alert. And those are the countries where BCG was "no longer necessary".

Remember one month ago, the coronavirus is an infectious disease of Asian people. Now it is an infectious disease of Western countries, who knows if it is not the disease of developing countries in the next few months.

On 2020-05-01 22:02:21, user CoffeeGeekmn wrote:

I'm just your average layperson looking for more info on the BioMedomics test and came across this study. I just had the BioMedomics test and the results showed IgG & IgM antibodies - the only covid symptoms I had were complete loss of taste and smell with no associated cold or other illness (this was back in December!). I live in Minnesota. Now everything I am reading says don't trust any of these test results. It's so confusing. Any thoughts on my test results showing both antibodies? Can I trust these or is it more likely a false positive?

On 2025-03-27 14:39:57, user DrZafar IqbalPhD wrote:

The peer-reviewed version of this article is available at https://www.jptcp.com/index.php/jptcp/article/view/7959 .

On 2021-08-13 02:51:57, user Zachary Hadden wrote:

This makes a lot of sense as my post covid experience since last December, recovery has been slow. I coded in ICU, brought back and recovered in 14 days where they started me at 70 liters of Oxygen for 4 days and had a gradual reduction down to 1 liter when I was discharged. No cardiac issues after stress test and echocardiogram. Pulmonary breathing performance tests show I have the lungs of someone that’s been smoking all my life. I’ve never smoked. CT scan shows the lower right lobe is collapsed, but I’ve been told this should not cause my shortness of breath issues. I feel like I have a more constricted airway than pre-covid. My pulmonologist is a joke. I’ve only had one video conference call with him and have had to get these tests scheduled on my own…. even the pulmonary test. I’ve still not had a follow up call since April. There aren’t any more pulmonologist available in my area. I guess if there is any consolation with this study, patients are improving.

On 2020-11-23 20:10:20, user TheMeerkat wrote:

To me the graphs in the pdf look like random distribution. I have no clue how anyone could decide that there is any correlation between values on two axes unless they decided it would be there before starting this research.

On 2022-01-16 20:08:17, user Daniel Halperin wrote:

Although the raw data from this study might suggest that vaccination offers little protection against risk of hospitalization from Omicron, the adjusted risk analysis is more hopeful. Examining cases from all clinical settings, the impact of vaccines against Omicron still looks weak, yet when restricting the analysis to cases from outpatient settings (which represented the vast majority of cases), the effect of full mRNA vaccination (2 doses) appears to be about a 65 percent reduction in risk of hospitalization, after adjustment. (Compared to about an 85 percent reduction against Delta.) However, there does not appear to be any difference in risk for people having received 2 versus 3 doses (against either Omicron or Delta), which would seem notable given the current policy focus to address the Omicron surge through administering and promoting booster shots?

On 2024-10-16 04:19:43, user CDSL JHSPH wrote:

I found this article very informative, I very much liked the introduction piece. I do have some hiccups in regards to the methods and some of the displaying of the results. I feel as through the explanation for the methods could use some work. When I read it I felt slightly overwhelmed because of the information. The same could be said of the results. I feel as though the results section did not explain the content well enough to where I was able to completely tell results from the presented figures. I think this issue could be solved by adding more explanations into the introduction or possibly adding more to the figures' subtext. Overall, I very much enjoyed the article and found the subject matter very exciting.

On 2024-10-15 23:16:55, user CDSL JHSPH wrote:

Thank you for sharing your exciting research. Tuberculosis is a serious infectious disease that imposes a heavy burden on the world. Prolonged treatment duration increases adverse drug reactions and reduces patient compliance, which is one of the most challenging aspects of TB drug treatment. Traditional methods have many shortcomings and limitations, so finding new methods that can accurately predict treatment duration is of great significance and critical importance. In this study, you found that model-based methods, especially MCP-Mod (Multiple Comparisons and Modeling), will outperform traditional qualitative methods in determining the optimal duration of antibiotic treatment. This is an exciting study.

However, I have some questions about your study. Your study focuses on the treatment of TB, do you want to extend it to other infectious diseases that also require long-term treatment, such as HIV, HBV, malaria infection? The dataset you used is from DGM, and I am not sure whether these generated patient data have the same heterogeneity as real patient data (do patients in the real world have more complex medical conditions that affect TB treatment?). In addition, in your study, it seems that all patients receive only one treatment regimen by default from the beginning to the end of treatment, but I believe that the situation in the real world may be more complicated. Some patients may change their treatment regimen during treatment for various reasons. Does MCP-Mod or other model-based methods still perform well in such a real environment?

Finally, the idea of finding or creating new methods to accurately predict the duration of treatment is very creative. Looking forward to your new discoveries.

On 2025-08-11 18:12:37, user Aluoch Naomi Roosevelt wrote:

A good paper

On 2022-08-12 15:45:38, user Daniel Corcos wrote:

As I understand it, lifting the mask requirement on March 10 rather than March 3 was associated with more COVID.

On 2020-04-10 15:16:29, user Guilherme Araujo Lima da Silva wrote:

Hi, Do you have the code available? Is it R, Python or Julia?

