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

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

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

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

This should be interesting in peer-review.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

That looks like a good correction. Thanks!

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On 2021-09-02 13:44:56, user ABO FAN wrote:

I do not understand the meaning of this paper at all.<br /> 1. There is no statistically significant difference between one and two corona deaths. This means that the vaccine is not effective.<br /> 2. The test period is until March 13, 2021, therefore the current mainstream delta strains were not tested.

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

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

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

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

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

Key findings:

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

Potential limitations:

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

Overall relevance for the field:

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

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

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

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

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

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

This paper should be peer reviewed and evaluated ASAP.

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

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

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

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

Johannes Wollbold, Weimar / Germany

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

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

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

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

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

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

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

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

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

Apparently so.

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

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

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

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

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

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

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

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

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

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

Posted my comment and then noticed yours)

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

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

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

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

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

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

Www.Ohri.ca/profile/shiremath

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On 2020-04-22 02:45:15, user Dr. Héctor Musacchio wrote:

My main concern is about false positives. How can we define asymptomatic case? How can we differentiate a false positive from an asymptomatic only with a positive test at a precise moment only?

On 2020-04-24 19:12:55, user 1ProudPatriot wrote:

They are continuing to retest/check for Type 1 and 2 errors. The statistical differences they study and many others are showing are so glaringly obvious as to early mitigate your criticisms, even if they are 100% correct. This study is most likely to be peer-reviewed. The number of authors across departments suggests the authors are well aware of the study's shortcomings. The Stanford group are not overstating their findings.

I have two requests: <br /> 1. Please provide your expertise and critical analysis of the studies done by Imperial College and the University of WA. <br /> 2. I challenge you to find a single college text on virology or epidemiology that suggests throwing out the principles of biology and all we have learned about viruses to follow the path of lockdowns. EVERY textbook says vaccine or herd immunity, period. Vaccines are difficult to develop due to cost, mutations and the time they take to develop and be safe for humans. The track record on vaccines is clear. That leaves herd immunity which we have done in the past. Mitigation of capacity is reasonable; but we are way beyond that now. There are reasons our "leaders" are doing this; but they don't imply common sense, nor are they scientific.

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

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

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

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

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

Best regards,

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On 2020-03-16 22:24:16, user Leslaw Milosz Pawlaczyk wrote:

Is this dataset available somewhere? I would be interested in helping developing this method further as I have lots of experience in that area.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On 2020-11-25 05:08:10, user ArthurConanDoyle wrote:

Layman here, w/Covid. Wondering why you don't use sputum for greater accuracy?

Of course, it's not as easy or ubiquitous as saliva, but maybe a sample option?<br /> The major point being accuracy is almost everything, other factors count, but...

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

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

Note the following quote from the paper:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Thanks much!

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

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

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

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

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

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

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

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

Hi,

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

Cheers,

Paul

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

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

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

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

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

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

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

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

On 2020-06-30 14:50:33, user Munir Hazbun wrote:

Congratulations with your results . We have published in Critical Care Exploration very encouraging results with a higher dose of MP. We learned early that at high dose MP work very well for rescue we have not have any prone position need and outcome are about 10% mortality in about 60 patients so far. Certainly optimal nursing and respiratory strategies are necessary for example we are not using propofol and use recruitment lung strategies

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

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

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

Hi,

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

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

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

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

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

Nice work and best wishes,<br /> Eric

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On 2020-06-27 10:57:04, user Filipe Pereira wrote:

Could be false positives. Some of the primers have similarities to the genome of other coronaviruses, which may be in circulation at the time.

http://covid.portugene.com/cgi-bin/COVid_primersandprobes_otherCoV.cgi

Could be contamination, it is crucial to sequence the amplicons to see which lineage was there (if any).

On 2020-06-25 22:40:27, user Greg Green wrote:

Mr. Cohen,

Great read. to be clear, what is your best estimate, in terms of percentage, of the number of false positives for current mass testing?

On 2021-08-12 02:48:52, user Johanna wrote:

It would be useful to report the interval between doses - or at least the interval regime in place in the region at the time of the study - due to the significant difference in efficacy for AstraZeneca with a 12-week interval as opposed to a shorter interval. In Australia, the AZ interval regime is 12 weeks, but a lack of data on efficacy with the longer interval, and consequent reporting of the relatively low efficacy with the shorter interval compared to Pfizer, has resulted in AZ being seen as the poor cousin, contributing to vaccine hesitancy. Lack of data means it remains unclear how great the difference in real-world efficacy between the two actually is. Reporting the interval between doses would at least clarify the applicability of results.

