On 2020-04-21 20:33:30, user Roleigh Martin wrote:

Why was not Zinc added to the dosage, many clinical reports have been made about how critical Zinc level monitoring and Zinc supplementation is to successful use of this Rx.

On 2020-04-22 02:20:27, user Mike wrote:

This was certainly an interesting paper. It's done a lot of work and the findings are notable. IMHO it warrants as much attention as the pro-HCQ study via Dr. Raoult. While it is entertaining, I will add that it is not conclusive, nor without fault. A double-blind study is still required, but it is worth the read.

Observations/Questions:

1. "hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease”<br /> 2. "we cannot rule out the possibility of selection bias or residual confounding”<br /> 3. demographic: 100% male, 66% black, median age ~70 (59 youngest)<br /> 4. uses PSM, which despite a common practice, could be considered controversial (https://gking.harvard.edu/f... "https://gking.harvard.edu/files/gking/files/psnot.pdf)")<br /> 5. Unless I missed it, I didn't see any specifics about how the treatments were administered.<br /> - How long before death were patients treated? <br /> - What was the quantity/frequency of the treatments? <br /> - Were the treatments consistent between hospitals?<br /> 6. The rate of ventilation was less in HC+AZ (half of the HC and no-HC rates). Why was that and what does that suggest?<br /> 7. Although they were statistically insignificant, what was the result of the 17 women not included in the study?<br /> 8. Why does the paper seem to address political points? It seems like the Abstract is editorialized, which I'm not accustomed to. The Conclusions portion (and page after) seeming to address topical issues of the times. Perhaps this introduces my own subjective bias, but I infer potential for analysis/deciphering bias when the study shows awareness of other controversial studies being conducted, rather than being a standalone independent study of its own; essentially, it leaves me to question motivations of the author, rather than that motivation being scientific discovery. I don't mind such commentary in the Discussion section, I'm just not as accustomed to seeing it in the Abstract.

On 2020-04-21 17:35:12, user Udub wrote:

Quite strange study !!! What was the purpose ? .. retrospective study to see if people that were given drugs hcq or hcq + azt (likely people with worrying/severe form of covid at least enough to prescribe meds) died more than people for which it was decided not to give any particular medicine (likely less severe form of covid ... only 50 were given azt on the no hcq group)...

what were the criteria to give or not hcq ? Were hcq / hcq+azt given with the first symptoms or at an already adavanced stage ?

Comparing deaths between people who seemed really sick (they need medication) with people not needing particular medication is a bit confusing ... conclusions show either lack of analysis or partiality

On 2025-11-25 22:51:24, user Radim Skala wrote:

The manuscript attempts to compare the properties of various nebulizers used in PIPAC; however, it contains a number of fundamental methodological, physical, and interpretational shortcomings that significantly reduce its scientific value. Most importantly, there is a complete lack of transparency in sampling – the authors do not specify the number of tested units, their LOT numbers, or their origin. It is furthermore documented that at least one of the tested nozzles was not obtained from the manufacturer but informally from clinical practice, which makes it impossible to control any pre-analytical handling, manufacturing conformity, or damage prior to measurement. In such a situation, the data cannot be regarded as representative or reproducible.

The experimental procedure also contradicts the basic physical principles of aerosolization according to fluid dynamics. Proper spray characterization requires stabilized pressure, a clearly defined distance between the nozzle and the impact surface, perpendicular alignment of the nozzle, and the use of a calibrated reference plane. Interpretation must take into account the differences between full-cone, hollow-cone, and swirl geometries. However, in the manuscript the distance between the nozzle and the impact surface fluctuates, the alignment is not perpendicular, the pressure is not stabilized, and the measuring tools used are not calibrated for scientific use. The consequence of these deficiencies is physically inconsistent results, such as unrealistic spray-angle values.

Another serious problem is the use of a Robert Bosch GLL/GCL laser measuring device intended for hobby use. This is a construction level, not a scientific optical instrument with a declared metrological uncertainty. This type of device is not capable of accurately measuring spray angles or providing a stable reference plane. Scientific conclusions based on data obtained in this way are not valid. Similarly problematic is the presentation of results – the spray photographs are not taken at the same scale or perspective. This fact is entirely obvious when looking at the physical rulers in the images: their relative size differs, the distances between the markings vary, and the images are differently enlarged or reduced. This makes any objective comparison between the nozzles impossible.

A very serious methodological error is the use of an incorrect pressure range for nozzle C. The authors report values of 7.4–18.1 bar (107–262 psi), but the validated manufacturer range is 100–330 psi, i.e. 6.895–22.75 bar. Thus, nozzle C was tested in a narrower range than its specification allows, which fundamentally affects turbulence, droplet size, cone shape, and spray-regime stability. Since pressure is the primary determining variable in aerosolization, this constitutes a fundamental error that renders the entire analysis of nozzle C invalid.

Corrosion is presented in the manuscript in a highly non-objective manner. The nozzles are single-use instruments intended for a maximum of 60 minutes of exposure, yet the authors subjected them to 12 days in an uncalibrated solution with undefined parameters. Such a test has no clinical relevance. Moreover, only the condition of nozzle C is presented, while the internal parts of the other nozzles – rubber seals, epoxy joints, moving pins, or machined metal surfaces that lose their passivation layer during machining – were not shown. It is highly likely that these components would exhibit similar or greater levels of corrosion. Images of the rear machined areas of the other nozzles, where threaded and grooved joints with high corrosion potential are located, are also missing. This selectivity fundamentally distorts the interpretation of the results.

The manuscript also ignores the fundamental issue of hot-spots typical of full-cone swirl nozzles, which produce a full cone with increased central energy density. It is precisely this construction that generates the highest risk of local overdosing and the formation of hot zones (“hot-spots”). By contrast, hollow-cone nozzles with a relieved center and a ring-shaped distribution exhibit lower local maxima and a significantly lower risk of hot-spots. These differences are clinically essential and should have been clearly taken into account in the assessment of aerosolization technology. Failure to address this issue renders the technological comparison in the manuscript incomplete and clinically misleading.

A serious ethical issue is also the undisclosed conflict of interest. At least one of the authors has prior scientific collaboration with the managing director of the company manufacturing Capnopen, which is one of the evaluated products and a direct competitor of nozzle C. This fact should have been stated transparently.

Overall, the manuscript suffers from fundamental shortcomings in metrology, experimental design, physical interpretation, graphical presentation, and transparency. In its current form, the presented data cannot be considered reliable, reproducible, or clinically relevant. If the work is to be regarded as a valid scientific contribution, it is necessary to thoroughly revise all experiments and their presentation.

On 2021-06-22 02:05:29, user GDY AirTech Enterprises wrote:

With recent developments in what we know about the current pandemic, information about the effectivity of air conditioning and ventilation systems are important. Easy access to papers like this is important for the sake of scientists and citizens alike. Knowledge should be accessible.

On 2020-04-29 09:22:52, user eliana miller wrote:

What about the zinc?

That is the way the Hydroxychloroquine works, without it it does not work!

Get the zinc, please!

On 2021-02-06 06:40:50, user David Epperly wrote:

Here's something that addresses Pfizer and Moderna and I agree that the 2nd dose is important. "While durability is improved with a 2 or more dose regimen, dose timing is subject to optimization."<br /> Evidence For COVID-19 Vaccine Deferred Dose 2 Boost Timing<br /> 1. Good efficacy of dose 1<br /> 2. Greater than 3 month durability of dose 1<br /> 3. Double vaccinated population<br /> 4. Dramatically reduce hospitalizations<br /> 5. Save ~ 90K US lives in 2021<br /> https://doi.org/10.2139/ssr...

On 2020-04-12 19:24:03, user Ben Vitale wrote:

Opinion: MIT grad students attempted to sanitize used n95 masks for reuse using Co 60 gamma radiation. The problem they reported was a loss in the ability to capture particles through electrostatic capture after radiation. <br /> Question… was a test for the used n95 masks electrostatic capture ability done before radiation? If so, could the loss of its ability to capture fine particles electrostatically be because of contamination rather than radiation. The problem may be compound and the masks may need to be washed before attempting to sanitize them for reuse. <br /> If the particle capture problem persists after cleaning and radiation, one might want to introduce some static electricity by rubbing a balloon with wool and placing the mask on top of it! This may work?

On 2020-09-13 07:52:10, user OxImmuno Literature Initiative wrote:

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

On 2021-10-20 16:54:26, user helgarhein wrote:

You reported a surprising result: in the group of 51health care workers who were replete (above 75 nmol/l) only 2 took supplements. I would not have expected so many people (49) to have replete 25(OH)D levels in indoor workers in Birmingham (52ºN) in May, without supplements. However we had in the UK an unusually sunny and pleasant spring in 2020. I guess many people used their free time to go outdoors, because it was so sunny and dry, cinemas, restaurants etc were closed and socialising happened mostly outdoors. I presume that the unusual finding of so many people with excellent 25(OH)D levels could be explained by having acquired those levels in the week or two before May 2020. But maybe a longer timespan with good vitamin D supply is needed to make really all immune actions work optimally?? Could this have skewed the curve to make it look U-shaped?<br /> But, as pointed out by Dr. Gareth Davies, the most important observation was missing: the out comes of those infected, the ICU admissions and the mortality rate.<br /> Helga Rhein, ?retired GP, Edinburgh

On 2020-06-27 20:40:02, user many wrote:

Major comments:<br /> The paper’s primary claim is not directly supported by the data shown in the manuscript, due to insufficient statistical analyses. The authors can improve their analyses to support their claim. Describing them below.

Figure 2 is key to supporting the primary claim of this manuscript. As of now, Figure 2a only shows a bar graph for each data point. I would recommend using a box plot that can represent the median, standard deviation, 25, 75 percentile values, etc.

The key sentence that brings out the claim (page 7, last line), uses a Ct> 26. Could you provide a reason for using the cut-off to be 26?

Along with the previous comment, when does the Ct value reach 26 for mild and severe patients? This question can be answered by redoing figure 2b. Currently, the figure shows scattered data points roughly 10. But, as I understand from figure 1a, there is possibly more data than what is represented in figure 2b. Therefore, I again recommend using a box plot in figure 2b to represent the true statistical variation of Ct over time.

