On 2020-01-26 06:35:13, user Wes Wong wrote:

Is the methods supplement available anywhere? I can't find it

On 2020-01-25 02:59:28, user AJ wrote:

Where did you see an "ascertain" rate? Your assumption?

On 2021-05-28 05:42:20, user Karl Elshoff wrote:

Because it supports 17 of the best studies we already have that, "None of the studies established a conclusive relationship between mask/respirator use and protection against infection." 1

1. bin-Reza F et al. The use of mask and respirators to prevent transmission of influenza: A systematic review of the scientific evidence. Resp Viruses 2012; 6(4):257-67

I got this from an article written by Dr. Blaylock titled, 'Blaylock: Face Masks Pose Serious Risks to Healthy', posted by Russell Blaylock, MD 11, 2020. I recommend you read what Dr. Blaylock wrote in its entirety.

On 2021-06-02 15:17:27, user Miglet32 wrote:

Something that could be accounted for by other measures such as distancing or increased handwashing protocols.

On 2020-04-19 10:09:36, user Ratnasingham Edward Shanthakum wrote:

I wonder if the humidity in very cold air facilitate the virus to be dried and suspended and taken further apart. Also would there be any electrical charge on the surface attract it to gas molecules.

On 2020-03-28 16:52:02, user Ben Auxier wrote:

I have sent the following questions to the authors by email:

=============================================================

Hello Dr. Santarpia,

I just finished reading your preprint, and I was wondering if you could clarify the following:

1. Most of the samples had RNA copy numbers of 0.1-0.5 /uL. If I am <br /> performing the back caclulations properly, this means the ct value was <br /> between 37 and 41. What was the ct value of the negative controls, or <br /> did the never reach detection threshold?

2. I cannot find any information regarding negative control samples. I see<br /> that you used no template controls, but I do not see for example a swab<br /> of the inside of a sterile container inside the hospital room to <br /> control for contamination during sampling itself and subsequent sample <br /> processing.

3. I do not know if there is an error in the calculations for your table <br /> (labelled as Figure 2), but almost all of your values have SD that <br /> overlap zero. Additionally I notice that your Figure 1A axis cuts off at<br /> zero, which fails to show the SD values overlapping zero. While I agree<br /> there will not be negative copies of virus in your sample, I think <br /> these SD values show something important about your measurement accuracy<br /> and precision.

I have posted these as a comment on the MedRxiv article itself if you would rather respond there.

-Thanks for your time

Ben

On 2021-08-27 15:48:14, user Kim wrote:

What about those who have never been vaccinated nor had any vaccines?

On 2021-08-26 14:57:06, user JK wrote:

Is anyone really surprised by this?

On 2021-09-15 17:18:14, user Chewbacca wrote:

The point of this study is to assess the natural immunity vs vaccine induced immunity. This study doesn't draw any conclusions on whether getting covid is safer than getting a vaccine. It simply evaluates the protection of people who already had covid.

So generalizability is not relevant because the study focuses on post-infection protection and people who died from covid aren't part of this subgroup. The only conclusion here is that the recovered population is statistically less at risk than the fully vaccinated population.

Selection bias is very far-fetched but might have some minor significance, it's hard to tell.

Information bias can just as well go the other way around. What makes you think that vaccinated people are more likely to get tested? Vaccines have been promoted as a miracle solution, so I'd think fully vaccinated people are less likely to go get tested because they think they're safe.

For cofounding, the fact that the population is younger in the previously infected group actually biases the study in favor of the vaccinated. Younger people go out and socialize more and they go to work every day. They are thus more at risk of contracting and transmitting the virus than elders who stay safely at home.

On 2021-10-19 16:11:02, user BGJ 1 wrote:

Follow the money for your answers. Also, that Kentucky study has been misrepresented badly. That study occurred in May, well before the delta variant hit Kentucky and in a population that was only about 25% vaccinated. It showed that of those that tested positive (about 24,000) about 990 of every 1,000 was not vaccinated or had Covid prior to vaccination. Of the other 10 out of 1,000, 3 had been vaccinated and 7 had Covid previously but were not vaccinated. 7 divided by 3 is 2.33 and from that some people concluded that you were twice as likely to get Covid if you had previously had Covid than you were if you were vaccinated. Very, very much taken out of context... but researchers can easily twist statistics to fit their agenda. Statistics don't lie, but people do.

On 2021-09-24 16:52:23, user Andy Bloch wrote:

It doesn't show that natural immunity is "better" than vaccines, even if there was absolutely no bias. It shows only that 2-dose vaccine-induced immunity waned (during this time period) more than natural immunity. Add a third dose a few months out and the vaccines catch up. A huge advantage of vaccines is the ability to control the dose, and spread it over time. Note that there was a significant increase in the rate of reinfections for people first infected prior to Nov 2020. If you look at Figure 1, and compare it to the rate of infection in Israel at the time, it suggests that people first infected prior to Nov 2020 had 3 times the chance of a reinfection in the study compared to those after. Click here to view some charts I made illustrating this.

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

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

On 2021-09-17 20:03:09, user USA Bottom Line wrote:

Would it be possible to include a fourth "No Immunity" group in this study? It would be extremely interesting to see how a group with no prior infection or vaccination would perform under the same conditions. The authors would be able to compute the efficacy of both vaccination and natural immunity during the study's time period. Perhaps they didn't do this because the population of "no immunity" people has become too small in Israel?

On 2020-04-16 06:06:53, user Hellbound Reaper wrote:

SARS-CoV-2 is the virus name..COVID-19 is the disease name..you can't catch a disease. :P

On 2023-08-13 10:24:43, user Cath Miller wrote:

Why are the "never vaccinated" grouped with those with 1 or 2 doses?

Is there a likelihood that people who reacted badly to 1st or 2nd jab didn't take a third?

On 2021-12-01 22:50:20, user Depp Jones wrote:

"This article is a preprint and has not been peer-reviewed "<br /> 32 times you can find in this article the wording "assume", 10 times assumption and 4 times "we set" and what else ever. Really, you think that will pass a peer-review? And if so apparently only possible in the pharmaceutical or medical industry.

On 2021-12-03 00:07:08, user Nils S wrote:

If it was true that unvaccinated were responsible for 90% of the infections, the incidences in Denmark would not be possible. Denmark’s share of unvaccinated in the population is roughly 1/3 lower compared to Germany. Following the results of the paper, the growth-rate in the exponential function for spreading the virus would be much smaller in DK, which would theoretically lead to much lower infections in DK compared to DE – if the analysis was correct.<br /> However, the incidences (7-day incidence per 100.000) in DE and DK started October 20th at the same level, close to 90. On November 28th Germany peaked with 482 while DK reached 505 and continued to increase. The Danish numbers do not fit to the results of this paper. The incidences should be much smaller due to higher vaccination rates in DK. Thus, the share of unvaccinated does not explain the growth of infections. It rather looks like, vaccinated and unvaccinated spread the virus similarly.<br /> I strongly recommend to test your hypothesis with data from other countries. And furthermore, I have strong concerns with respect to the RKI data used as input for your analysis. Due to the German regulations vaccinated do not test at all – except for a few exemptions. The entire data is heavily biased. UK for example provided much more reliable data. <br /> Best regards<br /> By the way, have a look at this Nature articel: <br /> https://www.nature.com/arti...

On 2021-11-30 07:55:24, user Hartwig Zehentner wrote:

What a tremendous model to prove ones view of life. Models are great, if they do, what they are supposed to do. I have a completely different idea, about the situation: If you force unvaccinated people to do tests for daily procedures or as entry ticket for work. Even if they are asymptomatic. And on the other side estimate even symptomatic (sneezing, cough, etc.) vaccinated people as "negatively tested".. (Example: I had two patients lately with confirmed COVID 19 despite being "fully vaccinated"; if they hadn´t had severe symptoms needing to go to the hospital, they both could have shown their "Vaccinepassport" for a tour through discotheques all night, where unvaccinated people are restricted from entering). And maybe many vaccinated but infected people have only mild symptoms, they surely don´t get tested, because of the green pass...<br /> So i´m very sure you can´t compare the groups of vaccinated and unvaccinated in regard of amount of tetsting. And with the background of vaccinated people with breakthrough infections being at least as infectious as unvaccinated people, for me this blaming of unvaccinated people is only propaganda, reminding me of germays worst times.<br /> Dr. med Hartwig Zehentner DESA EDIC

On 2021-12-02 12:45:22, user drummy_b wrote:

The Study worked with a effectiveness of the vaccines against <br /> transmission between 70% and 40%. Do we have any evidence for these <br /> assumptions? Furthermore, the effectiveness against transmission and <br /> against disease is not clearly separated in the text. The study should <br /> also provide a modelling with 0% effectiveness against transmission, <br /> then we could see, what matches best with the numbers we have in the real<br /> world.

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

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

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

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

On 2025-02-22 17:25:17, user Shawn M wrote:

The study's questionnaire has significant design flaws. The main issue is how the questions are worded - they repeatedly ask about 'health conditions that you have had as a result of vaccine injury.' This phrasing assumes vaccines caused these health problems before even asking the question. It's like asking 'When did you stop stealing?' instead of 'Have you ever stolen anything?'<br /> This problematic wording can influence how people respond in two ways. First, it might lead people to automatically connect their health issues to vaccines without considering other possible causes. Second, by focusing only on vaccine-related problems, the questionnaire misses important information about people's overall health that could explain their symptoms.<br /> These issues make it difficult to trust the study's findings because we can't tell if the health problems reported were actually caused by vaccines or if they happened for other reasons that weren't explored.

