On 2021-12-24 07:09:23, user ZedMcG wrote:

The UK has a seropositivity rate of 95%? Why the panic there? Do they not trust South African data or do they have a valid reason to believe that Omicron will have a different impact there?

On 2020-04-11 02:02:32, user SFHarry wrote:

It is important to note that the words "higher" and "lower" risk were used. If you look at the numbers it doesn't show the risk being that much higher (or lower). People should not be making decisions regarding how much risk they should allow themselves when interacting with the public without understanding these facts..

On 2022-05-12 15:22:37, user L. Collado Torres wrote:

Congrats on getting this massive project to the pre-print finish line! Kudos to you!

I specially like how you have formatted your work and made it "journal style" with embedded figure and figure legends, the two column layout, and overall it looks great. I also greatly appreciate that you shared the methods, supplementary figures, and supplementary tables on medRxiv (not everyone does so!). Furthermore, I love the tab "header_key" on your supplementary Excel file which describes all of the columns in your supplementary tables. That makes it much easier to understand the information you are providing. I also like that you mentioned the specific version numbers of the software you used, since software changes frequently in frontier fields like yours.

I might have missed it, but I could not find how to access the data you used or the code for this analysis. Not sharing data and code is detrimental to open science. For code, you could share it through GitHub, GitLab, or some other social coding platform (or directly on medRxiv: you currently have a note telling people to check the supplementary PDF file with the methods description). I would also encourage you to share your code permanently at a repository like Zenodo, Figshare, among others where you'll get a DOI. GitHub repositories can be deleted, so it's best to make the code permanently available. If you have questions about this process, I'd be happy to chat with you.

Best,<br /> Leonardo

On 2021-08-20 12:18:37, user Jodi Schneider wrote:

Were there any differences in the underlying populations vaccinated with Moderna (mRNA-1273) and Pfizer/BioNTech (BNT162b2) in the Mayo Clinic Health System?

On 2021-09-11 12:29:44, user David Freyer wrote:

Do we know what cycle threshold was used to determine a positive test; and was it the same for all groups?

On 2020-04-13 19:30:49, user Tomas Hull wrote:

I don't think there is an official study with autopsy results yet. They tested positive for CoV2, so it is assumed as the cause of death until autopsy.

https://www.theglobeandmail...

On 2020-04-21 06:06:51, user Paul Maxwell wrote:

But that is not what is compared for the "absolute risk"

On 2020-08-18 14:02:37, user Brad T. wrote:

This may get removed for being a competitor site, but this study found conflicting results.<br /> https://www.ncbi.nlm.nih.go...

On 2020-04-27 18:49:54, user Masao Fukui wrote:

Thank you so much for your comments.

We already discuss your major comments 1 and 2 in the discussion section of the paper.

Regarding your minor comment 2, as we write in our paper, we are not able to provide plots because there is no age-level data for other countries.

Regarding your minor comment 3, you can download the code and data from Data/Code.

On 2022-03-14 13:57:25, user SleepRhythm wrote:

This paper is now in press in Frontiers in Neuroscience - section Sleep and Circadian Rhythms: https://www.frontiersin.org...<br /> The medRxiv link will be forthcoming

On 2020-05-22 18:43:01, user Madhurjya P Bora wrote:

This paper has lifted many portions of texts in several places from the paper https://hal.archives-ouvert... by Eber Dantas, Michel Tosin, Americo Cunha Jr, especially in the Trust-Region-Reflective section.

On 2022-01-18 23:47:58, user Alexander Novokhodko wrote:

Was this patient vaccinated?

On 2021-06-27 22:42:22, user Dr Tanja Ninkovic wrote:

it is actually very relevant. spike protein is a transmembrane protein. a human cell which gets the mRNA vaccine in it starts producing the protein and gets killed by the immune system, and fully diggested. spike will not float around. the mRNA in lipid particles can float around and should be detected using the test they present here, if it goes into the breastmilk. but i cannot judge if the timeframe is correct. the mRNA vaccines are stable only for 8-10h in a body, some papers say, so i guess the timeframe is correct, but i don't understand than why is this paper not yet published. i can not getting a vaccine until i am sure that it is not going into the milk, and i would love to see what is going on with this research.

On 2021-07-27 11:05:46, user JustinReilly wrote:

As the article is now published, I urge everyone to go there and submit a comment! Thank you!

https://academic.oup.com/ci...

On 2021-07-23 15:12:27, user mef wrote:

More corrections here: https://covid19criticalcare...

On 2020-06-04 18:12:50, user Fahd Al-Mulla wrote:

I am concerned about this study as a scientist. Am I right by saying that they compared DNA from hospitalized Covid-19 patients to data obtained from databank?! if so how do we know that some people in the control group would not have been hospitalized if they were infected? Am I right? if so this is a major problem in this study.

On 2021-10-15 08:17:58, user Laura Van Poelvoorde wrote:

This research now has been published in Frontiers in Microbiology (https://www.frontiersin.org... "https://www.frontiersin.org/articles/10.3389/fmicb.2021.747458/full)")

On 2020-07-17 15:36:12, user Mathieu Perrin wrote:

Dear authors,

thank you for raising awareness that a low FPR does not per se translate into a high significance of a positive result. Hopefully, this will encourage labs to make an EQA for SARS-CoV-2.

1) Is it possible that the FPR actually depends on the prevalence rate? For instance, if the prevalence is high, there is a greater risk to contaminate a negative sample.<br /> 2) Should the FPR be lower if two tests are conducted on the same person? I expect this to be the case unless a negative patient always give positive results for some reason. If so, the practice of double testing should be generalized. I understand you have trouble determining precisely how each country defines a positive result, whether it is on a sample basis or if samples are pooled or if an individual gets tested several times.

Regards,<br /> Mathieu

On 2022-02-02 11:42:04, user Philip Ashton wrote:

Hello,

Thanks for posting this really fascinating paper, so much food for thought!

We looked at this in our journal club today, and one practical issue that came up is that we would like to know over what period and what season sampling was done at each site and how this relates to typhoid season at each site. Because Typhi is often seasonal and this could influence the results.

Thanks again!

Phil

On 2022-07-03 08:02:22, user Rony wrote:

The paper is now published at PLOS ONE:<br /> https://journals.plos.org/p...

On 2020-08-06 17:24:37, user MotherGinger wrote:

Did this study establish direction of transmission, or use "% of contacts infected" as a proxy for infectiousness?

On 2020-12-17 13:40:29, user Dr Anand Lakshman wrote:

Can the proportion of active infections found be compared to proportion found through routine testing for same period? <br /> Since we have samples collected over 14 days, can we look at RT PCR positivity for each day and calculate incidence over the study period?<br /> How did we account for various socio economic groups? The sampling appears biased towards lower socio economic groups as the settings are largely public hospitals. How was the sampling for the elderly and co- morbidities done, as that is only one which is truly community based random sampling?<br /> The active infection rate in Ballari district is an outlier. Needs to be verified.

On 2021-05-06 20:18:47, user Murray Stein wrote:

Important, well-conducted study. Results are puzzling. Antidepressant effects of IV ketamine are nicely replicated. Anti-PTSD effects are not. PTSD symptoms were reduced substantially after first infusion in all 3 groups (albeit statistically significantly more in the standard-dose ketamine group), and then stayed low and drifted a bit lower over the remainder of the study. Response rates were high and non-significantly different between all 3 groups (~60% for each of the ketamine groups, ~ 50% for the placebo group). This high a placebo response would not have been anticipated -- particularly given the selection of participants to have failed at least one adequate SSRI trial (although one wonders if this qualifies them as "antidepressant-resistant"). Will require some rethinking about future PTSD trial designs, including possibility that we should be measuring PTSD outcomes differently (i.e., doing something other than asking repeatedly about the 20 symptoms in DSM-5). I would be interested in hearing what others think, particularly with regard to clinical implications.

On 2020-06-01 19:37:39, user Marcelo Fernandes wrote:

The prediction model has several problems, and there are several wrong assumptions. At the moment, the number of cases and depths in Brazil is growing very fast. The results of this paper created a false feeling about Pandemic in Brazil.

On 2021-08-21 07:34:08, user Timothy Baer wrote:

Do you have a link for that study

On 2021-08-03 16:04:04, user Daniel Keyes wrote:

Overall the study seems strong and has tremendous impact potential. Many parts of the world could potentially prevent hospitalizations and save lives by proper allotment of vaccine resources based on evidence of prior infection if the conclusion is correct.<br /> I felt that the first diagram/flowchart could be improved: there should be vaccinated/unvaccinated for each of the two groups: previously infected, not previously infected. Would envision a branch/fork for each of the aforementioned groups rather than continuous across the same line in the diagram.<br /> Given the time being taken to review this article (it seems long, but actually is probably not that long!), the reviewers might consider extending the data to the end of June, which could provide implications with respect to delta variant. As it is, the Midwest, where the study is located, already has a very high percentage of delta variant. But this was probably not the case for the period up to May 15, the end date for the study. Delta started to be present in mid-March, but was not substantial for the ensuing 2 months.. But, of course, that might delay the review process even longer, and would not be likely to change the conclusion.

On 2020-06-30 11:48:25, user J. M. Groh wrote:

Hello, thanks for your important paper. May I suggest clarifying in the abstract the numerical effects that you saw, esp. reductions in the death rate in the treated group vs. controls (page 4, 5% mortality in the treated group vs. 45% in the control group, for groups of ~20 and ~50 patients). That is an impressive effect size. Thank you!

On 2024-04-28 21:04:46, user Marly Peel wrote:

PLEASE! PLEASE! PLEASE do more research & acknowledgement of this TERRIBLE problem! I just recently discovered info on this & it all matches my symptoms exactly. Imagine a horrific itch that you cannot scratch enough to make it STOP! I don't think I've ever been this close to panic as I have during those times. There's no way to sleep or rest AT ALL when this is happening. That doesn't even include the flaking, shedding, red & raw areas, irritated & antsy feelings one can have. WE NEED HELP! Plus, there needs to be a HUGE WARNING included with every top.steroid...that doctors know about & take to heart. Top.steroids might be a quick "fix"...but they DO NOTHING to address the underlying reason for the problem in the first place. It's time for common sense to COME HOME!

