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    1. On 2021-08-15 02:02:46, user bcwbcwbcw wrote:

      An online survey, where anyone can claim to have a PhD and no tests or controls for whether that's true? If you're anti-vax what better way to claim credibility than to lie and claim to have a PhD? In other past surveys , 6% of PhD's said they are Republican, yet the hesitancy results for PhD's are nearly the same as the strongest Trump supporters. (statistically possible but very unlikely.) (https://www.pewresearch.org... ) If I was a reviewer, I would ask see the breakdown of Trump support versus education level. If not consistent with other studies, the educational attainment data should be discounted.

      I took this survey and it likely has some use as far as changes in totals over time but PhD's not really.

      Let me give you a data point from a lab with about 1500 PhD's and tech staff. Everyone I've asked is vaccinated and I've asked everyone I'm in contact with.

    2. On 2021-08-15 10:02:06, user Anna Z. wrote:

      This paper is circulating among no-vax groups and used as a prof that educated people don't get the vaccine because they are not fooled by the government.<br /> How did you make sure that the survey was not circulated among no-wax groups that on purpose answered to obtain this result?

    3. On 2021-10-05 10:08:23, user Samantha Hester wrote:

      Members of the trans community are raising questions about your new exclusion criteria that eliminated people who self-identified as unicorns. Unicorns belong to the otherkin community and their responses could be in good faith.

      Please review this post from a trans advocacy organization for more details:

      https://www.facebook.com/pe...

    1. On 2021-08-16 15:59:43, user A. Jamie Saris wrote:

      There are some excellent comments below that I will not rehash, but I agree that this pre-print "as is" would not survive peer review without some serious revisions. Unfortunately, as this site is Open Source, this "study" is appearing in a lot of anti-vaxx rants on social media (it's been cited twice to me on Twitter so far today). It would be a great help if there were some printed caveats on sites like this (especially around topics where pseudoscience to outright quackery is rife) to dissuade people from taking VERY provisional results (from a flawed study with a modest number of participants) as "settled" science "proving the effectiveness" of Ivermectin.

    1. On 2021-08-17 14:26:39, user Andrew Sefton wrote:

      In the research, how were those previously infected by COVID-19 categorized? As unvaccinated? Excluded?

      Specifically, I am interested in the viral loads of those previously infected by COVID-19 as it relates to:<br /> "Delta viral loads were similar for both groups for the first week of infection, but dropped quickly after day 7 in vaccinated people."

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

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

    1. On 2021-08-20 23:58:21, user Chris Raberts wrote:

      This model ignores the wave form observed repeatedly over the past year and a half. Covid infection is not a never-ending exponential function. Terrible.

    1. On 2021-08-21 16:43:18, user Mark J Kropf wrote:

      A good many issues are of question in regards to this work, after mulling it over a good time. Firstly, evolution is always going on. If one is defining mutations in the most general sense, no treatment alters that rate. However, if one means by mutation the generation of some particularly problematic change causing a variant, then perhaps the logic dealt with here is relevant. Evolution is not a process which can be terminated or quelled, though it may be channeled and controlled! Secondly, a period of about 5.5 months can give some possible resonance to the supposed finding, but the ability to alter progression needs to really have significant follow up. Is the process of some unfavorable change (i.e my latter use of 'mutation' above) really limited or is it only impeded and delayed? A true ability to confirm requires a longer period of analysis and the current argument conclusion may be somewhat presumptuous in its statement. Thirdly, I am concerned that the numbers may yet be a bit too small for the conclusion reached, though running a study with the proper enrolled numbers for such comparisons is probably too problematic to be practical.

      I believe there is some evidence here, but perhaps not so complete as to be given the full impact that the conclusion provides. It is likely, but it is not confirmed to nearly the extent that I might desire for such a paper.

    1. On 2021-08-21 19:03:01, user Jonathan C wrote:

      Hello,

      Thanks for an interesting analysis. CDC estimates a far higher infection rate (36.77/100k, <br /> https://www.cdc.gov/coronav... "https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/burden.html)"), <br /> at a similar rate for the 0-17 y group, although they do not seem to show data for the 12-17 y group).

      Am I correct in interpreting your assumption that the infection rate for the <br /> investigated COVID-19-related period was at a far lower <10%? (and that 2.5% of all COVID-19 cases should represent males aged 12-17)

      Or is there some information missing regarding your analysis?

    1. On 2021-08-24 07:21:17, user Red wrote:

      This paper is missing one very crucial piece of information: 6-month adverse event followup. Table S3 still reports only adverse event counts up to 1 month after the second dose, but nothing about longer followup periods. This is a violation of a commitment from the study's protocol where it was stated that 6-month safety data will be reported (section 9.5.1). And the only reason I can think of why such a data was not reported is because it suggests the treatment is not as safe as it is claimed.

    2. On 2021-08-04 07:40:42, user Mike wrote:

      I'm curious about the HIV infected patients. There were exactly 100 in both vaccine and placebo group. If you look at the co-morbidity tables, no other co-morbidity is balanced in that way. I suppose it's possible that this occurred by chance but it's a very small one if so. Also, why did they include HIV+ patients in the study at all, if they exclude them from all reporting of deaths and adverse events? The HIV+ can lead long lives these days, it's not quite clear to me why they are being treated separately here, especially as it should hopefully be clear if they died of AIDS.