On 2020-04-25 16:58:34, user Mike wrote:

As a reminder, medrxiv.org displays this on their opening page:

Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

(I added the emphasis)

On 2020-04-24 05:20:43, user Olexiy Buyanskyy wrote:

Where is the zinc? Zelenko pointed that zinc is required!

On 2020-08-11 14:22:58, user David Curtis wrote:

Hi.

Just to say that you might want to consider citing this paper, which also analysed exome sequence data from ADSP:

https://onlinelibrary.wiley...

Regards

• Dave Curtis

On 2021-07-26 17:44:49, user Fortu Nisko wrote:

From expected results.

We intend to present the evidence in three distinct packages: study description, methodological quality assessment and data extracted. We intend on summarising the evidence and drawing conclusions as to the quality of the evidence.

Fair enough. A ruthlessly non-politiccal assessment of the quality of scientific evidence will be the most significant portion of the research. Perhaps you might add to the discussion portion of your research paper the impact of basing policy on evidennce that does not meet the standard for policy-grade evidence. This is a very important discussion. Policy-makers seem to be ignorant of the standards necessary to draw conclusions that then can translate into sound policies for public health. They seem to have fallen into the trap of self-perpetuating policies that become untethered from an assessment of the quality of evidence.

Wishing you luck and good fortune in your pursuit of a worthy goal re quality of evidence.

On 2021-11-09 13:00:01, user ingokeck wrote:

Dear Authors, two Questions:

(1) You state: "Partly vaccinated was defined as having received the first dose of a <br /> 2-dose schedule with a time since vaccination of at least 14 days." So you counted freshly vaccinated persons as not-vaccinated? IMHO this is a bad idea, because in the first 14 days after the 1. dose it is well known that the immune system is impacted by the vaccination and a high risk of testing positive for Covid19 exists. If you count these cases as not-vaccinated, this will skew your results towards higher vaccine effect.

(2) Thanks for plotting the case counts in figure 1. Did you check if there is some temporal imbalance in the cases? It seems the second part of your data interval has a substantial lower infection risk and may have higher vaccination numbers, i.e. you may have data that skews towards vaccinated in the lower risk time, also accounting for part of the measured vaccination effect. Could you please have a look at this as well? Thanks.

On 2021-08-03 11:19:56, user TBV wrote:

1. Since we don’t know characteristics of patients in each arm, these results could simply reflect the vulnerable, with weaker immune systems, being more likely to be vaccinated.
2. The authors throw out roughly 1/3 of the observations in an already small study because viral loads are low. Isn’t it possible these were mostly vaccinated people? So, by cutting off patients to only those with a fairly high viral load we generate the result that vaccinated people in the study have a high load

On 2020-02-10 07:08:01, user ScientistCN wrote:

Only 1099 patients were analyzed, how can we get the significant figure to 0.01%?

On 2020-04-19 19:15:06, user Michael A. Kohn, MD, MPP wrote:

From the 3439 people who showed up for testing, they were able to obtain 3330 valid specimens on which to perform the Premier Biotech serology test. Of these, 50 were positive. That’s 50/3330 = 1.5% . They tried to adjust for the fact that the people who actually showed up were not representative of the county population’s sex, race, and zip code distribution. But the main potential source of error is the accuracy of the test. At a low sero-prevalence like this, a small proportion of false positives can result in a large overestimate. They ran the Premier Biotech test on 30 serum specimens drawn prior to the pandemic and it was negative on all 30. If the error rate on truly uninfected individuals is 0.5%, and the test properly identifies 91.8% of previously infected individuals, then the true sero-prevalence is 1.1%. As the authors say, “Additional validation of the assays used could improve our estimates and those of ongoing serosurveys.” Having reviewed the test accuracy studies of this and other lateral flow immunoassays (http://covid-19-assay.net/ ), I believe we will end up with a true sero-prevalence of about 1% in Santa Clara County. But the authors made a reasonable estimate and did a great job of collecting this data and reporting their results and assumptions.

On 2020-04-24 06:11:48, user JM V wrote:

Oh, and for people who compare this to the flu, here is some lowballing of the disease:<br /> ~5 times higher expected infection fatality rate<br /> ~5 times higher expected infection rate w/o control measures<br /> Multiply those out for me please.<br /> I think that is a comparison.

On 2020-04-18 16:15:43, user spacecat56 wrote:

In reading the draft report of the study (pre-print, dated April 11, 2020) my predominant thought was, in choosing to respond to the invitation to the study participants are overwhelmingly likely to have self-selected based on their recent prior experience of symptoms that they suspect may have been due to COVID-19 infection.

The draft acknowledges the possibility of this bias but tosses it off as "hard to ascertain". But the draft also says that data on prior symptoms were collected; data which are entirely omitted both from the published analysis and from the published tables.

Because the analysis ignores this factor and because of the potential for this bias to totally dominate the analysis, in my opinion after reading the study draft, we still know effectively nothing at all about the prevalence of infection in the studied population. Accordingly I would expect to vigorously object to any attempt to incorporate the reported results into public policy and planning.

I would urge the study team to bend their efforts to addressing this deficiency. At a minimum, I suggest, the report should include the withheld prior-symptoms data. Preferably, some efforts should be made to deal with the difficulty of estimating the bias. Perhaps it would be helpful to subdivide the sample data based on yes/no prior symptoms and analyze each subset?

On 2020-04-24 05:00:13, user tom wrote:

And it works out to an IFR for NYC of at least 0.56% (counting diagnosed covid deaths only), 0.85% (including undiagnosed probable covid deaths), to 1.07% (all excess deaths). One more piece of evidence indicating that Stanford's test kits, methods, and/or analyses here led them to an IFR range (claimed 0.12-0.2% if not lower) that's about 5x too low

On 2020-04-22 16:02:39, user Texas Longhorns wrote:

The research paper does not indicate how many of those that participated had already been tested for Covid and what those test results were.

If they over sampled people that had already tested positive and recovered of course you will get a higher rate of positive antibodies. That would not be indicative of the general population.

There is also the problem of false positives because the test can trigger for the common cold that is also a coronavirus.

I don't think this research passes muster as any reliable indication of antibodies in the general population and should absolutely not be used as a basis to reopen businesses and large public gatherings.

Having antibodies to one strain of the virus may not give you any immunity to the more than 8 strains of Covid we know are out there.

Even if the test results are accurate at 2% that is nothing and you need at least 60% solid immunity to consider any large population to have herd immunity protection.

On 2020-04-19 17:16:57, user Fhnuzoag wrote:

There is unfortunately little reason to think data is even partially correct.

On 2020-04-20 23:15:57, user Yaud Xatrixer wrote:

What is the maker of the testing kit? What was the specificity of it?

On 2020-04-18 11:58:31, user Mortal Wombat wrote:

Bear in mind that they actually found a 1.5% infection rate.

Their adjustment upward in the rates came from<br /> a) Weighting for demographics because Hispanics and Asians responded in much smaller numbers -- while the much lower rate of interest in those populations suggests something far from a random sample among them.

b) They think their estimate of the test's accuracy needs to be weighted against the manufacturer's.

It's no wonder it took them two weeks to publish results that took 15 minutes to come back. Had to figure out how to figure out how to get the numbers up to the level they expected beforehand. Their raw results, using the manufacturer's accuracy estimate, would've given about 1.3%. And that's _before_ accounting for any upward bias due to sample self-selection for people who wanted to get tested because they thought they'd had it already.

On 2020-09-07 15:19:58, user VirginiaBoy1969 wrote:

This appears to look at weekly data, not annual, so you may be reading it wrongly. This is a methodological study, not a risk of infection study.

On 2020-09-14 14:10:20, user AlwaysThinking wrote:

You might find this insightful.

https://www.youtube.com/wat...

On 2021-01-22 12:24:37, user Jeany wrote:

See the final version published by Analytical Chemistry (ACS) (https://doi.org/10.1021/acs.analchem.0c04497) "Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning"

On 2020-05-17 07:28:24, user Robert Ray wrote:

Would this suggest that plasma transplants from recovered patients might supply the responsive T-cells that are missing in severe disease patients?

On 2020-03-27 17:09:13, user Peterson Biodiversity Lab wrote:

So one prediction from the models presented by Miguel Bastos Araújo and Babak Naimi was that of low or no local transmission of COVID-19 in humid tropical countries. They stated, "Much of the tropics have low levels of climate suitability for spread of SARS-CoV-2 Coronavirus owing to their high temperatures and precipitation... human populations will likely be spared from outbreaks arising from local transmissions..." Two weeks or so of further data say that that prediction is not robust--rather, it is proving quite wrong. See attached image... source: https://coronavirus.jhu.edu... https://uploads.disquscdn.c...

On 2020-08-31 13:17:21, user Kamran Kadkhoda wrote:

Great work! This suggests the specificity of the Euroimmun assay is around 33%!

On 2025-10-07 13:23:10, user Evolutionary Health Group wrote:

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

Here are our highlights:

The study examines the effect of cigarette taxes on smoking behaviors (participation, cessation, and intensity) and whether these effects differ by polygenic indices and timing of exposure to cigarette taxes.

The authors find that cigarette tax exposure during adolescence is a determinant of lifetime smoking status (cigarette tax is a deterrent of smoking participation), and the effect of cigarette taxes during adolescence is significantly higher for individuals with a higher genetic predisposition for smoking. The authors also find that ordinary least squares models underestimate the detrimental effects of smoking on chronic disease.

