6,998 Matching Annotations
  1. Mar 2026
    1. On 2024-12-14 16:10:34, user Yann Kull wrote:

      First of all, thank you to the researchers for advancing biomedical research on Long COVID.

      Here are some notes I had:

      individuals meeting long COVID criteria were defined as those who (1) reported presence of COVID-19 symptoms that could not be explained by alternative diagnoses; (2) reported ongoing significant impact on day-to-day activities; or (3) had any diagnosis codes of long COVID in their electronic health records. Primary analyses used population controls (i.e., all non-cases)

      What irks me about this selection is it is completely unclear what happens to people that develop post COVID cases of ME/CFS, POTS, or other common labels often included in long COVID subtypes.

      Does that count as an “alternative diagnosis” which means they aren’t in the study cohort. If so it might end up being a weird exclusion of more severe ME and POTS cases resulting from COVID because they are more likely to be separately diagnosed, while including mild ones under the long COVID label? This makes the data quite messy, and it worries me the long COVID label is doing more harm than good at this point. Studying a heterogeneous set of conditions resulting from a viral infection, perhaps through different mechanisms, as a single entity, will likely dilute useful subtype level findings.

      The data seems to be coming from the 2023 long COVID GWAS using the COVID Host biobank. Who’s major finding was an association with FOXP4 Locus

      FOXP4 has been previously associated with COVID-19 severity6, lung function8, and cancers9, suggesting a broader role for lung function in the pathophysiology of Long COVID.

      This suggests the signals they are picking up are likely related to susceptibility to lung damage from COVID, Post-ICU syndrome and the such. In this context, this study’s association with clotting genes makes more sense, and perhaps points to the fact even if there is a buildup of evidence behind the microclot data, it likely isn’t going to be relevant for post-COVID ME/CFS.

    1. On 2020-04-18 17:11:55, user Clint Cooper wrote:

      Please allow me five responses to this study:<br /> 1. Yes, it's true that there are large numbers of people who have probably been exposed to Covid-19 and experienced no symptoms and have antibodies. The best country to look at with regard to testing mass numbers of people randomly is Iceland. Icelad has now tested over 11% of its entire population and a lot of testing was truly done randomly. The fatality rate there is around .6%, or one in about 167 people. In New Zealand, which has also engaged in massive testing, the fatality rate is about .8% or 1 in 125 people. HOWEVER (and this is a big however). the fatality rate in both countries has gone up steadily and is continuing to go up. Also, in those countries the average age of people infected is much lower than in other countries, like Italy, who have been hit much harder by this disease. This actually jives with the original fatality rate given by the World Health Organization, which was around .3 to .5% for younger people, and markedly higher for older people. <br /> Also, the average fatality rate for the common flu is about 1 in 2,000. So even if we can agree that the fatality rate of Covid-19 might be lower than originally thought, it's way more dangerous than any common flu. It is also exponentially more contagious, which is a huge part of the problem. <br /> 2. As testing becomes more and more widely available across the planet, the fatality rate has gone markedly up across the board, not down. For closed cases, the fatality rate has gone from 3-4% initially to now 21% and rising.<br /> 3. The fatality rate in this study assumes that no one ever died at home from Covid-19. As a matter of fact, NYC is now including people who died at home from Covid-19 but a lot of US states and other countries are not, which would artificially lower the fatality rate, when it could actually be much higher.<br /> 4. To say that somehow the fatality rate of this disease is no worse than just a really bad seasonal flu is looney tunes and doesn't pass the eyeball test since many, many perfectly healthy people with no pre-existing medical conditions are dying as a result of this disease left and right, including young and middle aged people. That simply doesn't happen with seasonal flu. The self-reported symptoms of Covid-19 are also far worse than most self-reported symptoms of the common flu. Recovery time also appears to be longer, and many doctors are reporting lung and heart tissue damage.<br /> 5. There are about 18,000 people in Santa Clara County who have tested for Covid-19 and about 10% of those tested positive. Is it possible that the same people who tested negative could have already had Covid-19 and it was already defeated by their immune system and they now have antibodies and are testing negative? Could it be that these very same people who already tested negative for the virus are now volunteering to test for antibodies? In this case, there is a massive level of redundancy and the study is useless and can't be extrapolated to the general public. This study is far too small and not random enough to provide any usefull information whatsoever. We would need truly random testing of a much bigger group of people to provide any insight at all into what the actual fatality rate is. We would also need to include a much wider age range.

    2. On 2020-04-19 05:25:09, user Kaliahk wrote:

      Meanwhile in Alaska, 97% of all persons tested (those who are symptomatic or have had contact with a Covid patient) test negative. One would think if there are 80 times as many people who have it and don't know, that they would be catching a bunch of asymptomatic people in those tests.<br /> This study adjusts from a true rate of 1.5 % up to 2.8% or 4.2%? what adjustment do you make for finding your voluntary participants through Facebook ads? <br /> This study will not survive peer review, but it is not meant to. It is meant to be a talking point.

    3. On 2020-04-20 22:07:57, user Daniel Berg wrote:

      We have separate sources were an entire population or most of a population was tested. In the Princess Diamond cruise ship all were tested and we know how many fatalities. Likewise Iceland tested almost everyone and we know fatalities. All current assumptions regarding the mortality rates are inline with known examples.

    4. On 2020-04-23 03:02:45, user Michael A. Kohn, MD, MPP wrote:

      I looked deeply into this and it is correct. The authors apparently re-derived the correct formula, which I now know is called the Rogan-Gladen formula (Am J Epidemiol. 1978;107(1):71-6.) This formula is a weighted sum of 3 variances: the variance of the specificity estimate, of the sensitivity estimate, and of the proportion who tested positive in the sample. For specificity, they underestimated the standard deviation (which is the square root of the variance) by a factor of 3. For example, they used 0.13% instead of 0.39%. Overall, their confidence intervals are too narrow by a factor of 1.5 to 2. I wish they had reported their 50/3300 and then adjusted it based on sampling error from estimating specificity and sensitivity. The adjusted seroprevalence would have been 1.07% (CI 0.14% to 2.00%).

    5. On 2020-04-18 14:59:28, user Julie Larsen Wyss wrote:

      I was one of the 3300 that was tested. At this time I am told that those that tested positive for the antibody have not yet been informed. Any ideas why they have not informed the 50 or so positive participants yet even though they have released the study to the public?

    6. On 2020-04-18 22:41:11, user Dean Karlen wrote:

      Not sure what statistical abbreviation you are using when you say MSM. This is a first year statistics problem. 50 positives out of 3330, is consistent with the null-hypothesis (zero COVID antibody carriers in the sample) given that the measurement of false positives is limited to seeing 2 positives in a sample of 371 known negatives. This is not disputable, it is mathematics.

    1. On 2021-07-11 12:03:24, user Charles L. wrote:

      At least in Fig.1, colors are interchanged (blue, and not green, seems to be the susceptible group).<br /> Also, wouldn't be more realistic to model when 70-80% of population is fully vaccinated? As a 100% vaccination campaign will never be achieved and official govt. states that 70-80% vaccination is the goal in several countries.

    1. On 2021-12-04 01:07:35, user Balazs wrote:

      What were the Ct values for the positive results? <br /> Are you sure you have not investigated how many people with questionable PCR <br /> positive results ended up with another questionable PCR positive result?<br /> I thought even the WHO early Jan 2021 declared that a "case" have to <br /> have clinical signs, and PCR reports should include Ct values...

    1. On 2021-12-10 17:42:35, user BatchBeginner wrote:

      Only got uploaded less than a month ago. Not sure what you mean by "so controversial no one wants to risk their career and license", it doesn't seem very controversial at all to me, adds to previous studies with similar findings.

    1. On 2022-04-20 20:37:11, user Mark Czeisler wrote:

      Note from the authors:

      This paper was published in Sleep Health on 20 April 2022 following peer review. Below is a link to the article.

      DOI: https://dx.doi.org/10.1016/...

      Mark É Czeisler, Emily R Capodilupo, Matthew D Weaver, Charles A Czeisler, Mark E Howard, Shantha MW Rajaratnam. “Prior sleep-wake behaviors are associated with mental health outcomes during the COVID-19 pandemic among adult users of a wearable device in the United States.” Sleep Health. 2022. DOI: 10.1016/j.sleh.2022.03.001

    1. On 2020-06-05 12:01:10, user Alimohamad Asghari wrote:

      This article is published in this journal address:<br /> http://mjiri.iums.ac.ir<br /> Cite this article as: Bagheri SH, Asghari A, Farhadi M, Shamshiri AR, Kabir A, Kamrava SK, Jalessi M, Mohebbi A, Alizadeh R, Honarmand AA, Ghalehbaghi B, Salimi A, Dehghani Firouzabadi F. Coincidence of COVID-19 epidemic and olfactory dysfunction outbreak in Iran. Med J Islam Repub Iran. 2020 (15 Jun);34:62. https://doi.org/10.34171/mj...

    1. On 2020-04-29 21:17:20, user Rick56 wrote:

      The authors are addressing an important question. But I believe they have underestimated the length of time between exposure and testing positive.

      This matters because if you look at the raw data currently available for Wisconsin at the Johns Hospkins github, you see what appears to be a flattening of the number of new cases starting April 6 -- followed by a substantial spike starting April 22.

      Given this, it is especially important how one models the time between exposure (election; April 7) and testing positive. Because if that time could be 15-19 days, then there is a very plausible spike resulting from election exposures.

      The time from exposure to positive test = <br /> exposure to symptoms (incubation period) plus <br /> symptoms to testing (let's call it "testing delay").

      But the testing delay is also influenced by how readily testing is available.

      So, two problems:

      1. The incubation period they report using is a gamma (chi square is a type of gamma) for the incubation period, with a mean 5.2 and SD 2.3 days. The reference is Li et al, 2020. "Early transmission...". NEJM.

      But the Li paper notes that the 95%ile for this distribution is 12.5 days.

      When I use R to generate gamma distributions with a mean of 5.2 and 95%ile at 12.5, the SD is substantially greater than 2.3. Also -- that gamma gives about 18% of the incubation periods <2 days.

      Based on this, it seems likely that the author's distribution has a much thinner right tail than is consistent with the Li data. And perhaps 18% of their distribution could be < 2 days. So we need the specifics of the distribution the authors created.

      1. They used the testing delay from Beijing (Leung et al 2020. "First wave ...". Lancet. Which they model as gamma with mean 4.3 (SD 3.2) days from symptoms to testing.

      So, was the testing delay in Wisconsin as short as that in Beijing? Did the average person in Wisconsin get tested 4.3 days after symptoms start? Seems unlikely. Since the US has had such a terrible problem getting people tested, we need evidence that their testing delay is reasonable for Wisconsin.

      Unless the authors can address these points, I think it very inadvisable to claim that the spike in positive cases starting April 22 is completely unrelated to the April 7 election.

      [you'll have to look up the Wisconsin data on your own. I attempted to attach a plot multiple times without success].

      ~~~~~ here are the methods details from the authors' supplementary

      "We assume the incubation period distribution is gamma with mean and SD of 5.2 and 2.3 days [3]. We assume that the distribution of the time between symptom onset and confirmation is gamma with mean and standard deviation (SD) of 4.3 and 3.2 days, based on 186 cases reported in Jan-Feb 2020 in Beijing [4]."

      from their References<br /> 3. Li Q, Guan X, Wu P et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020;382:1199-1207.<br /> 4. Leung K, Wu JT, Leung GM. First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment. Lancet 2020;395:published online April 8.

    1. On 2021-08-17 16:35:52, user Paul52 wrote:

      This paper is circulating among anti-vax groups and is being passed off as a "poll" as opposed to a survey. <br /> That's the danger, and there's no way that you can "make sure" that it's not circulated in the wrong places.

      It shoud be withdrawn, with an explanation why, a critique of the people misusing it, and an abject apology.

    1. On 2020-05-01 21:51:10, user John Schuna wrote:

      Perhaps I am missing something, but the manuscript’s variance estimation method for test sensitivity and specificity remains unclear. It appears that sensitivity and specificity estimates were calculated from the summed raw counts across the described studies (Page 19) upon which exact 95% confidence intervals were constructed.

      As sensitivity and specificity data were drawn from multiple studies, it would seem prudent to use something like a generalized linear mixed-effects model (with study as a random effect) for variance estimation and subsequent generation of confidence intervals around your sensitivity/specificity point estimates. This would seem more straightforward for specificity analyses; however, this could be problematic for sensitivity analyses due to the small number of studies.

    2. On 2020-05-10 01:52:00, user Jerry L Kreps wrote:

      "More people" may be an artifact of the desire by some medical facilities, prompted by local and national politicians, to inflate the number of actual COVID deaths by declaring all deaths of questionable causes as COVID. My sister's relative, on her husband's side, died of a massive heart attack. On his death certificate the cause was listed as "COVID-19" (SARS-Cov-2). There are LOTS of cases of this happening. NY Gov Cuomo declared 3,800 as COVID victims.

      https://www.bloomberg.com/n...

      This is shown by the US "Daily Deaths" daily bar graph on

      https://www.worldometers.in...<br /> which oscillates wildly up and down, as if someone is putzing with the data. Similar graphs of other countries does not show this wild fluctuation. With supposedly six times as many cases as any other country the curve plotting the new death rate in the US should be much smoother. Only countries with 1/10th or less our new death rates are showing wild outliers, which is normal for small sample sizes.

    3. On 2020-05-02 05:20:23, user Shawn Flannigan wrote:

      If I understand correctly, the implication is that if the lower bound of their prevalence CI is lower than 1-specificity, the CI needs to include 0?

    1. On 2020-05-24 17:09:55, user Gary Kast wrote:

      Assuming that 1/3 of covid patients were taking the ace-I or arbs unless that is the percentage of the entire elderly pop taking them,( or at least the percentage of bp patients ) I would think that fact indicates a too high association of the meds and covid....I think general numbers should be discussed to support the conclusion. I see the math but question the assumptions and therefore conclusions without that additional number. If high bp is a comorbidity and patients takingbeta blockers and calcium channel and diuretics (b c d) are likewise or even higher numbers represented then clearly the type of bp meds is not too concerning. But if angiotensin drugs are only 20% of total bp meds consumed but 1/3 of patients in hospitals ...uh oh . Clearly not everyone who carries the virus ends up a patient .

    1. On 2020-04-22 22:51:38, user TREY RIVER wrote:

      From the study

      "However, hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease…Thus, as expected, increased mortality was observed in patients treated with hydroxychloroquine both with and without azithromycin.”

      Clarification of study in interview.

      and on MSNBC amazed<br /> “That’s just an observational study. It’s not a clinical study. It was done on a small number of veterans; sadly, those of whom were in the last stages of life, and the drug was given to them.”

      The drug “has been working on middle-age and younger veterans,” Wilkie added. By that, he meant that it was “stopping the progression of” COVID-19.

      http://www.msnbc.com/stepha...

      8:20min the answer quoted

    2. On 2020-04-21 21:46:26, user Doctor Hawaii wrote:

      You might want to refresh your understanding of statistics. Look at the P values and the CIs in the analysis. So, not significant is correct.

    1. On 2020-04-20 00:46:27, user deutsch wrote:

      A conclusion with only two days oh HCQ and such a smal sample is dishonest!<br /> The probability of missing real differences between the treatments is very high with such a small sample. For example with real death rate 2% vs 4% the probability of false conclusion is 90%....

    1. On 2020-05-12 19:13:29, user ohbaby wrote:

      This is old news. Plus this study doesn't do nearly enough to make the connection. Much more revealing is the vast majority of people entering the hospital are vitamin D deficient. It is even more prevalent for those with ARDS. Plus it was shown in studies, vitamin D has 3 specific mechanisms in combating this virus by reducing and modulating the cytokine storm,.. and upregulating peptides that disable the virion directly so it can't infect cells.

      Comparing countries vitamin D status to COVID-19 deaths is woefully insufficient. Especially when vitamin D deficiency is a worldwide pandemic. I wrote two articles with the scientific evidence here...

      https://www.dailykos.com/st...

      https://www.dailykos.com/st...