On 2021-03-17 11:01:56, user Olaf Storbeck wrote:

I hope this excellent paper receives the same attention like the rather poor work recently published ( https://www.medrxiv.org/con... ) which used a similar approach and failed to see the significant correlation between Vitamin D deficiency and Covid-19 due to severe errors in the data set and the methodology. <br /> However the message "Vitamin D is not correlated to Covid-19 outcome" was very fast amplified by the media worldwide as:<br /> - The Guardian (https://www.theguardian.com... )<br /> - The Business Insider (https://www.businessinsider... )<br /> - The Independent (https://www.independent.co.... )<br /> - Russia Today (https://www.rt.com/news/517... )<br /> - Politifact (https://www.politifact.com/... )<br /> - Hospital Health Care (https://hospitalhealthcare.... )<br /> - News Medical (https://www.news-medical.ne... )<br /> It is incomprehensible to me how this very obvious safe and efficient measure (sufficient Vitamin D supplementation for all) is neglected by nearly all authorities.<br /> I hope publications like this help to spread the meassage...

On 2020-10-30 14:16:43, user Michael Ford wrote:

Still have to wait for peer review to see how much weight this should carry. This is just a pre-print article.

On 2021-04-05 00:50:51, user Brandon Grant wrote:

The authors conducted secondary analyses to examine the effect of study type on the outcome of mortality for the studies of SARS-CoV-2 that were included in the primary analysis. However, the authors do not mention conducting secondary analyses to examine the same correlative relationship for any of the studies of any other virus besides SARS-CoV-2. This lack of equivalent data analyses and resulting lack of homogeneous comparisons of outcomes renders any conclusion based on the aforementioned data null and void.

On 2021-01-30 20:34:38, user kdrl nakle wrote:

Using unreliable data with elementary stats. Looks like a student paper..

On 2021-12-02 23:24:43, user rvga wrote:

Can you let us know how soon you can get this going - esp. with lineage of omicron variant is going to be very complicated. Thanks.

On 2020-08-07 12:37:34, user kdrl nakle wrote:

I don't see affiliation of authors in paper.

On 2019-09-30 05:15:29, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT SEPTEMBER 22, 2019

The epidemiological situation of the Ebola Virus Disease dated September 22, 2019

Monday, September 23, 2019

Since the beginning of the epidemic, the cumulative number of cases is 3,168, of which 3,057 are confirmed and 111 are probable. In total, there were 2.118 deaths (2007 confirmed and 111 probable) and 975 people healed. <br /> • 343 suspected cases under investigation; <br /> • 4 new confirmed cases, including: <br /> • 1 in North Kivu in Butembo; <br /> • 3 in Ituri, including 2 in Mandima and 1 in Mambasa. <br /> • 3 new confirmed deaths, including: <br /> • 2 community deaths, including 1 in North Kivu in Butembo and 1 in Ituri in Mambasa; <br /> • 1 confirmed death in Ituri in Mandima. <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.

NEWS

Beginning of trainers training in Goma on good clinical practices related to the second Ebola vaccine <br /> • The Ebola Virus Disease Response Information Management Coordinator, representing the Technical Secretariat, Mathias Mossoko, launched on Monday in Goma the training of trainers which runs from 23 to 28 September 2019 on the good clinical practices (PCBs) related to the second Ebola vaccine. <br /> • This training benefits from the expertise of CVD's Malians on the transmission of notions about good clinical practice. It aims to provide participants with the standards applicable to the design, conduct, monitoring and stopping of studies, to teach them the activities of audit, analysis, reporting and documentation with the guarantee that these studies 'rely on sound scientific and ethical principles. It is also intended to introduce participants to the correct documentation of the clinical properties of the vaccine tested or evaluated. <br /> • The Response Information Management Coordinator called the attendance participants to demonstrate better actors for the implementation of good practice in this second vaccine. <br /> • For its part, the chairman of the Immunization Committee, Stéphane Hans, said that this five-day training announces the forthcoming launch of the second vaccine that will come at any time in the targeted health zones. "We welcome this supplementary vaccine very positively compared to the first vaccine. This second vaccine has the advantage of preventing all strains of the Ebola virus. It is therefore positive for the population that will receive it, "he said while inviting all communities targeted by this vaccination to take ownership of this activity, once launched. <br /> • The training on good clinical practice will revolve around several presentations on different topics, among others, the Ebola virus disease, the responsibilities of the INRB for the QA system, study vaccines (storage, management, chain cold and accounting), inclusion and follow-up of pregnant women, community involvement and informed consent, etc. <br /> • This training was organized for the different actors involved in this project, including doctors, epidemiologists, clinicians and pharmacists. A total of 25 people from Kinshasa, including the INRB, UNIKIN, CUK and specialized programs and North Kivu, including the Provincial Health Inspectorate (IPS), the Provincial Division of Health Centers (DPS) and Health Zone Coordinating Offices (BCZS) are participating in this meeting. <br /> As a reminder, the recommendations of the MULTISECTORAL COMMITTEE ON THE RESPONSE TO THE EBOLA VIRUS DISEASE are as follows: * <br /> 1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes; <br /> 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; <br /> 3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days; <br /> 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. <br /> 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.

VACCINATION <br /> Opening of an expanded vaccination ring around two confirmed cases from 19-21 Sept 2019 in the Madidi health area in Mambasa, Ituri. Another satellite ring was opened at the Kitatumba General Referral Hospital in the Butembo Health Zone in North Kivu around the case notified on 22 09 2019. This case started the disease in the health area of Kasindi in Mutwanga, North Kivu. <br /> • The Expanded Program of Vaccines has received 4320 doses of vaccine at the national level; <br /> • Since vaccination began on August 8, 2018, 226,722 people have been vaccinated; <br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS <br /> • High-risk contact was intercepted at Kangote PoC in Butembo, North Kivu. This is a 28-year-old unvaccinated woman on the 14th day (D14) follow-up who was listed around a confirmed case in the Katwa Health Zone. During her interception, this woman presented some signs related to the #Ebola Virus Disease. She was sent to the Butembo CTE for treatment. <br /> • Kituku PoC providers in Goma, North Kivu, were assaulted by about 20 onlookers called "Maibobo" who were avenging one of their drowned during the night of 20 to 21 September 2019. These providers feel insecure and ask to be supported by officers of the National Police (PNC) or FARDC. <br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement) at the sanitary control points up to 22 September 2019 is 96,998,860; <br /> • 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.

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

On 2022-07-26 03:01:00, user Phil Pellett wrote:

This is an interesting and potentially important paper. It is worth noting that Yang et al. published a possibly related article in Journal of Infectious Diseases in 2019, “Evaluating for Human Herpesvirus 6 in the Liver Explants of Children With Liver Failure of Unknown Etiology” (PMID 30418598). I wrote an accompanying commentary (PMID 30496434). Searching Pubmed with "liver failure, hhv-6" turns up several other papers that connect to the subject. It seems prudent to expand the background of the paper to include mention of this literature.<br /> Best wishes,<br /> Phil

On 2021-11-22 18:02:48, user Timeisrelative wrote:

This is an excellent paper. I have a few minor comments related to the word choice and clarity that I hope are helpful to you.

1)The uses of the words "rate" and "rate of change" are problematic in this context. I think it would be more clear to use different words. A "rate" usually describes how much of something happens over a specified unit of time. So the "rates of change in antibody titres during 3-6 months" might be about 10%/per month. Your metric is defined as:

rate of change = [(Ab titre 6 months after the 2nd dose - Ab<br /> titre 3 months after the 2nd dose [12]) / Ab titre 3 months after the 2nd dose] × 100 (%)

I believe this metric would be better described as simply the "change" or "percentage change" instead of the "rate of change" since it doesn't have a unit of time in it's denominator. This phrase "rate of change" occurs at many times throughout the paper and I believe they all should be replaced with "change" or "percentage change".

2) I was confused by the meaning of this line near the end of the results section:

because the Ab titres 3–6 months after vaccination were significantly higher in women than in men.

If I correctly assumed your intention, I think this line could be written more clearly as: "because the Ab titres were significantly higher in women than in men at both 3 months and 6 months after vaccination"

3) I think it would be helpful to specify in the table headings and in the chart axes labels whether the measured titres were 3 months or 6 months post vaccination. This information is in the paper and the caption of the figures, but it would be clearer if, for example, the headings of tables 1 and 2 were "Ab titre at 6 months, median (IQR), U/mL" and the x-axis label of figure 2b was changed similarly.

On 2021-08-31 22:18:33, user Timmy Tester wrote:

Why would you use hypothetical modeling data <br /> to predict results? We have kids in school now, some with mask mandates some without. In the US, Europe and beyond? Why wouldn’t you look at real world data on actual kids in school? If you create a model that shows more covid spread with no masks, the result is kind of inevitable and not very scientifically valid.

On 2021-10-14 09:10:21, user J Hung Tran wrote:

They just measured virus load/Ct at one timepoint, I wonder how the Ct value progress over the course of infection between groups?

On 2020-11-16 06:38:23, user whitecat31 wrote:

At the 39th replicant when the exponential phase is basically over? Am I understanding that correctly? Seriously? Did you guys run a comparison standard curve with 39 points? Something like the 39th replicant would be considered below the limit of detection and LOQ. So yeah.. your sample was contaminated.

On 2021-01-27 16:50:34, user Eric O'Sogood wrote:

A couple things I noticed. Studies that have been peer reviewed and published with large statistically significant effect sizes are reported here as "no data" or, selectively negative individual outcomes from trials which did have positive effect sizes were chosen. I would be interested more in the source of these authors' methodologies. Standardized, widely validated methods were not used here. Considering Kory, Marik et al's meta-analysis has passed peer review and is accepted for publication, and Dr. Hill and Dr. Lawrie, both experienced systematic reviewers for WHO and Cochrane, came to opposite conclusions to these authors, I would say there is an extremely low likelihood this meta-analysis will pass peer review.