Future studies can explore other genetic ancestries and within-family GWAS.

Highlights the importance of youth-targeted tobacco taxes, taking into account the risk of initiating smoking.

On 2020-04-30 00:28:52, user conceitedlawyers wrote:

The paper is very important and interesting. Almost all commentators didn't seem to read the full paper. The author points out that the dosage considered in the in vitro studies is unlikely to be high enough. However, unlike 9/10 commentators, the author of the paper does NOT say that Ivermectin should be ruled out. The author suggests alternatives (e.g combination therapy using a mix of antivirals). I respectfully concur with the author and dissent from the views expressed in almost all comments above.

On 2021-04-13 23:06:29, user disqus_pagO5NCOKq wrote:

From the abstract above: "After the second vaccination, 31.3 % of the elderly had no detectable neutralizing antibodies"... does that mean the vaccination offers NO benefit to 1/3 of the "elderly"?

On 2020-11-03 05:06:24, user KOTTAISAMY K wrote:

Hoe to download the dataset from Taiwan's National Health Insurance Research Database (NHIRD).kindly share the dataset link or share the dataset. its very useful for My Research works. Otherwise share the dataset to mail. THANK YOU..

On 2021-08-23 04:17:45, user Anon wrote:

How about selection bias? Vaccinated people take covid more seriously which would lead to less infections.Not to mention this study was before Delta took over so the results are irrelevant

On 2021-07-23 21:59:46, user Vuong Trieu wrote:

This paper is now published at

https://www.openaccessjourn...

On 2021-02-09 15:09:34, user Gemma Quinn wrote:

i would say Colchicine should be considered and to avoid steroids for chronic situations

On 2022-01-13 18:25:17, user Mackenzie Lee wrote:

I think it's somewhat difficult to make solid claims re incident rates, etc, due to self-reported/-selected data collection via a Facebook site dedicated to survivors of COVID. The rapid data turnaround is nice of course, but a follow up with random sampling will be needed to substantiate claims.

On 2020-03-25 15:31:18, user Sinai Immunol Review Project wrote:

These authors compared the ABO blood group of 2,173 patients with RT-PCR-confirmed COVID-19 from hospitals in Wuhan and Shenzhen with the ABO blood group distribution in unaffected people in the same cities from previous studies (2015 and 2010 for Wuhan and Shenzhen, respectively). They found that people with blood group A are statistically over-represented in the number of those infected and who succumb to death while those with blood group O are statistically underrepresented with no influence of age or sex.

This study compares patients with COVID-19 to the general population but relies on data published 5 and 10 years ago for the control. The mechanisms that the authors propose may underlie the differences they observed require further study.

Risk stratification based on blood group may be beneficial for patients and also healthcare workers in infection control. Additionally, investigating the mechanism behind these findings could lead to better developing prophylactic and therapeutic targets for COVID-19.

On 2022-03-01 12:10:22, user Eric Fauman wrote:

There's a reason we use 5e-8 for detection of significant GWAS hits and that's because below that you're swamped with associations that are likely not real. You shouldn't do pathway enrichment on genes identified from SNPs at 1e-6; the results are likely meaningless.

On 2020-08-23 18:52:01, user Michael Shodell wrote:

Greatly enjoyed this paper as the logic, assumptions, and<br /> analyses are very-well described and readily followed. This also enables good critical assessments<br /> of the range of confidence to place in the numbers at which the author<br /> arrives. HOWEVER – by ignoring<br /> everything other than the sedentary in-flight, non-perambulating and generally<br /> observant passengers (see excerpts below), the author may have missed the<br /> greatest risk areas of flying.

For instance, when disembarking at the destination, the more<br /> crowded the plane (eg. a plane with middle seats occupied), the riskier this<br /> part of travel. I can tell you from recent<br /> experience that for up to 10 minutes passengers crowd the aisles awaiting disembarking<br /> and, being the flight conclusion, often with masks at half-staff or barely<br /> covering the face at all.

Probably similar consideration for use of toilets and aisle<br /> movement during the flight.

106 We focus on a particular passenger who is traveling<br /> alone, and assume that the primary

107 infection risk for this passenger arises from other<br /> passengers in the same row. We further

108 assume that additional risk arises from passengers in<br /> the row ahead and row behind. For two

109 reasons, we treat the risk posed by other passengers as<br /> negligible …

… we treat the risks associated with boarding

119 the aircraft, leaving the aircraft, visiting the<br /> lavatory, and touching surfaces in

120 the passenger cabin, as second-order effects.

On 2021-02-22 23:08:15, user Meg Beller wrote:

HOW do I get a neutralizing antibody titer test post Pfizer vaccine to see how my immune suppressed body responded?

On 2020-04-03 16:05:53, user John B wrote:

This is correct. In Hubei, daily deaths were not Gaussian. They were not symmetric about the peak date, rather there was a slower decay compared to attack (longer tail). There are better sigmoidal functions than erf. This study could probably be significantly improved. Also, holding some parameters from a Hubei fit constant in application to other geographies could address the issue with under-predictions from early-stage data, as is the case essentially everywhere in the United States. See https://twitter.com/JohnBur... for a peak at a similar-in-spirit but petters better-done estimates for several European countries.

On 2020-04-03 17:03:45, user just maybe wrote:

There are SIR models available that are more thorough.<br /> E.g. (Researchgate)

Batista, Milan. (2020). Forecasting of final COVID-19 epidemic size (20/04/03).

On 2020-04-01 16:28:50, user Erik Likness wrote:

Also, looking for the modeling methodology... Thank you.

On 2020-05-19 16:26:56, user Wizard of Oz wrote:

This study claims to compare the risk of dying of COVID19 to the risk of driving a car. It does so by assuming the former can be measured by the number of deaths that occured in a given timeframe divided by the population size in M. That is an utterly misleading metric. First of all, the data for COVID19 is incomplete (the pandemic is not over yet). Also the study does not take into account that up to 80% of the population can get infected if the virus is left unchecked, and that this has secondary effects causing many more die for lack of treatment. In conclussion the validity of this study's conclusions is highly doubtful.

On 2020-03-14 06:52:08, user Muhammad Yousuf wrote:

Hypokalemia is caused by SARS-CoV-2 virus due to its affinity for the Angiotensin Converting Enzyme (ACE) receptor that is present in the lungs, heart, blood vessels and the gastrointestinal tract of humans. It has been suggested from animal experiments that medications inhibiting this receptor (called ACEI or ARBs) could be a potential management strategy(1-2). Because ACEI and ARBs are medications mainly use for high blood pressure and would lower the BP, it is recommended that these medications should at least be used in patients with COVID-19 who are already suffering from hypertension or whose BP is not lower than 100 mm Hg systolic.

It would also be interesting to know the recovery and death rate of COVID-19 patients with hypertension or heart failure who were already using an ACEI or ARB medications compared with those who were not on suchmedications.

Abbreviations: ACEI= Angiotensin Converting Enzyme Inhibitors, ARBs= Angiotensin Receptor Inhibitors, BP= Blood pressure

References<br /> 1. Gurwitz D. Angiotensin receptor blockers as tentative SARS-CoV-2 therapeutics. Drug Dev Res. 2020 Mar 4. doi: 10.1002/ddr.21656. [Epub ahead of print]<br /> 2. Dimitrov, D. S. The secret life of ACE2 as a receptor for the SARS virus. Cell, 2003; 115(6), 652–653.

On 2021-10-14 19:09:32, user Dave Green wrote:

This trial was listed as one of the clinical trials being done on Ivermectin on the FDA website. The media has portrayed the use of this drug as completely ridiculous and idiotic. Yet, there are several clinical trials underway to prove or disprove its effectiveness. If its use is so "idiotic" then why would highly educated people bother to study it???

This is an example of one (of several) that shows it is effective and has promise. From what I have read this "effectiveness" increases if it is given early on. Where I live in Canada, if you have symptoms you are just told to self isolate until they become so bad you have to be hospitalized. You are not provided Vitamin D, Zinc, Ivermectin or any other form of treatment that could help prevent you from being hospitalized. Everyone criticizes any study that comes out and nothing can be proven or believed. It is so frustrating.

Thank-you to the people who performed this study. Your efforts to help the world are appreciated, if not by everyone, at least by me.

On 2021-08-28 16:42:57, user MS Simon wrote:

"Ivermectin for Prevention and Treatment of COVID-19 Infection: A Systematic Review, Meta-analysis, and Trial Sequential Analysis to Inform Clinical Guidelines"

Does the American Journal of Therapeutics routinely publish pseudoscience and quackery, or just sometimes?

Most importantly, what would motivate a doctor or a researcher to go to the trouble of creating and publishing a flawed or biased study for a generic drug that costs 1/3 of a cent per dose to manufacture?

On 2021-06-20 12:22:57, user Hlodovic wrote:

Has anyone given consideration to the fact that Ivermectin is administered to animals for intestinal parasites (worms, mainly)? Could it be that the ivermectin used in this study killed some kind of parasite common to most humans, thereby relieving the natural defense system from that fight and allowing it to attack the virus full force. Being already exercised by the battle of the parasites, the defense system would be strong. Suddenly relieving it of that battle could be like when you go in your car, but it seems to require that you give it a lot of extra gas. You realize the parking brake is on and release it. So the car suddenly takes off, throwing you back in the seat.