    1. On 2020-04-24 05:31:54, user Rajendra Kings Rayudoo wrote:

      To <br /> Yang Yu, Yu-Ren Liu, Fan-Ming Luo, Wei-Wei Tu, De-Chuan Zhan, Guo Yu, Zhi-Hua Zhou

      I read the paper want to know how this accurately measures the presymptomatic and asymptomatic people in populated countries like India <br /> And can you please tell how this actually works and give results to calculate<br /> And I also want to know how much percentage there will be the sucess ratio.

      By my opinion the 1st case to the recent one the areas which are located the surrounding people should be Quarantine and time and tested and also tells the people who they contacted in the period of time

    1. On 2021-12-30 20:48:47, user rick wrote:

      Donating vaccines is a completely uninformed idea. There are plenty of vaccines. Latin America is more vaccinated than the U.S. Nigeria, on the other hand, is plowing expired vaccines into landfill, because nobody wants the stuff. Pfizer says they can make a lot more vaccine right away; they just need orders. If you want to make sure no poor nation is deprived you send money, not vaccines. If you are afraid that they will go hungry, you sent money for that too. You don 't mail them french fries.

    1. On 2021-02-01 15:11:35, user Alessandro Soria wrote:

      Very interesting paper. To my knowledge, there are at least three other papers which look at the same topic (the effect of healthcare strain on COVID-19 mortality) from other perspectives: <br /> 1. doi.org/10.1371/journal.pon.... This is our recently published work, in which we tried to assess the impact of patient load on in-hospital mortality from COVID-19 based on hospital stress variables, such as the number of daily admissions, the number of total daily census, and the period before the peak, and we did find an independent harmful impact on mortality.<br /> 2. doi:10.1001/jamainternmed.2020.8193. In this analysis on the variation of COVID-19 mortality over 6 months in the US, the authors found that increased mortality reflects increasing numbers of cases in the community, possibly reflecting hospital burden.<br /> 3. doi:10.1001/jamanetworkopen.2020.34266. In this report on ICU in the US, there is a clear association between exceeding bed occupancy and increased mortality.

    1. On 2020-04-16 23:50:15, user Brian T wrote:

      MISLEADING UV DOSE! DO NOT FOLLOW THIS 5 uW/cm2 dosing!

      The UVA/B meter used in this study “General UVAB 137 digital light meter (General Tools and Instruments New York, NY)” (look up General Tools UV513AB Digital UVA/UVB Meter on Amazon) advertises measurement from 280-400nm, barely overlapping the wavelengths used in this study, 260 – 285 nm. Furthermore, this meter does not report on the energy at a given wavelength. Its possible that this study is grossly underreporting the dose of UV needed because their meter doesn’t read many of the wavelegths used.

      Previous research on SARS and MERS used 254 nm and noted much, much higher energy needed to kill these corona viruses vs this study's reported 5 uW/cm2):

      • MERS is inactivated at 90 uW/cm2 x 60 mins[1], dose of 0.324 J/cm2<br /> • SARS is inactivated at 4016 uW/cm2 x 6 min[2] , dose of 1.446 J/cm2

      [1] http://www.diniesturkiye.co...

      [2] https://www.sciencedirect.c...

    2. On 2020-04-16 13:24:14, user Rachel Tipton wrote:

      2 hours of wear! People ate having to wear these for 10 and 12 hours at a time, "decontaminate", and wear for another 10-12 hour shift. This is a serious limitation in the study! You're putting people at risk by releasing this information because hospital administrators will then jump on this and preach it like doctrine while the providers have to wear the same mask for shift after shift. Please go back and redo this study with a longer wear time in between decontamination. Then this will truthfully be applicable to the work force.

    3. On 2020-04-16 21:42:14, user Gracie wrote:

      Critical language from the full report "Quantitative fit tests showed that the filtration performance of the N95 respirator was not markedly<br /> 30 reduced after a single decontamination for any of the four decontamination methods <br /> Subsequent rounds of decontamination caused sharp drops in filtration performance of the ethanol-treated masks, and to a slightly lesser degree, the heat-treated masks. The VHP- and treated masks retained comparable filtration performance to the control group after two rounds of decontamination, and maintained acceptable performance after three rounds." Ethanol is not an acceptable treatment method.

    1. On 2022-05-24 20:25:23, user Carol Taccetta, MD, FCAP wrote:

      If a subject was still on immunotherapy at time of "recovery," the outcome of the adverse event cannot be considered as "resolved." It will also be important to follow these subject for relapse after therapy discontinuation, as immune-mediated conditions can sometimes relapse months, even years, after immunotherapy discontinuation.

    1. On 2021-10-27 18:02:33, user Sir Henry wrote:

      The definitions of severe COVID-19 and severe adverse events both come from the FDA. The agency has communications experts to standardize such terms. Calling these both "severe outcomes" should be uncontroversial.

      The FDA's definitions for severe COVID-19 (Appendix A) and severe adverse events (TOXICITY GRADING SCALE TABLES) match up:<br /> Grade 1, Mild adverse event, Mild COVID-19<br /> Grade 2, Moderate adverse event, Moderate COVID-19<br /> Grade 3, Severe adverse event, Severe COVID-19<br /> Grade 4, Potentially life-threatening adverse event, Critical COVID-19

      Table S6 of the pre-print cites this FDA definition of severe COVID-19, which specifically excludes the "critical" category ("No criteria for Critical Severity").

    1. On 2021-09-12 01:10:26, user Tracy Beth Høeg, MD, PhD wrote:

      Because we are seeing almost all of these post-vax events over the course of 1 week, you would need to divide by 52 so 140/52 = 2.7/million expected background rate.

    2. On 2021-09-11 15:07:41, user Meiyoubaizuo wrote:

      The FACTS completely destroy your statement.<br /> First, there have been 650,000 post-vax injuries and more than 13,000 post-vax officially reported on the VAERS database, which catches not even 10% of the total number! <br /> These experimental, potentially lethal drugs are annihilating the CD8+ cells of the jabbed, so they've become breeding machines for HPV, Epstein-Barr, cytomegalovirus and others, and the rates of ovarian, endometrial, and other cancers among the vaxxed are skyrocketing, with some doctors reporting a 20-fold increase.<br /> Second: the most highly vaxxed states and nations have the highest rates of severe illness. It’s the VAXXED who are flooding the ERs with ADE, which was predicted by numerous virologists. <br /> https://www.bitchute.com/vi...

      https://www.msn.com/en-us/m...

      https://freewestmedia.com/2...

      https://www.brighteon.com/7...

      https://www.zerohedge.com/c...

      ?https://report24.news/gibra...

      Third, as Biden said: ”We are going to protect vaccinated workers from unvaccinated co-workers," thus proving that the “vaccines” are absolutely USELESS! These baseless, senseless claims are further PROOF that the prions in the jab's spike proteins are completely destroying the brains of the jabbed!

    1. On 2020-03-23 18:07:21, user Sinai Immunol Review Project wrote:

      Summary:<br /> In an attempt to use standard laboratory testing for the discrimination between “Novel Coronavirus Infected Pneumonia” (NCIP) and a usual community acquired pneumonia (CAP), the authors compared laboratory testing results of 84 NCIP patients with those of a historical group of 316 CAP patients from 2018 naturally COVID-19 negative. The authors describe significantly lower white blood- as well as red blood- and platelet counts in NCIP patients. When analyzing differential blood counts, lower absolute counts were measured in all subsets of NCIP patients. With regard to clinical chemistry parameters, they found increased AST and bilirubin in NCIP patients as compared to CAP patients.

      Critical analysis:<br /> The authors claim to describe a simple method to rapidly assess a pre-test probability for NCIP. However, the study has substantial weakpoints. The deviation in clinical laboratory values in NCIP patients described here can usually be observed in severely ill patients. The authors do not comment on how severely ill the patients tested here were in comparison to the historical control. Thus, the conclusion that the tests discriminate between CAP and NCIP lacks justification.

      Importance and implications of the findings in the context of the current epidemics:<br /> The article strives to compare initial laboratory testing results in patients with COVID-19 pneumonia as compared to patients with a usual community acquired pneumonia. The implications of this study for the current clinical situation seem restricted due to a lack in clinical information and the use of a control group that might not be appropriate.

    1. On 2021-12-12 23:59:14, user tobydelamo wrote:

      78% of cases were in males. As a trangender man, I own and recognize my responsibility to correct historical health inequities that favored men. I'm proud to be vaxxed and boosted, and I urge all men to do the same. Myocarditis is extremely rare. Folks, let's not use these few cases as an excuse to not get vaxxed and keep current with boosters.

    1. On 2020-11-28 11:23:15, user Karl Pettersson wrote:

      How are the final sizes of the epidemics calculated in this framework? Are they estimated by simulation? It seems that for the cases with full immunity after infection, you can use eq S31 in https://doi.org/10.1101/202... with ?=0 in ? (p. 5) for varying susceptibility and ?=1 for varying connectivity, but they need to be adjusted for the cases with partial immunity.

    1. On 2020-03-26 07:52:06, user M.E.Valentijn wrote:

      Has anyone been able to verify their source claiming 33% prevalence of Type O in the general population? I can't find the journal that's cited for that, and a newer article says 30.2% for Han Chinese, not the nearly 34% claimed here. Though that's Han Chinese in general, not just in Wuhan. Can't find their other sources for normal blood types in the area either.

    2. On 2020-03-22 00:08:15, user Bret Johns wrote:

      It will be read by media/journalists but not necessarily understood. The phrase "not been peer reviewed" will not have any importance to them either. In the medical field "significant" means, "probably caused by something other than mere chance."

    1. On 2020-04-28 16:26:32, user Philip Machanick wrote:

      The description of what happened in Korea is grossly inaccurate. The Korean strategy included aggressive and comprehensive contact tracing and quarantining contacts.

      NYC illustrates where relying on herd immunity takes you. The Bronx has about 0.22% of POPULATION dead, i.e., mortality rate, not case fatality rate. Extrapolate that to all of the US and you have over 700,00 fatalities.

      This study is flawed because it does not take into account NPIs that have varied a lot - e.g., though Germany started late, they ramped up testing fast and adopted the S Korean strategy. Italy instead at the start focused on testing the most ill and hence miss mild and asymptomatic cases, resulting in a much higher case fatality rate.

    1. On 2021-09-08 03:23:50, user Tim Hinchliff wrote:

      This is such a great natural experiment to test lockdown efficacy. One wonders why it hasn't been published yet?

    1. On 2020-04-18 20:15:11, user Marya Lieberman wrote:

      table 1 lists one entry for NPV as 32/25 and gives a value of 91%. Looks like a transcription or math error.

    1. On 2020-06-03 14:31:19, user Nick Bauer wrote:

      Your paper specifically picks out "A-positive" individuals. I may be missing something, but I don't see any discussion of Rh factor in the text or presence in the statistics?

    1. On 2022-08-13 14:11:20, user Vijay Iyer PhD wrote:

      Thank you to all the authors for this contribution towards understanding Long Covid.

      A first-pass set of comments on the manuscript:<br /> * Fig 3 has 10 subpanels (A-J) but the caption references 11 subpanels (A-K)<br /> * Acronym CVC in Fig 4 does not appear to be defined <br /> * The phrase "double positive CD4+ and CD8+" T-cells may cause confusion in the field. Manuscript appears to be referencing their IL-4/IL-6 positivity. Some ME/CFS researchers (Selin & Gil) have meanwhile found hybrid CD4+CD8+ T-cells, which they also refer to as "double positive".<br /> * No commentary is given wrt why Galectin is chosen for the suggested "minimal set" of biomarkers over the various CCL & LCN markers with higher spearman rho wrt LCPS<br /> * Some commentary may be warranted of any lower significance distinction between the HC & CC cohorts with your models. There appears to be weak separability based on cortisol in Fig 6F. This may be a small hint towards the possibility of subclinical LC.

    1. On 2020-05-28 16:49:42, user Ruth Cleary wrote:

      Wondering whether Metformin Instant Release and Extended release readings were different from each other and, if so, by how much.

    1. On 2020-08-07 20:38:52, user Adam Garland wrote:

      We are developing a test for SARS-CoV-2 in saliva. Is there any chance you have saliva samples leftover from this study that you'd be willing/able to share with us?

    2. On 2020-05-05 22:31:22, user John Waldeisen wrote:

      Nice work Anne & team!!

      Do you know which swab the BD Universal Viral Transport system used in the trial? (i.e. cotton, polyester, or nylon flocked swabs?) From my past work, the flocked swabs are much better than cotton swabs and woven swabs at releasing pathogens off the swab. The better sensitivity from saliva might have been due to using a woven fiber or cotton swab, which retain more material (>80%), instead of a flocked swab.

      Also, it's been shown that asymptomatic infections are largely upper respiratory infections whereas severe infections (hospitalized) have moved to the lower respiratory tract. Hence, saliva may be more sensitive in more severe patients, yet nasopharyngeal swabs may be more appropriate for asymptomatic testing (i.e. drive-through clinics). It seems Fig. 3a may support this conclusion.

    3. On 2020-06-07 11:11:53, user peter kilmarx wrote:

      Great work! Why not use both in a pool of two specimens? You missed 8 positives with NP only and 3 positives with saliva only.

    1. On 2024-12-05 16:47:19, user Anna Carolina Viduani wrote:

      This is an excellent and highly relevant paper for Brazilian researchers and practitioners—congratulations on such an impactful contribution!

      I have just one very minor observation: while there is indeed a Dourados in Minas Gerais (MG), I believe the city referenced on page 10, particularly in relation to the suicide rate in Indigenous communities, is actually Dourados in Mato Grosso do Sul (MS).

    1. On 2020-04-04 01:47:57, user Criticalheritage wrote:

      From Tokyo Japan. Do you think low number of death rate in Japan is related to the BCG ? If so it is a good news to save the world. BCG production should be started immediately and given to the babies and possible patients in North America and Europe.

    1. On 2021-12-01 09:55:15, user Sven Franke wrote:

      Interesting study. Even as a pro vaccine person I can't begin to name all of the assumptions made here that are probably highly faulty. It would take to long. I will leave it up to other researchers with different financial backers. Btw. if the results were right, they should let the german RKI know. RkI revised their statement about the role of vacinated ppl in the epidemic about 4 weeks ago, stating that they do contribute after all. Also the trend is showing more and more infections among the vaxed. Ignoring this does no one justice, if we are to fight the pandemic together. Also where do the authors get the notion of this "socializing of vaxxed ppl mainly with ppl of their own vax status". In what science is this assumption grounded? It sounds very far fetched and frankly quite bigoted.

    1. On 2024-01-17 12:03:28, user Leonardo Martins wrote:

      This ancestral-reconstruction based phylogeographic approach has been used before by us in SARS-CoV-2 analyses: <br /> 1. for finding the number of transmission events into or outside Lebanon https://www.ncbi.nlm.nih.go... <br /> 2. For estimating migration patterns between regions of England https://www.nature.com/arti...<br /> 3. To count the number of exports and importations into Pakistan https://www.ncbi.nlm.nih.go...

      In our case we used the mugration model as implemented in TreeTime or ASR models implemented in Castor for R (https://cran.r-project.org/... "https://cran.r-project.org/web/packages/castor/index.html)")

    1. On 2020-06-07 22:27:50, user TNT wrote:

      Why did the doctors only administer 1000 IU/d? More serum vitamin D would have had greater immunoregulatory effect. Optimal immune regulation Is achieved at 100 nmol/L and many studies have demonstrated 4,000 IU/d is safe. Agree with the need of identifying patients’ serum content before the trial began

    1. On 2021-09-02 19:27:20, user Oy Vey Esme wrote:

      Have you also openly spoken out against the false positives being reported as true positives by the CDC and others? Because other research has shown, without a doubt, that the way the tests were conducted generated between 90% and 94% false positives in some cases. If extrapolated, that means that the covid pandemic was about on par for a bad flu year. Yes, I said it because that's what the numbers say.