To support the claim that symptom severity is more important than Ct or time since symptom onset, the CPE should be higher (with a p<0.01) in severe symptom patients than mild symptom patients, irrespective of the Ct or time since onset. The latter (CPE vs time since symptom onset) needs to be plotted in a box plot for better understanding.

Minor points:

Provide p-value on the graphs.

Use of --% “versus” --% sentence structure is misleading. For instance, in the results section, the last sentence, “… outpatients and hospitalized… are: 47% versus 18%...” Is 47% associated with outpatients? In which case, you’d be contradicting your own claim.

On 2022-01-16 04:06:03, user FreedomForEvar wrote:

I would like to know how many of these people in the Cohorts had previous infections le Natural immunity The Hospitals can tell and which did these people have Delta or Omicron?<br /> https://www.medrxiv.org/con...<br /> Death rate Los Angeles County Omicron 1 died out of 57,000 that is .0018% <br /> I recommend you take a look at this study that actually includes the Naturally immune START Acknowledging What has been around Since the Very beginning of Human life. <br /> Also <br /> Death rates per WHO<br /> 7 days ending Jan 11 <br /> World wide Death rate is .24% USA same time Death rate is .24% Same period For California Death rate is .09% <br /> 1st week of December USA Death rate is .90% per WHO<br /> Data from England and other countries Show that the Vaccinated are Catching Omicron/Delta virus 80% of the time<br /> it's time to figure out why the vaccine for Covid 19 Is no longer working<br /> What in Delta and what in Omicron Is causing this? What in the Vaccine Is causing this?

On 2022-07-15 12:36:40, user Bob wrote:

So what happened with the peer review process?<br /> 238 days have passed, about 2/3rd (66.85%) of a year, or 8 months have passed and no updates. It hasn't been declined and claimed to be wrong, nor has it been approved ...

Either the paper did a proper job or it didn't ....

On 2021-11-29 10:58:19, user Andy Bloch wrote:

This study had just 13 unvaccinated participants with no known prior SARS-CoV-2 infections. To say that it was "underpowered" is an understatement. It's incorrect to conclude "we found no statistically significant difference." Add this paper to the long list of articles that mistakenly interpret statistical significance. The authors and reviewers should read this comment: Scientists rise up against statistical significance.

On 2020-05-16 00:36:41, user Mehdi wrote:

A Stanford whistleblower complaint alleges that the controversial John Ioannidis study failed to disclose important financial ties and ignored scientists’ concerns that their antibody test was inaccurate https://www.buzzfeednews.co...

On 2020-04-21 03:58:41, user David Feist wrote:

The USC study had a slightly different methodology, and has given the same result as the LA County test ie 4.1% of 863 residents had the virus. The lead investigator at USC was Neeraj Sood, a professor of health policy and vice dean for research.

Two tests with the same result. Evidence is mounting...

On 2020-04-20 09:33:22, user mendel wrote:

This reasoning depends on the interpretation of page 6:

The total number of positive cases by either IgG or IgM in our unadjusted sample was 50, a crude prevalence rate of 1.50% (exact binomial 95% CI 1.11-1.97%).

English grammar is a bit ambiguous here, this can be read to mean that both IgG and IgM were required to be positive. The study's mathematical analysis is consistent with this; however, the manufacturer's test instructions are not.

The 95%CI given here does not reflect the CI for the specificity, however; it should really start at 0.

On 2020-08-18 18:07:44, user Eric Vallabh Minikel wrote:

Excellent, important study, with carefully considered conclusions from the authors. Some readers may assume that if plasma NfL can become elevated 2y before onset, then NfL could be used as a prevention trial entry criterion, a primary endpoint, or a basis for deciding which patients are eligible for drug access/reimbursement. Importantly, the authors of this paper do not assert that their data support those applications. I believe there are three key considerations here that should be factored into any clinical application of plasma NfL quantification in pre-symptomatic genetic prion disease: genotype (rapid vs. slow PRNP mutations), age (affects reference range for NfL), and cross-sectional (as opposed to longitudinal) number of people in a prodromal state at any given time. I have written a detailed blog post here: http://www.cureffi.org/2020...

On 2025-11-14 12:18:54, user Kaur Alasoo wrote:

This preprint has now been published at Nature Communications:<br /> https://doi.org/10.1038/s41467-025-63856-7

On 2021-08-27 21:37:41, user Infinite Monkeys wrote:

Why has the updated version of this article removed ~4,000 respondents from figure 1, of whom ~1,000 were PhDs? This affects the results of the survey regarding vaccine hesitancy by education, after it has been reported in the press. An explanation for discarding those results should be provided.

On 2020-04-02 04:55:23, user Sola Grantham wrote:

I would like to see an explanation of why states with lower current rates of growth are projected to have later peaks. This makes sense to me only in the case of herd immunity being the cause of the peak. Then the area under the graph would remain the same. Thus, to reach the critical percentage of population with immunity, a slower rate of infection would lead to a later peak. But if the cause of the peak is the assumed perfect adherence to social distancing, then wouldn't the date of the peak be more related to the date of practical enactment of the social distancing measures?

On 2020-04-03 17:14:59, user Paula Thompson wrote:

OK. While I do like to look at data, I don't understand comments abt this being too simplistic. Are the data too simple, and not fitting reality well, or are they good? Thanks for help.

On 2020-04-06 04:06:46, user Art Mills wrote:

The projections were updated and the numbers appear to be significantly better. But, why are we still projecting 17K in ICU beds as we speak when we know we only have around 3.5K in ICU beds from this nationwide at present? Shouldn't we match what we KNOW?

On 2020-04-10 13:51:26, user steve rubin wrote:

Does anyone know peak hospitalization during the 2017-2018 flu season? From the cdc summary there were 808,000 total hospitalizations with 61,000 deaths and I remember the flu season was pretty long. I wonder how the curves for new cases, deaths, hospitalizations and icu use looked. I remember stories that the hospitals were crowded but I don't remember stories about people dying because there weren't beds or ventilators.

I know that it's unpopular to compare coronavirus to the flu. Underestimating a threat is dangerous and could (and maybe did) lead to delay in ramping up testing and beds and ventilators and other necessary medical resources.

When people were predicting 2,000,000 deaths in the US and then 200,000 deaths I could understand the fears. But now they're predicting 60,000 deaths and it may end up half of that, so I think it's reasonable to make the comparisons.

Comparing situations to past situations is usually our best way to understand how to react. In terms of how contagious and how lethal this epidemic/pandemic is, it now seems that it and the flu are similarly contagious and that covid is much less lethal. The big difference is that we have a pretty big number of people with significant immunity to the flu while it's likely there was little immunity in our population to covid-19. If we end up with 200,000,000 people becoming infected but with only 60,000 deaths, then covid was a fifth as lethal as the flu for 2017-2018 with 3 in 10,000 infections dying vs 14 in 10,000 infections dying from the flu.

However the comparison to the flu can lead to some counter-arguments. For example, the cdc uses a multiplier of ~80 for estimated current flu infections vs confirmed flu infections. Applying that to covid-19 means that we have ~500,000 confirmed cases so we would have had 40,000,000 total infections leaving another 160,000,000 to go assuming 60% of the population for herd immunity. Projecting deaths would mean 17,000 + 68,000 for a total of 85,000. We'll soon know what that multiplier is for covid-19 because there are a number of antibody surveys going on in the US and internationally. You can bet that the same thing will happen for the flu next year and we'll have a more accurate estimate of infections and lethality for the flu rather than the current guesstimates.

A big question is how social distancing will have affected the final number of infections and deaths. It seems so logical that social distancing will curb infections and deaths, but many suggest that it may end up only prolonging the length of the pandemic while not making a significant difference in total final infections and total final deaths. The antibody tests may give us the answer to that as well.

On 2020-05-04 22:56:42, user Research Explained wrote:

Unfortunately there are a lot of statistical challenges with this study so wouldn't put a lot of stock in those numbers. Check out this in depth explanation of the study at www.researchexplained.org

On 2020-11-18 16:11:06, user D Greenwood wrote:

Impressive work. But could the finding anti-S and NAbs declines faster in males than in females simply be regression to the mean? The conclusions sound like males end up with lower anti-S and NAbs than females, but the results you present do not show this - they show M3-6 results much the same for males and females. Maybe if you showed the full trajectory over all visits, and analysed these using multilevel models, this would give some support to your claim. As a second point, please update the manuscript to give all estimates and confidence intervals, regardless of statistical significance, e.g. table 2. This way policy makers can combine your results with those of others and you make a greater contribution to science.

On 2021-06-26 09:53:47, user Maurizio Rainisio wrote:

Once more a paper on the effect of school closure aimed at supporting the strong belief that schools are one of the major causes of the CoViD-19 epidemic, trying to prove hypotheses that are set post hoc in a framework where the very concept of hypothesis testing is meaningless.

The way how inferential statistics is used is embarrassing; the misuse of the word "significant" while no null hypothesis is predefined (nor could be), and, if any were implicit, it would be adapted to the situation post hoc (the parameter k is selected to maximize Student's t).

Causality is inferred, while just coincidence is measured, without any consideration for other possible concomitant events. E.g.: The national referendum involving 25 millions of voters on September 20-21, would prove a better predictor of the increase of the epidemic curve using exactly the same method.

Wording like "The estimated overall impact of schools reopening is quantified in around 227,724 positives" and the header "school related positives" without the benefit of doubt is not a scientifically sound way to approach the issue; statements of this kind should not be accepted by any scientific papers reviewer.

A more careful analysis of the data looking at the changes the Rt parameter (or growth rate) that is the trigger to any increase in absolute number of infections, would show that in most of the regions the school openings happened after clear signals of trend changes provided by a properly computed Rt.