On 2021-12-26 08:33:43, user Jack Bean wrote:

"asymptomatic transmission" Really. No evidence for asymptomatic transmission. https://www.nature.com/arti...

On 2020-04-20 01:20:55, user JWJ wrote:

Did I read that right, this model is predicting 96,000 dead in Sweden by June 29 2020?

On 2020-05-17 15:05:13, user FailedPolitics wrote:

Oebsity and low D is also linked

On 2020-05-08 16:54:43, user Daniel Powell wrote:

I would guess that those with such severe vitamin D deficiencies at the point of this study don't get much sun under normal circumstances. The disconnect once one politicizes any finding is a false equivalancy. "Beach" does not equal "Vitamin D", or even sunshine. It's foggy as heck on the beach in front of my rental right now. And I get plenty of sun in my yard. I can also take vitimans daily if I am concerned about the levels.

On 2020-10-25 13:13:15, user John Roberts wrote:

Excellent analysis. The study mentioned that monoclonal antibodies will be added. At the top of the list should be leronlimab which is already in a phase 3 clinical study for severe/critical Covid patients with the primary endpoint mortality at 28 days. The interim analysis at 50% enrollment showed it is trending toward the endpoint and in fact another interim analysis was added at 75% enrollment.

On 2021-09-10 15:49:38, user skeptonomist wrote:

The paper shows very conclusively that the vaccine reduces infection rate. Because the overall death rate among those infected is small (on the order of 1-2% at most), the expected number of deaths in the placebo group is not large enough for a meaningful test of how death rate is affected.

On 2021-08-06 21:12:32, user BiotechObserver wrote:

You seem to have difficulty with math. The trial took place over a set period of time. If your argument is that only around 5% of people will be infected over 6 months, then please tell me what happens over a period of 10 years? Because last I checked, time didn't stop, and we all expect to live for more than a single 6-month spurt. The point here is the relative reduction in cases by the vaccine and relative reduction in severe cases (97%) because over time, the cumulative number of cases (and therefore severe cases, which are a subset of cases) climbs. It doesn't remain static. This point should be obvious.

On 2021-08-11 19:47:07, user BiotechObserver wrote:

How could you possibly know that, and what does it have to do with anything I said? Some vaccines provide very longterm immunity.

On 2021-12-03 04:53:25, user Emmasmom wrote:

Can someone please tell me where Table S3 is? I have downloaded the pdf but it only contains three tables. How do I find the supplementary materials?

On 2024-04-09 15:52:16, user Tarachopoiós wrote:

This looks like an intersting analysis. One question was around the correlation of predictors to TTFT. So growth rate requires time-series data to be estimated did you account for the time taken to estimate growth rate? One option would have been to use a joint longituinal time to event model to account for immortal time bias. How did you account for immortal time bias in your analysis i.e. the fact that tumour growth rate isn't known at your time zero? Or is it known? That wasn't clear in the methods.

On 2024-02-26 17:17:40, user Ciarán McInerney wrote:

Please, explain the<br /> situation that warranted the Bonferroni correction, and explain precisely how<br /> you came to the threshold of 0.01. The Bonferroni correction scales the level<br /> of significance by the number of comparisons being made. With 19,314 candidate<br /> features, this would make for a staggeringly small Bonferroni correction of<br /> 0.00005.

On 2020-05-07 20:47:41, user Dan T.A. Eisenberg wrote:

We are thinking of implementing this in my lab for research purposes and hopefully to expand testing capacity. Have you or anyone else you know of tested the stability of saliva samples for longer periods of time, adding in preservative, and/or keeping more of a cold chain (e.g. stored at +4 or -20 for some time)?

On 2020-04-05 13:09:17, user Advocatus Diaboli wrote:

You cannot do controlled trials for everything, especially not on human health and in an emergency. They did control for certain factors, but cannot for most as no data are available. It is just a hypothesis, and a very interesting one. If they are onto something, it woudl be irresponsible not to share it just because they cannot make it perfect. When the earthquake finds you on the beach, you may choose to stay there until you figure out the probability distribution of a possible tsunami, or you may just move to higher ground. You seem to prefer the former, but don't blame others for opting for the latter.

On 2020-04-05 21:45:02, user Tom Johnstone wrote:

There’s a multitude-centre RCT to test the protective effects of the vaccine against Covid-19 in healthcare workers in Australia. https://www1.racgp.org.au/n...

In the mean time, it would be prudent to remove the causal language from the article and abstract (“reduced”), as any results are purely associations.

On 2020-05-27 21:22:55, user Sinai Immunol Review Project wrote:

title<br /> SARS-CoV-2 serological analysis of COVID-19 hospitalized patients, pauci-symptomatic individuals and blood donors. <br /> Grzelak et al. medRxiv [@doi.org/10.1101/2020.04.21.20068858]<br /> Main Findings<br /> The prevalence of the SARS-CoV2-specific antibody responses in large symptomatic and asymptomatic populations has been of great interest to understand the incidence of and immunity against SARS-CoV-2 infection. To analyze the virus-specific antibody response, Grzelak et al. designed several assays: anti-nucleocapsid (N) and anti-trimerized spike (S) ELISAs, S-Flow cellular assay, LIPS (luciferase immunoprecipitation assay) and pseudovirus neutralization. They profiled several different populations that included 491 pre-endemic individuals, 51 hospitalized CIVID-19 patients, 209 pauci-symptomatic individuals reporting mild signs compatible with COVID-19, and 200 sera from blood donors.<br /> The full-length N protein or the extracellular domain of S in a trimerized form, which existed naturally on the viral surface, were used as ELISA antigens. In addition, to allow the detection of antibodies binding to various conformations and domains of viral glycoprotein by flowcytometry, S protein was expressed on the surface of 293T cells (S-Flow). Luciferase immunoprecipitation assay (LIPS) was also established with a panel of 10 different S and N-derived antigens, and N and S1 proteins were selected as the antigens for the further analysis based on their sensitivity. <br /> With the four assays, signals were consistently negative or low in the pre-epidemic samples, suggesting that a pre-exposure to human seasonal coronaviruses did not induce obvious cross-reactive antibodies to S and N protein from SARS-CoV-2. The analysis of 161 samples that combined different time point samples from 51 hospitalized patients, detected positives that ranged between 65 to 72 %. On the other hand, positivity rates in pauci-symptomatic individuals varied from 27 to 36 % between assays, suggesting that pauci-symptomatic individuals either had lower viral loads or the reported symptoms were not caused by SARS-Co-V2. Correlation analysis revealed that sera with high antibody levels were well detected by all the assays, and that the highest correlation were observed between ELISA tri-S and S-Flow.<br /> Lastly, the presence of neutralizing antibodies (Nabs) was evaluated by microneutralization (MNT) and pseudovirus neutralization assay using the sera from 9 hospitalized patients and 12 pauci-symptomatic individuals. A neutralization activity >80% was associated with ELISA N (>2.37; OD405 values), ELISA tri-S (>2.9; AUC values determined by plotting the log10 of dilution factor required to obtain OD405), S-Flow (>60%; anti-Spike IgG+ cells) and LIPS-N (>0.049; Signal-to-Noise ratio).<br /> Limitations<br /> As described in the text, the pauci-symptomatic population appears to be a mix of the individuals with SARS-CoV-2 infection and individuals with other conditions that had COVID-19-like symptoms (fever, cough or dyspnea). <br /> It will be informative to investigate the relationship between the presence of anti-viral antibodies and neutralization activity, and severity of COVID-19.<br /> Significance<br /> While some of the assays described here cannot be routinely performed in clinical settings, their higher specificity and sensitivity to detect antibodies and their neutralizing activity is important to understand the protection mechanism against SARS-CoV-2. <br /> Credit<br /> Reviewed by Miyo Ota as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

On 2020-05-19 19:13:19, user Plonit Almonit wrote:

The study assumes that behaviour changes coincided with official pronouncements. Except for school closures, that is not necessarily the case. For example, Sweden shows restrictions of movements and private contacts comparable to countries in lockdown. A direct behavioural measurement should be included in the study before publication. Speaking from my own private experience, the public discussion cumulating in Merkel's speech on the 12th of March, especially the news from Italy and France, caused behavioural changes (like avoidance of public transport, cancelling of parties) before they were officially mandated. Masks began to appear in public around that time and were sold out in the pharmacies, even though they were officially discouraged. Hoarding also began around that time, also a sign of behavioural change.

On 2020-05-07 03:35:17, user Mazyar Javid wrote:

I left a comment for the first version expressing my astonishment on how<br /> many seem to be obsessed with tearing this study apart and discrediting its<br /> findings altogether. I agree that the study has limitations (as a scientist and<br /> a peer reviewer, I am yet to see a “perfect” study). Nonetheless, the authors<br /> have made substantial attempts to address the limitations reasonably and adjust<br /> their results accordingly.

Since the publication of the original report, we have seen results of multiple<br /> serologic studies that have largely corroborated these findings: Studies in<br /> less affected areas (e.g. Czech Republic) which indicated very low prevalence<br /> of seropositiveness (effectively undermining the notion that most of positives<br /> in these studies are false positives, otherwise we would have seen similar<br /> relatively high prevalence of “positives” there too), to studies in heavily<br /> affected areas such as NYC which show higher prevalence but smaller ratio of<br /> seropositives to confirmed cases (due to higher frequency of testing).

The implications, that the IFR is significantly lower than what is publicly<br /> portrayed, and that in many areas, the prevalence is possibly much higher than<br /> can be practically managed with containment strategies, requiring other mitigation<br /> strategies with focus on vulnerable populations are enormous, yet I rarely see<br /> anyone among our decision makers taking any of these data into consideration<br /> despite all the claims that decisions are driven by nothing but “data”.