    2. On 2021-08-28 08:55:21, user Martijn Weterings wrote:

      In table 1a we see that the comorbidity factors correlate strongly with the main factor (vaccinated/natural). For instance the vaccinated group has two and a half times more immunocompromised people (420 Vs 164).

      This means that there is high degree of multicollinearity which makes the coefficients of the fitted models meaningless. We see for example in table 2a several negative coeffients for factors like diabetes, COPD and immunosuppression. These coeffients have a large estimated error and are not 'significant' but they *do* influence the other coefficients in the entire model.

      Errors that follow from this might also be increased due to the logistic function which 'pushes' coefficients to extreme values when the frequency in certain classes is close to 1 or 0.

      https://stats.stackexchange...

      https://stats.stackexchange...


      Asside from the correlated variables and the influence of this on model coefficients... The correlation is also an indication that the matched groups are still very different from each other, despite the matching. This means that the experiment is prone to selection bias.


      Despite these two facts these results are still very interesting. It would be nice if they could be presented in a more raw form such that the pattern may be better seen (e.g. do the cases all occur in the high risk group with comorbidities?), and not just the output of fitted coefficients from models.

    3. On 2021-08-26 19:01:49, user zlmark wrote:

      Do your results change significantly, if you analyze different age groups separately?<br /> In other words, what happens if instead of using the age as a covariate, you limit your analysis to a particular age group?

    4. On 2021-08-31 13:17:14, user Lardo wrote:

      Even if we assume that the results are accurate and natural immunity provides stronger protection than vaccines, in order to gain natural immunity one has to survive the COVID-19 infection, correct? If so, the question is: is the risk of complications from COVID-19 greater than the risk that comes with getting the vaccine? Since the study doesn't address it, I personally see no point in it whatsoever. I don't care if natural immunity is stronger, since I'd rather not get COVID-19 to begin with.

    1. On 2020-05-12 04:19:04, user BentBollards wrote:

      All info is peer reviewed and published numerous times since 1991.

      "Nonpharmaceutical Intervention (NPI) published discovery to cure the refractory dry cough that spreads Coronavirus and influenza". The 325 year medical mystery of finding a cure for the dry refractory cough - solved by Dr. Miles Weinberger, M.D. 40+ year cough researcher.

      I asked your esteemed colleague, Dr. Weinberger, what if there is no vaccine in sight? He said, "First, we need to cure the dry cough." [that spreads the virus.] Dr. Weinberger, M.D., 40+ year Immunologist and cough researcher, regarding mitigation and containment of cough aerosol droplet spray that is paralyzing the world. All references are peer reviewed and published multiple times in the most esteemed medical journals of the world. (Note: It does not cure any underlying disease - just the dry cough that is spreading the virus.)

      www.NonpharmaceuticalInterv...

      http://bit.ly/CureByProxy << Peer reviewed paper that started it all.

      http://bit.ly/CoughCure2020 << Peer reviewed paper children AND adults.

      Dennis Buettner<br /> Cough Research Manager for<br /> Dr. Miles Weinberger, M.D.

    1. On 2021-08-21 14:43:23, user Paul-Olivier Dehaye wrote:

      This paper has now been published (and presumably peer-reviewed).

      New title: Adherence and Association of Digital Proximity Tracing App Notifications With Earlier Time to Quarantine: Results From the Zurich SARS-CoV-2 Cohort Study

      https://www.ssph-journal.or...

      It still includes in the introduction, despite showing the opposite:

      These findings provide evidence that DPT may reach exposed contacts faster than MCT, with earlier quarantine and potential interruption of SARS-CoV-2 transmission chains.

    1. On 2020-04-12 15:01:25, user Xavier de Roquemaurel wrote:

      Wouldn’t a multi factorial analysis put in perspective the question? Testing together these factors : confinement, social distancing, masks, bcg vaccinations (strain by strain), number of intensive care beds per 000, etc... It could avoid a frontal confrontation and at the same time open the discussion.

    1. On 2020-12-01 22:15:47, user Pedro Emmanuel Alvarenga Ameri wrote:

      Hello all, I just had a chance to read the preprint. The work is pretty cool. Im conducting an investigation to validate a few risk scores and Im interested to validate this one too at a Rio de Janeiro population. However, in order to do so, it would be necessary to have the model intercept in addition to the coefficients available at table 1. Additionally, it would be also necessary to have the predictors units not available in table 1, and the range of each predictor, to perform the same normalization informed at the methods section. Is it possible to inform these missing information? At last, the web calculator mentioned at the paper is an excellent way to show and use the results, however its web address is not informed in the manuscript. Where can I find this web calculator? Looking forward to see the final version of the manuscript. May the force be with you all.

    1. On 2020-05-25 05:44:26, user AmCurious Sometimes wrote:

      And what about people who have had stand-alone Rubella vaccine (1x) and stand-alone measles vaccine (2x), in addition to 1 of MMR vaccine(1x). Some reports suggest at least 2 doses of MMR vaccine. Not so easy to currently get MMR vaccine during this pandemic. Many doctors are closed or have limited hours, etc. (Plus who knows if the doctors aren't spreading COVID-19 to their patients.)

    1. On 2020-12-09 12:20:53, user Vladimir Gusiatnikov wrote:

      The authors appear to treat viral loads quantified in transfer media as viral concentrations in mucus, however there typically is a 1.5 to 2 order-of-magnitude dilution as material is eluted from swab into media. As a result, the authors' estimates for the copy generation rate and copies per infectious quantum may be 1.5 to 2 orders of magnitude too low.

    1. On 2021-07-27 10:59:07, user JustinReilly wrote:

      My comment submitted 7/27/2021:

      The following letter from Tess Lawrie et al. strongly rebuts this review by Roman et al. I highly recommend reading the letter as it is succinct and presents damning points:

      “With misreporting of source data, highly selective study inclusion, ‘cherry picking’ of data within included studies, and conclusions that do not follow from the evidence, this article amounts to disinformation... We respectfully request investigation, and retraction of the article as it stands.”

      I join the letter’s signatories in calling for swift retraction. Thank you for your consideration.

      https://covid19criticalcare...

    1. On 2022-11-26 06:41:30, user Soichiro Obara wrote:

      Dear Prof. Schindler,

      First I (Soichiro Obara, the PI of this project) apologize for being replying to your great comments.

      Second, our project has modelled the European APRICOT as you commented. We would sincerely appreciate your suggestions from the viewpoint of the author of the APRICOT.

      On this matter, before launching this project, we got in contact with the principal investigator of the APRICOT, Prof. Walid Habre, who has been giving many suggestions and comments to us.

      As you might have concerns regarding data acquisition, he also gave comments as to how tough the data acquisition and cleaning in the APRICOT.<br /> Hence, this time, we assume that we may need to change the case report form (actually modelling the CRF of the APRICOT) after a pilot study which hopefully will be conducted February or March in 2023.<br /> (I have heard from Prof. Habre that a pilot study was conducted in three centers to examine the feasibility of the protocol and the CRF in the APRICOT.)

      If possible, I would appreciate your "specific and direct" suggestions as to which data items in the APRICOT might be difficult or be unnecessary to collect.

      Again we would sincerely appreciate your great suggestions and comments, if you kindly gave, in the future again.

      I am very pleased if you kindly get touch with me on behalf of the Asian Society of Paediatric Anaesthesiologist research committee.

      Soichiro Obara (Japan)<br /> e-mail address: soichoba1975@gmail.com

    1. On 2020-04-20 17:25:50, user Wei Zhou wrote:

      Sorry. I cant find the supplemental figures and tables, even though I found the rest of the supplemental data in the pdf. If you have seen it, can you give me a pointer? Thanks!

    1. On 2021-10-04 18:45:17, user MUltan wrote:

      A maternal cognitive ability measure would have been a much better predictor of infant cognitive ability than educational level, which is a rather poor proxy for mental ability. Having such a measure for both parents would be even better. Virtually all those with educational levels above high school should have some standardized test scores that would give a fair indication of mental ability. With the clinical setting, it shouldn't be at all hard to get at least a Wonderlic or other brief cognitive ability measure for nearly all the mothers, which would be vastly better data.

      The maternal stress questionaire is also a very indirect measure -- asking about time spent interacting with infants and the character of those interactions would have been much more informative -- though these questions were not asked of the cohort prior to the pandemic, so the data would be hard to interpret, I suppose.

      The paper seems to be trying to find a social environmental cause and neglecting the possibility that the mental performance decline could be due to an environmental toxin. The CV spike protein is by far the most plausible candidate for such a toxin, nothing else is sufficiently new and widespread to have such an effect size. From summaries of research I gather that the spike protein can be: toxic to blood vessel linings, cause clotting disorders, strokes, and low blood oxygen; can cross the blood-brain barrier and the placenta; is expressed in breast milk; and can sometimes cause various pathological immune reactions, including neurological damage in some cases. The spike protein levels will have been by far highest among vaccinated mothers, so comparing the mental performance of a cohort of infants who were gestating or breastfeeding when their mothers received an mRNA CV vaccine to a contemporaneous cohort of infants whose mothers were not CV-vaccinated (and preferably uninfected as determined by antibody testing) should clearly resolve whether the CV spike protein itself is the culprit for lower infant mental performance, or rather other, primarily social factors.

    2. On 2021-12-13 22:59:33, user Just Because I can wrote:

      Greetings RI team from Utah! I must begin with nicesties; "Go BRUNO"! My son graduated this past May 2021 from Brown. I am a speech and language pathologist with over 30 years of hospital, private and public school setting experiences. Over the past nine years, I have professionally focused on children ages 3-5 within the public preschool and private therapeutic settings. I service students and their parents with the most intensive and restrictive learning environments within our District due to cognitive, behavioral and communicative delays. I can't help but weigh in now, as I previously shared this article with my peers in August as I braced for the impact of the 2021 school year.

      Given your single assessment tool (I professionally do not profess strong decisions based on a single evaluative instrument, even as widely accepted at the Mullen), I've found your results to be intriguing and frankly, just as we anticipated.

      To compare to RI, our school district, closed schools for Remote Learning for only 3 mos. in the Spring of 2019 and returned to in person instruction with hybrid options in 2020. Of a caseload of 65 students, I had 3 that were online/virtual. In 2021, our District returned to essentially all in student learning.

      My informal observations this school year in Utah has been as follows:

      1. Increase in new referrals and eligible "older" 4+ year old children scoring remarkably delayed communication (Standard scores <50 given a typical range of 85-115) and no previous history of EI or preschool interventions. Our TIER 3, most restrictive preschool program has a marked influx of new referrals (e.g., total students in May was 24 and currently rises at 36 with 8 new referrals in Jan.)
      2. Many declined or rarely attended virtual Early Intervention supports, skipped medical wellness visits including dentistry during the pandemic.
      3. Increase in parent report of primary concerns with behavioral components.
      4. Given the current timeframe, we are NOT seeing marked progress with an influx in discharges (no longer eligible due to more typical standard scores). We are seeing progress and we have continued to see progress through the pandemic (which at times surprised me) but the levels of improvement are not as remarkable or typical as years past.
      5. Typical communication, fine/gross motor and even cognitive delays are still present but the comorbidity of exceptional delays in social/pragmatic and ultimately, behavioral skills combined make measured learning and ultimately IEP progress at a slower rate. Social/pragmatic delays are interfering with overall progress.
      6. Parent involvement, participation, enthusiasm and grit appear markedly depressed. Educational teams walk a fine line between empathy, compassion and expecting parents and care givers to step in and "do hard things" in difficult times. The teams are using external motivators such as pizza cards to motivate parents to attempt, complete and turn in 2x monthly parent based home practice pages.
      7. Increased rate of meeting attendance with Virtual options.

      Where do we go from here? I agree, measuring student outcomes is critical but supporting the parents (in any evidence based manner) is to me, a critical and crucial element. I thought the kids, once exposed to typical learning/situations and with repetition, our inflated numbers would flatten in a year and they would bounce back into typical ranges but it's the apathetic, tired, depressed parents that are lacking resilience and grit currently. I do think another component that would be most valuable and continues to need funding is Preschool for All (or most).

      Thank you to any cohort, parent, professional person interested in this dialogue, for reading my insights.

    3. On 2021-08-17 16:24:32, user Sean Deoni wrote:

      What I think is interesting, though, as someone else has shared, when looking at the data, it is motor skills that are pulling down the overall cognitive averages. Assessing motor skills relies more on demonstrating and mimicking, the on direct verbal instruction or watching facial expressions. So, I would have thought if it was all masks, we'd see the opposite - motor skills less affected than language. Doesn't mean that masks aren't important, but perhaps not the full explanation?

    1. On 2022-01-07 12:28:26, user Alex Frost wrote:

      So...robust evidence of strong protection via prior infection (lower for Omicron but still c. 60%).<br /> Separately, clear evidence of protection against symptomatic infection against Omicron for 3 doses of vaccine (2 shots + booster). <br /> Has anyone studied the effect of hybrid immunity = prior infection + 3 doses/3 doses + breakthrough infection? Surely that is endgame for global populations against Covid19.

    1. On 2021-07-05 05:35:47, user The Scrutinizer wrote:

      Sumedh Bhagwat you are really worried about the difference of 0.5% error? That is not the most imp thing to worry about right now. If you don't know this vaccine might be the best so far in comparison to all the genetic vax

    1. On 2020-05-22 13:15:29, user fc wrote:

      Summation: paper shows model with extreme sensitivity to initial conditions built into mathematical form displays significant changes in long term predictions (now with confidence intervals (TM)!) after changes to said initial conditions.

      While earlier intervention would probably have been better in reality, the conflation of the media of 95% confidence intervals on model prediction with 95% confidence intervals on truth is nuts, and its complete disregard of the sensitivity of the predictions to model assumptions is depressing (feedback effects, anyone? Buehler ? Cochrane ...?)

      This model is being seen to provide accurate answers to a question which it is least able to model with high precision.

    1. On 2022-12-19 02:33:05, user Charles Warden wrote:

      Hi,

      Thank you very much for posting this preprint. I think this is an interesting topic to learn more about.

      I was surprised at what seemed to me like a relatively small amount of difference for the EA-PGS versus the rare alterations (such as in Figure 2), but I am not sure if that is because of certain associations that I might have with “rare” and “monogenic”. I apologize if some of these questions are naïve and certain assumptions may be more or less relevant in certain situations.

      For example, I wonder if the phenotypic “deviators” might relate to part what I am trying to describe, and I think it would be good for me to take some time to better understand resources like Developmental Disorder gene panel from Gene2Phenotype.

      Nevertheless, as a starting point, I hope that you can help with at least some of the following questions:

      1) I could find Supplemental Figure S1. However, I see references to Supplemental Tables, when I can’t find additional uploaded “Supplemental” files.

      Am I overlooking something, or do the Supplemental Tables need to be added in a “v2” version?

      2) I thought Figure 1 was very helpful in gauging the relative influence on the different characteristics.

      However, the abstract mentions a “threshold for clinical disease”. I apologize that I don’t know the best full list of known genetic/genomic alterations that would provide a good reference, but I would be interested to know how the predictive power (which I assume is correlated with the beta values) might compare to something like trisomy 21 for Down Syndrome (although that affects many genes on chromosome 21).

      Reading this preprint helped me in terms of gaining familiarity with earlier publications, such as the AJHG Kingdom et al. 2022 publication. In that paper, I was interested in the set of 25 “known highly penetrant genes.” However, my understanding is that those were not used in a main figure because of sample size for sufficiently rare variants/alterations. For example, I recognized “Williams syndrome” and “Prader-Willi/Angelman” in Table S2 of the other publication, but I believe there were less than 20 UKB subjects for each of those diseases.

      I also apologize that I think that I am confusing the results a bit, since the other publication includes copy number alterations and Figure 1 in this preprint mostly describes “variants”. However, I hope that provides some sense of what I am asking about.

      For example, I don’t know if sample size is an issue, but I would be interested in seeing an additional category to compare the current results to something of comparable clinical utility can be defined (if possible, from individual variants in certain genes). I apologize if I am overlooking something.