On 2020-03-20 20:57:29, user Sylvie Vullioud wrote:

Could authors provide information to dissipate high risks of bias:

1. Manuscript was first published on mediterranee-infection.com website, not on medRxiv. On the manuscript on the website on mediterranee-infection.com, I can read 'In Press 17 March 2020 – DOI : 10.1016/j.ijantimicag.2020.105949'. It means that manuscript was already accepted by International Journal of Antimicrobial Agents at the time when the manuscript was deposit on the 20.03.2020 on medRxiv.

-> Pre-print on medRxiv is not a real pre-print to collect feed-back for manuscript improvement, as originally designed for. Moreover, medRxiv states: 'All preprints posted to medRxiv are accompanied by a prominent statement that the content has not been certified by peer review'.

-> There is an obvious potential conflict of interest, because last author Raoult is editor of the article collection COVID-19 Therapeutic and Prevention in International Journal of Antimicrobial Agents.

-> International Journal of Antimicrobial Agents is runned by Elsevier, suggesting 'If accepted for publication, we encourage authors to link from the preprint to their formal publication via its Digital Object Identifier (DOI)'.

1. Discussion on the controversy of main cited Chinese paper, ref 8 ?

2. According to paper, allocation of patients group was random but treated group is 51.2 years average and control group 37.3 years?

3. Article describes 3 conditions of patients: asymptomatic, low and high symptoms. Why?

4. Care to patients, biological and physiological sampling and analyses, and statistical analyses were not blinded. Why?

5. I think that no placebo was used. Why?

6. 6 patients on total of 42 were excluded from study: three patients were transferred to intensive care unit, 1 stopped because of nausea, 1 died. One left hospital. <br /> It is written :'study results presented here are therefore those of 36 patients (20 hydroxychloroquine-treated patients and 16 control patients). Why were dead, intensive care, and nausea patients not included in statistical treatment? <br /> -> This may be a selection bias? <br /> -> What about unwanted very worrying effects of the treatment?

7. 'The protocol, appendices and any other relevant documentation were submitted to the French National Agency for Drug Safety (ANSM) (2020-000890-25) and to the French Ethic Committee (CPP Ile de France) (20.02.28.99113) for reviewing and approved on 5th and 6th March, 2020, respectively'. Pre-print was posted on 20.03.2020. Time points on day 14 on patients.<br /> -> So recruitment and study started before approval of ANSM and French Ethic Committee? How is it possible?

8. How is it plausible that numerous authors (18!) participated equally to the work? Is it possible to add their respective contributions?

Thank you in advance for considering my questions. <br /> Regards, <br /> Sylvie Vullioud

On 2021-08-30 07:51:38, user Candice Chaplin wrote:

It states that the GENECUBE® HQ SARS-CoV-2 (TOYOBO Co., Ltd.) reagent was approved in October, 2021. As a layman, I don't quite understand this.

On 2020-09-01 03:16:55, user Dr. Amy wrote:

This discovery that telomere shortening and race increase the likelihood of Nasal ACE2 sars-cov-2 occupation is perhaps THE important piece explaining the disparities in severity while underscoring nasal acquisition and supporting aerosol Transmission.

On 2021-05-28 00:56:34, user Jian Zhang wrote:

According to Figure 2B, there is clearly a two- to three-fold increase of anti-Syncytin-1 after vaccination (especially 1-4d and 6-7w) compared to Day 0.

On 2020-08-15 23:30:43, user Nan wrote:

To those who tweeted and regarded this as evidence that masks don't work,

This article does NOT imply masks don't work. If one wishes to draw such a conclusion, a direct comparison is required on the disease risk when wearing masks versus not. From both the fifth and sixth comparison in the figure and a related article (https://www.bmj.com/content... "https://www.bmj.com/content/369/bmj.m1442)"), masks are better than not wearing at all! This article only says physical distancing is very important for cloth and surgical masks. It means that besides wearing normal masks, I should be cautious about a strict physical distancing. This agrees with common sense that the more protections (e.g., masks, distancing, etc.) we have, the safer we are.

Also, is physical distancing always easy and tangible to follow? The answer is no. You cannot guarantee that you are always in safe distances with other people in the street. In contrast, masks are a lot more perceptible. They reduce exposure to the contaminated air. Masks are also a sign of caution. A sign that everyone should protect their community by reducing transmission.

On 2020-05-28 08:18:17, user Philippe Brouqui wrote:

The paper of KIM et all reports on the response to treatment of hydroxychloroquine or<br /> lopinavir-ritonavir with or without antibiotic in a retrospective cohort study<br /> with comparison with standard of care. The evaluation has been carried out on<br /> moderate case only and no death were reported. They assume that HCQ and ATB is superior to both SCO and LR plus ATB in time to viral clearance, length of hospital<br /> stay, duration of fever and cough. Adverse event been significantly different<br /> from SOC but not different between the two arms of treatment and only<br /> mild. <br /> Methodology: Is appropriate for the aim<br /> -The study is relevant to the aims: treat patient early (non-severe disease) at the time to diagnosis to avoid complication and death<br /> - The study is relevant toward bringing new data in time to outbreak by using repurposing of drugs HCQ and LR <br /> -The study is relevant toward bias related to heterogeneity of care as a single center study.<br /> - Classification of patients referred to NIH Guidelines (NEWS Score) as mild, moderate and severe COVID<br /> - Definition of negative PCR and viral clearance is in adequation to previous published literature.<br /> -Treatment was done within the range of recommended dosage ; HCQ 200mg/ twice a day as well as for lopinavir/ritonavir 200/50 mg, however higher doses are generally used for HCQ (600mg/d). For antibiotics there were given as recommended