Somehow this reminds of Plato’s Allegory of the Cave: We saw the projections<br /> and took them as the reality, until one dared to escape and saw what really<br /> lied outside and came back to inform us of the findings, yet we, mesmerized by<br /> the shadows, could not believe it and rushed to chastise the messenger. So is our story, preferring model projections over actual data and getting upset when the latter does not support the former...

On 2021-07-01 17:46:23, user mehuldpatel wrote:

The published version is available at: https://jamanetwork.com/jou...

On 2020-08-13 07:57:05, user Zeit wrote:

Very interesting manuscript. I think it may be wise to remove isotopes from your data as it seems clear that you have associations of monoisotopic peaks and their isotopic peaks with phenotypes. If you correlate the retention times of ions most correlated with each other by area count/signal, it should reveal that they are non-independent ions.

On 2021-11-09 10:52:01, user Harry Wood wrote:

The Israeli study is flawed on many levels. This dissects the errors.

https://www.quora.com/A-rec...

On 2021-09-02 15:03:55, user snazzygina wrote:

What if someone had covid in July of 2020? Would they still have the same immunity levels? Would getting a single dose of pfizer or moderna boost their immune levels of the spike protein?

On 2021-10-20 16:48:45, user Ben Veal wrote:

I doubt it changes the conclusions for the reasons I've already explained. It could be checked by looking at the records to see how many people chose to be vaccinated after being infected for a 2nd time.

On 2021-08-30 02:09:22, user MÅtthew Michæl wrote:

Are you saying they didn't control for comorbidities?<br /> "After adjusting for comorbidities, we found a statistically significant 13.06-fold (95% CI, 8.08 to 21.11) increased risk for breakthrough infection as opposed to reinfection (P<0.001). Apart from age >=60 years, there was no statistical evidence that any of the assessed comorbidities significantly affected the risk of an infection during the follow-up period"<br /> ???

On 2021-09-14 21:53:44, user Kd June wrote:

For viruses?

On 2021-09-03 04:50:38, user Hucello Chuyucello, PhD wrote:

It looks like important factor is missing. Where is the interaction between vaccination and presence of comorbidity?

On 2021-08-29 03:08:09, user sartesian wrote:

"My main concern relates to underlying health status. The infected group will exclude people who have previously died from COVID. The vaccinated group will not. Thus, there is reason to believe the infected group will have better underlying health status than the vaccinated group."

How could the vaccinated group include those who previously died from Covid?

On 2021-10-12 21:03:37, user Ben Veal wrote:

No they're not, if you look at page 7 where it explains the treatment groups it says that group 2 (the pre-infected unvaccinated group) "had not been vaccinated by the end of the study period". So if, after getting reinfected, they went to get vaccinated (within the study period), they would be omitted from the study. <br /> Personally I think recovering from infection makes people less likely to get vaccinated, but perhaps people who've been infected twice are more likely to doubt their natural immunity, and seek vaccination. Steve makes a valid point.

On 2020-07-03 17:29:06, user Harry Wetzler wrote:

Your point is well taken. The last two sentences before the Conclusions state: "We acknowledge the limitations of this analysis, and hence, will update it in September after the August mortality counts stabilize. We will also include quality of life and comorbidity adjusted YLLs." Thank you for your comment.

On 2020-04-23 21:23:57, user Benjamin Goldhagen wrote:

There were dozens of comments here this morning. Where can they be found?

On 2020-04-25 15:11:00, user beencensured wrote:

This study would have been much more helpful if they could give what type of patients with which types of comorbidities had died with Clinical Characteristics of the Patients and demographic data.

Of these types of patients this is the mortality rate for each type of patient including demographics. This data would have been then useful though limited. Right now there are much sicker patient in HCQ group, and so more dead. So to rationalize the study, we should know the death rate for each comorbidity per demographic group including clinical characteristics of patients. This would have given some direction to the study.

On 2020-04-29 22:52:54, user Steven Markowskei wrote:

Could you kindly define what is included in "chronic cardiac disease". <br /> In particular does it include uncomplicated hypertension?

On 2021-10-16 13:53:34, user Sam Smith wrote:

Thanks for the great study, but when will you publish results what happens if one takes Sputnik light as a booster? I am only interested in boosters that give >90% protection against delta, because in Israel 3 doses of Pfizer gives >90% protection.

On 2020-08-12 15:00:46, user Peter wrote:

I think there's a small error in the abstract:

"When a CT cut-off of 33 was employed, above which increasingly, evidence suggests there is a very low risk of patients shedding infectious virus, the diagnostic sensitivity was 100%. The DSe and DSp of Direct-RT LAMP was 67% and 97%, respectively. When setting CT cut-offs of <=33 and <=25, the DSe increased to 75% and 100%, respectively."

I think, in the final sentence, you intended to write:

"When setting CT cut-offs of <=33 and <=25, the DSe and DSp increased to 75% and 100%, respectively."

Hang on - perhaps you did mean the sensitivity with different cut-offs, not the specificity...

Hope this helps...

Peter English

On 2021-11-14 09:47:38, user Justbeenschooled wrote:

There are a few incorrect spellings in this document. But the study is excellent and should be peer-reviewed.

On 2020-03-07 23:15:22, user Jens Schertler wrote:

Thanks for the publication!

1. Do you have data for symptom statistics by age group?
2. I suppose "Table 3: Risk factors for SAR-CoV-3 infection among close contacts" was a typo, it is SARS-CoV-2

On 2020-07-01 22:29:58, user John wrote:

Loneliness is prevalent in COVID-19 crisis. Patients with Coronavirus are more lonely during the pandemic. Interesting findings for health psychology, psychological impact, public health, epidemiology and psychiatry.

On 2021-08-20 02:48:13, user gospace wrote:

I would be willing to wager that if they separated out engineers, real ones, not software engineers, and non-degreed people working in engineering type professions, that they've got the highest rate of dreaded covid vaccine rejection. Not hesitancy, rejection. Maybe the software engineers too, I don't know enough of them to make a call on it.

On 2021-03-02 08:33:10, user Miroslava Zeliznakova wrote:

I am so disgusted how this research was done. The ethical principles were not followed. People didnt know that research is taking place, they were not informed about it. They were forced to test otherwise they have been threatened by government that they can't come out of their house, go to work, post office etc... I am from Slovakia and so many people suffered in hands of the government and i am surprised this study states the participants consent was gained. You should now do another study about how situation is in Slovakia now. Many people had got infected during mass antigen testing actually.

On 2024-08-22 14:42:59, user Gabriel Baldanzi wrote:

This paper is now published in EBioMedicine https://doi.org/10.1016/j.ebiom.2024.104989

On 2021-09-03 11:19:28, user Sam Wheeler wrote:

I noticed the main author Naaber worked at Synlab Eesti. <br /> Do you still use the same IgG spike test for customers of Synlab Eesti and Synlab Finland? It is difficult for customers to interpret as the only information Synlab tells that the reference value is below 50 AU/mL. I was tested at Synlab and got about 6000 AU in June 2021 and about 4000 AU in August after two vaccinations and no covid-19 disease. Perhaps I should take a third dose already in September for maximum protection? I got my second dose in June.

On 2024-06-02 22:51:12, user Hellen Paskaleva wrote:

p. 3, line 10: Clostridium is gram-positive, not gram-negative.

On 2019-07-09 23:24:44, user Guyguy wrote:

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

Tuesday, July 9, 2019

The epidemiological situation of the Ebola Virus Disease dated July 8, 2019:

Since the beginning of the epidemic, the cumulative number of cases is 2,428, of which 2,334 are confirmed and 94 are probable. In total, there were 1,641 deaths (1,547 confirmed and 94 probable) and 683 people healed.<br /> 322 suspected cases under investigation;<br /> 10 new confirmed cases, including 8 in Beni, 1 in Vuhovi and 1 in Oicha;<br /> 11 new confirmed case deaths:<br /> 5 community deaths, including 3 Beni, 1 in Vuhovi and 1 in Oicha;<br /> 6 deaths in Ebola Treatment Center including 3 in Beni, 1 in Mabalako, 1 in Butembo and 1 in Katwa.

The cumulative number of confirmed / probable cases among health workers is 128 (5% of all confirmed / probable cases) including 40 deaths.

NEWS<br /> Ebola Virus Disease in Uganda<br /> The Ministry of Health of the Republic of Uganda announced that all index case contacts have completed their mandatory 21-day follow-up period without developing signs of the disease. As a result, Ebola transmission in Kasese District was interrupted. As a reminder, the index case was a 5-year-old boy who had traveled with his mother to the burial of his grandfather who died of Ebola in Aloya, in the health zone of Mabalako.<br /> Uganda has strengthened its border surveillance system. Thus, all travelers coming from the DRC or having traveled to the DRC during the last 21 days must go through the sanitary control at Entebbe airport and at the various road and sea entry points of the country.<br /> Source: Ministry of Health press team on the state of the response to the Ebola epidemic in the Democratic Republic of Congo.

On 2022-02-08 07:24:12, user Ole Stein wrote:

Misleading and biased conclusions based on wrongfully datatreatment, where they have mixed vaxed with unvaxed, and so unvaxed included all vaxed less than 14 days since last shot and all vaxed include unvased post illness. Such mix is not just unetical, but makes the conclusion completely useless as it does not say anything about contamination between vaxed and unvaxed as they are mixed in their data input. The report should be discarded and removed as fraudulent science.

On 2022-09-19 01:01:30, user Miles Markus wrote:

A question (a subject for future research) arises, indirectly, from this impressive analysis.

Relatively few hypnozoites are present in chronic Plasmodium vivax malaria. But there is a large, concealed, asexual parasite reservoir.

So does tafenoquine prevent a significant proportion of P. vivax malarial recurrences by killing many non-circulating, extra-hepatic merozoites (see reference below)?

Or are the vast majority of recurrences of P. vivax malaria relapses (i.e. recurrences that have a hypnozoite origin), as has been suggested by various researchers?