      3) In this preprint, I also see “monoallelic (i.e., autosomal dominant)” in the methods. So, I think this already answers one of my question/questions, but I wanted to still say something to try and find the better way to describe what I would call “monogenic” diseases. It is possible that there might be some other explanation like needing additional characterization of individual variants (and I believe the earlier paper mentioned “very few” pathogenic variants were in ClinVar), but I would like to start with the possibility that perhaps there is a more precise way to communicate my thoughts.

      In other words, I would expect the clinical disease for monogenic diseases to be recessive in certain situations, and the questions that I had earlier related to whether there could be a noticeable number of developmental disorders that follow a recessive inheritance pattern (such as whether a homozygous variant counted as “2 variants”).

      Likewise, in terms of downstream effects, I thought Phenylketonuria/PKU affected some of the traits mentioned in this study (if dietary changes were not made in time). I don’t know if that was precisely considered a “developmental disorder,” but that is an example of what I think of when I see “rare” and “monogenic”.

      Please let me know if I have misunderstood anything, but my understanding is that this may go against the assumed dominant inheritance pattern for the genes. However, the question that I am trying to ask is how to categorize what I would call “monogenic” disease like PKU (as I understand it) and then compare that to the effects described for the associations in this preprint? I think one other way to describe this might be something like “positive predictive power” and yet another way might be something like “what are the proportion of individuals meeting the threshold for disease among carriers (if significantly higher than controls)”? However, I don’t know if there are issues with my use of terminology (and/or sample size, criteria to volunteer and consent, or something else).

      4) In terms of the clinical importance, I am not sure if there might be caveats/limitations to suggesting “PGS may provide some clinical utility by improving diagnostic interpretation of rare, likely pathogenic variants that cause monogenic disease”? For example, if a large enough number of individuals can be functional adults (or even adults with excellent health/success), then I might worry about the stigma of test results provide early in life (if predictive power was over-estimated). Based upon Figure 3, my understanding is that there is a reasonable chance that could happen with the EA-PGS? If that was true, then I hope that there is or can be a different term/classification to separate such a risk assessment from the genetic tests for diseases similar in severity to what I tried to list above (if I understand correctly).

      I hope that I can learn more, and I hope that these questions might also be helpful to some other readers.

      Thank you very much!

      Sincerely,

      Charles

    1. On 2020-09-09 19:12:11, user Michael Bishop wrote:

      I don't believe the authors' data, which would imply that SARSCOV2 was circulating with little increase or decrease in Dec 2019 - Feb 2020 until suddenly taking off in late Feb early March.

    1. On 2020-09-11 04:45:37, user Guest wrote:

      Very insightful! As described in method section, you included variable with p < 0.2 for your model C, but as I can see from table 3, the variable "Age at first marriage" has p value > 0.2 in model B yet this variable was included in model C. I'm curious to know what assumptions were made to retain this variable for the final model despite it clearly could not pass the p<0.2 criterion?

    1. On 2021-10-09 20:30:31, user j` wrote:

      Are you under the impression antibodies are the immune system's only means of protection?

      Have you reviewed previous studies showing robust immunity of mild infections?

    1. On 2021-09-19 11:26:29, user Day Evenson wrote:

      Is there any study that separates the unvaccinated into those who have had Covid and those who have not? I can't find any research on vaccinated vs previously infected. What is the lasting immunity between these groups?

    1. On 2020-09-14 20:13:03, user Guido España wrote:

      Thank you for your feedback. We agree that the assumption of face-mask <br /> protection is important. We decided to address this comment in the <br /> updated version of the manuscript by using values for face-mask <br /> protection for non-health care settings with an adjusted odds ratio of <br /> 0.3 (0.12-0.73) <br /> (https://www.thelancet.com/j... "https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)31142-9/fulltext)").<br /> We analyzed the impact of the lower and upper bounds of these estimates<br /> to account for uncertainty in face-mask efficacy. Changes in our <br /> assumption about protection afforded by face masks resulted in <br /> differences in the magnitude of cumulative infections and deaths. As <br /> expected, lower face-mask efficacy resulted in more infections and <br /> deaths. Although the numerical results changed depending on these <br /> assumption about face-mask protection, the relative impacts of varying <br /> levels of operating capacity and face-mask adherence were generally <br /> similar under these alternative assumptions. We are committed to a <br /> scientific approach to our analysis and have endeavored to inform our <br /> model with the best available evidence-based inputs with respect to face<br /> masks and in all other respects.

    1. On 2020-04-12 22:12:26, user Klaus K wrote:

      Thanks for an interesting paper! However I do agree with Clive Bates that it would be very helpful to have the multivariate analysis rerun to reflect current & former tobacco use as two separate variables, both for hospitalisation and for critical illness. <br /> If the hypothesis that nicotine modulates the ACE2-receptor is valid, this will be reflected as a higher OR in former tobacco users and a lower in current users.

    1. On 2020-04-08 23:59:15, user Christi Raunig wrote:

      Why is this model projecting a much less dramatic climb in daily deaths than has happened in other countries that are ahead of us such as Spain and Italy? I don't see any justification for believing that we will be so much better off. In fact, Italy's lock down has been much more restrictive than ours. Both Italy and Spain have had much longer lasting climbs in daily deaths than what is projected in this model for the US. I can't think of any reason we should expect to be able to blunt our peaks in the graphs compared to theirs. If you look at the graphs of the daily death count in both of those countries and were to project our country to have a similar experience, then we won't see a peak for another 10 days, and it will be closer to 5,000 deaths per day based upon our population.

    2. On 2020-04-08 15:59:31, user Vee_Kay wrote:

      Why have they dropped individual state numbers in the IHME projections? Instead they go to other countries that is of little interest to US....

    1. On 2021-07-14 20:26:08, user bruno ursino wrote:

      I came by this article now, so sorry for posting a comment at this time but it seems to me that no one pointed this out: the formula for the evaluation of Rt is completely wrong, indeed this can be shown just by applying this same technique to a simple SIR model.

      I think it's impossible to send here my plots, but I ask you to execute the following code using octave or matlab:<br /> `tf = 300;<br /> dt = 0.01;<br /> t = 0:dt:tf;

      mu = 1.7/100;

      T = 17;<br /> alfa = 1/T;

      R0 = 4;

      bN = R0*alfa;

      S = zeros(1,numel(t));<br /> I = zeros(1,numel(t));<br /> R = zeros(1,numel(t));<br /> d = zeros(1,numel(t));

      S(1) = 0.99999999;<br /> I(1) = 1 - S(1);

      for k = 2:1:numel(t)

      S(k) = S(k-1) + dt(- bNS(k-1)I(k-1));<br /> I(k) = I(k-1) + dt(bNS(k-1)I(k-1) - alfaI(k-1));<br /> R(k) = R(k-1) + dt(alfaI(k-1));<br /> d(k) = mu(R(k) - R(k-1));

      end

      T_steps = T/dt;

      Ri = zeros(1,numel(t));

      for k = (T_steps+1):1:(numel(t) - T_steps)

      aux = dt(sum(d((k):1:(k+T_steps))) - musum(d((k-T_steps):1:(k))));<br /> Ri(k) = d(k+T_steps)/aux;

      end

      R_t = zeros(1,numel(t));

      for k = (T_steps+1):1:(numel(t) - 2*T_steps)

      R_t(k) = dt*(sum(Ri(k:1:(k+T_steps))));

      end

      figure, plot(t((T_steps+1):1:(numel(t) - 3T_steps)), R_t((T_steps+1):1:(numel(t) - 3T_steps)))<br /> grid minor<br /> hold on<br /> plot(t((T_steps+1):1:(numel(t) - 3T_steps)), R0.(1-R((T_steps+1):1:(numel(t) - 3*T_steps))))`

      the blue line will be the Rt evaluated using your formula, while the red one will be the true Rt value. It's not only a matter of the exact values, but most importantly the issue is about the fact that your formula antedates the day in which Rt starts to decrease of a full month, thus it's not possible to use it to actually prove that the measures did or did not have an effect on the Rt value.

    1. On 2020-10-28 14:29:50, user Kamran Kadkhoda wrote:

      With a prevalence of 1.7%, sensitivity of even 95%, and specificity of 99% (which is very generous), one's PPV is no better than 62% meaning 38% of the results are false positive. But according to this publication, the PPV is around 25% given the specificity of 95%: https://pubmed.ncbi.nlm.nih...

    1. On 2020-05-07 22:07:31, user Dan T.A. Eisenberg wrote:

      Have you done any tests to see how stable the samples are for longer periods of time than in this paper? Also, can you clarify which Norgen RNA purification kits you used (Cell-Free or Total RNA kits)? Thank you. Trying to get this ramped up in my lab.

    1. On 2023-06-15 13:36:40, user Rachel Gibson wrote:

      This Scientific Correspondence has also been submitted to eLife.

      Comment on ‘The clinical pharmacology of tafenoquine in the radical cure of Plasmodium vivax malaria: an individual patient data meta-analysis’<br /> Authors: Raman Sharma1, Chao Chen2, Lionel Tan2, Katie Rolfe1, Ioana-Gabriela Fita2, <br /> Siôn Jones2, Anup Pingle3, Rachel Gibson1, Navin Goyal4*, Isabelle Borghini Fuhrer5, <br /> Stephan Duparc5, Hema Sharma2†, Panayota Bird2<br /> Affiliations: 1GSK, Stevenage, UK; 2GSK, Brentford, UK; 3GSK, Mumbai, India; 4GSK, Upper Providence, PA, USA; 5Medicines for Malaria Venture, Geneva, Switzerland<br /> *At the time of submission of this Letter, Navin Goyal is no longer an employee of GSK and is affiliated to Johnson and Johnson<br /> †At the time of submission of this Letter, Hema Sharma is no longer an employee of GSK and is affiliated to AstraZeneca

      Abstract<br /> A single 300 mg dose of tafenoquine, in combination with chloroquine, is currently approved in several countries for the radical cure (prevention of relapse) of Plasmodium vivax malaria in patients aged >=16 years. Watson et al.’s recent publication suggests, however, that the approved dose of tafenoquine is insufficient for radical cure and that a higher 450 mg dose should be recommended. In this response, the authors challenge Watson et al.’s assertion based on empirical evidence from dose-ranging and pivotal studies (published) as well as real-world evidence from post-approval studies (ongoing, therefore currently unpublished). The authors confidently assert that, collectively, these data confirm that the benefit–risk profile of a single 300 mg dose of tafenoquine, co-administered with chloroquine, for the radical cure of Plasmodium vivax malaria in patients who are not G6PD deficient, continues to be favourable.