On 2025-10-23 17:28:47, user Victor Ezeugwu wrote:

Hi medRxiv team, could you please provide an update to indicate that this paper is published in PloS One: https://doi.org/10.1371/journal.pone.0293382 .<br /> Thanks.

On 2020-05-29 18:17:32, user Peter Juhasz wrote:

Another study, that does not make too much sense, most likely because problems with the underlying assays. The flawed conclusions are so obvious that the authors should seriously consider retracting their paper (which now CNN has picked up and presented as "Breaking News".

So let's just do a back on the envelope math: if we assume that succumbing to or surviving COVID-19 takes about the same time until infected individuals develop antibodies of the IgG type (3-4 weeks), we had ~2,000 dead by the end of March in NY and ~2,000,000 infected claimed in the manuscript is suggesting a 0.1% mortality. However the fact is that by today we have almost 30,000 dead in NY suggesting 30,000,000 infected that is way over the entire population of the state.

Even if the numbers would be off by a factor of two or three, the early results extrapolate to a very high prevalence today. The authors should have run a small validation cohort at a high infection prevalence to prove such projected high prevalence on a recently collected sample set.<br /> This is poor science on display that does not help anyone.

On 2020-10-26 09:27:03, user Leaf Expert wrote:

Great research! The FDA reported that it completely endorsed the utilization of remdesivir as a treatment for COVID-19 requiring hospitalization in all grown-up and some pediatric patients.

Remdesivir is just to be regulated in a clinic or medical care setting fit for giving intense consideration similar to inpatient emergency clinic care. The medication, likewise alluded to by the FDA as Veklury, is the main treatment for COVID-19 to get FDA endorsement, as per a FDA news discharge. It tends to be utilized for grown-up patients and pediatric patiens who are more than 12 years of age and gauge in excess of 40 kg (88 lb).

The medication was as of late in the news after it was reported that it was among the medicines given to President Donald Trump during his session with COVID-19.

On 2021-01-05 22:41:19, user Troy Richlen wrote:

An important variable that this and other studies have not been able to adequately incorporate into this analysis is the effect of comorbidities on life expectancy of COVID-19 deaths which is due to a lack of appropriate statistical information.<<<br /> This is calculating the delta of the age of death due to Covid versus the average age of death for the population not the population of people who average 2.6 comorbidities. People who are obese, have diabetes and other significant health issues also will have a negative offset from the average age of death.

On 2025-02-03 12:06:39, user Prop Joe wrote:

The ability to control for genetic risk in observational studies using PGS is often quite poor as PGS tend to be very noisy on an individual level, it would be more effective to use something like PENGUIN ( https://www.pnas.org/doi/epub/10.1073/pnas.2408715121 ) or structural equation modelling

On 2020-06-27 14:00:46, user Kevork Hopayian wrote:

Study duration too short, 3 weeks definitely not long enough to pick up a cluster when the background risk is running low

On 2021-07-01 03:15:16, user Subhajit Biswas wrote:

Really excited to see that our original observation that pre-exposure to dengue may be cross-protective against COVID-19, has been further supported by the following study from Brazil!

Title of paper: Previous Dengue Infection and Mortality in Coronavirus Disease 2019 (COVID-19)

Abstract: We studied 2351 participants with coronavirus disease 2019; 1177 (50%) reported previous dengue infection. Those without previous dengue had a higher risk of death (hazard ratio: .44; 95% confidence interval: .22–.89; P = .023) in 60-day follow-up. These findings raise the possibility that dengue might induce immunological protection against severe acute respiratory syndrome coronavirus 2.

Link: https://doi.org/10.1093/cid...

This perhaps explains why mortality in dengue endemic regions like the Indian subcontinent, Africa and SE Asia is about 10-times less compared to dengue non-endemic regions.

Why Brazil is an exception?

Read following publications:

1. https://www.medrxiv.org/con... by Prof Miguel A L Nicolelis

2. https://doi.org/10.1016/j.c... by our Group

As of today, Worldometer says mortality per million population is 287 for India compared to 1863 for US & 1878 for UK (1st July, 2021). Indian population is almost 4-times the population of US with 0.4 million deaths compared to 0.62 million deaths in US.

On 2022-10-24 16:26:51, user KaAcWh wrote:

Dear Drs. Pretorius and Bell. Thank you for this interesting study. I am concerned, however, of your experimental design and statistical approach used. We know now, from various peer-reviewed publications, that covid vaccines can cause microclotting, platelet hyperactivation, immune dysregulation and can also lead to autoantibodies being produced. By having two study groups: i.e. controls and long-COVID sufferers, each including a fair amount of vaccinated individuals (33 vs 24%) and then comparing mean values of each response variable between these groups, it is not possible to examine the contribution of COVID vaccination to the values. This is a serious flaw in your study as it currently stands. I would be very interested in seeing the new results with two-way ANOVAs, GLMs or mixed effects models to take into account the effect of vaccination to your observed results. Without this approach, it is simply not possible to conclude what you and your coauthors have concluded.