On 2021-10-05 22:04:39, user Brooke wrote:

It would be useful to know what sorts of samples were used for PCR testing — were they nasal swabs or saliva?

On 2023-11-04 15:16:53, user Clive Bates wrote:

Two problems here.

First is scalability. This doesn't sound like an intervention that would engage many veterans, nor does it seem likely to be affordable or practical at the scale necessary to achieve a turnaround in the aggregate burdens arising from smoking.

Tobacco-related deaths exceed those resulting from homicides, suicides, motor vehicle accidence, alcohol consumption, illicit substance use, and acquired immunodeficiency syndrome (AIDS), combined.

Almost all of that excess mortality is attributable to smoking not nicotine. Tobacco harm reduction approaches may deliver more and sooner - e.g. encouraging migration to smoke-free alternative forms of nicotine use such as vaping.

Second, it is quite possible that veterans with forms of PTSD are benefiting in some way from the functional and therapeutic properties of nicotine. Again, an approach to smoking cessation that does not demand nicotine cessation may achieve nearly all the health benefits of quitting smoking without demanding withdrawal from nicotine use.

The trial could at least consider an additional arm to assess the utility of encouraging vaping for smoking cessation. It might achieve more for less.

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

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

On 2025-04-02 10:00:44, user Md Shahed Morshed wrote:

The published version can be found here: https://doi.org/10.3329/jacedb.v3i2.78642

On 2020-09-18 20:29:54, user David C. Norris, MD wrote:

This paper is fundamentally misconceived:

Biostatistically

This paper apparently arises out of the biostatistical perspective which presently dominates the design and analysis of dose-finding trials in oncology. Yet even by purely statistical standards, it suffers serious shortcomings. Most notably, it looks for an interaction (viz., dose-response) without first demonstrating or ensuring the existence of a main effect. Reference #153 in this paper (Hazim et al. 2020) reported a 5% median response rate in a systematic review of recent dose-finding trials. Would the authors venture to estimate what fraction of their 93 ‘analysis series’ employed a drug with a substantial therapeutic effect? Some indication might be found in what fraction of the treatments unequivocally demonstrated a therapeutic effect in subsequent phase 2 or 3 trials. Adashek et al. (2019) document a secular trend in overall response rate (ORR) observed in phase 1 trials which is “now almost 20%, or even higher (~42%) when a genomic biomarker is used for patient selection.”

Also arguably well within the purview of biostatistics would have been a decision-theoretic framing of phase 1 cancer trials. These trials may be understood as the earliest clinical steps in a learn-as-you-go (adaptive) drug-development process (Palmer 2002; Berry 2004). On such an understanding, aiming to treat early-phase participants at maximum tolerated doses (MTDs) in no way “dictates that an assumption is made … that higher doses are always more efficacious” (p. 4; italics in original). The authors’ use of “dictates” suggests they see something of logical necessity in this, and their further insertion of the logical quantifier “always” only exacerbates their overreach in formulating this central tenet of their study. Even the distinction between a logical assumption and a statistical prior gets lost in the shuffle. To remedy all this, the authors might consider attempting to state formally their understanding of the individual phase 1 trial participant’s decision-problem, complete with its essential uncertainties and some plausible utilities. (Within the community of investigators whom they address in the final paragraph of their Discussion, there is, I believe, broad agreement on the doctrine that these trials have therapeutic intent (Weber et al. 2016; Burris 2019). The authors would do well to take this patient-centered view as their starting point, as opposed to the dose-centered and unitary goal they proclaim at the end of their current Discussion.)

Furthermore, statistics is nothing if not a discipline for “mastering variation” (Senn 2016), and a paper that sets out to question the strict monotonicity of dose-efficacy ought also enquire as to the presence of inter-individual heterogeneity in dose-response. Note that such heterogeneity would tend to attenuate the maximum slope of a convex dose-response in aggregate.

Finally, the absence-of-evidence fallacy is widely appreciated among professional statisticians, yet seems to have been indulged liberally here without any safeguards such as are usually provided by power calculations.

Pharmacologically

Within statistics, there is a doctrine that statistical analysts should always engage ‘subject-matter experts’. But one sees in this paper no sign that any pharmacological concepts—let alone expertise—have been brought to bear on what would seem to be a pharmacological question. At a minimum, in any serious challenge to the ‘MTD heuristic’—as I have called it—one expects to find distinctions between on-target and off-target toxicities. In an analysis that invokes dose-response plateaus (whether these are conceived as approximate or absolute in this paper remains unclear), we ought to find discussion of receptor occupancy and saturation as underlying realistic mechanisms.

To some extent, a neglect of subject-matter knowledge may be embedded in the very form of the present analysis, which tries to deal with its question in aggregate (through statistical techniques such as standardization) rather than in its particulars.

Clinically

In the final paragraph of their Discussion, the authors proffer advice to clinical investigators. In light of the limitations—statistical, logical, subject-matter—catalogued above, this is premature and should be omitted. Any given phase 1 clinical investigator will be considering a candidate drug in its particulars, conditional on a great deal of preclinical data and perhaps even nontrivial PKPD and systems-pharmacology modeling. The authors acknowledge as much (p. 16), seeming to appreciate that they have conducted an unconditional analysis of highly conditioned decision-making. To investigators thus intimately engaged with pharmacologic particulars, the null conclusions from a marginal analysis such as this one can contribute little useful guidance. If it were proposed to submit this work for peer review in substantially its present form, only a statistical audience should be addressed—and then solely with a cautionary note that the finding of a dose-response interaction will not leap out at a statistician from a convenience sample of phase 1 studies in which a therapeutic main effect remains dubious and unexamined. The main lesson of this work is that statisticians ought to investigate questions of pharmacology in their particulars, and with recourse to subject-matter concepts and expertise.

References

Adashek, Jacob J., Patricia M. LoRusso, David S. Hong, and Razelle Kurzrock. 2019. “Phase I Trials as Valid Therapeutic Options for Patients with Cancer.” Nature Reviews Clinical Oncology, September. https://doi.org/10.1038/s41....

Berry, Donald A. 2004. “Bayesian Statistics and the Efficiency and Ethics of Clinical Trials.” Statistical Science 19 (1): 175–87. https://doi.org/10.1214/088....

Burris, Howard A. 2019. “Correcting the ASCO Position on Phase I Clinical Trials in Cancer.” Nature Reviews Clinical Oncology, December. https://doi.org/10.1038/s41....

Hazim, Antonious, Gordon Mills, Vinay Prasad, Alyson Haslam, and Emerson Y. Chen. 2020. “Relationship Between Response and Dose in Published, Contemporary Phase I Oncology Trials.” Journal of the National Comprehensive Cancer Network 18 (4): 428–33. https://doi.org/10.6004/jnc....

Palmer, C. R. 2002. “Ethics, Data-Dependent Designs, and the Strategy of Clinical Trials: Time to Start Learning-as-We-Go?” Statistical Methods in Medical Research 11 (5): 381–402. https://doi.org/10.1191/096....

Senn, Stephen. 2016. “Mastering Variation: Variance Components and Personalised Medicine.” Statistics in Medicine 35 (7): 966–77. https://doi.org/10.1002/sim....

Weber, Jeffrey S., Laura A. Levit, Peter C. Adamson, Suanna S. Bruinooge, Howard A. Burris, Michael A. Carducci, Adam P. Dicker, et al. 2016. “Reaffirming and Clarifying the American Society of Clinical Oncology’s Policy Statement on the Critical Role of Phase I Trials in Cancer Research and Treatment.” Journal of Clinical Oncology 35 (2): 139–40. https://doi.org/10.1200/JCO....

On 2020-04-18 21:04:02, user Katri Jalava wrote:

Manuscript does not include references for the methodology used. Furthermore, the mathematics behind the model is not being presented. More rigorous, referenced comments why you choose to use a model that is not widely used in infectious disease outbreak modelling would be useful, and preferable present the results in parallel with a standard SEIR model. You could also discuss IHME model.

For the parameters:<br /> • I am not sure how you calculated the deaths. If you used Wuhan data, all case fatality numbers need to be revised as China updated its numbers. This is also obvious from your figure 6. There are 61 deaths as per 18 April in HUS (and it does not include all 48 deaths outside hospitals), and ~ this number should be reached only around 1 May. There is something else wrong than just the Chinese number, I think. If I understand correctly from the text that you may have calculated the deaths from HUS data, it goes badly wrong, I am afraid. There is literature how to correct the ongoing outbreak death numbers to get accurate estimates, or use Chinese numbers. Calculating the mortality rates is one of the most challenging things. Even though new cases would stop today, number of deaths would increase for the next 3-4 weeks from the current case load. Simply dividing the number of deaths by total number of cases may only be used post-outbreak. <br /> • Individual characteristics should include underlying illness if possible, not only age. This is probably available from TTR, and there is surely some sort of enhanced surveillance done.<br /> • Would it be possible to estimate the success of movement restrictions based on overall mobile phone data?<br /> • Excretion is by disease severity/age, https://doi.org/10.1016/S14.... This is likely (one of) the reason(s) why the outbreaks are so explosive in the elderly people’s homes. But as the illness is often mild(er) during the first week (when cases infect onward), and it was also noted in the mentioned publication that there was not a difference between severe and mild cases in the initial/peak excretion (but # observations small), this may not need to be taken into account, but would need to be mentioned. Excretion (or lack of it) may need to be taken into account with children.<br /> • Cases should be ideally categorized to travel, community acquired and mass gathering participants as well as household contacts. These all have different time spent in the community before testing and isolation. Help line has probably an algorithm for the cases which could be used.<br /> • Massong 2008 is pretty outdated reference for a contact matrix, there are more recent ones. Note that especially school aged children from abroad may not be valid as there are no boarding schools in Finland.<br /> • Relative infectiousness period is quite short, it is up to a week, please refer to<br /> https://doi.org/10.1038/s41...<br /> • P(infection|virus contact), test more values, this is out of a hat(?) Needs a distribution (gamma) around it.<br /> • P(symptomatic|infection) 50 %, Ferguson’s figure includes mild cases, ie. it is not really asymptomatic, but “non-GP-seeking”.<br /> • P(death|severe, not hospitalized) 20 % seems too low. Please have a look on the elderly home data.<br /> • The assumption that test positive would lead to 0 % transmission is likely quite false. Most of the mild cases remain at their homes (they should ideally be isolated to a hcf, but this is unlikely happening). There are publications describing household cases where this may be estimated. This could and should be assessed ideally from HUS case data.