REFERENCE (the link below can be clicked on): Markus, M.B. 2022. Theoretical origin of genetically homologous Plasmodium vivax malarial recurrences. Southern African Journal of Infectious Diseases 37 (1): 369. https://doi.org/10.4102/saj...

On 2020-07-02 16:54:49, user Garganta Thiago Umberto Pereir wrote:

Federal Brazilian government ordered a nationa lockdown? When? It never happened!

On 2022-01-08 17:26:38, user Jay Haynes wrote:

After considering that omicron is in the wild and is proving to be much more transmissible, the recommendation here is too little too late.<br /> Furthermore, the implications of nasopharyngeal samples with culturable virus being increased among the un-vaccinated needs to be weighed against the findings of this study:<br /> https://www.medrxiv.org/con...

What were the culturable virus levels among the un-vaccinated convalescent?

On 2021-11-18 18:14:57, user Stephen wrote:

Although I tend to agree with the conclusion that achievement of herd immunity is unlikely globally, I do not think the model runs listed in the preprint are convincing. If it is assumed that the basic reproduction number R0 is about 6, as suggested, that would imply a DHIT (Disease herd immunity threshold) of about 83%, which is above the maximum assumed vaccine effectiveness used in the study (80%). While 80% represents a reasonable unweighted average of effectiveness over vaccines and recipient ages, it would be of interest to policy makers to see the results for the best vaccines, for which epsilon is in the 90% range. (Incidentally, the RKI is now saying that for the Delta variant, R0 is in the range 6.0 - 6.7,)

On 2020-04-18 06:35:20, user DomesticEnemy wrote:

About 5 weeks ago based on a study of the Diamond Princess cruise ship I estimated the death rate to be around 0.23% or so. Welcome.

On 2020-04-21 09:14:54, user Michael Rosenberg wrote:

Some additional information about performance of the Premier Biotech test is available at the distributors's web site. See links at the bottom of this page.

Package Insert shows false positive rate of 2/371 for IgG and 3/371 for IgM. It is not clear if same samples that tested positive for IgG also tested positive for IgM or these were different samples. Assuming best case scenario, cumulative FP rate for IgG and IgM is 3/371 (0.8%).

One could add to FP calculation 0/30 FPs reported in the preprint and 0/88 FPs mentioned by Dr. Sood in LA briefing yesterday. Adding these samples brings naive FP rate to 3/489 or 0.6%.

Distributor also provides what appears a submission for approval of the test by China FDA (link). This document shows 3/150 false positives for IgG and 1 - for both IgG and IgM. Therefore cumulative FP rate for IgG and IgM in this study is 4/150 or 2.7%. Note however that this number likely overestimates FP rate - all negative subjects in this study were COVID contacts excluded by PCR.

On 2020-04-18 04:37:52, user Jeff H wrote:

You raise a good point about using exact confidence intervals being preferable to approximate confidence intervals here. However, the confidence intervals in table 2 are small not because of the approximation, but because they incorporate false negatives (sensitivity) and not just false positives (specificity). This is all detailed in the Statistical Appendix.

[Edit: J Spence is correct, the false negatives bring the confidence intervals upwards away from zero, but actually slightly widen them. Curious that Table 2 only sensitivity/specificity adjusts when also making population adjustment. Seeing the test performance adjustment by itself would make clear the impact of delta method approximation by itself, although the Appendix provides enough data to do this on our own.]

On 2020-04-22 01:58:23, user Samuel Soroaster wrote:

The antibody they used according to this study performed the worst of the available COVID-19 antibodies with a specificity of only 87% which makes it useless to perform a serology survey. https://www.medrxiv.org/con...

On 2020-04-24 16:22:33, user gfrenke wrote:

According to the CDC website their flu statistics are based solely on people who were symptomatic. The CDC doesn’t’ do antibody tests after the flu season to see how many were infected with a flu virus but never had symptoms.

On 2021-08-11 18:25:13, user LeMoyne wrote:

The selection for testing is generally driven by self-selection, doctor's request and employment requirements. The selection for inclusion in this study is that the primary testing lab did the test, so this is a look at many or most if not nearly all positive tests in Dane County and other parts of Wisconsin during the month of July. <br /> Clearly either

1 the vaccinated are catching and carrying around the virus or

2 the PCR test can not distinguish between vaccination and the disease.

Given that people arent generally volunteering to have a swab stuck way up their nose I think the primary testing selection criterion is symptoms that may be covid. If the answer is 2 above then how many people are getting sick from the vaccine is a better (and still unstudied) question to ask.

Personally I think 1) is more likely and that the vaccines protective qualities are palliative and temporary due to emerging variants if nothing else.

On 2021-07-29 05:43:08, user FUnlim wrote:

Even though the authors claim to have desmostrated the downstream mechanisms by which the infection inpairs neuronal viability, mechanistically the manuscript still remains lacking of support for that.

Despite the fact that conditioned medium of SARS-CoV-2-infected astrocytes reduces neuronal viability, this can be caused by many things beside the metabolic alterations. So, it should be tested.

All conclusions are based on proteomics data only. They should validate the metabolite levels, mainly for the highlighted ones.

On 2021-02-07 02:46:04, user Mark wrote:

When will updated results be posted?

On 2020-12-25 14:25:32, user muthu venkat wrote:

The Systematic Review and Meta-Analysis is interesting to read and need of the time to compile such an evidence particularly for middle and low income country. The authors have made sure that there is no bias in selection and reporting the evidences through use of appropriate software and methods.

On 2025-02-23 19:55:05, user Jan Páleš wrote:

Hello, I cant find any Ees formula in the reference 10...

On 2021-09-30 12:14:12, user Joren Buekers wrote:

Exciting research! I hugely support focussing on continuous SpO2 measurements instead of discrete/spot check measurements only! I'm happy that this finally found its way to COVID research. <br /> A small remark/request: you indicated that "preprocessing of the raw SpO2 signal was performed using a block filter as in Levy et al.", but this block filter was actually developed in another study (https://doi.org/10.2196/12866) "https://doi.org/10.2196/12866)"). Would it be possible to acknowledge the original paper as well? (Sorry for the self-promotion, but I do think it's more correct to refer to the original paper).

On 2021-02-21 01:30:58, user Offer wrote:

Were the vaccinated tested at the same rate as the unvaccinated after enrollment date?<br /> As the tested unvaccinated population is larger than the tested vaccinated population following enrollment date is larger - we also don't know how frequently the unvaccinated were tested after enrollment date compared to the vaccinated population. (We only know they were tested 1 or more times, but not the actual test rate).

On 2021-06-12 18:25:00, user Tracii Kunkel wrote:

Then why do we get the influenza vaccine yearly? I've had the flu, I shouldn't ever need a flu vaccine again then should I?

On 2021-06-09 18:09:15, user Paul Cwik wrote:

Peer Review in this case does not mean that peers reconduct the experiments. It simply means that others (with suitable credentials) have read and accepted the paper as having correctly followed the scientific methods. In other words, they are simply looking for errors in the paper, not re-doing and confirming the results.

On 2021-06-13 17:13:57, user artpatronforever wrote:

Quote "No drug for prevention or treatment in earlier stages of COVID-19 are yet found;" In an alternate reality certainly that could be true. In that same alternate reality likewise it could be true that a dosage of a vaccine is properly the same for a 100 pound woman as for a 300 pound man. I choose not to place confidence in wisdom offered from that alternate reality where originates such lame disinformation. Truth has no agenda but disinformation certainly does have an agenda.

On 2020-06-07 12:40:21, user OxImmuno Literature Initiative wrote:

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

On 2022-06-24 22:03:50, user Charles Warden wrote:

Hi,

Thank you very much for posting this preprint. This certainly represents a large amount of work and careful consideration!

I have some questions / comments:

1) Is there a way for me to calculate enhanced scores for myself?

For example, I would like to learn more, but I was not very satisfied with the PRS that I listed for my own genomic sequence in this blog post:

https://cdwscience.blogspot...

2) In the blog post link above, there seemed to be a noticeable disadvantage to the PRS without taking the BMI into consideration for Type 2 Diabetes.

In this paper, age is an important factor in Figure 1 for the PRS.

If other non-genetic factors are known, do you have a comparison for non-PRS models? <br /> For example, I wonder how performance of age + BMI (+ other established factors) compares to the plot for Type 2 diabetes in Figure 1.

3a) I see that the percent variance explained is sometimes provided (such as Supplemental Figure 5), but sometimes it is not.

For example, in Figure 3, the effect per 1 SD of PRS is higher for LDL cholesterol than height. However, how does the ability to predict an individual's height from genetics alone compare to the ability to predict an individual's LDL from genetics alone?

After a certain age (as an adult), the exact value for my own LDL has varied more than my height. However, I was not sure how that variation by year compared to others and/or the variation over decades.

In general, I would like to have a better sense of how absolute predictability compares for height versus disease scores. I also understand that there are complications with binary versus continuous assignments, but it is something that I thought might be helpful.

3b) I see AUC statistics in Supplemental Figure 2, described as for AUROC. However, am I correct that some of the cases are not well balanced with controls?

If so, should something like AUPRC be provided (possibly as a complementary supplemental figure)? I believe the idea is described in Saito and Rehmsmeier 2015; the application is very different, but you can see the inflated AUROC values in Figure 1A of Xi and Yi 2021. I expect that there are other good ways to illustrate the differences with PRS in cases and controls of varying proportions, but that was one thought.

In the context of genomic risk, I might expect that high predictability in a small number of individuals may be preferable over a small difference in low predictability in a large number of individuals. There is emphasis on thresholds like top/bottom 3% (in many but not all figures), which I thought might be consistent with that opinion.

So, I think something like Figure 1 was helpful. In order to try and capture how false positives change when sensitivity increases, I am not sure if something similar for positive predictive value might help? I would consider that very important if the PRS might be used for screening purposes.

4) In the Supplemental Methods, I believe that you have a minor typo:

Current: 100,000 Genomes Project (100KGP). The 100,00 Genomes Project, run by Genomics England,<br /> Corrected: 100,000 Genomes Project (100KGP). The 100,000 Genomes Project, run by Genomics England,

Thank you very much!