Ethics

-Data were collected through the patient medical file of the hospital blinded and using patient dataprotection

Outcome measures<br /> -Correspond to aims delay between treatment initiation and viral clearance, discharge from hospital and symptoms resolution

Statistical analysis

This is classical analysis methods relevant to aim

Confounding bias/ Limitation:<br /> -Those relative to retrospective study but well a posteriori controlled <br /> -As a retrospective study of the 358 patients (270) 173 mild and 97 moderate covid-19 cases were analyzable for completion of treatment and data availability. <br /> - 3/270 patients were still ongoing treatment at time of release (1%)<br /> - 97 moderate Covid-19 patients were categorized HCQ ATB SOC (22) LR ATB Soc (35), SoC (40) and analyzed for treatment and outcomes<br /> -A posteriori comparative analysis shows that the two groups HCQ and LR were identical in terms of comorbidity and other known factors that may weigh on the outcome.<br /> -Comparison with the Soc group alone showed that this last was less severely ill<br /> (significantly less pneumonia), and factor associated with poor outcomes, such<br /> as low lymphocytes count, and elevated CRP were associated with the treated<br /> groups. Interestingly dyspnea was more prevalent in this SOC group but we know<br /> that absence of dyspnea (silent hypoxemia) is rather than dyspnea linked to<br /> outcome. This suggest that if a difference in treatment exist it will probably<br /> be under evaluated. <br /> - Retinopathy to HCQ as never been reported in such short treatment and HCQ in serum returns to negative in 15 days after end of treatment (unpublished) <br /> The limitation of the study as been well reported

Interpretation of results: adequate except comparison LR/LR and ATB<br /> Time to clearance are shorter particularly in the HCQ and ATB group for which time to PCR > 35CTis 12 days in what is published elsewhere<br /> -Cough resolve significantly better in the HCQ ATB and fever in the two treated groups compare to SOC.

Adverse events were more frequent but only mild

The subgroup analysis LR versus LR ATB should be interpreted carefully as we don’t know interval time to onset of the LR only arm which may interfere with viral clearance of this subgroup.

Conclusion<br /> This study appropriately show that HCQ & ATB is better than LR & ATB than to SOC<br /> to shorten viral clearance, resolution of symptoms, and to shorten hospitalization duration in moderate form of COVID-19. The role of ATB alone to shorten viral clearance is overestimated

Note : P BROUQUI , has no conflict of interest with the industry concerning this review<br /> but has already published study supporting the efficiency of HCQ and azithromycin in COVID-19.

On 2025-10-07 13:01:22, user Evolutionary Health Group wrote:

We at the Evolutionary Health Group ( https://evoheal.github.io/ ) really enjoyed this paper.

Here are our highlights:

Asks what role the microenvironent (including antibiotic administration) plays in shaping the phenotypic traits of S. aureus.

Shows increase in MRSA associated with coexistant pseudomons infection and ciprofloxacin.

Monoinfected (SA only) cases showed increased pigment and biofilm production. Coinfected (SA and pseudomonas) cases showed reduce pigment and biofilm production. Two of these phenotypic shifts coincided with ABX treatment, and these patients had significantly more MRSA infections

On 2020-05-26 20:56:26, user Sinai Immunol Review Project wrote:

Main Findings<br /> In this study, Bouadma and authors longitudinally profiled multiple immune parameters of a fatal case of Covid-19 that quickly developed multiorgan failure. An 80-year old male patient presented with fever and diarrhea that developed into multiorgan failure and hemoptysis over the course of 24 days that resulted in death. During this time, he was treated with broad-spectrum antibacterial agents, Remdesivir, and interferon beta-1a. Peripheral naive CD4+ and CD8+ T cells remained stable throughout, but effector memory T cells continually increased. Exhausted and senescent CD4+ and CD8+ T cells, and gamma delta T cells increased following day 14. Activated and exhausted B cells peaked on day 20. After day 16, NK cells and monocytes generally declined possibly due to lung trafficking. These fluctuations in immune populations were accompanied by induction of pro-inflammatory cytokines and Th1/Th2 factors that increased on day 14. Although some cytokines decreased following day 14, cytokines associated with T cell activation, exhaustion, and apoptosis continued to increase.

Limitations<br /> It is difficult to draw broad conclusions from one patient and this longitudinal study did not start at the onset of infection and symptoms. Furthermore, these observations were done on the peripheral blood without complementary analysis of the lung where they suspect NK cells and monocytes have trafficked to.

Significance<br /> This shows that immune cells proportion, functional state, and soluble factors fluctuate throughout disease progression. This is a broad overview of potential blood biomarkers that can be used to assess progression and severity.