On 2020-03-25 05:18:54, user Sinai Immunol Review Project wrote:

Summary: Based on a retrospective study of 522 COVID patients and 40 healthy controls from two hospitals in Wuhan, China, authors show both age-dependent and clinical severity-dependent decrease in T cell numbers with elderly patients and patients who are in ICU-care showing the most dramatic decrease in T cell counts. Cytokine profiling of COVID patients reveal that TNF-a, IL-6 and IL-10 are increased in infected patients with patients in the ICU showing the highest levels. Interestingly, these three cytokine levels were inversely correlated with T cell counts and such inverse relationship was preserved throughout the disease progression. Surface staining of exhaustion markers (PD-1 and Tim-3) and flow cytometry of stained peripheral blood of 14 patients and 3 healthy volunteers demonstrate that T cells of COVID patients have increased expression of PD-1 with patients in ICU having the highest number of CD8+PD-1+ cells than their counterparts in non-ICU groups.

Limitations: Compared to the number of patients, number of control (n= 40) is small and is not controlled for age. Additional data linking inflammatory cytokines and the quality of the adaptive response including humoral and antigen specific T cell response is much needed. T cell exhaustion study relies on marker-dependent labeling of T cell functionality of a very limited sample size (n=17)—a functional/mechanistic study of these T cells from PBMCs would have bolstered their claims.

Significance of the finding: Limited but contains interesting implications. It is already known in literature that in the context of acute respiratory viral infections CD8 T cells exhibit exhaustion-like phenotypes which further underscores the importance of mechanistic studies that can elucidate how COVID infection leads to lymphopenia and T cell exhaustion-like phenotype. However, as authors have noted, the data does point to an interesting question: How these inflammatory cytokines (TNF-a, IL-6 and IL-10) correlate with or affect effective viral immunity and what types of cells produce these cytokines? Answering that question will help us refine our targets for immune-modulatory therapies especially in patients suffering from cytokine storms.

On 2020-05-06 17:35:54, user Research Explained wrote:

Our group made a general public friendly summary of this study and its strengths and weaknesses. Check it out at: https://www.researchexplain...

On 2025-05-15 16:07:41, user Autoimmune neurology wrote:

This article was published in Frontiers Immunology https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1543781/full

On 2020-02-21 00:19:53, user Leon Yuan wrote:

The link for Supplementary material is not available, please update it, thanks!

On 2021-11-01 14:33:28, user happydog wrote:

This article has now been accepted for publication in Epidemiology & Infection (https://www.cambridge.org/c... "https://www.cambridge.org/core/journals/epidemiology-and-infection)").

On 2022-08-09 02:04:53, user Roel Ceballos wrote:

This is already published. The link to the publication is this https://mjst.ustp.edu.ph/in...

On 2021-04-17 09:20:30, user Anna Kena wrote:

Politically biased?

It is surprising and appears bold to include a category "values" (Werte) in a study of drivers of the Corona-pandemic. And if so, to associate it with only two very restricted indicators: the election behaviour for just one political party (out of six) and the creed Catholic, neglecting the main other creeds Protestants, and Muslim.

You state:

"During the period of intense exponential increase in infections, the proportion of the population that voted for the Alternative for Germany (AfD) party in the last federal election was among the top characteristics correlated with high incidence and death rates."

The obvious question is, what was your motivation to select just one political party for your study?

There are these six parties in the German Parliarment (Bundestag), listed here with their results in the 2017 election: CDU/CSU (32.9%), SPD (20.5%), AfD (12.6%), FDP (10.7%), Linke (9.2%), Grüne (8.9%).

Hence the study seems politically biased which makes its scientific value questionable and spoiles your otherwise interesting work.

It is desirable that you mend this flaw during the peer-review process by considering now all parties and the relevant creeds. As a spin-off you might even explain the currently highest values of infection in Thuringia from the "values" of the gouverning party Die Linke.

On 2020-07-27 06:13:06, user OxImmuno Literature Initiative wrote:

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

On 2020-06-04 09:38:49, user Rosemary TATE wrote:

This is very interesting. However, the most recent report by ICNARC, which is based on 9347 UK patients, suggests that ethnicity is associated with worse outcome in hospital and also with increased hospital admissions.<br /> https://www.icnarc.org/Our-...<br /> They are preparing a manuscript - hopefully it will be out soon.

On 2025-11-05 15:26:49, user Gyula Maloveczky wrote:

Some samples in the GSE86978 and GSE51827 datasets are identical. For example, GSE51827's Cluster_Patient_1 corresponds exactly to GSE86978's Cluster_Brx53.2. In the preprint, these samples appear to show differences in some analyses, while the FASTQ files uploaded to SRA for these two samples are identical (SRR4246525 and SRR1020057 for example are identical except for the header lines).

On 2021-12-12 13:59:45, user Andrew Hayward wrote:

“This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20029)”

On 2021-04-19 16:28:26, user Motti Gerlic wrote:

Happy to share our Final ver after peer review for this preprint which was published in Cell Report Medicine:<br /> BNT162b2 Vaccination Effectively Prevents the Rapid Rise of SARS-CoV-2 Variant B.1.1.7 in high risk populations in Israel https://t.co/Nazw3Og3uq<br /> https://www.cell.com/cell-r...

On 2022-01-21 13:17:53, user Frank wrote:

will this study ever complete peer review?

On 2020-04-20 08:36:31, user Thomas Clarke wrote:

Thanks very much for this extra information. Perhaps the single addition to this paper that would make it more informative would be an as complete as possible description of the cohort statistical characteristics with and without drug treatment, as might be found in an RCT. From your comments here I'd expect these to be fairly well matched in age distribution.

In doing statistical analysis we are applying methods to complex data and evaluation of the results is not always easy, so that supplementary information is always welcome.

Finally I stand by my comment that log(age) is less appropriate for this problem, and would expect 2^(age/7) to be a more appropriate transformed covariate because mortality is commonly expected to <br /> scale with age doubling every 7 years (approximately) and therefore this linearises the otherwise known strong correlation and therefore reduces noise from this.

I realise the methodological difficulty here in handling covariates, and that any ad hoc transformation can be seen as arbitrary. In fact a proper Bayesian approach for an uninformative prior would mean that a one-sided (0 - infinity) covariate v should be coded, as you do, as log(v). But the real world is not as simple!

From the title - I believe "Date" should be "Data"

On 2020-05-18 14:46:30, user OxImmuno Literature Initiative wrote:

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

On 2021-09-01 00:37:59, user Dave Fort wrote:

The link to your article was broken so I found a copy of it on Wayback Machine.

After finding the archived pdf, I realized that your link has a bracket at the end of it. If you edit the link in your post to remove it, it will work.

On 2021-08-26 04:25:01, user glit00 wrote:

Perhaps I'm overlooking something obvious, but why is there no table that shows hospitalisation OR for model 3?

Also, should table 4b be labelled as "model 3" and not "model 2"?

Finally, I think drawing conclusions on "model 3"'s p-values is a bit cheeky...

On 2021-09-09 22:31:22, user Sam wrote:

I'd be very interested to see a similar study conducted in Sweden, given the philosophy they took in the early days of the pandemic and letting it spread. I wonder how many of their population will have longer and stronger immune systems due to this tactic

On 2021-08-26 03:53:13, user IMO wrote:

Interesting study. Funny how little discussion there is from the media or the public health machine about immunity conferred by infection. No mention from on high about extending "passport" privileges to those who have been infected and then chosen not to get vaccinated. What's up with that?

On 2021-08-30 19:37:56, user 0/0 wrote:

It's ironic that so many lay-people from the US are commenting on (and mostly complaining about) a study that shows something contrary to the public narrative. They are clearly not aware of the large number of studies showing the effectiveness of natural immunity that have been published since the first of the year.

To the point, survivor bias is not relevant to the study or the conclusion; it's an attempt to extrapolate, or more accurately to correct for the lack of, alignment with a desired narrative. The study examines cohorts of existing people to determine effectiveness of the sources of immunity in those *already protected* cohorts. These findings do not recommend a course of action for those who are not yet protected - that's an entirely different study, and the explanatory narrative explicitly reinforces the importance of vaccination for those populations.

On 2025-09-15 17:39:19, user KATHRYN KELLISON wrote:

After learning that 52% of fibromyalgia syndrome patients actually have small-fiber neuropathy, I'm really sick of the trope that women's pain is to be blamed on their misbehaving central nervous system over-reacting to normal stimuli.

Those of us who have spent any time in patient support groups for autoimmune diseases fully understand how complaints to our GPs are met with the suggestion that our mighty brains are so powerful they fool us into perceiving pain that we don't really have. Meanwhile, research and prevalence studies show us that 5%-10 % of people have autoimmune disease. Many of those illnesses cause the very anxiety that keeps the patient from being diagnosed and treated.

It's my educated guess that hypocondriasis is still rare and that the other 48% of FMS patients who don't have small-fiber neuropathy have untreated poorly treated Hashimoto's or some other common. Autoimmune disease.

The medical field beads to stop assuming the low diagnostic rate is the same as prevalence. It is not. I have numerous autoimmune conditions that pain that picture in broad strokes; celiac disease Graves' disease, small-fiber neuropathy, POTS, & MCAS. All of these were assumed to have minute prevalence when they are actually all common issues for women.

This unscientific, fantastical mistreatment is far too common. There are serious protocol issues that should be addressed immediately

On 2020-05-07 14:55:07, user Villainess wrote:

Pretty exciting result for what sounds like an otc med in Europe!

On 2020-05-17 21:43:32, user Ricky wrote:

For those who are skeptical, just visit Quota (a website) and read all the anectdotal evidence, in the form of testimonials direct from Covid survivors, about the after-effects of the disease.

On 2020-06-21 12:49:38, user OxImmuno Literature Initiative wrote:

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

On 2021-04-22 07:09:12, user Dimitar Kolev wrote:

Can somebody please explain how they give results of 18-64 years already, but generally Sweden counties still not even call (or just started to call 60+ years old only). Or those are only risk groups, doctors, law enforcement and army? Or what?

On 2020-04-16 11:58:45, user Stef Verlinden wrote:

When will this article be published in a peer-reviewed journal? I think this, so far, is the only RCT study that supports the hypothesis that HCQ can prevent exacerbation of disease in COVID-19 patients with CT confirmed mild pneumonia. If correct, its importance can not be underestimated. In that case, early treatment of high-risk patients with HCQ could lead us the way to a faster exit out of the corona crisis...