A positive thing is that your study clearly shows (what was also known from international data) that suppression works well, mitigation is of less use. This is also logically evident when there is not major community transmission ongoing.

On 2021-07-12 13:43:17, user metalhead wrote:

Hi Tobi,<br /> but isn‘t it a correct consequence that one reconsideres his own risk in terms of such findings ? I am not talking about inducing fear but discussing these things

On 2021-12-20 23:18:35, user Nico wrote:

One more comment - it seems the survey was originally designed to look at impacts of covid itself on menstrual cycles - has that analysis been done? It would be useful to mention in this paper as well. If not already done - that seems like a good control: how do the effects of vaccination on menstrual cycles compare to covid itself? People get so focused on effects of vaccination, forgetting that in many cases effects of covid are far worse. Thanks. (Going to go and search now to see what I can find!)

On 2021-07-03 05:01:14, user Covid wrote:

Is this pre-print going to be published on real peer reviewed journals?

On 2023-09-04 21:32:53, user Joilson Xavier wrote:

This study is now published in Nature Communications doi:10.1038/s41467-023-40099-y

On 2020-04-21 19:31:05, user Pierre Balaz wrote:

Just to get all the details : which was the posology of then medications used ? (HCQ and AZT) ?

On 2020-04-22 12:15:25, user Thomas Aquinas wrote:

Yet in a poll of 6000 doctors worldwide who have actually, personally treated CV patients (unlike Birx and Fauci), doctors rated HCQ and Zithromax as the top #1 and #2 drugs in efficacy. (37% HCQ #1, 32% Azithromycin #1).

The effective protocol is already well-established. Drug therapy should begin at the onset of breathing difficulties, not after patients have been placed on ventilators, from which only 20-50% of patients currently survive. Doctors Zelenko and Didier have had success rates of well over 90% when following the standard protocol.

On 2020-04-22 15:03:20, user Eric Hall wrote:

But not a prospective study with a randomized control group. How do we know the HCQ groups weren't just sicker and it was used more like maximum medical therapy. Correlation doesn't equal causation.

On 2020-07-11 04:42:51, user Tom Jarman wrote:

the authors reached the conclusion that masks do not have a significant difference in person-to-person transmission for influenza-like illnesses, yet they still recommend use of masks. What am I missing here?

On 2025-08-07 18:34:27, user Sabir Awad Mustafa wrote:

Peer Review for Preprint (medRxiv)<br /> Title of the Preprint:<br /> Distribution, epidemiology, and antimicrobial resistance pattern of gram-negative bacteria isolated from blood: a retrospective study in a tertiary care hospital, Dhaka, Bangladesh<br /> Preprint Server: medRxiv<br /> Posted: June 26, 2025<br /> DOI: https://doi.org/10.1101/2025.06.25.25330327 <br /> Reviewer: Dr. Sabir Awad Mustafa Mohammedzein, Consultant in Medical Microbiology and Infectious Diseases<br /> The preprint delivers important information about gram-negative bacterial epidemiology and resistance patterns, which cause major healthcare-associated infections globally. The research comes at a crucial time because it addresses the growing problem of multidrug-resistant organisms (MDROs). The authors have gathered extensive data, which they present in an organized manner. The research confirms worldwide worries about antimicrobial resistance (AMR), particularly for Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa<br /> Strengths:<br /> The study presents essential resistant microorganisms together with geographically specific findings.<br /> The study uses well-arranged tables and figures to improve comprehension.<br /> The research properly focuses on MDR organisms together with ESBL production and carbapenem resistance because these issues are both critical and current.<br /> The discussion demonstrates an understanding of worldwide public health consequences. Suggestions for Improvement:<br /> Methodology Clarification<br /> The study needs additional information about how researchers chose their isolates and the specific period they included. Was it retrospective or prospective?<br /> Antibiotic Usage Data<br /> The inclusion of hospital antibiotic usage data expressed in DDD/1000 patient-days would improve the accuracy of resistance pattern correlations.<br /> Infection Control Factors<br /> The study would gain value by examining whether screening and isolation practices formed part of the surveillance system.<br /> Resistance Mechanisms<br /> The study would gain substantial strength through the inclusion of molecular data, which includes bla gene detection and MBL identification.<br /> Statistical Analysis<br /> The study needs more details about the statistical methods used for comparing resistance trends and determining their statistical significance.<br /> Minor Comments:<br /> The first occurrence of each abbreviation, including ESBL, MDR, and CRAB, must be written out in full.<br /> The conclusion needs a better distinction between research results and proposed recommendations.<br /> Overall Impression:<br /> The research provides significant value to the field of AMR and gram-negative pathogens in healthcare environments. The research findings confirm worldwide resistance patterns that emphasize the need for immediate antibiotic stewardship programs and resistance control measures.<br /> The authors should revise their work based on these clarifications to enhance both the study's impact and clarity.<br /> Reviewer’s Professional Statement:<br /> My role as a medical microbiology consultant and hospital laboratory and blood bank director helps me understand the essential importance of surveillance research. My experience as a director of multiple antimicrobial stewardship and infection control improvement projects has shown me that this preprint holds great potential to shape clinical practice after peer review and validation.

On 2021-07-26 09:07:20, user Jörg Hennemann wrote:

Dear authors, I do not get the point: In your raw data (table 1) the percentage of people dying from Corona Delta is 0.7%. All other variations cause 0.9% deaths for infected people. So, how can the risk to die from Delta be higher than for other variants? Where can we see how the "adjustment for age, sex, comorbidities, health unit, and temporal trend of the raw data works? Here in Germany people go wild because of this study, but I can not comprehend it. Thank you very much!

On 2020-09-03 20:23:26, user Mahdi Rezaei wrote:

Please see the demo results of this research in our 2-minute video clip below: <br /> https://youtu.be/FwCP2ySDshE<br /> I hope you like it. Your valuable comments/advice will be highly appreciated.

On 2020-05-02 06:26:29, user Jasmin Zessner wrote:

How come the authors only looked into countries most affected by SARS -COV-2 while ignoring the ones where lockdown was effective (Austria, Germany) and extrapolate that “lockdown is not effective in western Europe”

On 2021-07-06 06:43:05, user Fat wrote:

Someone please correct me if I'm mistaken, but this study relates only to T and B cell antibody reactions to the spike protein. It says nothing about all the other antibody proteins that the disease might have induced to differentiate and create variants, no?

On 2021-09-11 14:15:42, user TheBonesm wrote:

Exactly this. The CDC's page for VAERS states "It is not possible to use VAERS data to calculate how often an adverse event occurs in a population," however that is exactly what the authors have done. I am sure this will be caught in peer review.

On 2022-01-12 11:43:46, user kdrl nakle wrote:

There is nothing in this paper worth beyond what is already expected. The numerical predictions will likely be erroneous. I have no idea why would anybody want to write the stuff like this that wil be outdated in two weeks time.

On 2020-12-28 18:07:37, user Rogerio Atem wrote:

The 3 preprints of this series on COVID-19 epidemic cycles were <br /> condensed into a single article that summarizes our findings using the <br /> analytical framework we developed. The framework provides cycle pattern <br /> analysis, associated to the prediction of the number of cases, and <br /> calculation of the Rt (Effective Reproduction Number). In addition, it <br /> provides an analysis of the sub-notification impact estimates, a method <br /> for calculating the most likely Incubation Period, and a method for <br /> estimating the actual onset of the epidemic cycles.

We also offer an innovative model for estimating the "inventory" of infective people.

(Revised, not yet copy-edited)

https://doi.org/10.2196/22617

On 2020-04-06 11:57:49, user Sinai Immunol Review Project wrote:

Main findings<br /> It has been previously reported that COVID-19 patients exhibit severe lymphocytopenia, but the mechanism through which this depletion occurs has not been described. In order to characterize the cause and process of lymphocyte depletion in COVID-19 patients, the authors performed gross anatomical and in situ immune-histochemical analyses of spleens and lymph nodes (hilar and subscapular) obtained from post-mortem autopsies of 6 patients with confirmed positive viremia and 3 healthy controls (deceased due to vehicle accidents).