Credit<br /> Reviewed by Dan Fu Ruan, Evan Cody and Venu Pothula as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai

On 2022-03-28 18:14:47, user August Blond wrote:

Dear colleagues,<br /> I am having difficulty understanding figure 3, the two graphs that are plotted with GFP/EGFR.<br /> Zooming in on the four ovals - red, blue, black, green - I see that the scattered-plots are themselves contained in a smaller perfect ovoid.<br /> Can you explain how you manage the computer processing of your samples?<br /> In reference 13, the method for doing multiplex FACS, these close to perfect ovals do not appear. There are still points that are not perfectly integrated into the "virtual" geometrical structure.<br /> As is the case with all FACS using gating.<br /> Would it be possible to generate point clouds that have not been "artificially" modified after gating?<br /> Best regards,<br /> August Blond

On 2021-11-14 14:59:17, user Martin Jezierski wrote:

If they can't isolate/purify it, how can they determine 'viral load', or show any spread (especially in the asymptomatic)?

On 2020-04-02 02:14:17, user Van Hovenga wrote:

Correct me if I'm wrong but this seems to be a very crude model. Even if the data, assumptions, and methodology is sound, all of the models parameters are assumed to be static. Also, they fit data that is currently exponential to a sigmoid function to generate predictions. Even though there has been some observed location specific inflection points, I feel that there still has not been enough data collected past these points to make reliable predictions based off of curve fitting alone. It seems to me that the data and information about the virus is far to sparse currently to generate accurate statistical predictions. I really wish more light was being shed on the stochastic models that have been recently developed that account for the dynamics of the disease spread.

On 2020-04-17 17:15:59, user Susan N Dallas wrote:

Did we give up on the projections? Where is the last 5-6 days of data?

On 2020-05-18 14:12:18, user OxImmuno Literature Initiative wrote:

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

On 2020-07-20 20:58:06, user Dan Elton wrote:

This is classic p-hacking! Look at https://en.wikipedia.org/wi... and apply a correction (the simplest would be the Bonferroni correction, or dividing the p values by the number of comparisons done). I'm going to be really sad if a journal publishes this without a massive overhaul. Negative results are useful, but statistics have to be done correctly or you're doing everyone a big disservice!

On 2020-04-20 17:25:20, user Dylan Skola wrote:

Can anyone see where they're presented the MAF of the mutations? How many were fixed in the isolate and how many represented intra-host quasispecies at low abundance?

On 2025-06-10 15:54:17, user Mary Ellen Mackesy-Amiti wrote:

Final published version available: https://doi.org/10.1186/s12889-025-23387-8

On 2022-06-15 22:08:31, user Sir Henry wrote:

Would a confounding effect be that feelings of vulnerability enter patients' decisions to seek medical care and hospitalization? The history of public messaging in support of boosting is likely to make boosted individuals feel less vulnerable, and may account for the difference in hospitalization, even in the absence of non-psychosomatic VE.

On 2020-06-16 05:17:57, user Sukhyun Ryu wrote:

This manuscript was published, please follow the link below<br /> https://wwwnc.cdc.gov/eid/a...

On 2020-04-09 10:11:57, user Andrea Zille wrote:

Thank you for your excellent work. I have a suggestion to improve the protocol. In my opinion the 4 day "rest" of the PPE especially the masks should be implemented after the disinfection step. Leave used mask for 4 days could improve the proliferation of bacteria. Especially for the low temperature (80ºC) treatment, this could lead to a substancial bacterial load that a this temperature could improve the selection of more resistant and nasty bacteria. Fort this, I will also suggest to not use low temperature alone but eventually as a further step after UV treatment that affecting directly the DNA/RNA is much more effective in degrading virus and bacteria.

Andrea Zille, PhD<br /> 2C2T - Centre for Textile Science and Technology, University of Minho<br /> Campus de Azurém<br /> 4800-058 Guimarães, Portugal<br /> Tel: +351-253510285 <br /> Fax: +351-253510293<br /> e-mail: azille@2c2t.uminho.pt

On 2021-07-22 10:33:41, user David Simons wrote:

Hi,

Thanks for sharing this data, it may be interesting to include descriptives for those that were test negative for COVID-19.

Also in table 1 your numbers for smoking status do not appear to be accurate. You seem to be missing 2,610 smoking statuses for your COVID-19 positive sample.

On 2020-04-22 01:10:17, user Gunnar V Gunnarsson wrote:

After reading the paper I unfortunately find the usage of data to be misleading and I think you might have drawn the wrong conclusions.

The problem lies in the fact that once people went on ventilators they where given HC or HC+AZ. This re-categorised the patients by increasing the number of high risk patients in the HC and HC+AZ groups making the No HC an invalid control group.

Before ventilation the statistics was like this: (Table 4 in paper)

HC: 90 - 9 (10.0%) deaths - 69 (76.6%) recover - 12 (13.3%) onto ventilation HC+AZ: 101 - 11 (10.9%) deaths - 83 (82.2%) recover - 7 (06.9%) onto ventilation No HC: 177 - 15 ( 8.4%) deaths - 137 (77.4%) recover - 25 (14.1%) onto ventilation

We see that death-rate is about the same for all groups but HC+AZ seams to have the highest recovery rate but it might not be statistically significant.