      Introduction<br /> The Plasmodium vivax malarial parasite has a major economic and public health impact, especially in regions such as East Africa, Latin America and South and East Asia.1,2 When present in blood, P. vivax can cause acute malaria with episodes of chills, fever, muscle pains and vomiting. The parasite also has a dormant liver hypnozoite stage, which can reactivate after weeks, months or years, leading to relapses and, potentially, to severe anaemia, permanent brain damage and death.1,2 For effective treatment, eradication of both the blood and liver stages of P. vivax is required (radical cure).2<br /> Since 2018, regulators from the United States initially, and subsequently from Australia, Brazil, Colombia, Thailand, Peru and The Philippines, have approved tafenoquine (as a single oral dose of 300 mg in combination with standard doses of chloroquine) for the radical cure (prevention of relapse) of P. vivax malaria in patients aged >=16 years.1,3-5 A paediatric formulation that allows weight-band-based dosing of children (aged >=2 years) and adolescents is also approved in Australia (since 2022).5 Like primaquine, tafenoquine is an 8-aminoquinoline derivative effective against hypnozoites and all other stages of the P. vivax lifecycle; however, although the World Health Organization (WHO) recommends a 7- or 14-day treatment course for primaquine, tafenoquine is the first single-dose treatment for the radical cure of P. vivax malaria and therefore has patient adherence and convenience advantages.1,3,6 Nonetheless, as an 8 aminoquinoline, the safety profile of tafenoquine is similar to that of primaquine, and both agents can cause oxidant haemolysis in people with glucose-6-phosphate dehydrogenase (G6PD) deficiency.7,8 Acute haemolysis is usually short-lived and does not need specific treatment; however, in rare cases, severe haemolysis may lead to life-threatening anaemia (requiring red blood cell transfusions) or haemoglobinuric renal failure.9 In malaria-endemic regions it has been estimated that 8% of the population are G6PD deficient, although significant variation is reported across regions, with the highest country-specific prevalence estimated in Africa and Western Pacific countries.10,11 G6PD deficiency is an X-linked disorder; males are either G6PD deficient or have normal G6PD activity, whereas females exhibit a wide range of G6PD deficiency.2 Females may be symptomatic if they are homozygous, or if they are heterozygous and inactivation of their normal X chromosome (lyonisation) is skewed towards a deficient phenotype.2,12 Caution is needed because inter-individual variability in the pattern of lyonisation may cause heterozygous females with levels of enzyme activity between 30% and 70% of normal to test as normal for G6PD deficiency using qualitative, phenotypic, rapid diagnostic screening tests.13,14 To reduce the risk of haemolysis, the G6PD status of all potential tafenoquine patients must be determined with a quantitative test capable of accurately differentiating deficient, intermediate and normal G6PD activity levels, and tafenoquine should be withheld from patients with G6PD enzyme levels below 70% of normal.3<br /> Importantly, appropriate clinical practice for the use of 8-aminoquinolines in P. vivax malaria has always been precariously balanced between providing adequate activity against hypnozoites and the real risk of haemolytic harm to patients with G6PD deficiency.15 The cautious benefit–risk balance involved with the single 300 mg dose of tafenoquine has been questioned in a recently published paper in which Watson et al., hypothesise that the current recommended dose of tafenoquine 300 mg is insufficient and that a 450 mg dose of tafenoquine would reduce the risk of relapse.16 That dose is 50% greater than the 300 mg dose approved by the US Food and Drug Administration (FDA), Australian Therapeutic Goods Administration (TGA) and other international regulatory authorities.1,3-5 Herein, the authors discuss concerns regarding the conclusions of Watson et al.<br /> • The benefit–risk profile of tafenoquine 450 mg is not appropriately considered. For example, there is minimal discussion of tafenoquine safety data and key findings from a phase 1 study in healthy female volunteers heterozygous for the G6PD Mahidol variant. This important study demonstrated not only that the haemolytic potential of tafenoquine was dose dependent but also that a single 300 mg dose of tafenoquine had the same potential to cause haemolytic harm as the WHO-recommended dose of primaquine for uncomplicated P. vivax malaria (15 mg/day for 14 days).17,18<br /> • The authors acknowledge that data from the phase 2b, paediatric, pharmacokinetic (PK) bridging study TEACH19 were not available before submission of the Watson et al. manuscript. However, in the TEACH study, in which the tafenoquine dosage in paediatric patients was chosen to match blood exposure in adults receiving 300 mg, tafenoquine was efficacious and generally well tolerated: no patients withdrew from the study because of adverse events.19<br /> • The model used by Watson et al. to predict the recurrence-free rate at 4 months after a 450 mg dose is hypothetical and does not consider data regarding the tafenoquine exposure–response relationship. Importantly, tafenoquine exposure achieved with a single 300 mg dose approaches the plateau of the exposure–response curve; therefore, the incremental recurrence-free rate gained by the proposed 50% increase in dose is small and unlikely to be justified by overall benefit–risk considerations.3 In addition, as primaquine and tafenoquine have different PK and metabolic profiles, the authors consider the extrapolation of data from primaquine to tafenoquine to be problematic.2,9<br /> • The authors feel that, overall, some of the conclusions do not acknowledge evidence-based safety concerns for a >300 mg dose of tafenoquine and do not consider additional data from the INSPECTOR study that the recurrence rate of P. vivax infection within 6 months of tafenoquine treatment was not significantly affected by bodyweight.20<br /> Watson et al. mentioned the phase 2b dose-selection study (DETECTIVE) of tafenoquine,21 from which a single 300 mg dose was chosen for phase 3 evaluation in adults. However, the authors did not point out that, in this study, exposure was a significant predictor of efficacy and doubling the tafenoquine dose from 300 mg to 600 mg was associated with only a marginal increase (from 89.2% to 91.9%) in the primary efficacy endpoint, relapse-free efficacy at 6 months.21 Moreover, in addressing the INSPECTOR study of tafenoquine in Indonesian soldiers, the authors did not specify that this was a study of tafenoquine administered with an artemisinin-based combination therapy rather than chloroquine and, as such, is not directly comparable due to poorly understood but confirmed interactions impacting tafenoquine efficacy.20 Watson et al. also suggest that tafenoquine 300 mg is likely inferior to ‘optimal primaquine regimens’, but it is unclear whether such regimens are the WHO-recommended schedules of primaquine or regimens defined as optimal based on non-regulatory studies of primaquine. The authors provided no specific reference or dosage characterising optimised primaquine therapy, so this a priori inferiority cannot be evaluated.<br /> Methods<br /> The hypothetical causal model proposed by Watson et al. for the clinical pharmacology of tafenoquine for the radical treatment of P. vivax malaria is similarly problematic. Central to this model are methaemoglobin (MetHb) production and active metabolites. However, MetHb is not a validated biomarker of tafenoquine efficacy, and currently there is no evidence, from non-clinical or clinical studies, of circulating active metabolites of tafenoquine; if such metabolites were fleetingly present, they would require extraordinary potency to exert any significant pharmacodynamic effect.22<br /> Regarding radical curative efficacy, Watson et al. selected P. vivax recurrence within 4 months as their primary endpoint. However, the trial-defined primary endpoint at 6 months from the pivotal tafenoquine clinical trials8,21,23 was an FDA requirement and was mandated for analysis purposes. This was to maximise the probability of capturing relapses, including those from regions with longer latency periods. Watson et al. used the INSPECTOR study20 as one of two reasons to justify the selection of a 4-month endpoint. Relapse rates differ greatly from country to country, so the duration of the endpoint should not be based on rates observed in a single country. Moreover, the 6-month rate of loss to follow-up (only 9.1%) does not justify a change of treatment endpoint from 6 months to 4 months.<br /> In their efficacy models, Watson et al. explored the association between the odds of P. vivax recurrence and the following predictors: mg/kg dose of tafenoquine; AUC0–?; peak plasma tafenoquine concentration; terminal elimination half-life; and Day 7 MetHb level. However, details of how the best predictor was selected and how statistical significance was judged were not provided.<br /> Results<br /> Use of a 4-month versus 6-month follow-up period<br /> A key focus of the Watson et al. manuscript is that the authors describe a possible association between tafenoquine mg/kg dose and the odds of recurrence (using logistic regression), with a 4-month rather than the original 6-month follow-up. An odds ratio of 0.66 (95% confidence interval [CI]: 0.51, 0.85) is cited by Watson et al. in their analysis of the effect of tafenoquine mg/kg dose in patients who received tafenoquine 300 mg, but descriptive details for this result and the analysis are limited. Figure 2 in the Watson et al. manuscript shows Kaplan–Meier survival curves for time to first recurrence, based on tafenoquine mg/kg dosing category, but some areas require clarification, such as how the dosing bands were selected.<br /> Rationale for tafenoquine dose selection<br /> Importantly, the classification and regression tree analysis, in which a clinically relevant breakpoint tafenoquine AUC value of 56.4 ug·h/mL was identified, was not discussed.24 Population PK modelling revealed that tafenoquine 300 mg would provide systemic exposure greater than or equal to the AUC breakpoint in approximately 93% of individuals, who would have a high probability (85%; 95% CI: 80, 90) of remaining relapse-free at 6 months.24 Therefore, this ‘… model-based approach was critical in selecting an appropriate phase 3 dose’ for tafenoquine.24 Although data from the TEACH paediatric study19 were not available when Watson et al. conducted their analysis, had the data been available, they would have validated the AUC approach to tafenoquine dose selection, with an overall efficacy of approximately 95%.19 Individuals (aged 2–15 years) were given tafenoquine, based on bodyweight, to achieve the same median AUC as the 300 mg dose in adults (children weighing >10–20 kg received tafenoquine 100 or 150 mg; >20–35 kg received 200 mg; and >35 kg received 300 mg). The recurrence-free rate at 4 months was 94.7% (95% CI: 84.6, 98.3),19 and the TEACH study supported the successful approval of tafenoquine for children aged 2–16 years by the Australian TGA in March 2022.5<br /> Another important counter to the mg/kg-based dose selection is that, when bodyweight categories were fitted as a continuous variable in the INSPECTOR study (using data for the time to recurrence for all participants), neither bodyweight nor bodyweight-by-treatment interactions were statistically significant (p=0.831 and p=0.520, respectively).20<br /> Use of an unvalidated biomarker<br /> Although Watson et al. state that increases in blood MetHb concentrations after tafenoquine administration were highly correlated with mg/kg dose, no correlation coefficients were presented. It should also be re-emphasised that MetHb is not a validated, surrogate biomarker of antimalarial treatment efficacy as a radical cure for P. vivax malaria and was used as a safety measure in the INSPECTOR study.20<br /> Potential safety concerns<br /> In the Tolerability and safety section, Watson et al. state that severe haemolytic events were rare; however, this is because all the studies were randomised and controlled, which excluded patients with <70% G6PD activity. In addition, no mention was made that, in one of the constituent studies (which examined the dose–response for haemoglobin decline in participants with 40–60% G6PD enzyme activity),17 dose escalation of tafenoquine from 300 mg to 600 mg was not attempted due to safety concerns about potential haemolysis in patients with G6PD deficiency. In tafenoquine-treated patients in the real-world setting, some instances of severe haemolysis might be expected, and it is already known from the previously highlighted phase 1 study that the haemolytic potential of tafenoquine increases with increasing dose.17 Watson et al.’s Tolerability and safety section also mentions that one tafenoquine-treated patient had a >5 g/dL decrease in haemoglobin level, but the baseline haemoglobin level and tafenoquine dose are not mentioned. The section may have benefitted from a holistic discussion of safety parameters per tafenoquine dose group: for example, the occurrence of serious adverse events, gastrointestinal adverse events (beyond the selective discussion of vomiting within 1 hour post dose) and neuropsychiatric adverse events.<br /> Discussion<br /> Watson et al. conclude that ‘the currently recommended adult dose is insufficient … increasing the adult dose to 450 mg is predicted to reduce the risk of relapse’; however, the authors have raised several concerns relating to these conclusions. In particular, the authors feel that the safety concerns associated with a higher-than-approved tafenoquine dose have not been thoroughly considered: the safety analysis is limited, and the increased risk of haemolysis in patients with G6PD deficiency that a 450 mg tafenoquine dose (which is 50% greater than the approved 300 mg dose) would pose in vulnerable populations in limited-resource settings is not adequately discussed. In some malaria-endemic regions, 8% of the population may be G6PD deficient, although wide variability exists, and in sub Saharan Africa and the Arabian peninsula the prevalence of G6PD deficiency may exceed 30%.10,11 Therefore, in regions with fragile healthcare systems and limited availability of relevant testing for G6PD deficiency, potential exists for a significantly increased risk of haemolysis if tafenoquine is administered at an above recommended dose (450 mg). Importantly, off-label use of a dose not robustly evaluated in clinical trials would pose a considerable risk to patient safety.<br /> Regarding tafenoquine efficacy, the rationale for a dose increase to 450 mg has limitations. Watson et al. suggest that a 50% increase in the adult dose of tafenoquine (from 300 mg to 450 mg) would prevent one relapse of malaria for every 11 patients treated. However, this number-needed-to-treat estimate is not balanced by a number-needed-to-harm estimate for acute haemolytic anaemia. In addition, the phase 2b part of the DETECTIVE study21 showed that, in countries where the trial was carried out, single doses of tafenoquine 300 mg and 600 mg had similar relapse-free efficacy at 6 months (89.2% and 91.9%, respectively); therefore, the lack of additional benefit for tafenoquine 600 mg in DETECTIVE and the phase 1 study, which demonstrated dose-dependent haemolytic potential for tafenoquine, favour a 300 mg dose.<br /> In summary, based on currently available data, dosing tafenoquine at the approved 300 mg dose, in combination with chloroquine, carefully balances efficacy and safety in the radical cure of P. vivax malaria; indeed, tafenoquine 300 mg demonstrated a favourable benefit–risk profile in a comprehensive clinical development programme that included at-risk populations in regions with fragile or resource-restricted healthcare systems. The arguments raised by Watson et al. come with the concerns articulated here, and the authors confidently assert that a tafenoquine dose increase from 300 mg to 450 mg is not supported by available fact-based evidence for the radical cure of P. vivax malaria in adults aged >=16 years.

      References<br /> 1. GSK. US FDA approves Krintafel (tafenoquine) for the radical cure of P. vivax malaria [press release]. July 20, 2018. https://www.gsk.com/en-gb/media/press-releases/us-fda-approves-krintafel-tafenoquine-for-the-radical-cure-of-p-vivax-malaria/ (accessed 26 April 2023).<br /> 2. Hounkpatin AB et al. Clinical utility of tafenoquine in the prevention of relapse of Plasmodium vivax malaria: a review on the mode of action and emerging trial data. Infect Drug Resist 2019;12:553–570.<br /> 3. GSK. Krintafel. Highlights of prescribing information. https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/210795s000lbl.pdf (accessed 26 April 2023).<br /> 4. GSK, Medicines for Malaria Venture. Perú becomes second malaria-endemic country in Latin America to approve single-dose tafenoquine for radical cure of P. vivax malaria [press release]. https://www.vivaxmalaria.org/sites/pvivax/files/content/attachments/2021-01-25/GSK%20-%20MMV%20PRESS%20RELEASE%20TAFENOQUINE%20APPROVED%20IN%20PERU.pdf (accessed 26 April 2023).<br /> 5. Medicines for Malaria Venture. Single-dose Kozenis (tafenoquine) approved for children with Plasmodium vivax malaria by Australian Therapeutic Goods Administration. https://www.mmv.org/newsroom/press-releases/single-dose-kozenis-tafenoquine-approved-children-plasmodium-vivax-malaria (accessed 26 April 2023).<br /> 6. World Health Organization. WHO guidelines for malaria, 14 March 2023. https://www.who.int/teams/global-malaria-programme (accessed 26 April 2023).<br /> 7. Milligan R et al. Primaquine at alternative dosing schedules for preventing relapse in people with Plasmodium vivax malaria. Cochrane Database Syst Rev 2019;7:CD012656.<br /> 8. Llanos-Cuentas A et al. Tafenoquine versus primaquine to prevent relapse of Plasmodium vivax malaria. N Engl J Med 2019;380:229–241.<br /> 9. Baird JK. 8-Aminoquinoline therapy for latent malaria. Clin Microbiol Rev 2019;32.<br /> 10. Howes RE et al. G6PD deficiency prevalence and estimates of affected populations in malaria endemic countries: a geostatistical model-based map. PLoS Med 2012;9:e1001339.<br /> 11. P. vivax information hub. G6PD global prevalence. https://www.vivaxmalaria.org/diagnosis-treatment/g6pd-deficiency/g6pd-global-prevalence#:~:text=G6PD%20Global%20Prevalence,-Photo%3A%20Jaya%20Banerji&text=G6PD%20deficiency%20affects%20around%20400%20million%20people%20globally (accessed 26 April 2023).<br /> 12. Domingo GJ et al. Addressing the gender-knowledge gap in glucose-6-phosphate dehydrogenase deficiency: challenges and opportunities. Int Health 2019;11:7–14.<br /> 13. Chu CS et al. Haemolysis in G6PD heterozygous females treated with primaquine for Plasmodium vivax malaria: a nested cohort in a trial of radical curative regimens. PLoS Med 2017;14:e1002224.<br /> 14. Baird JK et al. Noninferiority of glucose-6-phosphate dehydrogenase deficiency diagnosis by a point-of-care rapid test vs the laboratory fluorescent spot test demonstrated by copper inhibition in normal human red blood cells. Transl Res 2015;165:677–688.<br /> 15. Shanks GD. Historical 8-aminoquinoline combinations: not all antimalarial drugs work well together. Am J Trop Med Hyg 2022;107:964–967.<br /> 16. Watson JA et al. The clinical pharmacology of tafenoquine in the radical cure of Plasmodium vivax malaria: An individual patient data meta-analysis. Elife 2022;11:e83433.<br /> 17. Rueangweerayut R et al. Hemolytic potential of tafenoquine in female volunteers heterozygous for glucose-6-phosphate dehydrogenase (G6PD) deficiency (G6PD Mahidol variant) versus G6PD-normal volunteers. Am J Trop Med Hyg 2017;97:702–711.<br /> 18. World Health Organization. Guidelines for the treatment of malaria, 3rd ed. https://apps.who.int/iris/handle/10665/162441 (accessed 26 April 2023).<br /> 19. Velez ID et al. Tafenoquine exposure assessment, safety, and relapse prevention efficacy in children with Plasmodium vivax malaria: open-label, single-arm, non-comparative, multicentre, pharmacokinetic bridging, phase 2 trial. Lancet Child Adolesc Health 2022;6:86–95.<br /> 20. Sutanto I et al. Randomised, placebo-controlled, efficacy and safety study of tafenoquine co-administered with dihydroartemisinin-piperaquine for the radical cure of Plasmodium vivax malaria (INSPECTOR). Lancet Infect Dis [2023 May 23:S1473-3099(23)00213-X doi: 101016/S1473-3099(23)00213-X Epub ahead of print PMID: 37236221].<br /> 21. Llanos-Cuentas A et al. Tafenoquine plus chloroquine for the treatment and relapse prevention of Plasmodium vivax malaria (DETECTIVE): a multicentre, double-blind, randomised, phase 2b dose-selection study. Lancet 2014;383:1049–1058.<br /> 22. GSK. Investigator brochure. Data on file.<br /> 23. Lacerda MVG et al. Single-dose tafenoquine to prevent relapse of Plasmodium vivax malaria. N Engl J Med 2019;380:215–228.<br /> 24. Tenero D et al. Exposure-response analyses for tafenoquine after administration to patients with Plasmodium vivax malaria. Antimicrob Agents Chemother 2015;59:6188–6194.

      Authors’ contributions<br /> Hema Sharma, Lionel Tan, Katie Rolfe, and Navin Goyal contributed to the conception or design of the studies the paper contains data from. All authors contributed to data analysis or interpretation. All authors contributed to the development and writing of this correspondence and approved the final submitted version.

      Conflicts of interest statements <br /> Raman Sharma, Siôn Jones, Rachel Gibson, Katie Rolfe, Lionel Tan, Ioana-Gabriela Fita, Chao Chen, Panayota Bird, and Anup Pingle are employees of, and shareholders in GSK.<br /> Hema Sharma is a former employee of GSK, a shareholder in GSK and a current employee of AstraZeneca. Navin Goyal is a former employee and shareholder in GSK and a current employee of Johnson and Johnson. Isabelle Borghini Fuhrer and Stephan Duparc have no conflict of interest to report. <br /> Acknowledgements <br /> Medical writing support was provided by David Murdoch, a contract writer working on behalf of Apollo, and Alex Coulthard of Apollo, OPEN Health Communications, funded by GSK Biologicals SA, in accordance with Good Publication Practice 3 (GPP) guidelines (www.ismpp.org/gpp-2022) "www.ismpp.org/gpp-2022)").

      Funding<br /> Funding for this article was provided by GSK Biologicals SA.

      Data availability<br /> Data sharing is not applicable to this article as no datasets were generated or analysed.

    1. On 2020-08-29 05:42:29, user ENT doctor Lee wrote:

      Every doctor would know infared temperature measurement at forhead is nnot quite accurate through practice. Wrist is a periphery region of body with relatively low temperature compare to axilla or middle ear. Wrist temperature can be easily down with wet situation with water.

    1. On 2020-12-18 11:30:03, user Wendy Olsen wrote:

      The paper is very useful.

      It is informative about a free data source for India known as the covid19india website.