    3. On 2021-08-05 17:53:36, user pedro paulo castro wrote:

      It doesn't seem right that a much lower number of subjects from the vaccinated group came down with COVID 19, but the same number died as in the placebo group, which seems to indicate therefore a higher proportion of deaths among those who contracted COVID 19 AND were vaccinated. There is a conspicuous lack of what would have been a very useful breakdown of the instances of death, in such a way that we could see, for both groups, what number of deaths was among those who had COVID or those who didn't have COVID. This prevents us from seeing whether a subject had COVID, but had his or her death reported as, say, cardiac arrest, for example, which might change the context a bit.

    4. On 2021-10-03 02:28:34, user OBS wrote:

      How come this preprint (and the very recent publication of this in NEJM) both say 15 deaths vaccine vs. 14 deaths placebo, but the FDA briefing document for the booster shot (which summarizes the safety of the primary 2-dose series, see page 7), says 21 deaths vaccine vs. 17 deaths placebo?

      https://www.fda.gov/media/1...

      21 vs. 17 doesn't seem to be an update of the 15 vs. 14 result, since the booster FDA briefing document specifies March 13, 2021 as the data cutoff date corresponding to the 21 vs. 17 result, and that is the exact same cutoff date mentioned in this preprint / NEJM article. So why the discrepancy- what is going on here?

    1. On 2021-08-26 07:10:10, user William Brooks wrote:

      To help readers clearly see the difference in infectiousness before, during, and after the various interventions (i.e., the states of emergency, school closures, and GoTo travel campaign),the authors should add the start and end points of the interventions in Figure 2.

    1. On 2021-08-27 02:57:37, user Jason Eshleman wrote:

      The author's model assumes that the generation time for the variants is the same. This seems to run counter to observations of a markedly shorter incubation period with delta. This analysis absolutely needs to be rerun without that assumption. Are we seeing greater transmission between generations or are we seeing a fitness advantage due to a shorter generation time?

    1. On 2021-08-27 12:30:01, user Nikos Salingaros wrote:

      Hello everyone. Alarming results indeed. Are there any data on the visual complexity of the indoor environment in which these babies were raised? Our group is trying to relate low intelligence to the lack of mathematical stimulation coming from visual patterns. This is especially relevant since exposure to natural complexity such as outdoor plants is severely limited during the lockdown. The preferred architectural style today is minimalist: very different from the visual complexity of past generations, and this factor might contribute. How do we get some data on this possibility?

    1. On 2021-08-27 22:08:03, user evasmagacz wrote:

      To look at the data from a different perspective:

      In your first dataset:

      Model 1: n = 16000 <br /> In patients who were previously infected: <br /> There were 5 symptomatic re-infections per 10000;<br /> Less than one hospitalisation per 10000, and no deaths.

      In patients who were previously vaccinated, <br /> There were 124 symptomatic re-infections per 10000;<br /> 5 hospitalisations per 10000 and no deaths.

      In your second dataset:<br /> Model 2: n = 46000<br /> In patients who were previously infected: <br /> There were 15 symptomatic reinfections per 10000; <br /> Less than one hospitalisation per 10000, and no deaths.

      In patients who were previously vaccinated, <br /> There were 105 symptomatic reinfections per 10000 <br /> 5 hospitalisations per 10000 and no deaths.

      In your third dataset:<br /> Model 3: 14000<br /> In patients who were previously infected: <br /> There were 16 symptomatic reinfections per 10000 <br /> Less than one hospitalisation per 10000, and no deaths.

      In patients who were previously infected and then vaccinated, <br /> There were 11 symptomatic reinfections per 10000 <br /> No hospitalisations per 10000 and no deaths.

    2. On 2021-10-30 04:38:45, user Rn wrote:

      The conclusions of this study stand in stark contrast to a report published today by the US CDC. https://www.cdc.gov/mmwr/vo...

      Among COVID-19–like illness hospitalizations among adults aged >=18 years whose previous infection or vaccination occurred 90–179 days earlier, the adjusted odds of laboratory-confirmed COVID-19 among unvaccinated adults with previous SARS-CoV-2 infection were 5.49-fold higher than the odds among fully vaccinated recipients of an mRNA COVID-19 vaccine who had no previous documented infection (95% confidence interval = 2.75–10.99).

    1. On 2021-08-29 20:54:09, user peter_wark wrote:

      Thanks again Recovery trial.<br /> Participants admitted with COVID19; unable to maintain SpO2 <94% despite FiO2 0.4.<br /> Mean age 57yrs<br /> Primary outcome was intubation or mortality at d30.<br /> CPAP HR 0.72 (0.53-0.96) p=0.03<br /> HFO2 0.97 (0.73-1.23) p=0.85<br /> The number needed to treat for CPAP was 12 (95% CI, 7 to 105) and for HFNO was 151 (95% CI, number needed to treat 13 to number needed to harm 16).

    1. On 2021-08-04 07:26:14, user oikoslibre wrote:

      In the first chapter you talk about PCR.