Now once people hit ventilation the re-categorisation occurs. More patients where given HC and HC+AZ which moved them from the No HC group to the HC or HC+AZ group. These groups therefore have a much higher % of ventilation patients because they where given the drugs after they hit ventilation.

The following data can be derived from the paper but is not presented:<br /> Once people hit ventilation we have the following results.

HC: 19 - 18 (95%) deaths - 1 (11%) recover HC+AZ: 19 - 14 (73%) deaths - 5 (27%) recover No HC: 6 - 3 (50%) deaths - 3 (50%) recover

If you compare these 2 tables, you see that 25 patient with No HC reach ventilation. Once they reach ventilation, 19 of these where give HC or HC+AZ, thereby moved from the No HC group to the other two. 79.5% of all patients reaching ventilation died so arguably 14 patients that died where moved from the No HC group to the other 2 groups only once they reach the much higher risk state.

Here are the number of people per group that got ventilation:

HC: 97 - 19 (19.6%) got ventilation HC+AZ: 113 - 19 (16.8%) got ventilation No HC: 158 - 6 ( 3.4%) got ventilation

So in the end result the No HC group had a very low % of patients who got ventilation and therefore should have a significant lower death rate which is then totally unrelated to the treatment.

On 2020-04-22 03:32:32, user Cheri Trigg wrote:

According to MedCram Zinc is what actually helps. Chloroquine is how the zinc gets into the cells. MedCram is a medical journal on Youtube. Update #32 and 34 go into depth on this. It is tragic to use a medication meant as a delivery system and not use it to deliver. Not sure to laugh or bawl. I hope the word gets out to use zinc before the zithromyacin at least.

On 2021-04-06 18:30:59, user John Simeral wrote:

A version of this manuscript has now been peer reviewed and accepted at IEEE Transactions on Biomedical Engineering. This medRxiv page will shortly link to that version, which is also indexed at PubMed:<br /> IEEE doi: 10.1109/TBME.2021.3069119. Online ahead of print.

On 2024-02-23 12:22:02, user Carsten Skarke wrote:

This preprint has been published at https://www.nature.com/arti...

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

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

On 2020-04-01 13:42:32, user Sinai Immunol Review Project wrote:

The authors analyzed lymphocyte subsets and cytokines of 102 patients with mild disease and 21 with severe disease. CD8+T cells and CD4+T cells were significantly reduced in both cohort. particularly in severe patients. The cytokines IL6 and IL10 were significantly elevated in severe patients as compared to mild. No significant differences were observed in frequency of B cells and NK cells.<br /> The authors argue that the measurement of T cell frequencies and cytokine levels of IL6 and IL10 can be used to predict progression of disease from Mild to severe Cov-2 infection.

Limitations of the study: The study demonstrates in a limited cohort similar associations to several other reported studies. The authors didn’t compare the changes in lymphocyte and cytokine with healthy individual (Covid-19 Negative) rather used an internal standard value. The recently preprint in LANCET shows The degree of lymphopenia and a pro-inflammatory cytokine storm is higher in severe COVID-19 patients than in mild cases, and is associated with the disease severity .

Relevance: This translational data identifies key cytokines and lymphopenia associated with disease severity although mechanism and key cellular players are still unknown. Higher level IL-6 production in severe patient suggests potential role of Tocilizumab (anti-IL6R) biologic although clinical trial will be necessary.

Reference: 1. Longitudinal Characteristics of Lymphocyte Responses and Cytokine Profiles in the Peripheral Blood of SARS-CoV-2 Infected Patients. Lui et al. LANCET infectious Diseases preprint<br /> https://dx.doi.org/10.2139/...

Reviewed By Zafar-RS

On 2019-11-19 17:15:54, user Guyguy wrote:

EPIDEMIOLOGICAL SITUATION OF THE EVOLUTION OF THE EBOLA VIRUS DISEASE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI IN THE DEMOCRATIC REPUBLIC OF THE CONGO AT NOVEMBER 17, 2019

Monday, November 18, 2019

• Since the beginning of the epidemic, the cumulative number of cases is 3,296, of which 3,178 are confirmed and 118 are probable. In total, there were 2,196 deaths (2,078 confirmed and 118 probable) and 1,070 people healed.<br /> • 407 suspected cases under investigation;<br /> • 4 new confirmed cases in North Kivu, including 2 in Mabalako, 1 in Beni and 1 in Oicha;<br /> • 1 new death of confirmed cases, including:<br /> o 1 new community death in North Kivu in Oicha;<br /> o No new deaths among confirmed cases in CTEs;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

NOTHING TO REPORT

VACCINATION

• 147 people were vaccinated, until Saturday, November 16, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;

• Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 253,545 people have been vaccinated;

• Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;

• This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been approved.