Sincerely,<br /> Charles

On 2020-11-08 03:03:45, user perrottk wrote:

Comments on “A Benchmark Dose Analysis for Maternal Pregnancy Urine-Fluoride and IQ in Children”<br /> I question the validity of attempting to determine a BMC for the effect of fluoride intake on IQ without first ascertaining if there is a real effect. The problem of this document is that it assumes an effect without making a proper critical assessment of the evidence for a causal effect.<br /> The draft paper relies completely on two studies which reported very weak relationships from exploratory analyses. Nothing wrong with doing exploratory analyses – providing their limitations are accepted. Such analyses can indicate possibilities for future studies testing possibly causes – but, in themselves, they are not evidence of causation. These studies provide no evidence of causal effect<br /> The studies this draft relies as evidence that fluoride causes a lowering of child IQ illustrates have the following problems.<br /> 1: Correlation is not evidence of causation – no matter how good the statistical relationship. And reliance on p-values is not a reliable indicator of the strength of a relationship anyway The two studies relied on here do not report the full results of statical analyses which would have revealed the weaknesses of the relationships.<br /> 2: These two studies were exploratory – using existing data. They were not experiments specifically designed to establish a cause.<br /> 3: Many other factors besides those investigated can obviously be important in exploratory studies where there is no control of population selection. While authors may claim confounders are considered it is impossible to do this completely – there are so many possible factors to consider. Most are not included in the datasets used and the researchers may make their own selection, anyway.<br /> The study of Malin & Till (2015), referred to in this draft, illustrates the problems. Malin & Till (2015) reported what they considered reasonably strong relationships (p-values below 0.05 and R squared values of 0.21 to 0.34 indicating their relationships explained 21% to 34% of the variance in ADHD prevalence). However, their consideration of possible other risk-modifying factors was limited. They did not include state elevation which Huber et al (2015) showed was correlated with fluoridation. The strength of Huber’s relationship (R squared 0.31 indicating elevation explained 31% of the variance in ADHD prevalence) was similar to that reported by Malin & Till for fluoridation.<br /> Perrott (2018) showed that when elevation is included in the statistical analysis the relationship of ADHD prevalence with fluoridation was non-significant (p>0.05). This show the danger of relying on the results of statistical relationships from exploratory studies where consideration of other possible risk-modifying factors is limited.<br /> 4: This draft paper relies on the reported links between cognitive factors and F intake without testing for a causal effect. But it also does not critically assess those correlations. The problems of confounders have already been mentioned but these two studies report very weak relationships or, in most cases, no statistically significant relationships.<br /> For example, of the 10 relationships between measures of fluoride exposure and cognitive effects Green et al (2019) reported that only 4 were statistically significant (Perrott 2020). That is not evidence of a strong relationship and underlines the danger of assuming correlations (especially selected correlations) are evidence of causation. Incidentally, this draft paper mentions the study of Till et al (202) which also reported relationships between fluoride exposure with bottle-fed infants and later cognitive effects. In this case only three of the 12 relationships reported were statistically significant (Perrott 2020).<br /> Even those relationship reported as significant were still very weak. For example Green et al (2015) reported a relationship for boys which explained less than 5% of the variance of IQ measures.

The relationships reported by Bashash et al (2017) were also extremely weak – explaining only about 3.6% of the variance in IQ and 3.3% of the variance in GCI. This weakness is underlined by other reports of relationships found for the Mexican ELEMENT database. Thomas (2014) did not find a significant relationship of MDI with maternal urinary fluoride for children of ages 1 to 3 although in a conference poster paper Thomas et al (2018) reported a statistically significant relationship for urinary fluoride adjusted using creatinine concentrations.<br /> 5: As well as ignoring the incidence of non-significant relationships from these studies this draft paper also ignores the findings of positive relationships from other studies. For example, Santa-Marina et al (2019) reported a positive relationship between F intake indicated by maternal urinary F and child cognitive measures. Thomas (2014) also reported a positive relationship of child IQ (MDI for 6 – 15-year-old boys) with child urinary fluoride.<br /> 6: The draft paper describes the two studies it uses for its analysis as “robust” but ignores the fact that the findings in these and other relevant studies are contradictory. For example, the findings reported in the two papers differ in that Bashash et al (2017) did not report different effects for boys and girls whereas Green et al (2019) did. Santa-Marina et al (2019) reported opposite effect to those of Bashash et al (2017) and Green et al (2019). These contradictory findings, together with the lack of statistical significance for most of the relationships investigated, are perhaps what we should expect from relationships which are as weak as these are.<br /> Summary<br /> The paper relies on weak relationships from exploratory studies. Such relationships, even where strong, cannot be used as evidence for causation and to assume so can be misleading. BMCs and similar functions derived without any evidence of real effects are not justified. While the derived BMCs may be used by activists campaigning against community water fluoride, they will be misleading for policy makers. This sort of determination of BMC is a least premature and a worst meaningless.<br /> References:<br /> Bashash, M., Thomas, D., Hu, H., Martinez-mier, E. A., Sanchez, B. N., Basu, N., Peterson, K. E., Ettinger, A. S., Wright, R., Zhang, Z., Liu, Y., Schnaas, L., Mercado-garcía, A., Téllez-rojo, M. M., & Hernández-avila, M. (2017). Prenatal Fluoride Exposure and Cognitive Outcomes in Children at 4 and 6 – 12 Years of Age in Mexico. Enviromental Health Perspectives, 125(9).<br /> Green, R., Lanphear, B., Hornung, R., Flora, D., Martinez-Mier, E. A., Neufeld, R., Ayotte, P., Muckle, G., & Till, C. (2019). Association Between Maternal Fluoride Exposure During Pregnancy and IQ Scores in Offspring in Canada. JAMA Pediatrics, 1–9.<br /> Huber, R. S., Kim, T.-S., Kim, N., Kuykendall, M. D., Sherwood, S. N., Renshaw, P. F., & Kondo, D. G. (2015). Association Between Altitude and Regional Variation of ADHD in Youth. Journal of Attention Disorders.<br /> Malin, A. J., & Till, C. (2015). Exposure to fluoridated water and attention deficit hyperactivity disorder prevalence among children and adolescents in the United States: an ecological association. Environmental Health, 14(1), 17.<br /> Perrott, K. W. (2018). Fluoridation and attention deficit hyperactivity disorder a critique of Malin and Till (2015). British Dental Journal, 223(11), 819–822.<br /> Perrott, K. W. (2020). Health effects of fluoridation on IQ are unproven. New Zealand Medical Journal, 133(1522), 177–179.<br /> Santa-Marina, L., Jimenez-Zabala, A., Molinuevo, A., Lopez-Espinosa, M., Villanueva, C., Riano, I., Ballester, F., Sunyer, J., Tardon, A., & Ibarluzea, J. (2019). Fluorinated water consumption in pregnancy and neuropsychological development of children at 14 months and 4 years of age. Environmental Epidemiology, 3. <br /> Thomas, D. B. (2014). Fluoride exposure during pregnancy and its effects on childhood neurobehavior: a study among mother-child pairs from Mexico City, Mexico [University of Michigan].<br /> Thomas, D., Sanchez, B., Peterson, K., Basu, N., Angeles Martinez-Mier, E., Mercado-Garcia, A., Hernandez-Avila, M., Till, C., Bashash, M., Hu, H., & Tellez-Rojo, M. M. (2018). OP V – 2 Prenatal fluoride exposure and neurobehavior among children 1–3 years of age in mexico. Environmental Contaminants and Children’s Health, 75(Suppl 1), A10.1-A10.<br /> Till, C., Green, R., Flora, D., Hornung, R., Martinez-mier, E. A., Blazer, M., Farmus, L., Ayotte, P., Muckle, G., & Lanphear, B. (2020). Fluoride exposure from infant formula and child IQ in a Canadian birth cohort. Environment International, 134(September 2019), 105315.

On 2020-07-30 17:31:33, user Wayne Saslow wrote:

Aerosol-sized droplets have been studied by physicists since at least 1897, when J. J. Thomson used them in determining the properties of electrons. In a chamber with no air current, he observed the fall of a water droplet; from its terminal velocity v he estimated the droplet radius R -- at terminal velocity the force of gravity downward is balanced by the (Stokes) drag force upward. The gravity force varies as the droplet volume (proportional to the cube of R) but the Stokes drag force is proportional to vR, so at terminal velocity v is proportional to the square of R: doubling R makes v four times larger.

Therefore the larger droplets in an aerosol fall out quickly, but the smaller droplets (but not too small to include a virus particle) remain much longer. So it should not be surprising that aerosols are important for coronavirus transmission; they stay in the air much longer than larger droplets.

To finish the story, knowing the droplet radius R helped Thomson in the following way: he was able to obtain the gravitational force on the droplet. He then put a sheet of negative charge below the aerosol, and found that some of the droplets floated, so the electric force due to electrons on the aerosol cancelled the gravitational force. This permitted an estimate of the charge on the electron. A few years later Millikan used less-quickly evaporating oil drops to make a more accurate measurement of the electron charge.

Why care? Without electrons, no atoms; without atoms, no molecules; without molecules, no DNA; without DNA, no biology.

On 2020-08-11 17:07:00, user John Kutil wrote:

Do you know when the study will be peer reviewed?

On 2020-04-07 20:57:35, user Xavier de Roquemaurel wrote:

The BCG strain does have an impact on the efficiency of the immunity. Could you run the study one step further and identify if the Tokyo-172 strain (or another strain) has a higher response against Covid-19?<br /> Data from Taiwan, Japan and Malaisia seem to say so. It needs now a scientific evaluation. Thanks. X

On 2021-01-27 15:44:21, user Steve Goodacre wrote:

Now published in PLOS ONE<br /> https://journals.plos.org/p...