Primary gross observations noted significant splenic and LN atrophy, hemorrhaging, and necrosis with congestion of interstitial blood vessels and large accumulation of mononuclear cells and massive lymphocyte death. They found that CD68+ CD169+ cells in the spleens, hilar and subscapular LN, and capillaries of these secondary lymphoid organs expressed the ACE2 receptor and stain positive for the SARS-CoV-2 nucleoprotein (NP) antigen, while CD3+ T cells and B220+ B cells lacked both the ACE2 receptor and SARS-CoV-2 NP antigen. ACE2+ NP+ CD169+ macrophages were positioned in the splenic marginal zone (MZ) and in the marginal sinuses of LN, which suggests that these macrophages were positioned to encounter invading pathogens first and may contribute to virus dissemination.

Since SARS-CoV-2 does not directly infect lymphocytes, the authors hypothesized that the NP+ CD169+ macrophages are responsible for persistent activation of lymphocytes via Fas::FasL interactions that would mediate activation-induced cell death (AICD). Indeed, the expression of Fas was significantly higher in virus-infected tissue than that of healthy controls, and TUNEL staining showed significant lymphocytic apoptosis. Since pro-inflammatory cytokines like IL-6 and TNF-? can also engage cellular apoptosis and necrosis, the authors interrogated the cytokine expression of the secondary lymphoid organs from COVID-19 patients; IL-6, not TNF-?, was elevated in virus-infected splenic and lymph node tissues, compared to those of healthy controls, and immunofluorescent staining showed that IL-6 is primarily produced by the infected macrophages. In vitro infection of THP1 cells with SARS-CoV-2 spike protein resulted in selectively increased Il6 expression, as opposed to Il1b and Tnfa transcription. Collectively, the authors concluded that a combination of Fas up-regulation and IL-6 production by NP+ CD169+ macrophages induce AICD in lymphocytes in secondary lymphoid organs, resulting in lymphocytopenia.

In summary, this study reports that CD169+ macrophages in the splenic MZ, subscapular LN, and the lining capillaries of the secondary lymphoid tissues express ACE2 and are susceptible to SARS-CoV-2 infection. The findings point to the potential role of these macrophages in viral dissemination, immunopathology of these secondary lymphoid organs, hyperinflammation and lymphopenia.

Limitations<br /> Technical<br /> A notable technical limitation is the small number of samples (n=6); moreover, the analysis of these samples using multiplexed immunohistochemistry and immunofluorescence do not necessarily provide the depth of unbiased interrogation needed to better identify the cell types involved.

Biological<br /> The available literature and ongoing unpublished studies, including single-cell experiments of spleen and LN from organ donors, do not indicate that ACE2 is expressed by macrophages; however, it remains possible that ACE2 expression may be triggered by type I IFN in COVID-19 patients. Importantly, the SARS-CoV-2 NP staining of the macrophages does not necessarily reflect direct infection of these macrophages; instead, positive staining only indicates that these macrophages carry SARS-CoV-2 NP as antigen cargo, which may have been phagocytosed. Direct viral culture of macrophages isolated from the secondary lymphoid organs with SARS-CoV-2 is required to confirm the potential for direct infection of macrophages by SARS-CoV-2. Additionally, it is important to note that the low to negligible viremia reported in COVID-19 patients to-date does not favor a dissemination route via the blood, as suggested by this study, which would be necessary to explain the presence of virally infected cells in the spleen.

Relevance<br /> Excess inflammation in response to SARS-CoV-2 infection is characterized by cytokine storm in many COVID-19 patients. The contribution of this pathology to the overall fatality rate due to COVID-19, not even necessarily directly due to SARS-CoV-2 infection, is significant. A better understanding of the full effect and source of some of these major cytokines, like IL-6, as well as the deficient immune responses, like lymphocytopenia, is urgently needed. In this study, the authors report severe tissue damage in spleens and lymph nodes of COVID-19 patients and identify the role that CD169+ macrophages may play in the hyperinflammation and lymphocytopenia that are both characteristic of the disease. It may, therefore, be important to note the effects that IL-6 inhibitors like Tocilizumab and Sarilumab may specifically have on splenic and LN function. It is important to note that similar observations of severe splenic and LN necrosis and inflammation in patients infected with SARS-CoV-1 further support the potential importance and relevance of this study.

On 2020-09-21 08:43:03, user ?????? ??????????? wrote:

The simplicity of the model, together with its generalization, are the<br /> advantages over complex models. Do you know that W. O. Kermack and A. G. McKendrick model can be reduced to the Verhulst equation?

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

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

On 2020-04-28 16:33:17, user Katri Jalava wrote:

Interesting paper, and fascinating model. I was a bit curious of your contact percentages. How do you come up with the numbers? E.g. for CS adult-adult would be reduced only by 20 % by closing the public events. I could argue that it is at least 60 %, especially if you have a look on SF1 in 10.1371/journal.pcbi.1005697. Also, if you have both CS and HO in place, you get 80 % + 20 % =100 % reduction for child-child contact(?).

Getting any data on impact of the closure measures from publications is hard. I think they have tried this in the UK from the case load data. Do you think you could do a telephone survey among Germans? Or if an app company would make a data collection tool where everyone could register their daily contacts during the outbreak, that would be cool. Good luck and thank you.

On 2021-03-29 19:49:55, user killshot wrote:

This paper needs major review. Statins do not "improve endothelial function". If anything they are anti-inflammatory. Also there is very little discussion of randomization. If the group is not randomized minimally with vitamin D levels, the whole study is meaningless.

On 2020-04-22 21:11:52, user Amy Weicker wrote:

Was zinc administered along with the CQ in this study? Not seeing it mentioned.

On 2021-02-14 21:31:21, user Dr. Stefan Pilz wrote:

This manuscript has just been published by the European Journal of Clinical Investigation:<br /> https://onlinelibrary.wiley...<br /> Many thanks for the interest in this publication!<br /> Best wishes,<br /> Stefan

On 2020-07-15 06:52:23, user Philipp Berens wrote:

The paper makes strong claims about the decline of antibody levels and neutralizing antibody titer. While no specific recurrence is made to the trendlines shown in Fig. 1 and Fig. 2A, these seem to underline the message promoted in the media, that antibody levels/titers go down over time and therefore there may not be immunity for a prolonged period of time.

For a paper making such far reaching statements, the statistical part is extremely thin. The trendlines are loess fits obtained with R using a span parameter of 1.5. This produces a fit which is quite obviously off. I extracted the data from the figure and recreated the plot using other parameter settings (see here for twitter post). For span parameters <1, the fit looks much more reasonable and I am sure also formal model comparison would confirm that. In particular, these fits do not predict declining antibody/titer levels after a certain period, albeit with high uncertainty.

On 2023-10-25 00:51:38, user Samina Sultana wrote:

Wonderful research structure! It's very admirable how much detail was provided to illustrate the process by which the literature to support the study purpose was selected. Guiding the readers through step by step process in which eligibility of each paper was determined through meticulous and fully blinded process not only instills trust from the audience but it also validates the credential of the information that has been analyzed and dissected to be included in this paper. I understand that the actual transition practices were vaguely described, but were there any information provided that would help synthesize the outcome of these 10 selected transition strategies already in practice? It would be a useful piece of information to support the purpose of this paper, which is to establish what already exists as a basis for future work on relative effectiveness. Examining the efficacy of these initial topology to highlight the importance of work done in this paper.

On 2021-06-01 00:21:43, user Pat Frank wrote:

"We show here that the mRNA from anti-COVID BNT162b2 (Pfizer) and <br /> mRNA-1273 (Moderna) vaccines is not detected in human breast milk <br /> samples collected 4-48 hours post-vaccine"

Nice, but irrelevant. The worry has been that the mRNA encoded spike protein gets into breast milk (and other tissues).

There does not appear to be any concern that the mRNA itself appears in breast milk. So the paper of Golan, et al., is irrelevant to the concern.

On 2021-07-24 06:42:21, user itellu3times wrote:

Need to compare with background - what is the vaccination rate for Houston, during the period of the study? This may completely dominate the purported findings.

On 2021-09-25 19:07:25, user Peter Dimitrov wrote:

Time frame : 60 days following vaccination; Location: who presented at a single academic institution/Ottawa Heart Centre. Patients were identified by admission and discharge records of the Ottawa Heart Centre. Sample size: 32 patients, 29 of which were male! Median time between vaccination dose and pain symptoms was 1.5 days. Startling findings by themselves, ought to raise curious questions not outright dismissal/withdrawal.

However, obviously the incidence rate based on total MRna vaccines in Ottawa area is waay off. Am curious to know disaggregated sex/age etc data of Myo/peri cases recorded in the exact same time period in all the other hospital treatment centres in Ottawa area?

On 2021-09-22 21:03:39, user Ovi Wan-Kenobi wrote:

where did you get the 1/1000 rate? I can't see it anywhere in the study mentioned.

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

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

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

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

On 2020-12-15 10:58:41, user NK wrote:

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

There are several methodological problems in this study.

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

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

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

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

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

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

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

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

The first study period lasted from February 27 to July 17. Thus, schools were closed for over 70 days of the first study period of 139 days. The infection rates in children at school age in the first study period were rather low (3.6 per 100 000 children per week between in the age group 10 -19 in week 19, 1.1 per 100 0000 children per week in week 25). In the last study period, the infection rates varied between 7 to 17 per 100 000 per week in the age group 10 - 19. Even if these rates are much lower than later weeks that were no studied (after week 42), the results from this second part of the study suggest an increased risk for teachers.

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

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

On 2020-05-03 07:57:39, user Soumi Ray wrote:

http://www.businessworld.in...