On 2020-04-16 12:20:10, user Marlowe Fox wrote:

The tests on the efficacy of HCQ are confounded by multiple variables, including comorbidities, symptom onset, prescription drugs (RAAS inhibitors appear to play a key role in viral intensity), and testosterone/estrogen level, to name only a few.

Geneticists, epidemiologists, and other scientists have long used casual diagrams to clearly show variables that may potentially confound their results (1). The Wuhan study at the very least would need to account for the following:

HCQ <— comorbidities —> recovery<br /> HCQ <— symptom onset —> recovery<br /> HCQ <— drug prescriptions —> recovery

Adjusting for the confounding variable would essentially smooth out the flow of information between the treatment (HCQ) and the outcome (recovery), allowing for the inference of causal effects.

Assuming observable data is not available to adjust for confounding variables, a casual mechanism (mediator) could smooth out the flow of information from the treatment to the outcome (so long as the mediator is not influenced by confounder).

Luckily, multiple in vitro studies have been performed. One study posits that HCQ lowers endosomal pH which ultimately inhibits COVID from binding to ACE 2 and decreasing viral intensity (3).

HCQ —> endosomal pH —>glycosylation of COVID cellular receptor —> ACE 2 binding —> viral intensity —> acute lung injury

Another in-silico study posits that HCQ blocks specific protein sites on the host ACE2 cell, thereby thwarting its attempt to infect it and preventing the cytokine storm (over-reaction of the lymphatic system) that some posit is responsible for Acute Lung Injury (3). So here we have an entirely different causal mechanism:

HCQ —> BRD-2 receptor sites —> cytokine storm —> acute lung injury

Despite these problems, some believe that the p-values obviate the need to control for potentially lurking variables. However, they are subject to myriad influences, known as p-hacking. Whether it is the number of tests performed or the number of comparisons made, it increases the chance of finding a statistically significant p-value (4). Three professional statisticians co-authored a paper reviewing the validity of the Wuhan study (5). There were several issues with the data upon which the two significant p-values were based.

I suppose there is also a pragmatic argument: The p-values, along with existing studies and reports, are sufficient enough evidence to offset any concern for lurking variables in these urgent times. In other words, how much evidence is sufficient to warrant large scale roll-out of a low-cost treatment that may have a beneficial effect, from saving individuals who would have otherwise died to curbing its spread?

The consequences of large roll-out: manufacturing, scaling, distribution chains, and so forth could result in a tremendous diversion of resources. How many pharmaceutical manufacturers even have the capacity to roll out production of this magnitude? What if they all start scaling their labor to produce this particular drug. You can’t just put this genie back into the bottle. Not to mention the scientific energy/intellectual capital that would go to proving or disproving this proposed treatment. And why? Because scientific evidence demanded it? No because a tortured p-value and unpublished/unsubstantiated anecdotal evidence caught the attention of some in the media, and it has been over-popularized as a panacea. What about the risk that HCQ is not an effective treatment despite large investments in cash and resources that have been invested? Do you think the wheels of capitalism turn so easily? Investors will want a return and if that means continually touting an ineffective drug through spurious science, they will continue to do so. What about individuals taking HCQ as a prophylactic, believing themselves to be protected against COVID? Or COVID+ individuals taking HCQ and believing themselves to be cured? Or individuals who think: Well, if I get it—I’ll just take HCQ and be fine. This would increase the spread of COVID. From my perspective, the ignorance to viral transmission and the required precautions is widespread. This is just one more reason not to acquiesce to the new social norms of wearing face masks, social distancing, and abiding by shelter-in-place rules. Here, I think an understanding of cognitive psychology is important to anticipate the future behavior of a society in which a cheap and easy-to-manufacture cure is published in the media.

To sum up, HCQ's efficacy is not sufficiently proven to warrant a widespread roll-out, because it could result in several downstream consequences, from the diversion of resources (both manufacturing capabilities and intellectual capital) to increasing the risk threshold of individuals--who spurious believe in an easy and cheap treatment--thereby increasing the infection rate. One of two things needs to happen. Clinical trials that properly adjust for all potential comorbidities. Or the discovery of a causal mechanism (in vivo), which would obviate the need to control/adjust for confounders. For me, this would tip the utilitarian scales in regard to the potential benefits versus the risks.

References

1. Judea Pearl and Dana Mackenzie. 2018. The Book of Why: The New Science of Cause and Effect (1st. ed.). Basic Books, Inc., USA.
2. https://www.ncbi.nlm.nih.go...
3. https://papers.ssrn.com/sol...
4. https://www.scientificameri....
5. https://zenodo.org/record/3....

On 2021-04-27 19:49:26, user louiea wrote:

The assumption: "we assume constant mask filtration pm over the entire range of aerosol drop sizes." is a bad assumption and supported by the referenced papers. Optimal mask efficiency can only be achieved with N95 masks that are properly worn (no gaps), All other masks types have filtration efficiencies around 50% or less. (ref 69).

On 2023-10-24 03:42:50, user Prasad Babar wrote:

Dear Dr. Bi et al,<br /> This preprint provides valuable insights into the declining effectiveness of repeat flu vaccinations, addressing a critical issue in influenza vaccine effectiveness. The use of real-world data and the exploration of factors such as vaccination timing and prior clinical infections is commendable. The paper's significance lies in its contribution to understanding complex factors affecting vaccine efficacy.<br /> The robust methodology, including the use of observational data and logical theoretical modeling of subclinical infections, supports the paper's conclusions. However, the absence of data on subclinical infections is a notable limitation, and the paper should acknowledge this gap more explicitly and discuss its potential implications for the conclusions.<br /> While the paper is generally well-presented, a simple illustration of the modelling approach would enhance accessibility. <br /> The lessons regarding the influence of the immune system, the importance of monitoring subclinical infections, and the need for empirical studies on subclinical infection rates are valuable. Further research in these areas and the development of future research directions should be emphasized.<br /> Overall, this preprint makes a substantial contribution to the field, challenging conventional vaccine efficacy assessment and emphasizing the potential role of subclinical infections. It provides important insights while acknowledging the need for empirical data on subclinical infections and a more explicit discussion of limitations and practical implications.

On 2020-05-30 01:10:44, user ajaxthegreat wrote:

This should be the final nail in the coffin for lockdowns. In a nutshell, lockdowns don't work, and especially belated ones are in fact worse than useless compared to more moderate NPIs applied earlier in the curve. Thus, ending stay-home orders and reopening most non-essential businesses can and should be done *yesterday* with practically no risk of resurgence of the disease. Higher-risk businesses like restaurants, bars, and nightclubs, as well as other amusements, should be reopened a bit more gradually of course, but once a country is at least two weeks post-peak (almost every country) they can begin reopening those as well, albeit with restrictions.

For masks, they probably do work well (just ask Japan and Taiwan) but confounding may have hampered the finding of any good signal in the noise for these policies beyond the first two weeks, especially since these policies were applied belatedly.

As for schools, closing them (even very briefly and locally like Taiwan did) likely worked in the short term, but more recent data show that reopening them does not seem to carry much if any risk of resurgence. For this particular virus, unlike with influenza, children are not superspreaders, in fact they are far less susceptible and infectious compared with adults, but school closures likely prevented at least some adults from infecting each other, both at school and by effectively forcing parents to work from home temporarily at a critical point in the epidemic curve.

On 2020-05-20 09:31:25, user Reks wrote:

Two comments and one question:<br /> 1. I think your reference 26 got mixed up? ( here: In a recent systematic review we concluded that the evidence in favour of face mask use outside of hospital was weak. 26)<br /> 2. The measures data are not entirely accurate: face masks were made mandatory in Poland on April 16th<br /> 3. Assume that countries tended to close down schools at roughly same epi stages. Your models, however sophisticated, would not be able to tease out the effects of school closures and any limiting factors that are inherent in the course of this epidemic, let's call them "natural" factors for want of a better term. Or would they? If not, should you mention that in the limitations? Can you perhaps check if this is likely to be the case (i.e. closures or other measures tending to be introduced at similar stages across quite a few countries)?

On 2020-03-20 14:09:17, user Bill Bruckner wrote:

How long does it take infected individuals to develop detectable antibodies to SARS-CoV-2?

On 2020-06-05 18:57:05, user Paul Gordon wrote:

Hi, nice work. One minor clerical issue you may want to address is that in Supplemental Table 2, the GISAID IDs for UC1-11 are incorrect (all have the same ID as UC12).

On 2020-06-19 20:14:01, user Marm Kilpatrick wrote:

This paper is now published:<br /> https://www.bmj.com/content...

On 2021-08-12 13:20:30, user Nicolas Gambardella wrote:

Something seems wrong with the tables 3, 4, 5, reporting efficacy. In most cases (Pfizer OR Moderna) is much lower than (Pfizer PLUS Moderna), as if the cases had received both vaccines. In some cases (Pfizer OR Moderna) is higher than (Pfizer PLUS Moderna). Where are the missing cases coming from? And in some cases it is much lower, like Pfizer=5, Moderna=5, Pfizer OR Moderna=1. <br /> Now, this could be the result of the case matching algorithm?

On 2020-04-20 06:30:11, user Brian Coyle wrote:

A study whose assumptions matter greatly, and where social psychological considerations are lacking. The statement "Compared to the rest of the population, students are 66% +/- 12% more likely to transmit the disease" has no reference, and is suspect. A proper definition of "asymptomatic" is lacking. The psych aspect is this: if a school or business faces closure because a single student or employee is found sick, immense pressure develops to hide one's sickness.

On 2022-09-28 22:59:10, user Miles Markus wrote:

With reference to the previous comment, perhaps the use of tafenoquine in humanized mice would shed some light on the matter. See:<br /> Markus MB. 2022. How does primaquine prevent Plasmodium vivax malarial recurrences? Trends in Parasitology 38 (11): In press. https://doi.org/10.1016/j.p...

On 2020-06-01 15:30:23, user Nathan Goodman wrote:

Regarding RJones1’s question about the data: WA Dept of Health provides downloads updated weekly https://www.doh.wa.gov/Emer.... The download is near the bottom of the page.

Timothy Siegel’s comment about the validity of using positive test results as a proxy for prevalence is absolutely correct. Sadly it’s the only data available. Various models use the data to estimate actual prevalence, eg, https://covid19-projections..., and more specifically. the WA estimate at https://covid19-projections...