      I would like your opinion on the following document

      https://www.fda.gov/media/1...

      When I read this document , it becomes clear that this test is of no use at all

      Positive results are indicative of active infection with SARS-CoV-2 but do not rule out bacterial infection or co-infection with other viruses. The agent detected may not be the definite cause of disease

      In this document I also read: Since no quantified virus isolates of the 2019-nCoV were available for CDC use at the time the test was developed and this study conducted, assays designed for detection of the 2019-nCoV RNA were tested with characterized stocks of in vitro transcribed full length RNA.

      Is it possible to write an article on this virus without the use of PCR data?

      Do you have the isolated virus?

    1. On 2021-08-05 18:41:36, user Ultrafiltered wrote:

      With the probability of a PCR match of 1 with any sample comparison to a reference given 8 billion genotypes against strands of 30 to 50 mRNA, as DNA is expressed in any and all cells, the study only shows how many in the population are expressing a gene similar to a COVID phenotype, thus why the CDC has pulled its support of the PCR tests and going back to the process of isolation and identifying cells discovered through patient exam, similar to current Influenza like analoques. The basis of this paper goes to show that if you're sick with disease, you are sick with the disease and shed components, just like any other virus. The idea this effect is novel in this paper is superceeded by years of virology and research.

    2. On 2021-09-16 07:33:29, user Chaos_14 wrote:

      This study doesn't mention how many vaccinated vs unvaccinated people were tested.

      "Notably, 68% of individuals infected despite vaccination tested positive with Ct <25, including at least 8 who were asymptomatic at the time of testing." (68% of what number?)

      Since we know immune response, even with vaccines, decreases with age, it would be helpful to know the ages of the people in both the vaccinated and unvaccinated groups.

      It would also be helpful to know the Ct in the samples of asymptomatic, <br /> unvaccinated people if there were any.

      While it's beneficial to know that it's possible for infected vaccinated people to carry a viral load similar to infected unvaccinated people, this study left me with a lot of unanswered questions.

    1. On 2021-08-06 23:22:56, user disqus_92pIDbtuHj wrote:

      Hey, where's the full description of method and limitations? I get that this was published in medRxiv, a free distribution server for unpublished preprints that haven't been peer reviewed. It even states preprints "should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information".

      This was a SMALL sample of 43 men... undergoing IVF and they served as their own self control. WHEN, was a sample after vaccination taken? WHEN was the baseline taken? HOW did they control for the effects of other variables... like the treatment recommendations these patients may have been following at the IVF clinic (especially since these were pulled Hospital IVF records)! They compared each man to his own baseline before and after vaccination, (14 men had male factor infertility, and 29 with normal spermogram results). Regardless all men were very likely receiving lifestyle, diet, or even medication recommendations! They also neglected to control season as a variable. Previous literature shows poorer sperm quality in Winter, and better quality in Spring. This design looked at two samples from each man somewhere between winter and spring. The same span of time for each man? No one knows!

    1. On 2021-08-07 16:14:30, user Dmitry Pruss wrote:

      Isn't it a time-of-testing confounding effect? In Israel, percent of positive tests increased from 0.1% in the beginning of the study period to 1.5% in its end, which would likely result in an artifactual increase of positive in those vaccinated (and tested) earlier...

    1. On 2021-08-08 19:23:45, user Sam Wheeler wrote:

      So against delta, 1 dose of The Moderna COVID-19 (mRNA-1273) vaccine seems much more efficient than 1 dose of Pfizer Biontech?<br /> And no data about how efficient is Moderna with 2 doses against delta?<br /> What do we know about Janssen = J&J? Janssen is very efficient if you take into account it is given as a single-dose, and one can boost it by taking a booster or primer with other covid vaccine.

    1. On 2021-08-09 15:03:31, user Disha Agrawal wrote:

      Figure 3b is surprising and difficult for me to understand. The Y-axis for all figure 3 results should be Geometric Mean of the ELISA tests, as per the text. Assuming that to be so, Figure 3b is Antibody to N protein, which should not be induced by Covishield. Yet most Covishield/Covishield samples seem positive, as shown, with no difference from Covaxin/Covaxin. A possibility I considered is that most people were already infected, but then the Covaxin/Covaxin group should have been strongly boosted. Clarification from authors or others who were able to figure it out is welcome.

    1. On 2021-12-01 22:44:50, user Tom wrote:

      The susceptibility of Chilrden was estimated by PCR-Testing alone and has a high variance in the 95-CI. I guess the numbers may be even lower.

    1. On 2021-09-14 21:28:12, user Alberto wrote:

      23 vaccinated individuals, samples collected 5.2 weeks (average) after the second dose of the vaccine. No information about age, health, etc... compared to 10 individuals infected one year prior to taking the blood samples and 7 infected less than 2 months prior to taking the blood samples. Again no information about age, health, etc...

      Conclusion: "Hence, immune responses after vaccination are stronger compared to those<br /> after naturally occurring infection, pointing out the need of the vaccine to overcome the pandemic".

      Isn't that conclusion going well over the possibilities of this study? When in real world studies with cohorts of > 25.000 individuals it has been proven that the immunity acquired from infection is vastly superior to that from vaccination, how should we take these results?