On 2025-10-21 22:01:38, user Carlos A. Fermín-Martínez wrote:

The published version of this work is now available at: https://www.nature.com/articles/s41514-025-00232-1

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

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

On 2022-12-29 19:11:31, user tshann wrote:

Given the stated benefits of these vaccines, why are we doing modeling studies rather than real RCT's. It's been over 2 years with these products, when will we see the science instead of more modeling studies?

On 2021-10-04 07:26:13, user Wolfgang Wagner wrote:

Int J Mol Sci. 2021 Aug 27;22(17):9306.<br /> Epigenetic Clocks Are Not Accelerated in COVID-19 Patients

PMID: 34502212 <br /> PMCID: PMC8431654 <br /> DOI: 10.3390/ijms22179306

On 2021-03-24 09:22:16, user Sarwah Al-Khalidi wrote:

This paper fills an essential gap by surveying the hesitancy rates of being vaccinated against the COVID-19 virus among Arab-speaking individuals, and investigating associated hesitancy factors. It is the first study of this scale in the Arab world, with over 36 thousand individuals from all 23 Arab countries and beyond.

The multidimensionality and the well-thought out plan of both the survey and the analysis are truly impressive. The use of 29 objective points to measure the level of Hesitancy gives this paper great power. The importance of this study is evident form results that indicate that 60% of the Arab population are hesitant to take the vaccine. This is a striking percentage to anyone fighting against this pandemic. Using multivariate analysis to deconvolute key factors effecting hesitancy makes results more comprehendible. Interestingly, results of the multivariate analysis show that people typically classified as high-risk (above 60 or have a chronic illness) are the least hesitant to take the vaccine, which could be reflective of the media and government’s influence on people’s decision.

Among the tested factors that could be affecting a person’s attitude, the frequency of taking the flu vaccine seems most convincing, and could be indicative of a person’s confidence or knowledge about vaccines. It is surprising that the hesitancy among health workers is not significantly less than that of those who don’t work in the health system.

By revealing the main barriers to taking the vaccine against COVID-19, results published in this paper are an essential step forward towards tackling the pandemic in the Arab world.

On 2020-07-03 20:49:23, user Brooke wrote:

"Asian" and "Other" are not appropriate ethnic categories. People of Chinese heritage are considered Asian. If you do not include Chinese people as Asians, then this ethnic category should be renamed "South Asian" (which includes people from India, Pakistan, Bangladesh, etc.). As for applying the term "other" to an ethnic group, this term literally "others" them. It may require more words to describe, but the more appropriate category for these participants would be "participants if more than one ethnicity or an ethnicity not listed in the survey." Although this tweet thread is about gender, the same gist applies here about ethnicity: https://twitter.com/theorig...

On 2019-08-03 19:56:40, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EBOLA EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI

Wednesday, July 31, 2019

The Epidemiological Situation of Ebola Virus Disease, July 30, 2019

Since the beginning of the epidemic, the cumulative number of cases is 2 701, of which 2 607 are confirmed and 94 are probable. In total, there were 1,813 deaths (1,719 confirmed and 94 probable) and 776 people healed.<br /> 293 suspected cases under investigation;<br /> 11 new confirmed cases, including 3 in Vuhovi, 1 in Mandima, 1 in Mambasa, 1 in Kalunguta and 1 in Nyiragongo (Goma);<br /> Continued search for the confirmed case in the health zone of Lubero dated 25/07/2019;<br /> 10 new confirmed cases deaths:<br /> 2 community deaths, including 1 in Beni and 1 in Mandima;<br /> 6 deaths at ETC, including 3 in Beni, 2 in Mabalako and 1 in Butembo;<br /> 2 deaths at the ETC of Beni;<br /> 6 people recovered from ETC, including 4 Mabalako, 1 in Katwa and 1 in Butembo;<br /> Two live health workers are among the new confirmed cases of Mambasa (non-vaccinated) and Vuhovi (vaccinated). The cumulative number of confirmed / probable cases among health workers is 148 (5% of all confirmed / probable cases), including 41 deaths.