For what it’s worth, weekly case counts (meaning the number of positive tests) has declined steadily in WA from 2,555 week of Mar 22 to 1,256 week of May 17 (the last week for which the DOH download is reasonably complete). Over the same period, case counts for the youngest group (age 0-19) have increased from 65 to 180.

The pressing question is whether this increase is real or an artifact of testing strategy. Are more kids getting sick, or is it simply that more kids are getting tested.

Dr. Malmgren’s preprint is silent on this question.

On 2021-07-10 10:07:37, user Caio Salvino wrote:

Hi.<br /> In my opinion, it’s impossible affirm that the “assymptomatic” cases was transmiting the virus without verify the cycle threshold of RT-PCR detecting RNA at oropharyngeal swabs samples. Only reporting like positive or negative is insuficient for affirm infectivity.

On 2020-09-24 20:42:31, user Marcus Roscher wrote:

Interesting findings... but one might not agree with their interpretation: strong but late measures as in most countries lead to many also lethal cases and then a sudden case drop. If the tested seropositive group is representative enough to deduce 44-66% infection rate of the population is questionable IMHO. And if so we don’t know what influence it really had on the case evolution (considering possible reeinfections or weak till no immunity with mild and no symptoms) ... so it’s not clear if there is a kind of herd immunity and second in such short time. On the other hand this would mean we would have 400-500 death per 100k population in older societies in order to reach some kind of Heard- immunity. What a price!

On 2024-04-24 21:14:09, user Austin Bessire wrote:

I have personally suffered from TSW and this work is unimaginably valuable from a patient's perspective. Insight as to how there is increased expression of mitochondrial complex I helps legitimize my suffering and provide more understanding as to how I may be able to treat it. I also am grateful to see that abnormalities were induced by glucocorticoid exposure both in vitro and in a cohort of healthy controls to rule out it being solely environmentally caused.

On 2020-04-08 03:48:43, user iBonus iBonus wrote:

The biggest reason why Coronavirus is so easy to spread in the community is that infected persons have an incubation period of about 14 days, and there are no obvious surface symptoms. Many people do not know if they have been in contact with incubators.

The most effective way to implement the mathematical model is to use the smartphone registration app and also to install dedicated terminals in public places such as a library, cinema, school, and gym to record where and when the citizens have visited.<br /> When a person is reported as virus-infected by medical authorities, the system immediately puts all persons who appear in the same place at the same time as the confirmed patient in the past 14 days into an Alert list and transmits it to all terminals.

• 10% public participation of our program, will reduce COVID19 spread by 40% <br /> • 30% public participation of our program, will reduce COVID19 spread by 80%

https://uploads.disquscdn.c...

https://covid2019system.com/

On 2020-05-07 03:52:42, user Alisha Geldert wrote:

We thank the authors for their detailed analysis of a suite of N95 decontamination approaches, with specific appreciation for the direct applicability to medical center needs. We see the manuscript – once published in a peer-reviewed journal – as being an excellent resource for medical center decision makers, as well as those working to implement the decontamination methods. With a spirit of attention to the existing peer-reviewed literature and rigor needed in this crisis, we offer a review of areas where improvements would benefit the study as well as (and more importantly) any readers who may adopt the approaches. The authors are aware of the following major comments summarized below, and are working diligently to provide necessary clarifications and revisions.

1. The UV-PX experimental design and choice of combination approach does not appear to be consistent with evidence on effective approaches for UVGI/UV-C ultraviolet decontamination of N95s, presenting a major concern. To address this, consider providing a reader with clearer justification for the ‘unconventional’ approach by perhaps answering the following questions:<br /> ---Were longer duration UV-PX treatments investigated? The fluence delivered during the 5-minute treatment time is unsupported by the evidence for UV-C decontamination of N95s [Lore et al., 2012; Mills et al, 2018; Heimbuch & Harnish, 2019].<br /> ---It is not clear why the authors suggest coupling of UV-PX with moderate RH heat before testing UV-PX alone, when the benefit of adding UV-PX is not described (perhaps stemming from the very low pathogen inactivation observed with UV-PX alone, as would be expected from the ~50X too low delivered germicidal fluence using this protocol). As the protocol deviates from CDC guidance [CDC, 2020], a rationale and supporting peer-reviewed references would be essential.

2. Important details are missing in the methods section. Please provide key details about the UV-PX setup to ensure replicable research reporting, specifically:<br /> ---Measures taken, if any, to ensure respirators are directly illuminated on both sides. <br /> N95 respirator placement relative to and distance from the light source. As irradiance, and therefore fluence, depends on distance between source and target, this is a critical parameter.<br /> ---Please specify the reflective material used in the UV room, the make and model number of the flame irradiance spectrometer, and whether the irradiance measurements reported in Supplementary Table 3 were measured within the UV room with reflective walls or within an alternative setting. Do the irradiance measurements represent the irradiance at the side of the N95 facing the Xenex UV-PX source or irradiance at areas indirectly exposed to UV light? <br /> ---Please clarify whether the measured irradiance represents the irradiance of one pulse or the average irradiance over multiple cycles.

3. There appears to be a potential issue with the conclusions reported in the abstract: the specific experimental parameters shown to yield high levels of pathogen inactivation (moderate RH heat) were not tested for N95 function, so the following statement might be confusing or misleading:<br /> “High levels of biological indicator inactivation were achieved following treatment with either moist heat or VHP. These same treatments did not significantly impact mask filtration or fit.”<br /> The limitations of the proposed approaches and the need for additional testing should be clarified.

References cited: <br /> 1. Lore et al., 2012: https://academic.oup.com/an...<br /> 2. Mills et al., 2018: https://www.ncbi.nlm.nih.go...<br /> 3. Heimbuch & Harnish, 2019: https://www.ara.com/sites/d...<br /> 4. CDC guidance on N95 decontamination: https://www.cdc.gov/coronav...

On 2025-12-03 08:36:21, user Published wrote:

This paper has now been published: https://doi.org/10.1371/journal.pone.0326344

On 2021-08-14 21:10:03, user Daniele Sardinha wrote:

10.4236/wjv.2021.113004 <br /> Sardinha, D. , Lobato, D. , Ferreira, A. , Lima, K. , de Paula Souza e Guimarães, R. and Gondim Costa Lima, L. (2021) Analysis of 472,688 Severe Cases of COVID-19 in Brazil Showed Lower Mortality in Those Vaccinated against Influenza. World Journal of Vaccines, 11, 28-32. doi: 10.4236/wjv.2021.113004.<br /> published

On 2021-07-10 20:28:13, user Michel Prémont wrote:

Interesting study but I have two questions.

1. The study indicates "honey (1 gm/Kg/day) and Nigella sativa (80 mg/Kg/day)". The quantity of honey: is it 1 milligram/kg or 1 gram/kg ? 1 g/kg is a huge quantity (70 g/day for a 70 kg person.
2. Under what form was the nigella ? Seed, oil, ground seeds....

Thank you.

On 2021-09-16 13:24:58, user Theo Sanderson wrote:

The apparent pattern of back mutations at position 142 is an experimental artefact due to errors in some Delta sequences. It emerges from the fact that Delta has SNPs in the primer binding site for ARTIC amplicon 72 (in a previous ARTIC scheme) which often result in the failure to amplify this amplicon, containing the G/D 142 locus, from Delta samples. Small amounts of contamination from other genotypes (e.g. B.1.1.7) that are amplified normally at this location can then lead to an amplicon here (typically with reduced depth). This results in a final sequence which appears to have a back-mutation at this position, and phylogenetic analyses can tend to group such samples together on trees.

T95I is in this same amplicon.

It is likely that the Ct correlations observed here reflect the fact that the correct G142D call is much more likely to be detected despite the low efficiency of amplification for samples with higher viral loads.

On 2024-02-15 16:26:15, user Goober68 wrote:

How does your method compare to EstiMeth by Freytag et al?

On 2020-10-02 20:40:57, user Juan Mejía Vilet wrote:

This paper is now available at Salud Publica de Mexico 2020; https://doi.org/10.21149/11684 Link: https://saludpublica.mx/ind...

On 2020-04-30 21:06:27, user Tim Lawes wrote:

A great paper by very respected researchers and clinicians, ruined by a bizarre press-release saying COVID-19 'as deadly as Ebola'. Let's take a fact-check on that one:<br /> 1. Case fatality rates not equivalent: Ebola CFR 50-75% in recent outbreaks, not 33% as in COVID-19. If referring to high-income country (HIC) stats only, talking handful cases treated in HIC with Ebola, all working age occupationally fit health workers, CFR ~18% (n=5/27 quoted).<br /> 2. Totally different age of death: Ebola median 30-35 yrs, COVID 80yrs. Ebola 95% deaths <60 yrs, Covid ~10% < 60yrs.<br /> 3. Translate age at death to Years of Life Lost (YLL): comparing age at death profile provided by Doherty et al to Ebola papers, each Ebola death 'costs' 45 YLL, vs. each COVID death costs 1.4 YLL.<br /> 4. Translated to population impact. To exceed an equivalent burden of YLL per capita in West Africa in 2013-16 would require >1 million deaths in UK from COVID-19.

To compare the mortality profiles of Ebola and COVID-19 is at best bad science, at worst an example of misinformation that perpetuates global health inequities. I don't imagine authors intended this, but I'm afraid its this sort of comment that creates hysteria, rather than appropriate responses. As a paediatrician we are seeing children coming to harm from avoiding hospital and not being seen in community due to misjudged risk assessments. A genuine thank you for your contribution to science, but please ensure reporting is responsible.

On 2020-06-28 15:15:20, user Norman wrote:

Thank you very much for your important article. There is an emerging “unseen “ epidemic of COVID-19 induced chronic fatigue syndrome. Do you have any information regarding this ?

On 2020-05-05 18:21:51, user Valerie Natale wrote:

I looked at supplementary figure 1 and I'm not convinced that anyone should be jumping to use the N protein in a diagnostic assay.

It looks like the ELISA for the N protein had MORE false negatives than the ELISA for the S protein (10 vs. 8).