On 2022-02-10 09:12:52, user Alban Ylli wrote:

This article should be updated to match the same article published in BMC Public Health. Several results are (slightly) different

On 2021-04-06 07:47:45, user NAZ Mohamed wrote:

This article is now published in the International Medical Journal<br /> Full text is available at

https://www.researchgate.ne...

On 2020-11-25 07:42:20, user Carol Shadford wrote:

When you say 'continual sensation of having had a “nasal douche”' are you referring to a feeling that the sinuses have been cleared out and are now empty or is that referring to the rushing feeling you get when chlorinated water accidentally goes up your nose -- a wasabi-like feeling?

On 2021-08-24 09:17:07, user Martin Steppan wrote:

A fundamental methodological caveat of this article is the date / season of sample collection. Breakthrough infection samples were collected in the sprjng-summer period of 2021 only (apr-jul), whereas unvaccinated samples seem to be predominantly from fall / winter 2020 (apr-dec). It has been shown in many studies that sars-cov-2 virions are temperature-sensitive and less active / infectious in warm environments. Hence, the results of this manuscript may reflect a seasonal pattern in infectivity. The authors may want to control for this statistically by either (1) using a matched design of samples from similar dates; (2) include historical temperature data for the Netherlands as a covariate / proxy for this likely bias. Due to this reason, the analyses in their current form do not rule out this bias, which casts doubt on the authors' implicit hypothesis that vaccination status moderates the link between viral load and infectiousness.

On 2021-06-19 05:24:16, user David Gurwitz wrote:

On June 18 2021, Duarte et al. published in Lancet EClinical Medicine this peer-reviewed article, reporting on the outcome of a clinical trial conducted at at a university and a community hospital in Buenos Aires, Argentina: "Telmisartan for treatment of Covid-19 patients: An open multicenter randomized clinical trial".<br /> DOI:https://doi.org/10.1016/j.e...<br /> From their Abstract, note in particular this:<br /> "Death by day 30 was reduced in the telmisartan-treated group (control 22.54%, 16/71; telmisartan 4.29%, 3/70 participants; p = 0.0023). Composite ICU, mechanical ventilation or death was reduced by telmisartan treatment at days 15 and 30. No adverse events were reported."

On 2021-09-15 21:29:23, user omar okasha wrote:

I have to say this is rather odd way to do BRA. I am not commenting on your observed rates, as others already did. So I will focus on the expected rate side. First, the OE analysis should be based on background rates of myocarditis in the general population. There is an abundance of publicly available data from massive collaborative projects such as OHDSI or ACCESS, so I don't really understand your decision not to compare background rates of myocarditis. But more troubling is the choice of COVID hospitalisations. It's almost a rule of thumb that the expected rates should never be based on a condition that may be influenced by the vaccine in question or, for that matter, any public health/mitigation policies that are contextually related. One could immediately see vaccination could have differential effect on both sides of the comparison: on one side it would drive COVID hospitalisation down, given the potential effect on transmission, and on the other side it could potentially drive myocarditis among vaccinated kids up, if the risk is real. As a result, you will overestimate the risk of myocarditis among the vaccinated. The effect of non-interventional mitigation measures will further decrease the risk of COVID-19 hospitalisation, but without having an effect on the risk of post-vaccination myocarditis, leading to further overestimation of the risk of myocarditis among the vaccinated. Though too obvious, this was apparently overlooked by the US CDC. The OE analysis should also be based on the same conditions and the same risk windows, which is far from what you did here. Thus, the risk of COVID-19 hospitalisations cannot be considered the counterfactual in this analysis. <br /> Last, I think you should have highlighted in the abstract that the risk of COVID hospitalisations among those with comorbidities was actually greater than the risk of myocarditis. Otherwise it's rather misleading.

On 2020-09-22 19:05:10, user fennudepidan wrote:

If applicable, please cite the following peer-reviewed version of the manuscript: Wu, X., Nethery, R.C., Sabath, M.B., Braun, D. and Dominici, F., 2020. Air pollution and COVID-19 mortality in the United States: strengths and limitations of an ecological regression analysis. Science Advances (in press).

On 2020-04-23 00:38:21, user Alexey Karetnikov wrote:

Have you determined actual viral loads in samples taken from patients, and have you compared them with viral loads in Vero cells? Also, have you looked at possible correlation between the severity of symptoms of the patients and your CPE in Vero cells? This would be much more meaningful than mere infectivity assays in Vero cells. I could not find these data in your manuscript, unless I have missed them.

On 2020-07-27 21:49:29, user Dude Dujmovic wrote:

94% in the abstract, 92% in the body of text?

On 2020-10-05 14:16:29, user Julii Brainard wrote:

Our article got kicked back for flaw= reporting 'suspected' not only confirmed cases in same period. I will be curious how Ian's team's work gets received using same case criteria.

On 2020-02-13 16:35:13, user dontlistentothepundits wrote:

To the study authors <br /> What medications did the patients receive during their hospitalization ? Were any of them taking Avelox or other Fluoroquinolones or antibiotics that have side effects that include the kidneys ?

On 2021-10-21 21:51:01, user CDSL JHSPH wrote:

Thank you for sharing your clinical study! I greatly enjoyed reading your experimental design and wanted to compliment the impeccable organizational flow of this manuscript. I also appreciated the information discussed in the introduction, since I wasn't fully aware of the details regarding BA metabolism and the link it had to the microbiome. I noticed in the section of the results discussing "age related changes in bile acid and microbiome profiles" figure 2D was mentioned twice, if I am not mistaken I believe figure 2C shows an increasing trend with age. I was also wondering whether you encountered any outliers in the P2Ab group, that may have been omitted due to an insignificant contribution, that did not show a significant decrease in conjugated bile acids over time? If there were any, could this be due to confounding lifestyle factors? Once again, this was a very interesting experiment and i'm hoping to see larger studies conducted in the future!

On 2020-04-07 19:27:46, user Archisman Mazumder wrote:

Indian study showing COVID-19 affects the 20-39 yrs age group most in India. This really has to be studied further. Even the Health Ministry of India corroborated the findings.

On 2023-03-02 18:33:37, user Daniel Park wrote:

Fascinating. Lines up well with other evidence including the Lewnard et al. study showing interactions b/w pneumococcal carriage and SARS-CoV-2. We also saw similar patterns with viral load (+ severity) and pneumococcal carriage with human endemic CoVs: https://journals.lww.com/pi...

On 2020-06-21 12:42:23, user OxImmuno Literature Initiative wrote:

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

On 2020-10-17 19:50:42, user Martijn Hoogeveen wrote:

The paper has been accepted by Elsevier Science's journal Science of the Total Environment on October 11, 2020. Link will be shared when live.

On 2021-11-15 08:07:51, user kdrl nakle wrote:

Awesome, but now you need manufacturer.

On 2020-08-12 11:31:19, user Johanna wrote:

I would like to alert the authors and readers that the estimate reported from Aiello 2010 and 2012 is that from the comparison "face mask/hand hygiene vs Control", and not the comparison "face mask only vs Control". Surely, when numbers of face mask vs Control is available, one wouldnt want to include a measure confused with hand hygiene on top of face masks? The corresponding estimate for face masks alone for the 2012 paper was 1.08 (0.86-1.34). For face mask + hand hygiene, it was 0.78 (0.59-1.05), wich tells quite a different story. I am afraid this preprint needs another round of proof-reading of the extraction of raw data from the original articles.

On 2021-04-09 12:49:29, user Francesco Pilolli wrote:

In spite of the difficulties encountered by other studies evaluating the efficacy of therapies in outpatients, this work describes an impressive statistically significant reduction in the hospitalization rate.<br /> This study reports a share of hospitalised patients in the “recommended” cohort (2,2%) similar to the one described in the placebo groups of the Pfitzer-Biontech (2,5% https://www.fda.gov/media/1... ) and Moderna (3,3% https://www.nejm.org/doi/fu... ) vaccine studies between symptomatic cases (these studies did not exclude hospitalised cases at the onset), but it describes an impressive 14,4% share of hospitalised cases in the “control” group.<br /> This rate is much higher than the one described in the placebo group in the Bamlanivimab and Etesevimab study in high-risk outpatients (7% https://www.fda.gov/media/1... ) and in the COLCORONA trial again in the placebo group of high-risk outpatients (5,8% https://www.medrxiv.org/con... ).<br /> It’s peculiar that this study (carried out on general population and excluding severe cases at onset) describes a hospitalization rate in the control group much higher than that observed in other studies in high-risk patients, considering also hospitalisation at onset.<br /> I think that the majority of the difference of the hospitalisation ratio between “recommended” and control group could be explained by the choice of selecting 88 out of 90 cases of the control group from people infected in the first wave in the province of Bergamo, one of the most severely hit zones in Italy.<br /> The control group required swab or serological positivity but the swab test capacity was limited in Italy during the first wave and it is very unlikely that all the symptomatic people underwent a serological test. During the first wave many symptomatic people were at home without having undergone any swab. The limited test capacity causes a high underestimation of paucisymptomatic and mild cases resulting in a high rate between hospitalisation and tested cases.<br /> In fact the Italian ratio between hospitalisation and tested cases from March to May 2020 (the same infection period of 88 out of 90 patients of the control cohort) was 36,4% compared to the 7,8% observed from October 2020 to January 2021 https://www.epicentro.iss.i...<br /> This difference was much higher for the province of Bergamo. Data about daily hospitalisation by province are not public but we know the cases ( https://lab24.ilsole24ore.c... and deaths ( https://www.istat.it/it/fil... ) by province until December 2020. While the ratio between Italian cases and deaths was 14,8% from March to May 2020, it falls to 2,2% from October to December, in the same periods the rate deaths/cases in the province of Bergamo was 23,4% (almost one patient with positive swab every four died in the first wave) and 1,5% (less than the Italian average).<br /> Therefore, it is very likely that the majority of the difference in the hospitalisation rate between the “recommended” (from the second wave) and the “control” cohort (from the first wave in the most hit zone in Italy) is explained by the different historical moments which were characterised by a large difference in test capacity and many symptomatic people at home without getting tested during the first wave.