      Since reading the paper, I explored this website. It has an API for data scientists to use the data. This paper by Vandana Tamraka, Ankita Srivastava, Mukesh C. Parmar, Sudheer Kumar Shukla, Shewli Shabnam, Bandita Boro, Apala Saha, Benjamin Debbarma, and Nandita Saikia is very useful in giving a summary of the age-sex-specific individual records in the database at a specific date in mid 2020. Since then, I believe the website Covid19india has now arranged to provide only District summaries which omits age-sex details.

      The paper is also very useful in providing an analysis of cumulative cases, over time, from March to July 2020, with a spatial autocorrelation correction. This is impressive and helpful. On the other hand, the spatial autocorrelation variables are not causal mechanisms, and they can reduce the apparent impact of other variables that do represent background causes or events. Even so, apparently the social-group variables at the District level did have some correlation with the cases (ie with cumulative contagion) in the time-series model, even after the spatial correction.

      I enjoyed the smoothly written conclusions of the paper.

      Regards - Wendy Olsen - - @Sandhyamma is my Twitter name, or meet me alternatively using Facebook.

    1. On 2020-04-03 05:01:21, user Jacob G Scott wrote:

      Please find our update, with HIGHER recommended exposure times for porous PPE, on our github repo: https://github.com/TheoryDi...

      We expect another update in the coming days with filtration/fit testing results at these exposures, as well as biologic validation.

      Please also see recent CDC guidelines: https://www.cdc.gov/coronav...

      and a cooperative groups recommendation for N95 decontamination: https://www.n95decon.org/

      Please stay safe and healthy.

    1. On 2020-08-11 14:13:04, user Randy Von Fistenburg wrote:

      Has this type of study not already been performed in other countries before this? It was my understanding that results of such studies from countries whose initial wave hit earlier than UK, concluded no increased risk for those with HIV infection (on ARV treatment). It would seem that government health officials, NHS patient advice and statements from HIV organisations and charities were entirely wrong when, at the start of the lockdown period, they assured public the complete opposite was the case: As long as those infected with HIV were taking ARV medication then they did not have increased mortality risk compared to rest of population. I remember a small study done in Barcelona and a larger one in China both seemed to indicate no increased risk, but I find it highly irresponsible for advice from official sources that was then used to make policy on what was considered high risk groups and organisation of shielding and other provisions and protections , not be backed up by research such as this study to be absurd - Its outrageous for these for these statements and advice to have been offered in the first place!

    1. On 2020-06-25 15:16:45, user dottore b wrote:

      "Dexamethasone reduced deaths by one-third in patients receiving invasive

      mechanical ventilation (29.0% vs. 40.7%, RR 0.65 [95% CI 0.51 to 0.82];

      p<0.001)" is misleading as this is an 11% decrease in the death rate. It's like saying the death rate went from 2% to 1% and trumpeting a "50% reduction in the rate of death".

      For those interested in a very good discussion of this trial from Dr Dan Griffin an intensivist at Columbia, this is a great link and every practitioner should be a TWIV listener

      https://www.microbe.tv/twiv...

    1. On 2020-07-29 22:25:43, user P. J. wrote:

      When you download the PDF, you will see all relevant info. ALL patients also got hydroxychloroquine and 3/7 also got azithromycin. Interestingly no heart issues, no deaths, better outcomes. Is it the combo...maybe? Honestly, I don't care as long as it works, but let's be up front about it.

      Seven patients out of 7 received at least one dose of the study drug?? Only 3/7 even got the full treatment? (It looks like with an average length of stay of 14-24.5 days, there was plenty of time to complete a 14 day course, assuming treatment began on the first day.)

      They do not give any breakdown of the drug group vs control as far as co-morbidities so they will need to do that going forward.

      In the end, there were 5 patients. Not sure if all those were on HCQ, as they leave that out. Were any of the five on azithromycin? Who knows? It says "overall" 3 patients received the full course of the study drug. Ok, is that overall of the 7 that started, or the five little patients that remained? Let's ASSUME 3 of the final 5 got the full 14 days, plus maybe HCQ and maybe AZ? There was no statistical significance in the length of time weaning from HFNC to NC 02. Time to room air was about 1.5 days sooner...so 36 hours.

      " Six patients in the control<br /> group (33%) required mechanical ventilation (p value compared with opaganib groups=0.13), 2(11%) required ECMO, and one required tracheostomy"

      The drug group also had better D-dimer results and higher baseline lymphocytes going into the study which are both markers seen in patients who tend to have better outcomes, drugs or not. There was no difference in the rate of CRP improvement between the control and drug group. They couldn't measure true normalization of lymphocyte count because the control group received steroids.

      Am I the only person routinely disappointed by the quietly buried info on HCQ? I think it was the RECOVERY remdesivir arm where patients weren't randomized until day 10-12 (well past the point where an antiviral would be of significant benefit) and 85% received HCQ up until starting remdesivir...and some even while taking it. A good number in the severely ill group were already maintaining O2 sats of 94% on room air when started on Remdesivir...in nursing, as far as oxygenation, we call that "stable." I don't know..maybe it's just me.

      The results of this amazing new drug just aren't impressive when this sentence is included by the authors:

      "In total, seven patients received at least one dose of opaganib since April 2, 2020. All<br /> patients received hydroxychloroquine (HCQ), however one stopped HCQ prior to opaganib<br /> treatment due to borderline Q-T interval in ECG. Three patients received azithromycin as well. One patient, who received both HCQ and azithromycin, developed diarrhea after two doses of opaganib, and the treating physicians decided to stop all his medications. A second patient who deemed to be in severe condition, was weaned to low flow oxygen within hours, and was discharged on RA (how long had he been on HCQ? Was he also on Azithromycin?) after receiving two doses of opaganib. Therefore, five patients were included<br /> in this analysis. Overall, 3 received the full 14-day course of opaganib, and 2 patients received 11 and 7 days respectively, before being discharged."

      2/5 received 11 and 7 days of study drugs before being discharged. Were they discharged on the last day of treatment? I don't think so since discharges were from 14-24.5 days in the treatment group. Why was therapy discontinued before discharge? 15.2-29.5 days until discharge in control group. Not sure who fell where so hard to know if that was statistically significant or not. But, the rate of decline as far as needing ECMO or mechanical ventilation were good...maybe, I mean with better D-dimer (not sure how much better...no info there) And higher lymphocyte count at the onset of the study, (Again, not sure how much higher) It's hard to know if the drug helped, if the other drugs helped, or if those patients were more stable going in and would have recovered either way. It just feels like another non-study study. I also have no idea how big the control group was. OH wait, there's a table. I missed it. The control group is over 3x the size of the trial group...come on guys. The control group had 3-4x the comorbidities..so a stacked control group in number and chronic disease manifestation. Mean lymphocyte count in the control group was 850 vs. 1100 in the drug group. Other labs as listed in Table one when you click on the PDF, but overall, the control group was sicker.

      I would be interested to know how the drug group (that got HCQ, study drug, and AZ) did vs the control group patients who got HCQ and AZ) That would actually be a more fair comparison...well maybe. I can't be sure since the control group was sicker and had more comorbidities to begin with.

      I started this analysis wondering if there was an exciting new drug that could really help and I finish still wondering the same thing. I am beginning to question if any of these studies have people familiar with research standards running them. No randomization, no blinding, no real placebo control group, (I understand the ethics of having a "no treatment" group that truly gets "no treatment" and respect that all patients deserve treatment so placebo will always be a treatment group.)

      Doctors on the drug company payroll or affiliated financially with the drug company, data analysis of trials and studies done by the sponsoring drug companies, writiing of studies by drug companies and or their employees rather than doctors without bias....I just find it all questionable.

      I keep reading studies that leave out randomization, control group, blinding, etc. The inclusion of gold standard research methods could give us real scientific data. Why does the scientific community routinely fail to integrate the known gold standards in their studies? Do they feel their drugs wouldn't stand up to such rigor?

    1. On 2020-03-13 23:55:07, user Cadence C wrote:

      Singapore health ministry stated that pre-symptomatic transmission is not a prominant mode. How did the authors conclude that 40% to 80% there are asymptomatic transmission ?

    1. On 2025-02-21 05:07:22, user Evan Stanbury wrote:

      This paper has a noble goal: To identify patients who have suffered long-term vaccine injury (ie iatrogenic, and potentially eligible for vaccine compensation schemes). It is important to distinguish these patients from from Long COVID, since they have very similar symptoms.

    1. On 2021-11-30 20:32:11, user Toa_Greening wrote:

      Based upon MoH data 30/11/2021 Unvaccinated are 3.5x (8.21/2.35) likely to be hospitalised from a case of Covid not 25x.

      No doses received prior to being reported as a case <br /> Cases 3518 Hospitalised 289 Hospitalisation rate 8.21%

      Fully vaccinated at least 7 days before reported as a case <br /> Cases 1194 Hospitalised 28 Hospitalisation rate 2.35%

    1. On 2020-04-13 13:39:56, user Rosemary TATE wrote:

      Hi, I dont see the STROBE guidelines checklist (for observational studies) uploaded, although you ticked yes to this<br /> "I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. "<br /> A lot of people seem to ignore these but they are important and any good journal will require them.<br /> Can you please upload? Many thanks.

    1. On 2021-06-11 09:54:15, user Patrik D'haeseleer wrote:

      How did you deal with correcting for multiple hypothesis testing in this study? It sounds like you focused on one sub-population of 255 out of >1200 patients. How many different sub-populations did you wind up testing, how many different medications, and how many different tests per medication?

    1. On 2020-04-02 23:28:48, user Sinai Immunol Review Project wrote:

      Review of paper titled:

      Virus shedding patterns in nasopharyngeal and fecal specimens of1COVID-19 patients

      Zhang et al. 2020

      Keywords: Viral shedding, testing specimens.

      Summary

      The authors tested feces, urine, plasma, nasal/throat swabs (respiratory samples)<br /> for SARS-CoV-2 virus load analysis by qPCR several days after illness onset<br /> (DAO).

      • All plasma samples were negative (n=56).

      • Two urine samples were positive from patients that had severe disease and were positive at least 16-21 DAO (n=56).

      • 10 of 12 cases (83.3%) tested positive for fecalsamples.

      • 14 of 21 cases (66.7%) were positive for respiratory samples.

      • Respiratory samples were positive for 21 DAO, nevertheless fecal samples were still positive.

      • Median duration of virus shedding was 10.0 days in respiratory samples

      • For fecal samples median shedding was 22.0 days for the feces.

      • Viral titers of respiratory samples peaked at six to nine DAO. and at 14-18 DAO for fecal samples, and the highest virus titers at the peak was significantly higher for feces (105.8 copies/ml, mean 5623 copies/ml) than of respiratory samples (106.363 copies/ml, mean 2535 copies/ml).

      Importance of findings and caveats

      Notably, these data reflect viral RNA and there is mention of infectious particles.<br /> Without these data, it is difficult to ascertain the significance of this paper. While these data demonstrate that the duration of fecal viral RNA shedding is significantly prolonged when compared to viral RNA shedding from the respiratory tract, it is critical for the field to ascertain if this represents infectious virions or not. If viable virus were to be isolated from<br /> the GI tract, that would indeed be very concerning for potential feco-oral transmission of SARS-COV2. As such, this paper does not establish this important fact.

      Review by Jovani Catalan-Dibene and validated by Saurabh Mehandru as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2021-02-09 15:49:22, user Rhonda Witwer wrote:

      Great study! What was the source of your Type 3 resistant starch? Different sources have been shown to have different effects, making it important to disclose the RS source.

    1. On 2021-09-01 20:00:22, user Peter Hanse wrote:

      This should be checked against "Experimental investigation of indoor aerosol dispersion and accumulation in the context of COVID-19: Effects of masks and ventilation" Physics of Fluids 33, 073315 (2021)

    1. On 2022-02-17 20:37:35, user RT1C wrote:

      Please consider correcting the following: "To adjust for this, we defined the proximate overt immunologic challenge (POIC) as the most recent exposure to SARS-CoV-2 by infection or vaccination." The vaccine does not give SARS-CoV-2 exposure. Thus, as written this is confusing and incorrect.

    1. On 2019-07-17 16:54:37, user Guyguy wrote:

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

      Tuesday, July 16, 2019

      The epidemiological situation of the Ebola Virus Disease dated July 15, 2019:<br /> Since the beginning of the epidemic, the cumulative number of cases is 2,512, 2,418 confirmed and 94 probable. In total, there were 1,676 deaths (1,582 confirmed and 94 probable) and 703 people healed.<br /> 423 suspected cases under investigation;<br /> 11 new confirmed cases, including 5 in Beni, 2 in Mandima, 1 in Mabalako, 1 in Vuhovi, 1 in Katwa and 1 in Komanda;<br /> 8 new confirmed cases deaths:<br /> 3 community deaths, 2 in Beni and 1 in Mandima;<br /> 5 deaths at Ebola Treatment Center, including 4 in Beni and 1 in Goma;<br /> 3 people cured out of Ebola Treatment Center including 2 in Butembo and 1 in Katwa.

      136 Contaminated health workers

      The cumulative number of confirmed / probable cases among health workers is 136 (5% of all confirmed / probable cases), including 41 deaths.

      163,533 Vaccinated persons

      The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 19 May 2018.

      75,321,895 Controlled people

      NEWS

      Follow-up of the situation of the pastor's contacts who traveled to Goma

      On Monday, July 15, 2019, 37 high-risk contacts and 40 Goma confirmed case contacts were vaccinated at the Afia Himbi health center where the patient had been isolated before being transferred to the Ebola Treatment Center. In total, 97 contacts in the broad sense have already been listed to date. Vaccination will continue until all identified contacts have been vaccinated.<br /> Among the contacts identified were two women from the pastor's family traveling with him. After the pastor's transfer to CTE, they hid in Goma and some people thought they fled to Bukavu in South Kivu province. Fortunately, the two women were found in Goma on Tuesday and will be vaccinated.

    2. On 2019-07-20 05:46:57, user Guyguy wrote:

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

      Friday, July 19th, 2019

      The epidemiological situation of the Ebola Virus Disease dated 18 July 2019:<br /> Since the beginning of the epidemic, the cumulative number of cases is 2,546, of which 2,452 confirmed and 94 probable. In total, there were 1,715 deaths (1,621 confirmed and 94 probable) and 721 people healed.<br /> 478 suspected cases under investigation;<br /> 14 new confirmed cases, including 6 in Beni, 5 in Mandima, 1 in Katwa, 1 in Mabalako and 1 in Mambasa;<br /> 10 new confirmed cases deaths:<br /> 6 community deaths, 2 in Beni, 2 in Mandima, 1 in Mabalako and 1 in Mambasa;<br /> 4 CTE deaths, 2 in Butembo, 1 in Katwa and 1 in Mabalako;<br /> 3 people healed out of Beni ETC

      .167 152 Vaccinated persons

      76,319,878 Controlled people<br /> 80 entry points (PoE) and operational health checkpoints (PoC).

      138 Contaminated health workers<br /> One health worker, vaccinated, is one of the new confirmed cases of Mandima.<br /> The cumulative number of confirmed / probable cases among health workers is 138 (5% of all confirmed / probable cases) including 41 deaths.

      Source: Ministry of Health press team on the state of the response to the Ebola epidemic in the Democratic Republic of the Congo

    1. On 2020-03-30 15:27:50, user Sinai Immunol Review Project wrote:

      Summary and key findings: Summary of clinical trials registered as of March7, 2020 from U.S, Chinese, Korean, Iranian and European registries. Out of the 353 studies identified, 115 were selected for data extraction. 80% of the trials were randomized with parallel assignment and the median number of planned inclusions was 63 (IRQ, 36-120). Most frequent therapies in the trials included; 1) antiviral drugs [lopinavir/ritonavir (n-15); umifenovir (n=9); favipiravir (n=7); redmesivir (n=5)]; 2) anti-malaria drugs [chloroquine (n-11); hydroxychloroquine (n=7)}; immunosuppressant drugs [methylprednisolone (n=5)]; and stem cell therapies (n=23). Medians of the total number of planned inclusions per trial for these therapies were also included. Stem cells and lopunavir/ritonavir were the most frequently evaluated candidate therapies (23 and 15 trials respectively), whereas remdesivir was only tested in 5 trials but these trials had the highest median number of planned inclusions per trial (400, IQR 394-453). Most of the agents used in the different trials were chosen based on preclinical assessments of antiviral activity against SARS CoV and MERS Cov corona viruses.