Also, the negatives in the N assay in both systems were all over the place, with at least 1 or 2 giving false positives. The legend doesn't explain what all those lines in the figures are, but the N protein ELISA is in no way as tidy as the N protein LIPS assay.

Why is there no ELISA for ORF8?

Finally, the sample size (15 patients and was very small. They should have done this work on 50+ patients and the same number of controls. Results using small sample sizes can look sooo good, until you pile more data in, and suddenly...it gets messy.

On 2020-10-21 13:51:53, user Bruno Buonomo wrote:

This manuscript is now published in Royal Society Open Science https://royalsocietypublish...

On 2021-07-07 18:10:04, user rusbowden wrote:

Research abounds that shows masks work for #COVID19. Should we use them for the flu too?

Yes, shows this study: https://www.medrxiv.org/con...

from the abstract: "Particularly, our simulations suggest that a minority of individuals wearing masks greatly reduce the number of influenza infections. Considering the efficacy rates of masks and the relatively insignificant monetary cost, we highlight that it may be a viable alternative or complement to influenza vaccinations."

On 2021-09-01 16:46:01, user WGardner wrote:

I would like to know more about how you controlled for fidelity of mask usage? This should consider whether or not people consistently wore masks, and wore them correctly. Having a mask mandate is a poor marker for whether or not masks work as it does not equate to people actually wearing masks.

On 2021-09-15 13:57:08, user Notbuyingit3337 wrote:

Gorski, no conflicts of interest there, right? smh

On 2021-03-21 23:57:56, user M K wrote:

Run a PCR for the moderna mRNA. Did that get transferred as well?

On 2021-06-23 15:59:54, user Alain Tremblay wrote:

Do the authors have more information regarding the seropositive cases. Are these believed to be seropositive due to late phase of acute illness, prior SARS-Cov-2 infection, or prior vaccination? Since the trial recruited well into the vaccination effort in the UK, vaccination status of participants should be reported as well. Thanks for this great effort!

On 2020-05-23 23:03:15, user Hilda Bastian wrote:

I have written a post that includes some criticisms of this preprint after brief review: http://hildabastian.net/ind...

On 2020-07-18 00:57:36, user Kamran Kadkhoda wrote:

Despite other reports such high seroprevalence in healthcare setting highly suggests false positivity. Ideally all positives should have been confirmed by neuralization assay. Since most were mild/moderate/asymptomatic and they admit 50% were confirmed this is an attestation to high false positivity of their screen test. I refer them to the large Wuhan study with 2% sero-prevalence as they confirmed all cases with neuralization. Most positives found here are probably from common CoVs...for the record specificity of 100% is a mathematical impossibility.

On 2020-07-06 18:41:52, user Fatnot wrote:

Unlikely that just zinc supplementation would work,,,a zinc ionophore is also required.. We also have the report from Dr Zelensky, in Rockland County, NY, who treated hundreds with<br /> a combo including zinc and HCQ, resulting that few required hospitalization. The report is anecdotal...but another term for a set of anecdotes is of course DATA And with data and analysis, one can draw conclusions and confidence intervals.

On 2020-05-18 03:32:28, user D J wrote:

University of Washingoton to conduct a study, but no mention of zinc.

https://www.kiro7.COM/news/uw-enrolling-patients-study-test-hydroxychloroquine-azithromycin-covid-19-treatment/JG3X5AFTVZGKLE2CTNH72KCWAM/#continue_below

On 2021-08-09 20:32:15, user KS wrote:

I haven't scrutinized this paper but even if all the results are accepted, the one-line "Conclusions" at the beginning is highly problematic without qualifiers. "Unlikely to benefit"? This study is limited, so the conclusion can't be so broad. Are elderly or long-haulers unlikely to benefit? You've got a 42 day window (seems arbitrary) so if you got the disease 6 months prior are you unlikely to benefit from the vaccination? The study doesn't address any of these things, yet makes a huge leap in its conclusion. This is a pre-print so PLEASE make a conclusion that fits your experiment and data. Because it's likely the only thing the general public will read and it will become the basis for more misinformation.

On 2021-07-19 10:59:49, user Kaja Abbas wrote:

This paper was published in eLIfe on June 24, 2021.<br /> https://doi.org/10.7554/eLife.67023

On 2020-05-27 02:34:42, user Aaron wrote:

It would be a good addition to show the breakdown of patient demographics for those samples included in Figure 4 to show whether there are differences in the samples collected for each clade thus far. If there are any significant differences, those could be just as important as the viral sequence, if not more so. While I see that authors tried to control for these variables, it'd still be a good idea to show this information in a table in the main figures.

Additionally, the differences in the rate of spread for each clade are probably much more attributable to the cities themselves that each clade is primarily associated with rather than any differences in the virus; there are major differences in the infrastructure and movement of individuals depending on the metropolitan area. I don't find it particularly surprising that any viral sequence(s) associated with NYC would spread faster than those found in Washington or Chicago. The differing responses of each city in shutting down public movement will also play a big role here.

On 2020-03-25 03:52:12, user Renee Chan wrote:

Hi Dr Liao, Prof Zhang and Prof Zheng, May I know if you have done any fixation of the cell isolated from BAL before doing the downstream procedure using 10X genomics?

On 2020-04-06 19:59:09, user Virginia Savova wrote:

Are you planning to release the count matrices to crowdsource analytics and speed up the impact of this data on drug discovery? The time is now.

On 2020-06-05 06:44:23, user Valeriy wrote:

Hi! Is there a systematic bias? <br /> I mean that patients firstly have done their samples and then healthcare specialist.<br /> This workflow could affect quantity of epithelial cells collected on each step

On 2022-03-27 17:55:48, user Ludo Waltman wrote:

I have posted a review of this paper at https://doi.org/10.21428/7c....

On 2024-12-06 02:09:34, user xPeer wrote:

Courtesy review from xPeerd.com

Summary

The preprint titled "RGnet: Recessive Genotype Network in a Large Mendelian Disease Cohort" introduces RGnet, a novel tool for analyzing recessive genotypes in large cohorts, focusing on compound heterozygotes and homozygotes. The study applied RGnet to the SLC26A4 gene within a cohort of individuals with hearing loss, identifying significant pathogenic variants and demonstrating the tool's potential for advancing the understanding of recessive genetic disorders. The paper highlights the novelty of RGnet, the methodology involving variant preprocessing, phasing, network construction, and permutation-based enrichment analysis, and presents the results from its application to the CDGC cohort.

Potential Major Revisions

1. Reproducibility and Data Availability:
2. Ensure that the datasets and tools used in this study are accessible. Although the paper mentions the availability of RGnet on GitHub, details about accessing specific datasets (e.g., CDGC data) were not explicit.

3. Example: "RGnet is available from GitHub at https://github.com/jiayiiiZeng/RGnet " (page 1) but does not provide direct links or instructions for data access.

4. Robustness of the Methodological Framework:

5. Explain the justification for the chosen phasing methods (trio-based, read-based, expectation-maximization algorithms) and their combination.

6. Example: "This study employs a combination of trio-based phasing, read-based phasing, and an expectation-maximization phasing algorithm" (page 3). However, specific reasons for selecting these methods are not provided.

7. Statistical Analysis:

8. Provide a more detailed description of the permutation tests used for RG enrichment analysis and why 100,000 permutations were specifically chosen.

9. Example: The paper states that "100,000 permutations were performed" without detailing the basis for this choice (page 5).

10. Ethical Considerations:

11. Include a section discussing ethical considerations, particularly concerning patient data privacy and consent given the sensitive nature of genetic data.
12. There is no mention of ethical reviews or consent processes, which is crucial for studies involving human genetic information.

Potential Minor Revisions

1. Typos and Grammar:
2. Correct minor typos and ensure grammatical consistency. For example:
3. Line 18, page 1: "To address this 18 gap" should be "To address this gap".

4. Line 58, page 2: "research3,4" should be "research" followed by proper citations.

5. Formatting Issues:

6. Ensure consistent citation formatting throughout the text.

7. In the reference section, ensure that all references, such as URL links, are formatted and hyperlinked correctly. For example, repeat the formatting used for URL links like " https://doi.org/10.1101/2024.12.02.24318353 " for other references as well.

8. AI Content Analysis:

9. The paper does not provide any indications of AI-generated content. It appears authentically authored by humans, considering its depth and technical specialization.

Recommendations

1. Increase Transparency in Methodological Choices:

2. Provide a more granular explanation of the methodological decisions, particularly around the choice of phasing methods and permutation tests.

3. Enhance Data Accessibility:

4. Ensure that all datasets and supporting materials are accessible, with clear instructions for researchers wishing to replicate the study or apply the RGnet tool.

5. Incorporate an Ethical Review Section:

6. Add an ethics section discussing how patient data was handled, the consent process, and any relevant ethical approvals obtained for this study.

By addressing these major and minor revisions, the paper can be significantly strengthened, ensuring clarity, reproducibility, and ethical adherence, which are vital for advancing research in genetic studies.

On 2021-02-28 00:56:39, user Kevin wrote:

Still, the vast majority of studies have shown significant increases in survival and with a drug generally as safe as Ivermectin waiting for perfect evidence is deadly and foolish. Remdisivir was approved with much less efficacy and much more side effects (many severe). I find it laughable that we are tip-toeing around with ivermectin but there was no problem at all pushing a drug through approval that hadnt shown a significant increase in survival but, hey, atleast it will help you get out of the hospital faster! - If your lucky enough to survive that is.

On 2021-07-18 15:08:21, user Larry James wrote:

Many physicians in the US are unfamiliar with using HCQ (HYDROXYCHLOROQUIN), since it is not a commonly prescribed medication. I am a physician in this category. In the very beginning of the pandemic, I was curious so I researched HCQ and found it listed as a very low risk QTC prolonging medication (it was in the same risk category as high dose Celexa (citalopram). (QTC is a heart EKG measurement). HCQ can be bought inexpensively without a prescription in many countries and it has been in use for over 30 years. Today, if you look up HCQ on QTC risk medication websites , you will see that it has jumped up two categories of risk, to the highest risk category known for prolonging QTC. This has likely had a chilling impact on its use. One must really consider the rational and legitimacy for this new QTC risk determination, particularly in light of its long history of safe use, its potential benefit an illness which had no other real medication treatment options and the fact that it is a very inexpensive medication. Of further interests is the fact that a fraudulent article was published through an esteemed publication, Lancet, during the beginning of the pandemic, which almost instantly shut down studies that were ongoing at that time.