On 2020-04-07 23:34:20, user Karl Riley wrote:

It's worth looking at the benefits of a strategic infection variant, whereby those known to be at least risk of death are exposed to the virus in a controlled environment and then 'released' back into the general population thereby facilitating herd immunity. You could even have those, then known to be immune, as a form of shield in areas looking imminently vulnerable (hospital admission figures could be part of the data used for this) to the spread of the infection.

On 2024-12-20 20:46:20, user Jakub wrote:

You have stated: "We performed targeted metabolomics to quantify the absolute abundance of known uremic toxins, including (...) 4-ethylphenyl sulfate (4-EPS) (...) in plasma of this cohort. As expected, CKD and PAD+CKD groups had significantly higher levels of all these uremic toxins (Figure 3A)." Unfortunately, Figure 3A does not provide data on 4-ethylphenyl sulfate. May you add data on this solute?

On 2020-03-22 15:56:46, user Sinai Immunol Review Project wrote:

Main findings<br /> The authors characterized the immune response in peripheral blood of a 47-year old COVID-19 patient. <br /> SARS-CoV2 was detected in nasopharyngeal swab, sputum and faeces samples, but not in urine, rectal swab, whole blood or throat swab. 7 days after symptom onset, the nasopharyngeal swab test turned negative, at day 10 the radiography infiltrates were cleared and at day 13 the patient became asymptomatic.

Immunofluorescence staining shows from day 7 the presence of COVID-19-binding IgG and IgM antibodies in plasma, that increase until day 20. <br /> Flow cytometry on whole blood reveals a plasmablast peak at day 8, a gradual increase in T follicular helper cells, stable HLA-DR+ NK frequencies and decreased monocyte frequencies compared to healthy counterparts. The expression of CD38 and HLA-DR peaked on T cells at D9 and was associated with higher production of cytotoxic mediators by CD8+ T cells.<br /> IL-6 and IL-8 were undetectable in plasma.<br /> The authors further highlight the presence of the IFITM3 SNP-rs12252-C/C variant in this patient, which is associated with higher susceptibility to influenza virus.

Limitations of the study<br /> These results need to be confirmed in additional patients.<br /> COVID-19 patients have increased infiltration of macrophages in their lungs{1}. Monitoring monocyte proportions in blood earlier in the disease might help to evaluate their eventual migration to the lungs.<br /> The stable concentration of HLA-DR+ NK cells in blood from day 7 is not sufficient to rule out NK cell activation upon SARS-CoV2 infection. In response to influenza A virus, NK cells express higher levels of activation markers CD69 and CD38, proliferate better and display higher cytotoxicity{2}. Assessing these parameters in COVID-19 patients is required to better understand NK cell role in clearing this infection. <br /> Neutralization potential of the COVID-19-binding IgG and IgM antibodies should be assessed in future studies.<br /> This patient was able to clear the virus, while presenting a SNP associated with severe outcome following influenza infection. The association between this SNP and outcome<br /> upon SARS-CoV2 infection should be further investigated.

Relevance<br /> This study is among the first to describe the appearance of COVID-19-binding IgG and IgM antibodies upon infection. The emergence of new serological assays might contribute to monitor more precisely the seroconversion kinetics of COVID-19 patients{3}. Further association studies between IFITM3 SNP-rs12252-C/C variant and clinical data might help to refine the COVID-19 outcome prediction tools.

References<br /> 1. Liao, M. et al. The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing. http://medrxiv.org/lookup/d... (2020) doi:10.1101/2020.02.23.20026690.<br /> 2. Scharenberg, M. et al. Influenza A Virus Infection Induces Hyperresponsiveness in Human Lung Tissue-Resident and Peripheral Blood NK Cells. Front. Immunol. 10, 1116 (2019).<br /> 3. Amanat, F. et al. A serological assay to detect SARS-CoV-2 seroconversion in humans. http://medrxiv.org/lookup/d... (2020) doi:10.1101/2020.03.17.20037713.

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

On 2020-04-23 01:55:25, user TREY RIVER wrote:

https://www.mediterranee-in...

A medical rebuttal to add to the logical ones provided by simply reading Page 12 in which the authors of this work state that they EXPECTED the medicated patients to have a higher death rate.

On 2020-04-22 22:01:00, user Wolfgang Wodarg wrote:

Maybe you just forgot, that the prevalence of G6PD-deficiency among <br /> black citizens is about 20 -30%. If you give them some sort chloroquine <br /> in a high dose and don't think of favism, hemolysis and mikroembolia in <br /> brain, kidneys and other organs, they will die.<br /> If doctors go on doing that in Africa, it get's the taste of genocide. Please see my <https: <a href="www.bmj.com" title="www.bmj.com">www.bmj.com="" content="" 369="" bmj.m1432="" rr-22="">comment here:

On 2021-10-04 14:53:53, user Mark Purtle wrote:

This article only addresses one part of induced immunity ie antibodies. No mention of cell-mediated immunity and that may be as important or more so long term. Not enough research in that aspect of immunity thus far.

On 2025-05-20 23:35:08, user Richard Rebello wrote:

Now published online https://www.nature.com/articles/s41467-025-59661-x

On 2022-07-29 09:25:01, user Dr. D. Miyazawa MD wrote:

Please also refer to previous studies.

Hypothesis that hepatitis of unknown cause in children is caused by adeno-associated virus type 2 (08 May 2022)<br /> https://www.bmj.com/content...

Daisuke Miyazawa. Possible mechanisms for the hypothesis that acute hepatitis of unknown origin in children is caused by adeno-associated virus type 2. Authorea. May 16, 2022.<br /> DOI: 10.22541/au.165271065.53550386/v2

On 2020-02-02 15:58:08, user Martin Modrák wrote:

Summary: The provided analysis can IMHO be a helpful complement to other efforts to estimate incubation rate of 2019-nCoV. The uncertainty of estimates of incubation rate and other intervals provided in the abstract is likely greater then what is reported, the numbers thus should be treated with caution. Only cases outside of Wuhan up to January 24th 2020 are included (31 - 43 cases are available for the individual subanalyses).

This review has been crossposted on pubPeer, medRxiv, prereview.org.

Disclaimer: I lack background in epidemiology to let me evaluate whether the proposed modelling approach is a standard one, if much better tools are available or if there are possible issues with the underlying data. In the following, I therefore focus primarily on the statistical aspects of the method employed, without considering alternative approaches.

The big picture:<br /> The main idea of the preprint is to use cases of 2019-nCoV reported in patients that spent only a short time in Wuhan to estimate incubation rate. The underlying assumption is that those patients could have been exposed to the virus only during their stay in Wuhan.

Strengths:<br /> The approach is interesting in that it removes the need to directly guess when/how the patients got into contact with the virus. It is also conceptually simple and requires few additional assumptions.

I find it great that multiple models for the time intervals are tested and reported. The fact that the models mostly agree increases my confidence in the results.

I further congratulate the authors on being able to put the analysis together very quickly and provide a clear and concise manuscript. I am thankful they posted their results publicly as soon as possible.

Limitations:<br /> The main disadvantage of the chosen approach is that it let's the authors to only use a fraction of the reported cases and that the approach is only valid on data from the early phase of the epidemic. Once more cases happen outside Wuhan, the number patients who have become infected elsewhere will increase and the approach of this preprint will no longer be applicable. This is however not strongly detrimental to the manuscript and it could hopefully serve as one of many approaches to estimate the characteristics of 2019-nCoV, each with its own strenghts and limitations.

There are however some specific points I find problematic in the manuscript.

1) Using AIC for model selection might be brittle, especially since the differences in AIC are very small and the AIC itself is a noisy measure. Using some sort of model averaging and/or stacking would likely be beneficial.

2) Also, no explicit effort to verify that the models used are appropriate has been reported. A simple model check would be to overlay the actual data over Figure 1 (e.g. the empirical CDF produced assuming both exposure and onset happend in the middle of the interval). Similar effort could be useful for Figure 2.

3) Taking 1 and 2 together implies there is substantial uncertainty about which model is the best. Further, no strong guarantees that at least one of the proposed models is appropriate were given. The uncertainty bounds computed using only the "best fit" model are therefore certainly overly optimistic as they ignore this uncertainty. While this is challenging to account for mathematically, I believe it should be reported prominently in the manuscript to avoid confusion.

4) While using only visitors to Wuhan makes sense to estimate the incubation period, the estimates of time from illness onset to hospitalization and/or death would likely benefit from including all cases. I don't see why only using cases outside of Wuhan for these other estimates is beneficial. I can however see why incubation period might be the primary focus of the paper and therefore a dataset with cases in Wuhan was not constructed.

5) For some reason the link to supplementary data is broken (probably not author's fault), so I cannot investigate the dataset. Code is also not available so it is hard to judge the modelling approach in detail.<br /> I have contacted the authors and will update this review if I receive that data and/or code.

The only issue I feel strongly about in this manuscript is with the abstract, which should IMHO clearly state that only a small number of cases has been used and that the uncertainty is likely larger than what was computed. Otherwise the paper seems to be a good contribution to the global effort to understand 2019-nCoV.

On 2020-11-11 00:15:13, user kdrl nakle wrote:

This is not to be trusted, we have no idea how the patients were selected (if at all) for SORT <9 and >9 and there is no control group for either. For all we know the results could easily be because of the course of the disease than about remdesivir.

On 2022-02-19 17:39:42, user Zywicki wrote:

Are the Supplementary Tables available? Particularly Table S4 with the breakdown of AE's. There is a Figure that summarizes it but not the raw data. I didn't see it linked here--forgive me if I overlooked it. Thanks.

On 2020-07-16 19:17:14, user Kamran Kadkhoda wrote:

Such high sero-prevalence suggest very high false passivity rate...

On 2021-10-03 09:50:51, user kdrl nakle wrote:

Interesting. Authors spent only three sentences to speculate why would this be the case. But this would also imply that vaccination induced immunity is more effective than natural immunity and I don't think this is yet conclusively proven.