Organization of the Coordination Workshop for the Ebola Response to the Ebola Epidemic

The Technical Secretariat of the Multi-sectoral Epidemic Response Committee of the EVD is organizing a coordination workshop from 31 July to 02 August 2019 to coordinate the response to the EVD epidemic at the Karibu Hotel in Goma in the province of North Kivu.<br /> This workshop aims to brief the Technical Secretariat of the Multisectoral Committee by coordinating the response on the organization of the current response in order to enable it to make informed decisions thus avoiding a major disruption of the response.<br /> It will enable the Technical Secretariat to inquire about the current epidemiological situation of EVD and the main challenges to be addressed, to learn about the current response structure (organization of the different levels of coordination) and the new strategic plan for the response (PSR4) and synergy with the security, humanitarian and financial sectors, as well as the operational readiness of DRC neighboring countries to create a favorable environment for the response.<br /> It will also allow to discuss challenges and perspectives related to priority themes (pillars). This workshop will result in the priority actions to be carried out over the next 90 days and the overall orientations on the response, as well as the new organizational structure of the response.<br /> It should be noted that under SRP-4, effective and coherent change in strategies, effective coordination, consistent standards and support for the most vulnerable communities are envisaged at risk in the provinces of North Kivu and Ituri while preventing the spread of the epidemic in other provinces and countries bordering the DRC

Death of the second confirmed case of Ebola in Goma

The second confirmed Ebola case from Goma died on Wednesday 31 July 2019 at the ETC Nyiragongo of Goma located in the General Reference Hospital of this city.<br /> This last case of Goma is a patient, who began to present the symptoms of EVD on July 22, 2019. On July 30, 2019 he went to the Goma General Referral Hospital (HGR) located in the Nyiragongo Health Zone, where he was directly transferred to the ETC for appropriate care. The ETC, being installed within this HGR.<br /> Previously, he was treated as an outpatient by a nurse in a private community health center in the Nyiragongo Health Zone.

180,558<br /> Vaccinated persons<br /> 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 19 May 2018.

80,118,963<br /> Controlled people<br /> 80 entry points (PoE) and operational health checkpoints (PoC)

148<br /> Contaminated health workers<br /> Two live health workers are among the new confirmed cases of Mambasa (non-vaccinated) and Vuhovi (vaccinated).<br /> The cumulative number of confirmed / probable cases among health workers is 148 (5% of all confirmed / probable cases), including 41 deaths.

Source: The press team of the Ministry of Health.

On 2025-06-13 08:49:30, user TU wrote:

From an author of Ref.60: Thank you for your citation of our work on DOCK8 (Life Sci Alliance, 2021). The structure reported is DOCK8 DHR-1 domain, which binds PI(4,5)P2. I believe that the relevant structure in your context is rather DOCK8-DHR2/Cdc42 reported in another work: DOI: 10.1182/blood-2012-01-407098. Please check it.

On 2021-08-29 19:50:51, user Yvonne wrote:

Based on Pfizer (6 month) study, the vulnerable started getting vaccinated on a great scale in February (USA) if you add 6 months that would put that vaccinated population at August, therefore the question would be asked, once the 6 month time frame of those vaccinated within a specific period, be deemed “unvaccinated” come August? With increasing spike cases/hospitalization in August (USA) and the term “unvaccinated” being used, who are within the description of “unvaccinated”, those never getting a vaccine? Or would the term include those who were vaccinated and now have passed the 6 months? I think August would be more of a complete study, if the term “unvaccinated” group is clearly defined. That would require maintaining that data, tracking the expiration of the 6 months when those vaccinated are spiking in cases. While this is helpful, the public should be shown how the spikes are increasing in August for full transparency and even comparison.

The next spike of population vaccinated in April 2021 (USA) will hit the 6 month cycle in October. Therefore December will show if the spikes in November are from that vaccinated group.

On 2020-04-07 17:56:44, user Pavel Valerjevich Voronov wrote:

https://academic.oup.com/gl... - this article from 2008 year confirms assumptions in regard to blood type, but with SARS-Cov. Please evaluate it too.

On 2021-08-04 18:58:21, user Ghatotpach Pilandi wrote:

Should correct for risks (comorbidity, genetic predisposition to diabetes, etc) and risk-level of job.

Regression analysis can be used because sample size is sufficient. Or some variant of ANOVA

On 2020-10-10 03:18:10, user Ning Wei wrote:

How to apply dose For Fig 3? What is the initial condition for Cp and Ca in Fig.3 ?

On 2021-08-31 15:57:16, user leoniehaimson wrote:

Did you project what weekly testing of 100% of students would achieve in terms of infection reduction?