    1. On 2021-12-15 06:52:55, user MD PhD wrote:

      Although it's a small sample size still it would be worthwhile to know the antibody response to booster/third dose in 6 months vs 9 months group post-vaccination. Additionally whether these groups received first and second shots at 3-4 weeks or 7-8 weeks interval will offer pertinent information since this basic difference rendered more antibody response in the latter groups as per studies (the point being that boosters might turn out to an immediate requirement for the 3-4 weeks vaccination interval group while the 7-8 weeks interval group might potentially be able to put it off for a month or so in light of prior studies showing a robust antibody response with delayed vaccination)

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

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

      T95I is in this same amplicon.

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

    1. On 2021-09-16 13:35:24, user David Brown wrote:

      There is evidence that abdominal obesity in both humans and chickens is determined by the fatty acid profile of the diet; specifically, the linoleic acid content. Read pages 7-9 of this 2019 Master's Thesis. https://trace.tennessee.edu...<br /> For further comment regarding linoleic acid intake and vulnerability to COVID-19 complications, read these articles:<br /> https://www.medpagetoday.co...<br /> https://www.science.org/doi...

    1. On 2021-09-19 12:46:53, user daan joubert wrote:

      I rhink you are referring to the article entitled "Africa Dailye deaths.100k etc" showing the difference between the high incidence in the upper and lower parts of the continent compared to the equatorial region where Ivermectin is used against tropical parasites and there are few deaths. It seems to have been removed for some guessable reason.

    1. On 2021-09-22 01:46:06, user jhick059 wrote:

      Dear authors,

      I believe your denominators (15,997 Moderna doses and 16,382 Pfizer doses) are off by more than a factor of 10.

      Ottawa Public Health has 342,656 doses of Moderna and 485,178 doses of Pfizer between 2021-06-01 and 2021-07-31. Link: https://open.ottawa.ca/data...

      You also state (pg. 6/20) that your data suggest a tenfold higher incidence than other papers estimating an incidence of 1/100,000. A tenfold higher incidence than 1/100,000 is 1/10,000, which is closer to the value you would obtain with the adjusted denominator.

      Sincerely,<br /> Joseph Hickey

    2. On 2021-09-22 03:14:20, user Norsksoul wrote:

      It is a preprint article but they basically identified all vaccine recipients in Ottawa during the June 1 through July 31 study period. <br /> This was the denominator of the study group. <br /> Anyone from this study group that was admitted with Acute Myocarditis or Pericarditis within 1 month of a Moderna or Pfizer vaccine became the numerator. <br /> So 32 cases occurred in 32,379 vaccine recipients which comes out to a 1/1000 incidence. This study should be done in the 12-18 year old age range and the incidence would likely be even worse.<br /> But wait,....it gets even worse. <br /> That 1/1000 incidence is in a group of 32,000 men AND women. <br /> But out of 32 cases of myocarditis, 29 occurred in men. <br /> That’s 90%! <br /> They unfortunately don’t give the data on male/ female percentages in the study group denominator but if we assume a 50/50 split, then the male incidence is actually 29/16,189 or 1 in 558 males vaccinated. <br /> 1/558<br /> 1/558<br /> 1/558<br /> Let that sink in for a minute. <br /> This is reckless medical malpractice at its worst.

    1. On 2021-09-23 06:52:46, user White Rabbit wrote:

      There are several issues about the meta-analysis by Martinoli et al. for example they wrote they did a meta-regression in order to explain the the huge between-study heterogeneity affecting the results, but no meta-regression results appears anywhere. They observed a statistically significant publicaton bias ("We found an indication for publication bias (P=0.03)" ,page 10) a serious but unaddressed issue. Ther are also inconsistencies between the results and the conclusions, e.g. though they found that "Children and adults showed comparable SARS-CoV-2 positivity <br /> rates in most studies" (page 9)" the abstract reads "children are 43% less susceptible than adults".Furthermore in some tables and forest plots, they used as denominator the total of students and staff altogether instead of students only, to estimate the students incidence.

    1. On 2021-09-23 15:49:33, user kdrl nakle wrote:

      What is needed more is the distance between the shot and data collection. We need longer duration period for VE evaluation. Your time period is too short.

    1. On 2021-09-28 15:09:49, user Tomas Maximus wrote:

      Looks like the proportion of breakthroughs climbed dramatically as time went on, with breakthrough accounting for 17% of total new cases in July. Wonder what the August and September numbers showed.

    1. On 2021-09-29 04:15:27, user Nikki wrote:

      I work as an account Escalation Specialist/call center supervisor who takes over Escalated calls. I've never had issues with missing small details which are required to do my job. I caught covid in mid July, had a horrible experience with two weeks worth of severe vertigo, nausea, fever spikes, tons of phlegm, panic attacks. <br /> One month and a half after recovery, I've had 4 major fails which may ultimately end up costing me my job. <br /> My pcp, therapist, and boss appear to disregard this when I try to explain to them about the fogginess. <br /> As a very detail oriented person, I just don't miss those things.... never in my 15 years in callcenter experience.