On 2020-09-05 15:23:44, user Kwon Seokjoon wrote:

Then, why not even FDA UEA trial for the Saliva test until now (9/04/20020) ???

On 2021-07-10 22:08:06, user Mazzs wrote:

Australia is currently showing good data on precise outcomes for delta variant cases.

On 2021-11-06 02:10:25, user David wrote:

I disagree with your pessimistic analysis. There is evidence that Vaccination after Infection produces Hybrid immunity, along lasting immunity that protects against variants. That will help Iran, now 42% fully vaccinated and rapidly increasing. Additionally, there is positive new from Pfizer, they announced the result of Phase 2/3 trials of Paxlovid, it is 89% effective at preventing hospitalisation in SARS-CoV-2 positive vulnerable cases. There will likely be other antivirals soon. We are close to the end of this pandemic.

Callaway, E. 2021. COVID super-immunity: one of the pandemic’s great puzzles. Nature, 598, 393–394, https://doi.org/10.1038/d41...

On 2022-01-11 17:30:23, user Franciska Ruessink wrote:

Read the study in the link, and on current regulations :https://en.coronasmitte.dk/....<br /> A large part of the unvaxxed oppose to tests as well.

On 2020-08-04 19:47:00, user Kamran Kadkhoda wrote:

The specificity of 85% doesn't support your conclusion...

On 2020-10-16 12:42:55, user Christopher Leffler wrote:

This paper demonstrating the effectiveness of masks was just accepted to the first and only peer-reviewed journal we sent it to--it's pubmed-indexed, both print and online.

On 2020-07-18 17:50:20, user Matthew Almario wrote:

Who is the manufacturer of the UV light?

On 2020-04-28 09:20:22, user Carlos Gaspar Reis wrote:

What hydrogen peroxide concentration was used, 3%?

On 2022-01-28 20:28:06, user Charlie Jones wrote:

Does the background of the person affect their suicidal ideation (ie socioeconomic status, family situation).

On 2023-08-21 16:51:06, user Maria Vanderléia Araujo Maximi wrote:

This review resulted from the graduate-level course "How to Read and Evaluate Scientific Papers and Preprints" from the University of São Paulo, which aimed to provide students with the opportunity to review scientific articles, develop critical and constructive discussions on the endless frontiers of knowledge, and understand the peer review process.<br /> The preprint titled “Differential modulation of attentional ERPs in smoked and insufflated cocaine-dependent associated with neuropsychological performance” associated the cocaine consumption with reduced attentional event-related potentials (ERPs, namely P3a and P3b, indicating bottom-up and top-down deficits respectively. In this study was evaluated these ERPs considering the route of cocaine administration. <br /> This study had the hypothesis that smoked cocaine dependent (SCD) would exhibit reduced modulation of the P3a, while both SCD and insufflated cocaine dependent (ICD) would show reduced modulation of the P3b.<br /> The authors examined the differences in the P3a and P3b potential between SCD and ICD, and their relationship with neuropsychological performance.<br /> Below are some suggestions for revisions pertaining to the various sections of the manuscript.<br /> Abstract: The abstract provides a nice summary of the study.<br /> Introduction: The introduction section would be strengthened by further discussion, such as including a description of differences between schooling and SCD and/or ICD use, and their relationship with neuropsychological performance.<br /> Methods: If possible, it would be important to have information about how long the participant has been a cocaine user.<br /> Results: Descriptive statistics are good, including mean age, biological sex and education for the study group and comparison group. Additionally, if available, the authors are encouraged to include participants’ handedness. Missing data, if any, should be indicated in this results section. <br /> The preprint could be improved by expanding the comparisons and analyzes obtained from data on schooling and use of SCD or ICD. It could also be improved by emphasizing the need for these findings to be known and shared with the scientific community. This way, the authors would be able to analyze schooling and use of SCD and/or ICD, granting a deeper assessment of this information.<br /> Discussion: Limitations of the study have been pertinently included in the discussion section.<br /> The content of this research is very interesting, innovative and may have implications for the relationship between differential modulation of attentional ERPs in smoked and insufflated cocaine-dependent and neuropsychological performance.

On 2020-04-16 08:22:00, user Ben wrote:

Yes, following this logic (afais) full herd immunity should be reached around 600 deaths per Million population. Spain just passed 400. If 40% of Spaniards were infected as of two weeks ago (mortality lag) even a small serosurvey should reveal this.

On 2020-06-05 12:25:29, user skibloo wrote:

Yyes,being B- I'd be interested to know if rh negatives are an inclusion and if so the determination of the study..Again A positive results.

On 2020-06-07 14:24:04, user kenneth katz wrote:

ABO epitopes are post-translational modifications (diifferent patterns of glycosylation). The S protein is highly glycosylated around the region of receptor binding. Could it be the association of severity correlating with glycosylation variation be because the same glycosylation variation is applied to the S sites and affects S function?

On 2023-11-21 02:18:06, user Marco Confalonieri wrote:

The finding that high glucose levels can predict glucorticoids (GCs) benefit surprised most of us. All we who performed the included RCTs thincked to hyperglycemia as an adverse effect of GCs, not paying attention to glucose blood level at admission. Nevertheless, there are several reports pointing out hyperglycemia but not diabetes alone associated with increased in-hospital mortality in community-acquired pneumonia (BMJ Open Diab Res Care 2022;10:e002880). It should be noted that AI doesn't have the same prejudices than human researchers.

On 2021-09-14 21:49:42, user Cengiz Kiliç wrote:

Dear Dr Swedo et al,

We read with enthusiasm your consensus paper. We are looking forward to its publication, since it is very timely and much needed. We believe such a consensus, reached at by an international panel of experts, and using rigorous criteria, will be very helpful to set the main principles for advancing research, in an area where little is known. Such a clinical guideline will limit the circulation of several existing diagnostic criteria sets that have little relevance with the clinical presentation of the disorder. We especially appreciate your (strongly) emphasizing the fact that misophonia is a sound-sensitivity disorder, and not a disturbance of any sensory input.

At our Stress Assessment and Research Center (STAR) of Hacettepe University, Ankara, we have been conducting research on misophonia (as well as other stress disorders) since 2015. Our first study*, which was just published last month, presented prevalence rates on a random population sample, using our own proposed diagnostic criteria (it is a pity that our study did not appear in time to be included in your literature search). Our second study was a treatment study comparing the effects of psychoeducation, filtered music and exposure in 60 misophonic outpatients, which we are preparing for publication. Our follow-up study (of the population-study sample) is still ongoing. We touched upon the limitations of the existing proposed diagnostic criteria sets in our BJPsych paper’s supplement, and would be happy to share our views in more detail (if requested).

Sincerely,

Cengiz Kiliç, Professor of psychiatry<br /> Gökhan Öz, psychiatrist <br /> Burcu Avanoglu, psychiatrist<br /> Songül Aksoy, Professor of audiology

Misophonia Research Group, Stress Assessment and Research Centre (STAR)<br /> Hacettepe University, Ankara

Email: star@hacettepe.edu.tr<br /> Phone: +90-312-3051874

* Kiliç C, Öz G, Avanoglu KB, Aksoy S. The prevalence and characteristics of misophonia in Ankara, Turkey: population-based study. BJPsych Open. 2021 Aug 6;7(5):e144. doi: 10.1192/bjo.2021.978. PMID: 34353403; PMCID: PMC8358974

On 2023-09-09 17:35:30, user Leonardo Fontenelle wrote:

It is refreshing to see scientometrics used for something else than ranking!

While each one has its own objectives, I'd like to point the authors to another study using a bottom-up approach, "Research themes of family and community physicians in Brazil" (https://doi.org/10.1101/202... "https://doi.org/10.1101/2021.12.22.21268269)"), which is approved for publication in the AtoZ journal. Its reference list includes two more articles leading to it.

In brief, we listed the country's family doctors, listed their journal articles, grouped the articles and the corresponding keywords in research themes, and then described the postgraduate trajectories leading to the main themes. Like this new work, ours valued the reproducibility and sharing the analytic code, while inevitably need some manual data curation.

On 2021-09-13 12:12:16, user Patrick Hunziker wrote:

Interesting paper.<br /> Might be useful to discuss it in the light of<br /> https://doi.org/10.33218/00...<br /> and<br /> https://ssrn.com/abstract=3...

On 2022-01-13 01:08:32, user Dr. Marvin Lara wrote:

If it gives a negative efficacy after 90 days. Does that mean it is actually destroying your immune system?

On 2021-08-29 20:48:28, user Corine GeurtsvanKessel wrote:

yes it has been submitted and we are waiting for the reviewers

On 2021-08-29 20:42:48, user Corine GeurtsvanKessel wrote:

Thank you, we will add the raw data. The differences in culture probability when compared to van Kampen et al. can be explained by the timing (very early sampling versus sampling in already hospitalised patients) and the fact that most patients in van Kampen et al. already had mounted an immune response.

On 2022-02-15 21:25:00, user Cabeça Livre wrote:

Introduction

The spread of a novel infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the first epidemic wave. The point of transition between phases I and II is known as the herd immunity threshold (HIT) [...]

Did you mean "between phases II and III"?

On 2020-10-05 16:47:41, user Michael Sibelius wrote:

Very impressive work! Have you done any work on extending this to the second wave? Since your model could fit observed numbers of hospitalisations and ICU cases, it would be really interesting to see what it does for the second round of epidemic, now that children have gone back to school, and many people have returned to work.