MONITORING AT ENTRY POINTS

• New positive case among Mukulya Checkpoint alerts in Beni, North Kivu. It is a lifeless body of a 35-year-old man from Oicha for burial at Kabasha in Butembo;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 117,987,763 ;

• To date, a total of 112 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 2021-08-15 19:44:30, user Sean Deoni wrote:

Hi Pasco, I completely agree the scores are super low - hence even our shock. The mask question is a good one - we raise it in the discussion as well - and whether kiddos were unable to hear us / understand us etc. it’s hard to test directly since we can’t do the control non-mask yet. But we might expect that that would affect the older kiddos as well and we don’t really see that. I can tell you from other data we have from using LENAs that language interaction with these kiddos is way down but we need to investigate that further.

On 2020-07-20 01:35:17, user Rami U wrote:

A message from the authors: <br /> This manuscript is accompanied by a user-friendly data mining website. Check it out: http://www.covidcellatlas.com/

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

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

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

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

On 2020-05-05 14:23:59, user John Huppenthal wrote:

From January 1, 2020 to April 11th, the study period, over 40,000 fewer people died in 2020 than in the same period in 2019.

That's an amazing number.

You would expect an additional 13,000 people would die in 2020 just from the increase and aging of the population.

Adjusted for that effect, 53,000 more people died in 2019 than in 2020.

By the logic of the study, Covid-19 had 53,000 excess deaths in 2019.

A lot more than the 15,000 it had in 2020.

Every year, they do a vaccine effectiveness study. The results of that study need to be coughed up a whole lot sooner this year to unravel the true numbers.

This study did not produce the true numbers, not even close.

On 2020-07-10 14:48:32, user jeromee5000 wrote:

And possible effect on fresh fish production<br /> And transmission by foodborn.

On 2020-09-13 08:20:33, user OxImmuno Literature Initiative wrote:

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

On 2021-03-12 16:18:56, user NickArrizza wrote:

Are you aware that up to 80% of the co-morbid conditions associated with<br /> 94% of all deaths from COVID-19 are totally preventable (and reversible<br /> within weeks) with a whole plant based diet that lowers inflammatory <br /> markers and hypercoagulability thought to be highly correlated with <br /> severity of illness in COVID-19?

On 2021-08-23 10:16:41, user David States wrote:

Figure 1, panel C is key to much of the discussion. I’d like to see the actual data points as well as the fit curves. Also the units on the x-axis, genome equivalents per mL, are calculated from Ct using a proprietary undocumented formula and are not used elsewhere. I’d like to see a second x-axis labeled in Ct.

On 2022-02-19 00:22:41, user Sam Smith wrote:

No fever after 4 doses. 19% or 9% fever after only 3 doses:<br /> "No fourth dose vaccine recipients reported fever that lasted for >48h. However, 19% of the BNT162b2 control group and 9% of the mRNA1273 control group reported fever that lasted >48 hours (Table 1)".

"Participants in the first arm were enrolled to receive a fourth dose of 30µg BNT162b2 on Dec 27-28, 2021. One week later, on Jan 5-6, 2022, addition of the second arm was approved and additional participants were enrolled to receive 50µg mRNA1273 as a fourth dose".

Surprisingly, Moderna has less adverse reactions.<br /> "Adverse reactions were reported in 80%(Pfizer) and 40%(Moderna), respectively".

On 2023-03-10 13:40:40, user Attila Kovács wrote:

Dear medRxiv Staff, our article has been published in JASE: https://pubmed.ncbi.nlm.nih... Please add this to this preprint version. Thank you!

On 2021-08-06 22:27:57, user Ewin Barnett wrote:

Am I the only person wondering where the discussion of the autopsy results was published? In fact VAERS is now easily over 5,000 vaccine-related deaths yet zero autopsies.

On 2021-08-01 07:53:29, user Dlya Truby wrote:

Folks read "Supplementary Appendix" page 12: Deaths: Vaccinated group - 15; Placebo (unvaccinated): - 14.

On 2021-08-06 22:23:54, user Ewin Barnett wrote:

The government of Scotland reported that 5,522 have died as a result of being vaccinated. No other data released like what percentage had comorbidities or were low on vitamin D at their time of admission to hospital.. No data released as to the appropriate percentage of the national population had been vaccinated. For a nation of about 5.5 million, this represents at least 0.1% risk.

On 2025-10-28 14:47:35, user W.R. wrote:

The paper has been published: https://doi.org/10.3390/medicina61111931

On 2021-09-24 14:10:59, user Kelly Ellis wrote:

They haven't compared any unvaccinated people in this study, yet the anti-vaxers are already claiming it proves the mRNA vaccine causes this.

On 2021-07-01 18:18:58, user vinu arumugham wrote:

You don't seem to have covered T cell homing. T cells induced by injected vaccines will home to the skin. T cells induced by infection will home to the lungs.