    1. On 2021-10-02 14:59:26, user Alberto wrote:

      Thanks for the detailed report. I'd only like to ask about the last sentence included in the abstract: "The beneficial and protective effects of the COVID-19 vaccines far <br /> outweigh the low potential risk of neurologic and psychiatric reactions. Going through the paper I haven't seen anything that attempts to estimate these rinks vs. benefits in any way (let alone a systematic way, by age, risk of severe disease in case of COVID-19, etc...). It seems like a statement that's been added there arbitrarily and does not belong to a scientific paper that not actually evaluating any risks associated with the disease itself or the vaccine efficacy to prevent them.

    1. On 2021-10-03 07:19:18, user Ruth Berger wrote:

      That age and male sex are major risk factors is well known; mortality associations with pandemic wave should not be reported without factoring in varying levels of underdiagnosis (to my knowledge, it was larger in the first wave than the second) and age-specific vaccination rates.

    1. On 2021-10-04 06:54:30, user kdrl nakle wrote:

      Simple yet important result, meaning we should definitely know Cp (Ct) value after getting tested. The next thing would be to investigate transmissibility but that is obviously much harder research.

    1. On 2021-10-07 22:22:53, user Robyn Schofield wrote:

      "As the devices do not meet medical device electrical safety standards (EN60601) they were operated at a distance of >=1.5metres from any patient." Can the authors please clarify - what wavelength the UV was operating at, and whether this device has been tested for ozone production / loss rates. I assume that the EN60601 requires ozone production to be tested for? If ozone is being produced (or destroyed to odd oxygen) that this would need testing before deployment in a medical setting. Ozone, a respiratory irritant gas, will easily travel more than 1.5m (so distance should not be seen as useful in setting safety protocols for electronic air cleaning devices in a medical setting).

      Are hospital rooms with no ventilation in line with current infection prevention and control or hospital design / operational guidelines in the UK? In Australia this would be in breach of both our hospital design and operating guidelines which require a minimum of 6 ACH for all hospitals.

      The effectiveness of UV with air high flow rates has to be questioned (because the exposure time for bio-aerosols is short) - are the authors able to separate the effectiveness of the filtration over the UV features? Most literature on this point shows that in real-world operation the HEPA provides 99.97% of the removal of bio-aerosols from air and the advantage of UV is untested / unproven (this is particularly true at 1000m3/h flow rates this device is operating at). I assume this device will be noisy >65dB - can this please be specified.

    1. On 2021-10-11 18:40:32, user Andrew T Levin wrote:

      Comment #1: Research in Context

      1. Diamond Princess Cruise Ship. The manuscript makes no reference to any epidemiological analysis of this episode, which informed seminal assessments of the age-specific infection fatality rate (IFR) of COVID-19.[1-4] Nonetheless, that evidence is particularly relevant, because the cruise ship’s passengers included 1231 individuals ages 70+ who were not merely “community-dwelling” but healthy enough to embark on a multi-week grand tour of southeast Asia. Following extensive RT-PCR testing, 335 passengers ages 70+ were confirmed to have been infected with SARS-Cov-2, and 13 of those passengers died from COVID-19 – an IFR of about 4%. Moreover, the strong link to age is underscored by the even higher IFR of 8% for passengers ages 80+. Given the size of that sample (which meets the 1000+ threshold used here), this evidence should certainly be incorporated into this meta-analysis.

      2. Comprehensive Tracing Programs. The manuscript makes no reference to countries that succeeded in containing the first wave of the pandemic in spring 2020 through systematic tracing and testing of all contacts of infected individuals.[5] Such evidence is particularly relevant here, because the virus was contained within the “community-dwelling” populations of those locations and never spread to any elderly care facilities. For example, in the case of New Zealand, there were 256 infections and 19 deaths among adults ages 70+ -- an IFR of about 7%.

      3. Hospitalized Patients. The manuscript cites a single study (published in July 2020) that examined the association between comorbidities and mortality risk of COVID-19.[6] However, that study was not able to distinguish whether comorbidities were linked to greater prevalence (the probability of getting infected) or to a higher IFR (the risk of mortality conditional on infection). Unfortunately, the manuscript makes no reference to any subsequent studies on this issue. In particular, a large-scale study of U.K. BioBank participants found that measures of frailty were indeed associated with higher mortality rates in the overall panel but not linked to mortality within the subset of hospitalized COVID-19 patients.[7] In effect, the prevalence of COVID-19 was markedly higher among residents of U.K. nursing homes compared to individuals of similar age living in the community, but the IFR was not significantly different. Those findings directly contradict a key assertion made at the start of this manuscript.

      4. Prior Meta-Analysis of Community-Dwelling Populations. The introduction of this manuscript neglects to mention that an existing meta-analysis study (published in Nature in November 2020) was specifically focused on assessing IFRs excluding deaths in nursing homes.[8] That study estimated the link between age and IFR using seroprevalence and fatality data for adults less than 65 years old, and then showed that the model predictiions were consistent with data on fatalities among community-dwelling adults ages 65+. Moreover, that study used seroprevalence data adjusted for assay characteristics, and the results were obtained using a rigorous Bayesian statistical model that incorporated random variations in the time lags between infection, seropositivity, and fatal outcomes – a striking contrast to this manuscript, which uses rudimentary assumptions to address those issues.