      The primary outcomes of the studies were clinical (66%); virological (23%); radiological (8%); or immunological (3%). The trials were classified as those that included patients with severe disease only; trials that included patients with moderate disease; and trials that included patients with severe or moderate disease.

      Limitations: The trials evaluated provided incomplete information: 23% of these were phase IV trials but the bulk of the trials (54%) did not describe the phase of the study. Only 52% of the trials (n=60) reported treatment dose and only 34% (n=39) reported the duration. A lot of the trials included a small number of patients and the trials are still ongoing, therefore no insight was provided on the outcome of the trials.

      Significance: Nonetheless, this review serves as framework for identifying COVID-19 related trials, which can be expanded upon as new trials begin at an accelerated rate as the disease spreads around the world.

    1. On 2021-02-24 19:02:08, user George Orwell wrote:

      The findings of this review are an outlier, in stark contrast to the rest - those produced by the WHO, FLCCC, EBM-C, and @CovidAnalysis. This pre-print says the studies considered had "7412 participants" but only reported mortality data on under two hundred of them. Even then, it shows Ivermectin reduced mortality (logRR: 0.89, 95% CI 0.09 to 1.70, p = 0.04), but reported Ivermectin was "not associated" with reduced mortality.<br /> It excluded the vast majority of the FORTY-ONE clinical trials with results, 18 published, the rest in preprint, .<br /> So even though the authors reported on a small fraction of a small fraction of the results, they still found significant improvement in the most important and elusive metric of all to show improvement in, mortality. But nonetheless, they reported this as a negative finding.<br /> As is widely reported, "The probability that an ineffective treatment generated results as positive as the 41 studies to date is estimated to be 1 in 2 trillion (p = 0.00000000000045)."

    1. On 2021-08-09 15:16:23, user VT wrote:

      Please do not post docx-files. Some researchers will be unable to download those files due to security concerns.<br /> Thanks!

    1. On 2020-07-02 18:46:51, user Julio C. Spinelli wrote:

      Having personally arquitected several clinical trials, the phase II results in young volunteers forces me to provide a word of caution to our collective desire to quickly develop a vaccine for COVID-19. <br /> The frequency and severity of many of the AE's described in this preprint for the young (18-55) and healthy population described here doesn't bode well for the results of a phase III clinical trial. Not until the phase II results of the older cohort are known. Furthermore, extrapolating these data to the Latin and Black populations would be pure hubris on our part. Further phase II data is required before we move into phase III trials<br /> Dr. Julio C. Spinelli

    1. On 2020-07-21 22:11:37, user BiotechObserver wrote:

      "Screened patients either had confirmed SARS-CoV-2 infections by PCR, or suspected disease, defined as being told by a physician that symptoms may be related to SARS-CoV-2 or exposure to someone with confirmed SARS-CoV-2 infection... In addition to screening potential donors, Mount Sinai also offered the Mount Sinai ELISA antibody test to all employees within our health system on a voluntary basis."

      It would be helpful to know what percentage of each of these 4 subsets of screened patients (out of the 51,829 total screened) were positive vs. negative on the ELISA test. <br /> Your sensible subsequent explanation on sensitivity findings notwithstanding, (it seems plausible you are detecting positive in the ELISA test >95% of those with a confirmed past infection), this breakdown would still be valuable from an epidemiology perspective.

      "The vast majority of symptomatic cases that were screened experienced mild-to-moderate disease, with less than 5% requiring emergency department evaluation or hospitalization."

      It would be helpful to visualize in a few additional figures the breakdown of various measures (titer ranges, decline/increase, neutralizing activity) stratified by severity of symptoms (asymptomatic vs. mild vs. moderate vs. hospitalized, or asymptomatic vs. mild/moderate vs. hospitalized).

      Thank you.

    1. On 2020-04-06 16:47:11, user smallbusinessrocks wrote:

      A MORE REASONABLE DEATH RATE FOR THE C-19 FLU 4/6/2020

      Food for thought.

      As a young actuaries, many years ago a group of us tried to identify causes of death from older people dying with several SUD (serious underlying disease). We gave up, cannot clearly identify cause. Most doctors certifying cause of death do not know what caused it, if from SUD. Most people age 65 and over have two or more SUD. Seven thousand people with SUD die each day in the United States.

      People have touted various rate of death from the C-19 flu in America, starting with 4.5% and reducing quickly to current 1.29%. There will be many more deaths from the current infected.

      These death rates are grossly overstated – every pandemic, it is the same thing – death rates are wildly overstated at the beginning. A calculation, using a better basis, is 0.73% -<br /> more than the ordinary flu, but not 1.3% or 4.5%

      Truer denominator: in all but Iceland and Pacific Princess, we need to multiply the total cases by four. Why? Because we are only testing a segment of symptomatic cases (coughing, etc), but the asymptomatic cases are 80% of the total. Except for Iceland - they tested a large group drawn from the general population, not just the ones showing<br /> symptoms, found 75% asymptomatic (multiply denominator by factor of four). The<br /> Pacific Princess tested all 2500 on boat – the Pacific Princess 1% death rate<br /> is highly affected by median age of cruise passengers, in general, of 60 to 69<br /> years. Diamond Princess has asymptomatic 83% - multiply by five

      Truer numerator, is much less than the reported deaths, we would estimate about 0.2 of the 81% of deaths who have "SUD" - serious underlying disease; and 1.0 for all others. We estimate a weighted multiplier as (.2 deaths x 1.0 + .8 deaths x 0.2 = .36 of deaths<br /> reported). Why? Because many die from pneumonia in the USA each year, typically as the final stage of some other SUD (per NCHS). Doctors cannot prove a death from someone having the C-19 flu is CAUSED BY the C-19 flu, rather than the person with C-19 flu died WITH the C-19 flu. Needs research, but impossible to split causes. Reported deaths of<br /> person WITH C-19 flu now are 100% ascribed to C-19 flu currently.

      In USA, a truer estimate of the<br /> actual death rate is therefore, at April 5, 0.73%:

      Numerator: 8173 deaths x .36 = 2942<br /> deaths FROM C-19 flu – multiply this times 3 for future deaths from this<br /> cohort equals 8826 - divided by - Denominator:<br /> 301147 cases x 4 = 1204558 to include asymptomatic – yep, the current number of<br /> cases is four times the reported numbers. This is very good news, because it<br /> reduces the mortality rate.

      Twelve months from now, we can look<br /> at the total deaths in the USA, and compare that with the 2.8 million deaths<br /> for 2018. 2.6 million of 2018 deaths were from about seven serious<br /> underlying diseases, many people having three or more suds.

      Equals 0.73% truer death rate...more<br /> than 0.12% from ordinary flu, but well below 1.29%

      The C-19 flu is just a flu. <br /> The C-19 flu is just a flu <br /> The C-19 flu is just a flu

      Pete A

    1. On 2020-02-25 12:11:41, user Igor Nesteruk wrote:

      Dear colleagues,

      Unfortunately, the coronavirus epidemic in Italy is developing very much like we have seen in mainland China (details in my preprint).

      http://dx.doi.org/10.13140/...

      Only very strict quarantine and safeguards can stop the spread of the infection throughout Europe.

      May be, this information could be useful for your investigations.

      I have found today the accumulated number of cases in Italy – 229 - on the official site of Italian Health Ministry.

      http://www.salute.gov.it/po...

      This point was already in the figure from

      http://dx.doi.org/10.13140/...

      We need the correct and reliable information about the accumulated number of cases. Do you have any links?

      Be careful and healthy!

      Sincerely yours,

      Igor Nesteruk,

    1. On 2020-07-28 15:25:40, user Maxim Sheinin wrote:

      This is an interesting analysis. It would be important to discuss the impact of long-term care facilities in the discussion section,as in many countries about 50% of Covid deaths originated in these facilities.

    1. On 2020-03-28 00:45:53, user Adam Sobel wrote:

      Would also like to see expanded cohort to include a range of disease severities. Most reproductive-aged men would currently be expected to experience mild symptoms; if there is a correlation, is it linear wrt severity?

    1. On 2020-06-02 14:41:57, user Matthew Healy wrote:

      If at least some of the institutions participating in a seroprevalence study have access to stored blood samples collected before December 2019, those could also be used as negative controls.

    1. On 2021-07-13 17:09:58, user intros pector wrote:

      "Fully vaccinated"? Full immunity by Covaxin is considered to be achieved only 2 weeks after the second dose, but patients 0a and 0b are reported above to have travelled a few days before that, unfortunately. Plus, sitting in a plane for ~20 hours would have resulted in virus overload for patients 0a and 0b. Providng more such details would make the paper more amenable to detailed conclusions.

    1. On 2023-12-29 17:07:05, user Brinda Gour wrote:

      Hi, greetings for the day!<br /> This paper mentions that the supplementary data will be available upon request. Could you please grant access to supplementary material for me? This will be helpful for my review. Thanking you.

    1. On 2022-12-27 18:27:33, user Bahrad Sokhansanj wrote:

      A peer-reviewed version of this manuscript has now been published: Sokhansanj BA, Zhao Z, Rosen GL. Interpretable and Predictive Deep Neural Network Modeling of the SARS-CoV-2 Spike Protein Sequence to Predict COVID-19 Disease Severity. Biology (Basel). 2022 Dec 8;11(12):1786. PMID: 36552295; PMCID: PMC9774807. https://doi.org/10.3390/bio....

    1. On 2021-04-06 09:02:36, user Hieraaetus wrote:

      1) An observational study on 90 patients from the end of 2020 compared with 90 patients treated during the first wave (Mar-Apr 2020): this is a bias! They should compare patients observed exactly during the same period. <br /> 2) In the paper there is no trace about the "Home-Therapy Algorithm": there is a list of allowed drugs but there is not an Algorithm that describes how use these drugs. Thus , the 90 patients did not underwent to a standardized treament.

    1. On 2025-09-17 10:47:48, user Albert Kirshen, MD, FACP wrote:

      Interesting article for palliative care or pain medicine. The authors could improve the generalizability of this reseache if<br /> 1) Specific information were provided about the cannabis used, i.e. % THC, %CB, form (smoked, oil, ingested), dosing<br /> 2) A clear description of the population evaluated, i.e. demographics, health condition(s), were provided<br /> 3) Prior history of cannabis use was noted<br /> to mention but a few.

    1. On 2021-08-30 04:59:27, user William Brooks wrote:

      The authors estimate that if the UK government's hadn't extended restrictions for another month, daily hospital admissions would have reached 3400, whereas they peaked at only 1400 due to restrictions being extended. However, according to Our World in Data, peak weekly admissions in July were higher in the UK than all mainland European countries except for Spain and considerably higher than in countries with fewer restrictions and smaller percentages of population vaccinated such as Sweden and Croatia.

      To better assess the results of the UK government's decisions, it would be more informative to compare England's outcomes to the real-world outcomes of other European countries instead of models that may overestimate the effects of government actions.

    1. On 2020-08-17 01:03:42, user BannedbyN4stickingup4Marjolein wrote:

      I was referring particularly to the part of the Twitter thread on T-cells. You're commenting mainly on some other subject matter at the end of the thread (masks). I don't think it's appropriate to have a long discussion with you about the efficacy of masks in the comment section for a pre-print article about herd immunity. So whilst I disagree with you, I shalln't go in to that.

      As regards T-cells, the "bogus information" to which I was referring was a Twitter thread by a lapsed opthalmologist (James Todaro MD) which has had quite wide circulation. You may not have come across this, so fair enough, but many others have and have been profoundly mis-led by it.

      Professor Crotty is one of the guys whose research identified the cross-reactive T-cells in the first place, so whilst you might find his descriptions "ridiculous", I'm going to put more weight on his discourse than those of an anonymous Disqus poster.

    1. On 2020-04-25 23:09:56, user wbgrant wrote:

      One more publication in support<br /> Environmental predictors of seasonal influenza epidemics across temperate and tropical climates.<br /> Tamerius JD, Shaman J, Alonso WJ, Bloom-Feshbach K, Uejio CK, Comrie A, Viboud C.<br /> PLoS Pathog. 2013 Mar;9(3):e1003194. doi: 10.1371/journal.ppat.1003194. Epub 2013 Mar 7. Erratum in: PLoS Pathog. 2013 Nov;9(11). doi:10.1371/annotation/df689228-603f-4a40-bfbf-a38b13f88147.

    1. On 2020-08-01 16:36:24, user Dude Dujmovic wrote:

      Term "loss expansion" deserves definition, it sounds like oxymoron. The table 2 is unreadable, you need to separate weeks into separate graphs to make sense of that.

    1. On 2020-10-30 19:50:12, user Louis Rossouw wrote:

      There is a typo on page 8. Second last paragraph discusses excess mortality and refers to Appendix P. I think it should refer to Appendix Q.

    1. On 2020-03-27 20:03:16, user Brian Coyle wrote:

      Important and significant study. Should lead to policy. One question: (only) 1 of 347 asymptomatic infected people transmitted to someone. But study also says the rate of asymptomatic transmission is .0033%

    1. On 2022-01-05 01:05:11, user Paul Wolf wrote:

      I would have liked to see a direct comparison to delta and omicron, which is what everyone has on their minds. This has two familiar mutations, N501Y and E484K, and no others? Where do most of them occur: on the RBD, N Terminal Domain, or furin cleavage site? Do the 46 mutations suggest a jump to another species? Omicron is acting like a completely different virus, and this one found in France is just as mutated.

    1. On 2020-03-21 20:58:27, user Sinai Immunol Review Project wrote:

      This study was a single-arm, open label clinical trial with 600 mg hydroxychloroquine (HCQ) in the treatment arm (n = 20). Patients who refused participation or patients from another center not treated with HCQ were included as negative controls (n = 16). Among the patients in the treatment arm, 6 received concomitant azithromycin to prevent superimposed bacterial infection. The primary endpoint was respiratory viral loads on day 6 post enrollment, measured by nasopharyngeal swab followed by real-time reverse transcription-PCR.

      HCQ alone was able to significantly reduce viral loads by day 6 (n = 8/14, 57.1% complete clearance, p < 0.001); azithromycin appears to be synergistic with HCQ, as 6/6 patients receiving combined treatment had complete viral clearance (p < 0.001).

      Chloroquine is thought to inhibit viral infection, including SARS-Cov-2, by increasing pH within endosomes and lysosomes, altering the biochemical conditions required for viral fusion1,2. However, chloroquine also has immuno-modulatory effects that I think may play a role. Chloroquine has been shown to increase CTLA-4 expression at the cell surface by decreasing its degradation in the endo-lysosome pathway; AP-1 traffics the cytoplasmic tail of CTLA-4 to lysosomes, but in conditions of increased pH, the protein machinery required for degradation is less functional3. As such, more CTLA-4 remains in endosomes and is trafficked back to the cell surface. It is possible that this may also contribute to patient recovery via reduction of cytokine storm, in addition to the direct anti-viral effects of HCQ.

      Despite what is outlined above, this study has a number of limitations that must be considered. First, there were originally n = 26 patients in the treatment arm, with 6 lost to follow up for the following reasons: 3 transferred to ICU, 1 discharge, 1 self-discontinued treatment d/t side effects, and 1 patient expired. Total length of clinical follow up was 14 days, but the data beyond day 6 post-inclusion are not shown.