On 2020-04-15 14:08:11, user Barry I. Levine wrote:

Waiting to see adequate data re ARBs. Losartan shows lung protective effects in many animal studies vs. ARDS, and in at least 2 human retrospective studies vs. ARDS or COPD, and may be a useful adjunctive treatment for COVID-19

On 2020-08-15 14:01:48, user Dom_Pedulla wrote:

Joao not only had Dude made some very good points, but in observational trials like this, everything depends on the nitty gritty data. I notice the huge qualifier "recent" in the results sentence, noting that carefully since in many studies these kinds of adjectives disclose or hint at certain erroneous tendencies or conclusions in even in "meticulous peer-reviewed studies". I am requesting the paper to analyze for myself, and suspect strongly that what it may show is a "benefit" for only the very recently vaccinated, and that either long after it either ends up being a net liability as regards COVID death risk, or that the timing isn't possible to discern because the investigators avoided studying all but the recently vaccinated.

We'll see.

On 2021-10-06 06:00:28, user Stuart wrote:

Could the incorporation of altered nucleosides into the viral RNA affect the ability of the reverse transcriptase in the RT-PCR reaction from actually detecting the viral RNA, even if it is there? Can they verify the results using antigen tests instead?

On 2020-09-02 14:24:31, user Maha Abou El-Naga wrote:

Good work , it explained the situation there clearly .. well done????

On 2022-01-24 01:15:03, user Fergal Daly wrote:

The paper uses linear regression on a non-linear variable (cases/100k). Does it apply directly to cases/100k or is it against log(cases) which should be somewhat linear?

On 2020-05-02 01:27:06, user fennudepidan wrote:

Notice: In the revision on April 24, 2020, we have updated our analysis using data up to April 22, and importantly in which we have adjusted for additional confounding factors that also reflect the timing of the epidemic's spread, the timing of the social distancing policies and the population age distribution. Consequently, we revised our finding as that an increase of 1 ug/m3 in PM2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%).

On 2021-12-27 23:17:44, user Ralph Bertram ?????????????/ ???? /???? wrote:

Dear readers, the supplemental html files are available here

https://c.gmx.net/@63828482... <br /> (all nodes)

https://c.gmx.net/@63828482... <br /> (only pos)

On 2020-07-15 13:15:39, user E Y wrote:

Something is wrong here, the IHME projected 2020 total US death is about 250000, that's 0.08% of the US population, how can that cause 1% of reduction of life expectancy of US population?

On 2020-11-05 16:58:58, user Sorin Draghici wrote:

Hi, Thanks for your great work. Your preprint refers to patients 1 through 20 plus patients A-D. The associated GEO dataset GSE150316 has only patients 1 through 12 but then A through J. The GEO data set also has 7 samples allegedly from placenta. Can you please clarify this? Which 20 patients are referred to in the paper? How about the placenta sample?

On 2020-04-28 00:30:59, user Mark Reeder wrote:

I am advocating that the authors, in the interest of public health, fill in the blanks of the following statement:<br /> "It was found that ___ of the 7 patients reclassified from the 'No HC' to the HC group (after ventilation began) died. Likewise, ___ of the 12 patients reclassified form the 'No HC group' into the 'HC+AZ' group died."<br /> Based on a comparison of Tables 4 and 3, the first blank must be either 6 or 7 whereas the second blank must be between 7 and 12, inclusive.

If the groups are compared based on whether they were given the drug(s) PRIOR to ventilation or prior to discharge, the HC+AZ is better by either a 20% margin over the 'No HC' group or by a FACTOR of 6. <br /> To wit, let's assume that all 12 of reclassified as HC+AZ died. That would mean that only 2 in the original HC+AZ group died. Since we have no idea when the HC+AZ drug was administered to those who died without ventilation, a fair comparison would show that HC+AZ, one might justifiably count only the 2/90 (2.2%) in that group (excluding deaths w/o vent.) as having had HC+AZ early enough in treatment. It would also mean that 3+(6 or 7) + 12 out of 162 (13.6%, also excluding deaths prior to ventilation) eventually died. <br /> This would be a huge difference with HC+AZ coming out as a terrific alternative (factor of 6 better) if given early enough. By the same logic (pre-vent treatment only, excluding non-vent deaths), the worst case for HC+AZ would still mean a 20% IMPROVEMENT over the control group! <br /> But we cannot know unless the authors (or others) are ethical and transparent enough complete the sentence above. Even if they disagree with the foregoing analysis, what is the downside in providing those numbers?<br /> I understand the difficulty of dealing with imperfect data. But for that very reason, good science demands that all information be placed on the table.

On 2020-05-09 21:33:19, user christopher starling wrote:

What positive HCQ evidence does anyone have that provides usable scientific data and answers the same questions being asked here?

On 2020-05-30 01:02:55, user Maxim Sheinin wrote:

Timely analysis. I'm curious if it's worth showing relationship between positive test rates and case fatality rates. Here's a blog post on the topic from a few weeks ago: https://medium.com/@maxbel1...

On 2020-10-26 16:15:21, user Michael O'Hare wrote:

Drawing any conclusions from a paper in which of 84,000 + people less than .5% actually had evidence ( 361 reported having had a positive biological test) of covid infection seems optimistic.

On 2021-02-06 06:44:29, user kdrl nakle wrote:

I have a hard time to believe in this. Another strange thing is that more women than men were hospitalized.