      5. Other Meta-Analyses. The introduction of this manuscript briefly refers to two other meta-analysis studies of the link between age and IFR.[5, 9] However, the manuscript then asserts: “Importantly, the vast majority of seroprevalence studies include very few elderly people.” (p.5) That assertion is supported by a single citation to the SeroTracker database, which provides comprehensive coverage of all existing national, regional, and local seroprevalence studies across the globe.[10] However, this assertion is completely incorrect as a characterization of the preceding meta-analysis of age-specific IFRs. As indicated in Levin et al. (2020, figure 5), that meta-analysis study included seroprevalence data on older adults (including narrow brackets for ages 60-69, 65-74, 70-79, and 75-84 as well as open-ended brackets for ages 60+, 65+, 70+, 80+, and 85+) from nine national studies (Belgium, France, Hungary, Italy, Netherlands, Portugal, Spain, Sweden, and the U.K.) and eight regional locations (Ontario, Canada; Geneva, Switzerland; Connecticut, Indiana, Louisiana, Miami, Missouri, and San Francisco, USA).[5]

    1. On 2021-10-17 22:54:41, user Rob Reck wrote:

      If appears that there is no differentiation given to to the amount of time that passed since a subject contracted CoVid19. Waning immunity is an issue that has been studied. Certainly more study would be a good thing. But there is enough current data to know that it does happen. People who have had CoVid19 do get re-infected.

      Given the existence of even a small number of reinfections, the claim that a person who previously was infected with CoVid19 need not be vaccinated is not supported by this study.

    1. On 2022-10-24 11:51:28, user Indi Trehan wrote:

      This article has now been published after peer review: The Journal of Pediatrics 2022; 247: 147-149. doi: 10.1016/j.jpeds.2022.05.006.

    1. On 2020-04-06 19:55:46, user Sinai Immunol Review Project wrote:

      Clinical Characteristics of 2019 Novel Infected Coronavirus Pneumonia:A Systemic Review and Meta-analysis

      The authors performed a meta analysis of literature on clinical, laboratory and radiologic characteristics of patients presenting with pneumonia related to SARSCoV2 infection, published up to Feb 6 2020. They found that symptoms that were mostly consistent among studies were sore throat, headache, diarrhea and rhinorrhea. Fever, cough, malaise and muscle pain were highly variable across studies. Leukopenia (mostly lymphocytopenia) and increased white blood cells were highly variable across studies. They identified three most common patterns seen on CT scan, but there was high variability across studies. Consistently across the studies examined, the authors found that about 75% of patients need supplemental oxygen therapy, about 23% mechanical ventilation and about 5% extracorporeal membrane oxygenation (ECMO). The authors calculated a staggering pooled mortality incidence of 78% for these patients.

      Critical analysis:<br /> The authors mention that the total number of studies included in this meta analysis is nine, however they also mentioned that only three studies reported individual patient data. It is overall unclear how many patients in total were included in their analysis. This is mostly relevant as they reported an incredibly high mortality (78%) and mention an absolute number of deaths of 26 cases overall. It is not clear from their report how the mortality rate was calculated. <br /> The data is based on reports from China and mostly from the Wuhan area, which somewhat limits the overall generalizability and applicability of these results.

      Importance and implications of these findings in the context of the current epidemics:<br /> This meta analysis offers some important data for clinicians to refer to when dealing with patients with COVID-19 and specifically with pneumonia. It is very helpful to set expectations about the course of the disease.

    1. On 2023-12-12 14:56:15, user Tanmoy Sarkar Pias wrote:

      This paper has been accepted to an IEEE conference. A link (& DOI) to the IEEE Xplore will be added when this article is published. Please see the following copy right details of IEEE.

      2023 26th International Conference on Computer and Information Technology (ICCIT), 13-15 December, Cox’s Bazar, Bangladesh

      979-8-3503-5901-5/23/$31.00 ©2023 IEEE

    1. On 2023-12-19 12:39:03, user Christos Proukakis wrote:

      Response to: “Is Gauchian genotyping of GBA1 variants reliable?”

      Marco Toffoli1,2, Anthony HV Schapira1,2, Fritz J Sedlazeck2,3,4, Christos Proukakis1,2 *

      1. Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, UK
      2. Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
      3. Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
      4. Department of Molecular and Human Genetics, Baylor College of Medicine, TX, USA

      * To whom correspondence should be addressed: c.proukakis@ucl.ac.uk

      We recently described two methods for GBA1 analysis, which is hampered by the adjacent highly homologous pseudogene: Gauchian, a novel algorithm for analysis of short-read WGS, and targeted long-read sequencing 1. Tayebi et al have applied the former to WGS from 95 individuals, and compared it to Sanger sequencing 2. They report concordant genotypes in 85, while 11 had discrepant calls (we note that this leads to a total of 96). In addition, they report 28 false Gauchian calls in 1000 Genomes Project (1kGP) samples. Gauchian was developed because the homology of the GBA region requires a short read variant caller that does not rely solely on read alignments, and can identify specific variants known to be pathogenic. To understand the cause of these discrepancies, we reviewed their data, and conclude that they are mis-interpreting Gauchian results in 8 of the 11 discrepant samples, and incorrectly using Gauchian to analyze low-coverage 1kGP samples.