On 2022-01-10 23:20:22, user Litawor wrote:

The previous version of this preprint additionally described adjusted <br /> analysis with important covariates related to vaccination status and <br /> vaccination timing. Why is that analysis omitted in this version? <br /> Matching does not remove the need for statistical adjustment.

On 2021-02-08 16:35:58, user Cristina Aosan wrote:

Thank you so much and congratulations for this great clinical study ! As physician and practitioner of natural therapy I use propolis from 28 years and was sure it acts in Covid 19 infection. The people to whom we recommended after pandemic started, had very good results, both as prevention and as treatment for those already with symptoms, even for those in a severe condition. My surprise was how fast propolis acts. It's excellent to have such scientific confirmation. Thank you again, good luck further on, and waiting other interesting and useful news like this study.

On 2024-05-06 14:16:22, user DocLee wrote:

How about you break it down by infection versus reinfection? I would think you have the relevant data as you seem to have the history of those previously infected and not infected. But, for some reason, you don't seem to be putting it in these papers of yours.

If you're using the entire population which includes all persons previously infected and those not previously infected, claiming that the number of doses correlates to an increase in infection doesn't make any sense as a good portion of your population has already been infected. Without breaking it down into infection versus reinfection, you really can't make that claim as you're actually looking at initial infection versus reinfection. If the rate of initial infection increases with each dose among those that have not been previously infected, you'd have an argument.

On 2021-08-19 02:48:38, user Sheila Halpenny wrote:

I assume everyone responding here will use the same “logic” to apply to every other poll taken.

On 2021-06-15 08:35:55, user J W wrote:

The two underlying studies are not compatible, they have different outcomes regarding effect of school closures, obligatory masks effect etc. Using them as a base then does not seem plausible. Next, a significant impact which might mimic sesonality is vaccination, any filtering of the effect out? Why a sinusoid should be the right function, why not to model seasonality based on the fundamentals like actual temperature, sun hours proportion of a day and maybe regular school holidays as a proxy for vaccations and holidays? The two studies do not cover a year and do not cover even full switching on/off the government intervention, thus they may transfer other causes to impact of interventions and/or seasonality.

On 2019-08-28 13:55:51, user Larry Parnell wrote:

Among 237 variants in miRNAs, we found rs2291418 in the miR-1229 precursor to be significantly associated with Alzheimer disease. Our in silico analysis and in vitro miRNA expression experiments demonstrated that the mutant G allele enhances the production of miR-1229-3p {Ghanbari Ikram 2016 Sci Rep 6:28387, PMID 27328823}

On 2020-04-29 14:05:10, user Maxwell wrote:

Note the massive conflicts of interest for these "experts." So we are to trust a study whose authors receive money from an industry that will be profiting handsomely from the very thing they are studying? Unfortunately that is the current state of affairs in Academia particularly in the sciences.

For example:

DMW has received consulting fees from Pfizer, Merck, GSK, and Affinivax for topics unrelated to this manuscript and is Principal Investigator on a research grant from Pfizer on an unrelated topic.

Can we also get a full disclosure from Mr. Weinberger on any personal investments he may have in pharmaceutical companies or anything related to that industry.

Can we also get full disclosure on the funding that Yale School of Public Health receives from industry? That includes any and all foundations connected to the pharmaceutical industry.

On 2021-07-26 17:27:59, user Fortu Nisko wrote:

The research should not use PCR or tests derived of PCR for assessing 1-Infection 2-infectiousness 3-illness. If the research depends on flawed data, at its root, then, the conclusions drawn will be no better. First establish what you are actually looking for - an intact viral particle that can be cultured. Further, establish that each supposed transmission be verified using such a method. And, de4fine the actual illness that is supposed to be directly associated with the pathogen you are looking for; that means a syndrome of acute severe respiratory distress. Not a cough or a wheeze; not a fever; not a symptom that is applicable to many other potential causes. So make the causal relationship front and center. Specifically identify and test for the particular causal agent; specifically verify illness caused by that causal agent. Failing that, your research will be for nothing specific - not for a specific infection, not for a specific transmission, not for a specific malady. This should be noted in the strenghts/weakness portion of any research paper produced from your efforts.

On 2022-06-08 17:08:32, user Ted Gunderson wrote:

Should this be considered a scientific study or an advertisement?

What evidence is there that what the authors refer to as "(non-variola orthopoxvirus and monkeypoxvirus specific)" actually causes the disease that is currently being diagnosed all over the world as "monkeypox".

This is a paper funded by Roche that says "Our tests work!"

"ML and DN received speaker honoraria and related travel expenses from Roche Diagnostics."

Roche has gotten lots of press recently about their monkeypox tests.

https://medicalxpress.com/n...