On 2021-06-03 12:03:42, user Sahan Laboratory wrote:

I think use of HCQ with Glychrryzin will be best for recovery of COVID patient. <br /> This type of study should be combined with other form which will provide best result for upcoming trials. <br /> Suggestion - Use of HCQ with Glychrryzin in treatment of Ventilated COVID19 patient.

On 2020-04-12 04:43:17, user Bárbara Souto wrote:

It seems that the authors want to reinforce an "almost-effect" of chloroquine. They wrote that matched 25 pairs of patients from Changsa, the only place using chloroquine, to compare the 25 individuals who have taken chloroquine, as a kind of case-control nested study. They said they found a difference of 12% and none patient in chlorquine group got worse (with a almost significance. p = 0.074). Well, two groups of 25 with zero outcome in one of them and 12% difference means that only three people in the comparison group got worse. A very small number to consider. But what about the p-value? 0.074 is a very promising p-value, suggesting that the non-significance was just a type II error. We should believe that this p-value is a probability derived from a Fisher exact test. But not. The p-value of a Fisher test from these numbers is 0.234. The 0.074 p-value came from a chi-square calculation. The authors have forgotten that the chi-squared test must not be used when there is a zero in one of the cells. I hope that the reviewers realize this shameful mistake and ask for correction.<br /> Francisco Souto<br /> Brazil

On 2020-11-23 07:29:44, user Andreas Haas wrote:

The peer-reviewed article has been published in JIAS: https://onlinelibrary.wiley...

On 2020-07-03 08:50:08, user Roberto Avelar wrote:

Very interesting work. Thank you for citing CellAge! Just wanted to let you know we have published our database now ( https://genomebiology.biome... )

Cheers,<br /> Roberto

On 2020-12-26 04:26:03, user Peter Tomasi wrote:

The authors of this study (Corona-Ciao) https://www.medrxiv.org/con... draw conclusions from the results of serologic testing for a still ongoing extremely high-exposure environment in the study area.

They suggest these conclusions also to be valid in a general way for schools that apply preventive measures in high exposure environments.

Serologic tests only get positiv after a certain period of latency post onset of symptoms (POS).

The collection of samples started October 26, when case numbers in the general population of the study area just had very rapidly risen to an extremely high level and continued until November 19.

The rise started suddenly September 30 and was most massive from October 14 till October 30. After the described sharp and fast rise case numbers remained more or less at the very high level ever since. <br /> https://www.zh.ch/de/gesund...

In the discussion of the conclusions it is important to know in which exact extent serum sample collection respected the necessary POS-latency for them to be truly representative of the very high exposure environment the authors draw their conclusions for.

The Study used the ABCORA 2.0 binding assay of the Institute of Medical Virology (IMV) of the University of Zurich (Ref. 22). The publicly available document describing the test gives no information about the latency.<br /> https://www.virology.uzh.ch...

It nevertheless refers to the following study: Seow, J., et al. Longitudinal evaluation and decline of antibody responses in SARS-CoV-2 infection. medRxiv, 2020.2007.2009.20148429 (2020). https://www.medrxiv.org/con...

This document states the mean time to seroconversion from POS against at least 1 antigen to be 12.6 days (Line 117).

The authors of Corona-Ciao specify samples in their assay (ABCORA 2.0) were defined as seropositive for SARS-CoV-2 if at least two of the 12 parameters were above the cut-off (Line 172).

As a rough estimate I therefore suppose the usual latency of the test to get positive to be somewhat longer than 12.6 days, maybe 14 to 21 days? If we ad 7 more days for safety, we have 28 days.

I suppose the Institute of Medical Virology of the University of Zürich has validation data for its ABCORA 2.0 Test that specify latency from POS. It would be interesting to have validation data for children, if they exist.

If we assume a latency of 28 days, a substantial amount of samples could have been collected while the level of the exposure environment was not yet as high as the one the authors draw their conclusions for.

To clarify this worry, it is important, that the authors release complete information about when exactly collection of the samples occurred for all study participants and which exact latency from POS they assume on which validation data of the used ABCORA 2.0 Test.

On 2020-08-21 05:23:58, user Lucy Telfar Barnard wrote:

Hi there, this is a really great review. Just one problem: the reference numbers in the paper don't seem to match the references at the end. Pretty sure all the references to paper 41 comparing tests of cloth and surgical masks aren't talking about Leete's 1919 Lancet paper?

On 2021-11-03 13:22:41, user Rene Warren wrote:

This study has now been peer-reviewed and published: https://peerj.com/articles/...

On 2020-12-20 10:40:04, user Martin Reijns wrote:

Please note that this paper has now been published after peer review in PLoS Biology:

https://doi.org/10.1371/jou...

On 2021-08-19 11:53:03, user Brian Mowrey wrote:

Er.. Is anyone able to discern how "unvaccinated" subjects were located? The authors refer to them as "patients" - patients of what? At times in the text it seems like the study is using retroactive performance of individuals who were vaccinated - say, that if someone is vaccinated in May, they are eligible for matching for the previous months. But I don't see how that would allow them to have enough subjects for July.

On 2022-08-11 17:07:47, user Roman Kosoy wrote:

This article was accepted at Nature Genetics in July 2022 at: https://doi.org/10.1038/s41...

On 2020-11-18 12:34:24, user John Lambiase wrote:

Useless study. You have to dose the patient daily. The considered therapeutic range of >30.0 ng/mL is laughable. Anyone who has studied Vitamin D in a meaningful way understands dosage and therapeutic ranges of 40-60 ng/mL. There was enough anecdotal evidence out to point researchers in the right direction on how to dose patients. Not to mention where is the CBC differential results. It is interesting how all these critical covid patients had an avg platelet count over 300. Something is not right here because most critical patients are low in Platelets and Monocytes as well as lymphocytes.

On 2020-02-12 07:04:04, user Marc Bevand wrote:

Table S3 in supplemental data says there are 3665 confirmed patients with 2019-nCoV infections. All the numbers in the table add up to 3665. However the rest of the preprint claims 4021 confirmed patients. What explains this discrepancy?

On 2020-09-27 05:53:27, user Vincenzo Cerullo wrote:

So obvious that some viral infection can trigger autoimmune diseases.... so why not use this to trigger anti-tumor immune response!!

On 2021-12-28 09:32:57, user Joe Random User wrote:

Table B clearly says that some / many of the participants had only just received their booster jab on December 2nd. The date of the private gathering was "early December" and the genetic sampling results were received by December 8th. So most likely the private gathering took place between December 2nd and December 7th.

Everbody knows that it takes 2 weeks for the antibodies to develop to their full potential after the third booster jab.

Since this article does not specify how many of the participants had not been fully vaccinated with the 3rd booser jab the data in the article is insufficient to learn anything about the omicron variant's resistance to the booster jab.

I recommend that the authors produce a revised paper where they more carefully describe the vaccination dates for the 3rd jab for all participants.

On 2019-10-02 02:06:42, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 29 SEPTEMBER 2019<br /> The epidemiological situation of the Ebola Virus Disease dated September 29, 2019<br /> Monday, September 30, 2019

• Since the beginning of the epidemic, the cumulative number of cases is 3,191, of which 3,077 are confirmed and 114 are probable. In total, there were 2,133 deaths (2019 confirmed and 114 probable) and 991 people healed . <br /> • 346 suspected cases under investigation; <br /> • 3 new confirmed cases, including: <br /> • 1 in North Kivu in Kalunguta; <br /> • 2 in Ituri, including 1 in Mambasa and 1 in Mandima; <br /> • 4 new confirmed deaths in Ituri, including: <br /> • 1 community death in Ituri 1 in Mandima; <br /> • 3 confirmed deaths in CTEs in Ituri, including 2 in Mambasa and 1 Komanda; <br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 160 (5% of all confirmed / probable cases), including 41 deaths.

Synthesis of epidemiological data at week 39 (from 23 to 29/09/019)

• Number of probable new cases: 3 <br /> • Number of new confirmed cases: 20 <br /> • Number of new healings: 16 <br /> • Number of new deaths: 12 <br /> • Community: 4 <br /> • Confirmed deaths: 8

NEWS

Local providers of 17 silent and hard-to-reach health areas in Mambasa in Ituri sensitized on EVD

• One hundred and two local providers of 17 silent and hard-to-reach health areas in the Mambasa Ebola Virus Disease Response (EVD) sub-coordination were sensitized from 29 to 30 September 2019 in women's ward in Mambasa in Ituri province on this disease;

• This took place during a briefing day for the purpose of helping to stop the transmission of Ebola Virus Disease in this sub-coordination in order to prevent its spread to other health zones. , DRC provinces and neighboring countries;

• This day also had the objective of setting up a functional alert system in the community and in the health structures of the target health areas and a communication system allowing a rapid response in case of notification of a validated alert. , a new confirmed or probable case and accelerate ownership of the response by communities, their leaders and local health system actors;

• These local providers were trained on EVD basics, early definitions / detections of cases and actions to be taken, as well as escalation of alerts, risk communication and community engagement. They were also trained on dignified and safe burial (DHS), active case finding, community-level monitoring tools and reporting system, risk communication and community engagement;

• Awareness Day was opened by Mambasa Territory Administrator Mr. Idriss Koma Kukodila in the presence of the Deputy General Coordinator for Ebola Response to the Epidemic, Dr. Justus Nsio Mbeta, the Physician the coordination of the Mambasa Health Zone, representing the Mambasa sub-coordinator of the response and the field coordinators of WHO and UNICEF;

• The sub-coordination of the Mambasa response includes 3 health zones, including Mambasa, Lolwa and Mandima, and 28 health areas, including 6 hot spots reporting cases within 14 days. These include Binase, Lolwa, Mambasa, Salama, Mandima and Some;

• The 17 health areas are: Banana, Tabala, Bandishende, Makoko II, Epulu, Salate, Molokai, Bukulani, Akokora, Pede, Bakaiko Kenya, Nduye, Bongupanda, Malembi, Bahaka, Lolwa and Some. These are health areas that do not report EVD alerts and are areas of difficult access and insecurity.