On 2020-07-24 16:43:50, user Kamran Kadkhoda wrote:

The correlate of protection is not inferred this way it is typically inferred through prospective vaccine trials in SARS-CoV-2-native volunteers.

On 2020-10-28 18:00:00, user Tomas Hull wrote:

How is herd immunity tested?

On 2020-08-20 10:33:20, user Giovanni Landoni, MD wrote:

here you can find published evidence of reduced 30-day mortality in COVID-19 patients in Italy (from 25 to 2%) https://pubmed.ncbi.nlm.nih... <br /> Decreased in-hospital mortality in patients with COVID-19 pneumonia.<br /> Ciceri F, Ruggeri A, Lembo R, Puglisi R, Landoni G, Zangrillo A; COVID-BioB Study Group.<br /> Pathog Glob Health. 2020 Jun 25:1-2. doi: 10.1080/20477724.2020.1785782. Online ahead of print.

On 2021-01-30 23:05:47, user disqus_uZtSLivn1O wrote:

CFR increases when the rate of unscreened infected individuals increases (you mention this yourself). The proportion of positive tests increased sharply in December; an indicator of a higher incidence of unreported cases. This is not an interesting finding in my opinion.

On 2020-04-02 02:41:56, user H RC wrote:

Is it possible that the right hand side of the fifth ODE in equation (1) has a mistake?, It has "S" instead of "R"

On 2020-05-12 17:17:05, user Michael A. Kohn, MD, MPP wrote:

As I said in my comment on the first version of this pre-print, the authors did a great job of collecting this data and reporting their results and assumptions. From the 3439 people who showed up for testing, they were able to obtain 3330 valid specimens on which to perform the Premier Biotech antibody test. Of these, 50 were positive. That’s 50/3330 = 1.5% . They re-weighted their sample to reflect the county’s sex-race-zip code distribution and reported an estimated county-wide sero-prevalence of 2.8%. In the first version, they miscalculated their confidence intervals. In the original pre-print, they reported 2.81% (95CI 2.24-3.37%); in this one they are reporting 2.8% (95CI 1.3-4.7%). Their new confidence interval is 3 times as wide as that originally reported. This was not delta method versus bootstrapping; it was a simple matter of plugging the wrong numbers (variances) into the well-known Rogan-Gladen formula that adjusts apparent prevalence based on an imperfect test (which the authors apparently re-derived). We have posted an online calculator that calculates the confidence interval correctly: https://www.sample-size.net/prevalence-estimation/

On 2020-05-02 01:07:55, user Alexey Karetnikov wrote:

On the recent episode of the science podcast "This week in evolution", Vincent Racaniello (Professor of Virology, Columbia University, New York) has made a couple of important critical points: 1) You have not performed any actual virus infectivity assays in cells. You should perform plaque assays. Detecting pieces of viral RNA is just meaningless without plaque assays that would reveal the presence of the infectious virus. 2) The cell line you have used, Vero-E6, is deficient in the interferon expression, and it cannot be used for analyzing virus infectivity. These cells can be used for other purposes, e.g., for growing virus stocks, but not for the assays on virus infectivity. Here is the link to this episode: https://www.microbe.tv/twie... And again I would like to emphasize the necessity to change the title. You are not analyzing "pathogenicity", the term that applies to the infection at the organism level. You are only looking at the cytopathic effects in cell culture (and even that is meaningless by itself, without plaque assays).

On 2020-12-19 17:11:21, user Gary Bayer wrote:

As an actuary whose required training includes construction of mortality tables, life tables and life expectancies, I attempted to verify the results. Unfortunately the details of the methods are too vague to be easily followed, so instead I attempted a standard approach to creating life expectancies. Starting with the 2017 US life tables, I explored modifying the "qx's" (probabilities of death in the next year for an individual aged x) but assuming a one time nature of Covid-19, only the specific current age (and perhaps the following age) should be adjusted for any age cohort. Therefore, for an individual age 10, only the qx for age 10, and perhaps age 11, should be adjusted to reflect the impact of Covid-19 on life expectancies. The age adjustment should be reflective of mortality risk at that age. At this point on time, based on the CDC's reporting of excess mortality, there is no evidence of increased mortality for idividuals under the age of 15. In other words, Covid-19 has not changed this cohort of individuals at all.<br /> The best guess that I can make as to what the authors were trying to express is that Covid-19 has, or is expected to reduce the average age at death this year by a year. I do not know if this is true or not but can see some merit in estimating that result.<br /> One final note, I visit the IHME Covid-19 website almost daily. It is a great tool for seeing the current state of Covid-19 in the United States, and a great tool for policy makers to get insights on what they may need to be planning for in the next couple of weeks. However, a simple look at it's various projections for daily deaths clearly shows the naivety of the estimates of what might happen in the beyond a couple of weeks. An adage that I always rely on as an actuary is the results can only be as good as the assumptions--even if the model being used is good.

On 2023-12-19 10:26:31, user Jaspreet Mahindroo wrote:

This article has been published in the Janapanese Journal of Infectious Diseases following peer review and can be viewed on the journal’s website at https://doi.org/10.7883/yok...

On 2020-04-28 03:55:27, user nicky wrote:

CFR data as of 27th April<br /> https://uploads.disquscdn.c...

On 2020-03-20 16:15:46, user Juan B. Gutierrez wrote:

Supplemental material, data, and source code: https://tinyurl.com/USA-COV...

On 2021-07-13 14:03:05, user Olga Mazlova wrote:

“Patients admitted to hospital were eligible for the trial if they had clinically suspected or laboratory confirmed SARS-CoV-2 infection and no medical history that might, in the opinion of the attending clinician, put the patient at significant risk if they were to participate in the trial… Patients with known hypersensitivity to aspirin, a recent history of major bleeding, or currently receiving aspirin or another antiplatelet treatment were excluded.”<br /> So, after having excluded patients with initially extreme blood viscosity values, you left the wide middle part of the normal (Gaussian) curve of blood viscosity value distribution. It means that the trial participants probably had normal or somewhat low or, on the contrary, somewhat elevated – but underdiagnosed - blood viscosity. Why did you prescribe aspirin to the whole range (except extremes and control, of course) – and not only to those predisposed to elevated viscosity of blood?.. It is logical that the dose of aspirin should be increased proportionally to the excess of the blood viscosity values. Patients with initially normal blood viscosity may need only minimal (preventive) doses of aspirin or need none. Patients with low blood viscosity can be at risk of bleeding, so the substance should not be prescribed in such cases. There should be a personalized approach to the patients, with analyzing their blood tests and even tiny individual symptoms.

On 2020-05-07 03:37:58, user sekkai wrote:

The authors fail to declare potential COI.

As shown in the website of the facilities conducting this research, the authors recruited patients for commercial purpose, and each of the patients paid approx. 50 US dollars for antibody testing.

Also, Mr Eiji Kusumi, one of the authors and directors of the facilities responsible for this study, often advocates for the usefulness of antibody testing on television, and could benefit financially from the disclosure of this study.

These two points above were not mentioned in this study, which casts ethical doubts.

On 2021-12-30 12:02:04, user madmathemagician wrote:

Small whole numbers, like "daily new cases and deaths", can not even be expected to obey Benford's distribution.

Zeroes can even not occur in a Benford's distribution, but are numerous in the source data set.

On 2020-07-08 14:37:20, user rede2fly wrote:

Association does not indicate causation. The study has no control for the Covid-Quarrantine-Frustration factor. The author began the project with the intent to show causation and failed. The research was funded by anti-firearm organizations with the same goal.

Why is no one talking about WHO is doing the shooting and WHO is getting shot?

On 2021-08-28 19:27:31, user __ wrote:

Could someone factually explain to a layperson what these results mean?

On 2021-06-09 23:47:14, user Gnash wrote:

Is there any data on any group who received only AZM or only received HCQ?

On 2021-06-10 09:22:10, user cat's eyes wrote:

What were the baseline characteristics of the 37 patients who survived on HCQ compared to the patients who died? From Table 1 patients who survived were generally healthier and younger than those who died. Table 4 should provide adjusted and unadjusted hazard ratios. Also, did you test for interactions between HCQ/AZM and predictors such as age and steroid use?

On 2021-12-21 15:40:13, user aleksj wrote:

For Slovenia, the leading dashboard (and #1 search term in the country) has somehow been omitted https://covid-19.sledilnik....

On 2022-01-10 10:36:43, user Zeph wrote:

If I'm understanding this, it's based on a one day event model. So for example, if one was going to have a wedding, this might give some relevant data about how many unvaccinated people would need to be excluded to avoid one new infection at that event.

It is not calculating the risk over, say, six months - which might contain just that one wedding, or might include going to night clubs every week, or to work every day. Those longer term scenarios would require different calculations.

Is that a fair summary of it's application?

On 2025-10-15 20:46:32, user jpirruccello wrote:

This has been published; please see https://pubmed.ncbi.nlm.nih.gov/38477908/

On 2021-05-15 22:46:36, user sam wrote:

Here is the journal article

https://royalsocietypublish...

On 2021-09-23 16:12:53, user kdrl nakle wrote:

Surprisingly high and in discord with most known researches so the real question here is how good is the data collection on infections.

On 2022-01-27 14:04:35, user disqus_UJiE4jrszi wrote:

One pre-exposure prophylaxis RCT (McKinnon et al.) is missing.

On 2020-10-24 04:40:50, user gr2012 wrote:

I understand that very early use has some advantages.