      Among the 11 (11.5%) samples with inconsistent calls with Sanger (Table 1), four (Pat_08, Pat_26, Pat_28 and Pat_58) were not called as the variants are not on Gauchian’s target list, which includes all ClinVar variants in December 2021. These variants, and any others, can be easily added (see Supplementary Information). Three other samples (Pat_75, Pat_76 and Pat_79) had low data quality resulting in large variation in sequencing depth across the genome, as shown by the median absolute deviation (MAD) of genome coverage: 0.269, 0.128 and 0.127 (three highest values among all samples). Gauchian recommends trusting calls in samples with MAD values <0.11, and produces a warning message if this is exceeded. In all three samples, the GBA1+GBAP1 copy number was a no-call (marked as “None” in the output file), indicating that Gauchian could not determine the copy number due to high coverage variation. Variants were not called because no further analysis was done beyond copy number calling. These should not be viewed as false negatives, as the warning message and the report of no-calls should prompt the user to obtain higher quality data or consider alternative sequencing. Among the remaining 4 samples with inconsistent results: Pat_03 had a Gauchian call of heterozygosity for p.Asn409Ser, while Sanger reports this as homozygous. Review of the IGV trace (Tayebi et al. Supp Figure 1) shows that at least 10 reads (around a fifth of the total) have the reference base, and therefore it is hard to conclude this is homozygous. Review of the Sanger trace (not provided) could determine whether there is a low peak representing the reference allele. We cannot provide a conclusion, and additional analysis is recommended. Mosaicism could be a plausible explanation, and this has been reported in GBA1 3,4, albeit not at this position. Pat_47 had a false negative p.Leu483Pro call. Pat_16 was indeed wrongly genotyped as homozygous for p.Asn409Ser, related to the adjacent c.1263del+RecTL deletion. Pat_92 had all expected variants called, but the heterozygous p.Asp448His was mis-genotyped as homozygous. In summary, there is one false negative and two wrongly genotyped variants (heterozygous variants called homozygous). Gauchian’s precision is therefore 98.9% (175 out of 177 calls are correct). Its allele-level recall/sensitivity is 99.4% after excluding alleles not on Gauchian’s target list, and samples which could not be analyzed due to high coverage variation. Alternatively, it can be calculated as 97.2% if only samples with high coverage variation are excluded, 96.2% if only alleles not on the target list are excluded, and 94.1% if all these samples are considered .

      Tayebi et al. concluded that Gauchian is not able to call recombinant variants without providing orthogonal evidence. In Pat_95, Pat_71 and Pat_16, they examined alignments in IGV and reported absence of supporting reads for Gauchian calls, but all recombinant alleles called by Gauchian were consistent with Sanger. This highlights that read mapping in this region is unreliable (variant supporting reads may align to the pseudogene), making interpretation of alignments in IGV very challenging. Gauchian is designed to untangle ambiguous alignments, locally phase haplotypes and make correct calls. Particularly, in Pat_95, they claimed that Gauchian called the expected RecNciI variant but got the mechanism of the recombinant allele wrong (gene conversion vs. gene fusion). This claim appears to be based on incorrect interpretation of IGV alignments, i.e. seeing 3’ UTR mismatches associated with GBAP1 does not necessarily indicate gene fusion, as they can be misalignments, or even part of the gene conversion. The RecNciI in Pat_95 is a gene conversion, as indicated by the normal copy number between GBAP1 and GBA1. Tayebi et al. claimed that this is a gene fusion without orthogonal evidence. In addition, they claimed that Gauchian misreported copy numbers in Pat_92, Pat_42 and Pat_72, again without orthogonal evidence. We validated Gauchian copy number gains by digital PCR in four cases 1. While particular recombinants could be prone to erroneous copy number calling, we do not know what “other techniques'' identified a different copy number in Pat_92. Orthogonal validation using digital PCR would resolve this. Finally, it is true that Gauchian does not have all possible recombinants on its target list, as it is designed to focus on recombinant variants in exons 9-11, because others are rare and detectable with standard callers.

      Tayebi et al. reported 4 samples where Gauchian missed variants in GRCh38 compared to GRCh37. Among these, two (Pat_35, Pat_75) were due to incorrect alignment settings that resulted in abnormally low mapping quality throughout the region. It is likely that ALT-aware alignment was on for all samples except these two. The remaining two (Pat_16, Pat_78) reflected an area of improvement for Gauchian to better call p.Asn409Ser, which is not a GBAP1-like variant, and can thus be called well by standard callers.

      We reported Gauchian calls of 1000 Genomes Project (1kGP) samples, validating some by targeted long reads 1. Gauchian called zero samples with biallelic variant in exons 9-11. However, Tayebi et al. reported a completely different set of Gauchian calls in the same samples (in their Table 4). This was caused by incorrect use of Gauchian on old low coverage WGS (median coverage <10X, https://ftp.1000genomes.ebi... "https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase3/data/)"), rather than 30X (https://ftp-trace.ncbi.nlm.... "https://ftp-trace.ncbi.nlm.nih.gov/1000genomes/ftp/1000G_2504_high_coverage/data/)").