VACCINATION

• Since vaccination began on August 8, 2018, 230,489 people have been vaccinated;

• The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature measurement) at the sanitary control points is 100,607,920;

• To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

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

On 2020-07-03 03:58:20, user Pedro wrote:

Considering that many doctors prescribe ivermectin as strongyloidiasis prophylaxis before the administration of high doses of corticosteroids, and that the use of dexamethasone has been shown to be effective in reducing mortality in patients with Covid-19 in RECOVERY Trial, was there any difference in the use of corticosteroids between the groups in this study?

On 2020-08-20 08:26:41, user Sonia Johnson wrote:

From the authors; this has now been published in Social Psychiatry and Psychiatric Epidemiology: <br /> https://link.springer.com/a...

On 2020-10-23 15:19:56, user Nicole M. Bouvier wrote:

This preprint is now published in revised form, including new data: <br /> Convalescent plasma treatment of severe COVID-19: a propensity score–matched control study<br /> Sean T. H. Liu, Hung-Mo Lin, Ian Baine, ..., Judith A. Aberg, Nicole M. Bouvier <br /> Nat Med 2020, DOI https://doi.org/10.1038/s41591-020-1088-9

On 2020-06-01 14:51:31, user OxImmuno Literature Initiative wrote:

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

On 2025-04-14 13:17:06, user Ammar wrote:

missing supplementary table1

On 2020-05-23 16:44:37, user Rosemary TATE wrote:

Thank-you for this well-written and interesting paper. It's very puzzling s that ethnicity was not a factor for hospital mortality (either unadjusted or adjusted rr's). Statistics reported here in the UK suggest that ethnic minorities are at far higher risk. This recent preprint on US deaths suggests the same.(https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.05.21.20109116v1.full.pdf)")

Do you have an explanation for these disparities. Could it be that non-whites are less likely to go to hospital in the US? Or is there another reason?

On 2024-01-05 11:17:42, user William Cawthorn wrote:

The peer-reviewed manuscript based on this preprint has now been published here: https://doi.org/10.1016/j.c...

On 2021-09-01 16:24:36, user Brian Schneider wrote:

Well done on providing clear tradeoffs of mitigation protocols.

Any chance you share the code? Not that I want to run the model, however I would like to take your results and adapt them to my specific circumstance. i.e. change the the initial population infections of 0.005 (or 500/100k) to suit my area of 0.0002 (20/100k) and see what the probability of infection is, given the remaining parameters are unchanged. <br /> The SIR model Euler version looks mostly linear, but given your accounting of additional factors such as testing rate, asymptomatic, etc it wouldn't be in the end.

It would be very cool to turn this into a tool, so that parents could say, if the probability of infection is greater than X, I would like to pull my child from school. Where that probability of X is met when I see my school zone transmission rate of Y or more per 100k.

I code in Python, but volunteer to help if interested.

On 2021-02-26 03:39:12, user Larisa Tereshchenko wrote:

Now published in JACC: Heart Failure: JACC Heart Fail. 2021 Feb;9(2):100-111. doi: 10.1016/j.jchf.2020.09.006. Epub 2020 Nov 11. PubMed PMID: 33189627

On 2021-12-13 18:41:26, user Rogelio Martinez wrote:

Dr. Deoni,

Any thoughts regarding possibility of increased lead exposure? Although, if lead was a main driving factor one would have thought the effects would have been worse for 2020 babies.

Could the drastic decrease in cognition simply be given the novelty of having a new face that is wearing a mask? There are several anecdotal experiences in which an infant is unable to recognize their own father after they shave their beard or hair.

Given the development of facial recognition even in the absence of a fear response a child exposed to a masked face is only getting about 50% of the information they would normally get from an unmasked individual. Kids don't develop full holistic facial recognition until the age of 6 if I am not mistaken.

I think it would be difficult to ace an exam in which you are only presented 50% of the instructions, but I am unfamiliar with the testing used. How much is guided by facial expressions that require more than just the top half of the face?

On 2021-11-23 11:21:00, user Zacharias Fögen wrote:

"Among fully vaccinated household contacts, the crude SAR was similar for fully vaccinated index cases compared to unvaccinated index cases (11% vs. 12%), but this was confounded by age of the index – both SAR and proportion of vaccinated index cases are higher in the oldest age groups (Supplementary Table S1)"

This is not counfounding. You are introducing a bias.<br /> Among age groups 50+, SAR between two vaccinated V-V (21.5%) is the same or less compared to U-V (22.22%, n.s.) or V-U (18.25%, n.s.) which clearly makes no sense if the vaccination had any benefit.<br /> There is an equal age distribution, about 10% over 75.<br /> (I used data from table S1).

Also, among age groups 30+, Vaccinated Index cases are significantly (p=0.01) less likely to infect an unvaccinated (12.55%) than a vaccinated person (18.15%) clearly indicating that a vaccinated person is more careful when interacting with an unvaccinated Person.

So, there is insufficient Control for confounding, as you did not control for risk avoiding behaviour. Risk Avoiding behaviour influences both likelihood of being vaccinated as well as compliance to social distancing and other infection-avoiding behaviour. So vaccinated people are less likely to be infected because they avoid it more through social distancing, which seems to decrease with age, as the analysis of age group 30+ and 50+ combined demonstrates.

On 2021-10-26 07:55:37, user TheUnderdog wrote:

Why is the 40% and 63% 'effectiveness' solely attributed to the vaccine, and not to the individual's own immunity (including natural immunity)?

I would argue this shows an opposite effect. The vaccinated group only have a 40% effectiveness of not getting infected, whilst the natural immunity group have a 63% effectiveness rate of not being infected.

If it was just the individual's own vaccine that was preventing onward transmission to others, then we'd expect the percentages to both groups to be the same. In-fact, if the vaccines even worked we'd expect the effectiveness percentages to be flipped around, with vaccinated people seeing more effective protection.

This study just appears to reinforce natural immunity as offering better protection, which correlates with the Israel datasets showing natural immunity works better against Delta (see: https://www.timesofisrael.c... "https://www.timesofisrael.com/study-covid-recovery-gave-israelis-longer-lasting-delta-defense-than-vaccines/)").

On 2020-07-23 09:56:15, user Jonathan wrote:

One has to hope for a vaccine and/or effective treatment before the colder northern hemisphere seasons. If not, a second wave is almost inevitable. Thank you for your vital and ongoing work.

On 2024-10-09 14:55:31, user Emma Chambers wrote:

This is now published in the peer-review journal npj Vaccines and the link to the paper can be found here https://www.nature.com/articles/s41541-024-00878-0

On 2021-03-03 08:20:31, user Martijn Hoogeveen wrote:

Our followup in MedrXiv shows that "Seasonal patterns COVID-19 and Flu-Like Illnesses comparable" https://www.medrxiv.org/content/10.1101/2021.02.28.21252625v1#disqus_thread

On 2020-04-06 18:06:44, user Ziv Gan-Or wrote:

I am sorry to say, but the title is somewhat misleading, the authors did not show that "ACE2 variants underlie interindividual variability and susceptibility to COVID-19 in Italian population". What the authors show is that there are ACE2 variants found in Italians and not in Asians, and that in-silico tools predict that they might have structural or functional effects. I am certain that there are variants in Asians that are not found in Italians and are with similar predictions. We need population-based genetic studies to determine what the authors suggest in the title. Nevertheless, this is interesting and worthy of additional studies.

On 2020-07-17 13:12:12, user Liam Golding wrote:

What is the detection limit of this assay? I assume it's >log0.

On 2020-06-03 04:00:14, user ??????? ??????? wrote:

You can not trust the testimony of patients who are admitted to hospitals with a serious illness. Currently, the entire public health system is anti-smoking. For example, insurance companies may apply certain restrictions for smokers. Therefore, patients hide the fact of smoking. In connection with the above, the fact of smoking should be documented by objective methods.

On 2020-09-24 19:07:43, user Steve Schaffner wrote:

The paper reports that Rh-positive blood type and mortality are positively correlated. According to Supplemental Table 3 (which doesn't seem to be accessible from the preprint server), mortality is also positively correlated with Rh-negative status. Since people can only be Rh+ or Rh-, this is not possible. I suspect the authors didn't remove samples with missing blood type information before doing the calculation -- information that is more likely to be missing for those who survived. If this is what happened, the high correlation with Rh+ type simply reflects the high prevalence of Rh+ in the population.

On 2021-10-01 18:41:38, user Paul Tupper wrote:

Thanks for this very valuable study. Do you have plans to do a similar one for younger age groups?

On 2021-10-06 17:29:33, user Trevor Madge wrote:

Forgive me I may have misunderstood the paper, but is the dataset only including those who where "sick" with COVID19? Does it exclude all asymptomatic infections?

On 2020-07-23 01:12:23, user William Croft wrote:

Many reports surfacing online of reinfections (google covid reinfection). Within weeks or months of the 1st infection, after antibodies no longer exist. This would seem to caution against antibody based approaches. Unless the goal is re-vaccination every three months(!) Admittedly profitable for manufacturers. ;-)

On 2020-09-30 21:20:56, user Fabrizio Illuminati wrote:

Excellent analysis, showing the crucial role of heterogeneity in pathogen transmission. However, one should be aware of the fact that heterogeneity is a metastable trait: in time, and in a dynamic situation of shifting habits and contacts, large-scale homogeneity sets in. This implies that on medium- to long-time scales the type of immunity provided by heterogeneity is lost. It is ok and an important ingredient to set up containment strategies on a short- to medium-time scale while we wait for an effective vaccine. Moreover, it clearly works well at the urban level, where one can assume constant and persistent levels of heterogeneity. It will not work so well for the interaction with suburban and rural areas.

On 2021-01-17 10:18:21, user T.R. Raju wrote:

I am unable to figure out the time points- when the study was initiated and when it was closed.

On 2025-10-21 15:31:18, user David Bacsik wrote:

The final version of this manuscript is now available in the Journal of Clinical Microbiology: https://doi.org/10.1128/jcm.00415-25