      Strikingly, in supplementary table 1, results of the real-time RT-PCR are listed for the control and treatment arms from D0 – D6. However, the data are not reported in a standard way, with a mix of broadly positive or negative result delineation with Ct (cycle threshold) values, the standard output of real time PCR. It is impossible to compare what is defined as a positive value between the patients in the control and treatment arms without a standardized threshold for a positive test. Further, the starting viral loads reported at D0 in the groups receiving HCQ or HCQ + azithromycin were significantly different (ct of 25.3 vs 26.8 respectively), which could explain in part the differences observed in the response to treatment between 2 groups. Finally, patients in the control arm from outside the primary medical center in this study (Marseille) did not actually have samples tested by PCR daily. Instead, positive test results from every other day were extrapolated to mean positive results on the day before and after testing as well (Table 2, footnote a).

      Taken together, the results of this study suggest that HCQ represents a promising treatment avenue for COVID-19 patients. However, the limited size of the trial, and the way in which the results were reported does not allow for other medical centers to extrapolate a positive or negative result in the treatment of their own patients with HCQ +/- azithromycin. Further larger randomized clinical trials will be required to ascertain the efficacy of HCQ +/- azithromycin in the treatment of COVID-19.

      References

      1. Wang, M. et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Research vol. 30 269–271 (2020).
      2. Thomé, R., Lopes, S. C. P., Costa, F. T. M. & Verinaud, L. Chloroquine: Modes of action of an undervalued drug. Immunol. Lett. 153, 50–57 (2013).
      3. Lo, B. et al. Patients with LRBA deficiency show CTLA4 loss and immune dysregulation responsive to abatacept therapy. Science (80-. ). 349, 436–440 (2015).
    1. On 2022-01-17 04:02:45, user ChadEnglish wrote:

      Edit: I've talked to the author so I may not need help as below request. But I'm still interest if anybody has additional suggestions.

      -- ORIGINAL --<br /> Hi all. I'm hoping somebody can help me address an inconsistency that I don't see that any comments have mentioned. I'm trying to build a risk model for policy but I'm getting the reverse result from this paper when applied to a full risk model.

      As I look at it, the problem appears to be that this study compares the risk of myocarditis for people who have already tested positive for COVID-19 versus the risk of people after vaccination. The summary conclusion in the abstract makes the statement, "Young males infected with the virus are up 6 times more likely to develop myocarditis as those who have received the vaccine."

      This seems correct and consistent. But the discussion in the full paper makes the statement, "Whether considering all the risks and benefits of COVID-19 vaccination or just myocarditis, vaccination appears to be the safer choice for 12-19-year-old males and females."

      That statement doesn't appear to follow from the analysis. The analysis is comparing conditional probabilities with different conditionals. The comparison only applies to people who already have COVID-19 infection. The latter statement isn't comparing conditional probabilities between COVID-19 versus vaccination, but total myocarditis risks between vaccinated and unvaccinated status. To get that, you would have to multiply the conditional COVID-19 myocarditis risk by the risk of acquiring COVID-19 infection for the age range.

      [Edit: I understand it now as being a comparison of vaccination vs intentional COVID-19, so the abstract is indeed correct and the later statement may be somewhat correct if the context is understood.]

      The model I'm using is the total risk from myocarditis should be:<br /> P(M) = P0 + P(V)·P(M|V) + P(C)·P(M|C)

      Here P0 is the background risk. P(V) is the probability of being vaccinated which is 1 if vaccinated and 0 if unvaccinated. P(M|V) is the conditional probability of getting myocarditis from the vaccines, which this paper investigates. P(C) is the risk of getting COVID-19 for the age range and vaccination status. P(M|C) is the conditional probability of getting myocarditis given that you have already tested positive for COVID-19, which is also what the paper investigates.

      I don't have good estimate yet for the risk of getting COVID-19 for this age range, gender, and vaccination status, but the rough proxy estimates I have are that the risk of getting COVID-19 if you are unvaccinated is about 3.15% per year average, and for vaccinated I have about 0.35% per year. These values will also vary with outbreak waves, variants, age range, which vaccines, and other factors.

      [Note these estimates are from Canadian data, so are quite different in the U.S. and other jurisdictions.]

      The risk of getting COVID-19 is, of course, time variable. To be consistent with the study these can scale to 90 days as P(C) = 7.7e-3 for unvaccinated and P(C) = 8.6e-4 for vaccinated.

      The estimates from the paper for 12-17 year old males is P(M|V) = ~67 per million (6.7e-5) chance of myocarditis from vaccination and P(M|C) = 450 per million (4.5e-4) from COVID-19.

      Plugging these into the above myocarditis risk for unvaccinated and vaccinated cases, and subtracting the background risk to compare the increased risk for unvaccinated and vaccinated cases, gives:

      P(M,U) - P0 = (0)(6.7e-5) + (7.7e-3)(4.5e-4) = 3.46e-6 = 3.5 per million per 90 days<br /> P(M,V) - P0 = (1)(6.7e-5) + (8.6e-4)(4.5e-4) = 6.74e-5 = 67.4 per million per 90 days

      The odds ratio then becomes 68/3.5 = 19.2. This suggests that given the option of getting vaccinated or remaining unvaccinated for the next 90 days, and you don't currently have COVID-19, your risk of myocarditis from vaccination is almost 20 times higher than taking a chance on not getting COVID-19 over those 90 days. This makes intuitive sense because the risk of getting COVID-19 is low.

      This odds ratio will change over time as your chances of catching COVID-19 increase over time. Using the above assumptions, the risks are equal after 5.3 years of being unvaccinated, which of course the assumptions of the model will be long out of date.

      I can't get a case here in which vaccination appears to be the better option for myocarditis overall. If you don't have COVID-19, it appears better to try to avoid both vaccination and COVID-19. If you do have COVID-19, your paper applies but then it is too, but by then it is trivia and can't be used for a decision. It appears to be more an issue of risk tolerance than actual risk calculation.

      It's possible the risks of getting COVID-19 are much higher for the age range and conditions here, which would shorten the cross-over point and reduce the odds ratio, but to get a conclusion that vaccination is the better option for myocarditis in any reasonable timeframe seems to require unreasonably high probabilities of catching COVID-19. (Maybe omicron numbers will do it, but then the risks of myocarditis could be quite different.)

      (Please note that I'm speaking here only for myocarditis. For general risks of hospitalization and death, the relative risks are quite different so I'm not suggesting this should be the dominant deciding factor.) [In fact, any decision should include all-cause analysis, as the author mentioned to me too.]

      Does anybody see any significant flaws in my model here, or note where I've misinterpreted this paper? Thanks for any feedback.

    1. On 2021-11-30 09:10:43, user Glenn LGG wrote:

      With the study running as far back as December, it's bound to capture a lot more unvaccinated during a time with higher risk of exposure.<br /> This is just one example of how the study does not take into account inherent risks.<br /> That makes it flawed.<br /> Furthermore the incidence of 5.2 /10k only increased to 5.8/10k in the control group during the delta wave. As this is supposedly time (duration) adjusted, what does it say about delta being far more infectious? (As claimed by the CDC)<br /> It seems to be contradicted by this finding.

    1. On 2020-08-23 15:06:23, user Ibezimako wrote:

      This study design is more of a cross-sectional survey and analysis of data from a database. I did not see it as 'prospective/longitudinal cohort.

    1. On 2021-05-11 13:08:35, user Tomas Hull wrote:

      There was no placebo group... <br /> If the same study was among the unvaccinated frontline health care workers, dealing with SARS-CoV2 patients, wouldn't most of them have at least detectable IgG and IgM titers??? <br /> Why not test the same group of people again 2-3 months later and see what the antibody titers are, if detectable at all...

    1. On 2020-10-14 20:35:53, user BannedbyN4stickingup4Marjolein wrote:

      If "A fraction of the population may also already be intrinsically resistant to infection as a consequence of high functioning innate immunity" as the paper claim, how is it that infection rates of c. 85%, with the potential to rise further upon further exposure (for example https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.08.13.20173161v1)"), have been observed in homogenous populations?

      Such phenomena should surely be referenced in the authors' discussion, without which an entirely theoretical model such as that produced is perhaps an unreliable basis upon which to formulate policy prescriptions.

      There is also a recent paper commenting on cross-immunity (https://www.nature.com/arti... "https://www.nature.com/articles/s41577-020-00460-4)") the conclusions of which the authors should carefully consider.

    1. On 2020-04-01 13:46:59, user Sinai Immunol Review Project wrote:

      Main Findings: This is a simple study reporting clinical characteristics of patients who did not survive COVID-19. All patients (mean age=69.22 years) had acute respiratory distress syndrome (ARDS) and their median time from onset to ARDS was 11 days. The median time from onset to death was 17 days. Most patients were older male (70% male) with co-morbidities and only 11 % were smokers. 75% patients showed bilateral pneumonia. Many patients had chronic diseases, including hypertension (58.33%). cardiovascular disease (22.22%) and diabetes (19.44%). Typical clinical feature measured in these patients includes lymphopenia and elevated markers of inflammation.

      Limitations: As noted by the authors, the conclusions of this study are very limited because this is single-centered study focusing on a small cohort of patients who did not survive. Many clinical parameters observed by the authors (such as increase levels of serum CRP, PCT, IL-6) have also been described in other COVID19 patients who survived the infection

      Relevance: This study is essentially descriptive and may be useful for clinical teams monitoring COVID19 patients.

      Comment by Zafar

    1. On 2020-07-01 00:05:45, user ??? wrote:

      Dear Colleagues

      I'm Jaehun Jung, the corresponding author of the manuscript.

      Our manuscript was published after peer-review as follows.

      'Ji W, Huh K, Kang M, Hong J, Bae GH, Lee R, Na Y, Choi H, Gong SY, Choi YH, Ko KP, Im JS, Jung J. Effect of Underlying Comorbidities on the Infection and Severity of COVID-19 in Korea: a Nationwide Case-Control Study. J Korean Med Sci. 2020 Jun;35(25):e237. https://doi.org/10.3346/jkm...

      Our published version have the following changes, please refer to the newly published paper.

      1) Database changes<br /> -HIRA combines epidemiological investigations data from Korea's Centers for Disease Control and Prevention and extends the database until May 15. Our published version are based on this recent database. Therefore, the results of the pre-print version and the printed version are quite different.

      2) Case definition and comorbidity identification

      The pre-print version was able to check past history of more than 5 years. However, due to the expansion of the DB, only the past history can be confirmed within the past three years, and there has been a methodological adjustment.

    1. On 2021-05-07 16:36:27, user Gustavo wrote:

      It would be very interesting if the researchers compared the levels of vitamin D (25OHD) in the two sisters. Vitamin D is actually a hormone with an immunomodulatory effect. A 2010 survey identified that sufficient levels of vitamin D are crucial for the activation of CD8 + killer T lymphocytes:

      https://www.sciencedaily.co...<br /> von Essen et al. Vitamin D controls T cell antigen receptor signaling and activation of human T cells. Nature Immunology, 2010; DOI: http://dx.doi.org/10.1038/n...

      This finding was confirmed by these two recent studies:

      -Circulating Vitamin D levels status and clinical prognostic indices in COVID-19 patients<br /> https://t.co/FpTJ0vwWkc

      -The association between vitamin D levels and the clinical severity and inflammation markers in pediatric COVID-19 patients: single-center experience from a pandemic hospital

      https://t.co/Cb8kYk5wo5

    1. On 2023-11-15 15:22:22, user Ryon wrote:

      The analysis evaluating off-label use of hormonal therapy in OC is fascinating. The methods of adjustment for known, quantifiable variables via IPTW is valid. However, this work could be improved by a discussion of unknown confounders that might have affected the observed associations. For instance, in breast cancer and prostate cancer, the decision to give hormonal therapy or chemotherapy is very influenced by patient frailty, for which ECOG scores are a crude measure. Things like total disease burden, sites of metastases, etc, which are difficult to quantify and sometimes not included in the FH database would be things that should be absolutely considered. More granular commentary of what variables are balanced / imbalanced, and variables that could affect treatment assignment other than the ones quantified, and likely direction of residual bias, are needed for more thorough evaluation of whether the reported analysis supports the hypothesis of off-label effectiveness of these drugs.

    1. On 2020-06-25 15:24:39, user Nojan Aliahmad wrote:

      great work with very good control. The impact of unregulated cytokines and inflammatory compounds (such as CRP) on COVID-19 is a very important discussion. Future clinical trials can show how effective will be vitamin D supplements in reducing these unregulated compounds.<br /> Dexamethasone is the first drug showing success in reducing the mortality rate of COVID-19 in clinical trials. It also works on the principal of reducing unregulated cytokine.

    1. On 2020-12-24 23:19:01, user Matthias Fax wrote:

      By design, this study could only fail to meet its hypothesis. It only proves what was to be expected. They used inappropriate dosage in oral form. They accepted an inappropriate delay after onset of symptoms. They didn't mention the significance of 25OHD sufficiency for patient outcome, indicating that the oral dosage was given too late to be of any immunological use.

    1. On 2021-09-06 06:07:04, user William Brooks wrote:

      The author estimates that Tokyo contains 6 infectious people for each person who tests PCR positive, which is probably an underestimate since the test positivity rate was over 20% during most of August. But even if the ratio is 6:1, this means Tokyo's infection fatality ratio outside of healthcare settings is below 0.01%, which hardly justifies the author's desire to search the city for health people who might have enough SARS-Cov2 DNA in their nose to return a positive result on a 40-cycle PCR test.

      Also, the author seemingly doesn't know that the first three states of emergency (SoE) started after infections were already falling [1], making all three not just ineffective but also unnecessary. Overestimating the effects of non-pharmaceutical interventions, he calls for the government to copy policies that have failed throughout the world based on a superficial understanding of a few cherry-picked examples: Taiwan has has a 5.2% case fatality rate, so there are obviously a lot of infected people who don't get tested, while Australia and New Zealand are back in lockdown again after failing to "control the virus." Since there are more cost-effective pharmaceutical interventions for actual Covid patients, they should be prioritized.

      [1] https://doi.org/10.1101/202...

    1. On 2021-07-10 21:46:46, user Merja Rantala wrote:

      But you did not have a proper control group! You can't say anything about association of spectacles with covid based on this work.

    1. On 2021-02-02 22:30:54, user Philippe Marchal wrote:

      The authors write "We believe that the large excess mortality seen around the world during the COVID-19 pandemic is robust to the exact model specification". This is clearly false.

      Consider for instance controlling for age structure. See

      https://www.math.univ-paris...

      which is taken from

      https://www.ons.gov.uk/peop...

      At the end of week 24, there is no excess mortality in France, while the graph on p.5 shows a substantial excess mortality. See also Bulgaria and Czechia, which have a substantial *negative* excess mortality at that time. This does not appear in the graphs.

      It should be clear that given the age structure of countries where a baby boom occured after WW2 and given the fact that the mortality rate grows superlinearly as a function of the age, the number of deaths will grow superlinearly in time. A linear regression as used by the authors will not<br /> capture this phenomenon. Thus the related baseline will be lower than the baseline computed by controlling for age structure.

      Another major concern is the way the authors modelize the noise $epsilon$ on p.3. I suppose $epsilon$ should be $epsilon_t$, i.e. the noise depends on time, otherwise this makes no sense. But the model seems to assume that the random variables $(epsilon_t)$ are independent, which is obviously not the case: otherwise, there would be no epidemics lasting more than a week! It is a bit ironic that, in a paper studying a pandemic, the authors use a model that cannot describe the annual flu epidemics.

    1. On 2020-06-28 02:19:40, user LB wrote:

      I appreciate the difficult circumstances under which this study was conducted, but would like some clarification, because there are some discrepancies in the data. The text states that "All patients who needed supplemental oxygen therapy in the control group also required further ICU support." However, the table shows only 8 of the 16 requiring ICU support. This section, "Among 9 patients given DMB within the first week of onset of symptoms, only one patient required oxygen therapy. This patient was one of the two cases which deteriorated within 24 hours of DMB initiation." seems to indicate that two patients in the DMB group required ICU care, but only one is listed in the table.

    1. On 2021-08-26 18:46:13, user vicweast wrote:

      If a vaccinated person contracts covid-19 (breakthrough infection) and their symptoms do not include symptoms like coughing/sneezing... are they as contagious as a person who has coughing/sneezing symptoms? This is what I am not reading anywhere, and yet it seems to be exactly the point.