On 2020-06-10 21:37:52, user La-Thijs Mokers wrote:

HCQ isn't even the active component in the andecdotal cases of succesful treatment. You have to administer the HCQ together with a zink-supplement, else nothing will happen for sure. Also you need to get the timing right; this suggested treatment will only work during the early stage of infection, when viral load is relatively low. Herein HCQ merely functions as ionophore for the Zn2+ ions ( https://www.ncbi.nlm.nih.go... ), so that they can easily pass the cellwall into the cell, where they will inhibit viral replication ( https://www.ncbi.nlm.nih.go... ). Nothing fancy to it if you know how to use freaking google. Ofcourse loads of misleading studies will be continued published - like the recent Lancet drama of Mehra et al -, leaving out zinc and testing ridiculously high dosage of HCQ on very ill patients with a sky high viral load. No wonder you get a negative result if your research setup is designed to fail like that.

On 2020-09-13 01:19:25, user mzbaz wrote:

There is an unfortunate typo in the horizontal axis unit label of Fig 3b, which should be "minutes" not "hours", consistent with the "15 Min Rule" vertical line, as well as the discussion in the text.

On 2021-09-20 16:46:59, user Inga Andersdotter wrote:

This is exactly what Dr. Scott Gottleib predicted would happen (a subvariant of Delta with mutations taking over next,) so it will be very interesting to keep track of this one. There hasn't been much traction in the general media yet.

On 2020-03-20 22:29:51, user Brian Coyle wrote:

This effort estimated the CV19 RO as 25. Peeking into their parameters, they assume one is asymptomatic and transmitting the disease for 20 days. The largest study to date, Li et al., which Aguilar and Gutierrez use for other data, found this was 2 or 3 days. Aguilar and Gutierrez claim the symptomatic infectious period is almost 40 days. Li et al. found 5 or 6. Although camouflaged with a lot of statistics, with assumptions like these, results like RO 25 are inevitable.

On 2024-10-07 13:30:05, user Dimy Fluyau wrote:

Preprint is published.<br /> Fluyau, D.; Kailasam, V.K.; Revadigar, N. Rapid and Prolonged Antidepressant and Antianxiety Effects of Psychedelics and 3,4-Methylenedioxy-methamphetamine—A Systematic Review and Meta-Analysis. Psychoactives 2024, 3, 476-490. https://doi.org/10.3390/psychoactives3040029

On 2020-06-30 08:08:24, user OxImmuno Literature Initiative wrote:

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

On 2020-07-27 20:23:39, user Marm Kilpatrick wrote:

Thank you for this large study. Were you able to assess when the patients first lost their sense of smell? I'm convinced by your study (and others) that this symptom is much more specific in identifying COVID-19 patients than other symptoms (e.g. cough or fever). But I'm still not sure if it is a useful symptom for people to use to isolate or get tested. If this is one of the first symptoms then it could be very useful but if it isn't apparent until 3 or more days after cough or fever start then it would be of less importance for isolation (but still could be useful for finding other chains of transmission via contact tracing). Thank you!<br /> marm

On 2022-02-17 20:47:23, user RT1C wrote:

Another point of confusion: "An individual was considered protected by natural immunity 14 days after testing positive for COVID-19 by a nucleic acid amplification test (NAAT). If not previously infected, a person was considered protected by vaccine induced immunity 14 days after receipt of the second vaccine dose of an mRNA vaccine. " and "A vaccine booster was defined as at least 1 dose of any COVID-19 vaccine at least 90 days following COVID-19 infection for those with natural immunity (i.e. those previously infected), or a third dose of a COVID-19 vaccine at least 90 days following the second dose of an mRNA COVID-19 vaccine for those with vaccine-induced immunity (i.e. those not previously infected)."

This is all very confusing, stemming from your broad use of "natural immunity" to include those who were vaccinated before or after infection. Figure 4 is entitled with "natural immunity" but includes people with 0, 1, 2 or 3 doses. Based on the definitions in the text quoted above, that doesn't seem possible. Did they get infected and then receive 0-3 doses AFTER infection and still called "natural immunity" subjects? What about people who received 1 or more doses before infection? Are they counted among the vaccine-induced immunity subjects? In my opinion, your definitions and uses don't seem consistent or understandable.

Furthermore, because other research has shown a difference in immune response when people are vaccinated then infected vs. infected then vaccinated, you should not combine these as one group. Did you make any attempt to compare these situations? Shouldn't you?

Look at Fig. 2, for example. I assume that many of the subjects included in the curves on the left ("Natural Immunity") actually were vaccinated at some time, since Fig. 4 shows that many with "natural immunity" were vaccinated by 0-3 doses. How, then, are we to interpret Fig. 3? Is the weaker immunity with longer durations since POIC to be interpreted as time since infection, or time since vaccination (which would count for resetting POIC)? Is the weaker immunity with longer durations due to decay of natural immunity as the text seems to imply, or is it due to confounding with vaccination? (After all, doubly vaccinated have higher susceptibility in Fig. 1). These issues make it difficult to understand your study.

I think you probably have the data for an informative analysis, and your method of analysis looks promising (I prefer it to the "person-days" approach used in some other work). Please consider reexamining the dataset with a clarified definition of "natural immunity" that accounts for all combinations of vaccination and infection including sequence.