      We are grateful to Tayebi et al for assessing Gauchian analysis of this very challenging gene 2, but note that most discrepancies were due to incorrect use or misinterpretation of results. “No call” samples due to inadequate data quality cannot be considered false negative, as no calls are provided, and warnings of noisy coverage are given where applicable. Samples with inadequate coverage should obviously be avoided, as Gauchian is expected to perform at coverage >30X. Gauchian does not call variants not on its target list, which can be expanded. We provide updated recall (99.4%) and precision (98.9%) values. We have not seen any evidence of the alleged inability of Gauchian to call recombinant variants, and would welcome orthogonal copy number assessment of discrepancies. We show that Gauchian can be used for GBA1 assessment when coverage and data quality are adequate. We do note a limitation in genotyping p.Asn409Ser, a non-recombinant variant that can be called by standard variant callers, which we recommend running together with Gauchian for a complete call set. Finally, in clinical cases where absolute certainty is required, Sanger sequencing could be considered, with targeted long read sequencing another option 1,5–7.

      Table 1. Details on the 11 samples where Gauchian and Sanger are inconsistent.

      Gauchian calls Sanger Assessment,Tayebi et al. Our assessmentSample Copy Number of GBA1 and GBAP1 GBAP1-like variant in exons 9-11 Other unphased variants Genotype Prediction

      Pat_08 4 None p.Asn409Ser p.Asn409Ser/p.Gln389Ter False Negative Missed variant is not on Gauchian's target list

      Pat_28 4 None p.Arg535His p.Arg535His/Cys381Tyr False Negative Missed variant is not on Gauchian's target list

      Pat_58 4 None p.Asn409Ser, p.Arg296Ter p.Asn409Ser, p.Arg296Ter, c.203delC False Negative Missed variant is not on Gauchian's target list

      Pat_26 4 None p.Asn409Ser p.Asn409Ser/p.Arg502Cys False Negative Missed variant is not on Gauchian's target list.

      Tayebi et al.’s Supplementary Figure 1 shows no variant at p.Arg502Cys (c.1504C>T), but a different variant at the neighboring position, p.Arg502His (c.1505G>A), which is not on Gauchian's target list.

      Pat_75 None (No Call) NA NA p.Arg502Cys/p.Arg159Trp Missed Copy number is a no-calldue to high variation in depth so no further variant calling was performed. Coverage MAD 0.269

      Pat_76 None (No Call) NA NA p.Asn409Ser/p.Asn409Ser Missed Copy number is a no-call due to high variation in depth so no further variant calling was performed. Coverage MAD 0.128

      Pat_79 None (No Call) NA NA p.Leu483Pro/p.Arg502Cys Missed Copy number is a no-call due to high variation in depth so no further variant calling was performed. Coverage MAD 0.127

      Pat_03 4 None p.Asn409Ser p.Asn409Ser/p.Asn409Ser False Negative Gauchian call is supported by reads, see Tayebi et al.’s Supplementary Figure 1.

      Pat_47 4 None p.Asn409Ser p.Asn409Ser/p.Leu483Pro False Negative True false negative

      Pat_16 3 c.1263del+RecTL/ p.Asn409Ser, p.Asn409Ser p.Asn409Ser, c.1263del+RecTL False Positive Heterozygous p.Asn409Ser misgenotyped as homozygous as Gauchian did not know the exact breakpoint of the c.1263del+RecTL deletion, which is very close to p.Asn409Ser.

      Pat_92 7 p.Asp448His/p.Leu483Pro,p.Asp448His p.Asp448His/ p.Leu483Pro+Rec7 False Negative There is no false negative. Rec7 is reflected in the copy number call (copy number gain). This GBAP1 duplication does not have any functional impact on GBA, so Gauchian does not report it as a GBA variant. Heterozygous p.Asp448His misgenotyped as homozygous.

      Acknowledgements

      We are grateful to Xiao Chen and Michael Eberle for helpful comments. They are former employees of Illumina and current employees of Pacific Biosciences. This research was funded in in part by Aligning Science Across Parkinson's [Grant numbers 000430 and 000420] through the Michael J. Fox Foundation for Parkinson's Research (MJFF).

      Competing interests

      FJS receives research support from PacBio and Oxford Nanopore. AHVS has received consulting fees from AvroBio, Auxilius, Coave, Destin, Enterin, Escape Bio, Genilac, and Sanofi and speaking fees from Prada Foundation.

      Supplementary Information

      Add new variants to Gauchian’s config file

      The four new variants can be added to Gauchian’s config file as follows.

      For hg38, add the following lines to gauchian/data/GBA_target_variant_38.txt

      chr1 155236304 A GBAP G c.1165C>T(p.Gln389Ter)<br /> chr1 155236327 T GBAP C c.1142G>A(p.Cys381Tyr)<br /> chr1 155239989 CGGGGGT GBAP CGGGGGGT c.203delC(p.Thr69fs)

      Add the following line to gauchian/data/GBA_target_variant_homology_region_38.txt<br /> chr1 155235195 T 155214568 C c.1505G>A(p.Arg502His)

      For GRCh37, add the following lines to gauchian/data/GBA_target_variant_37.txt<br /> 1 155206095 A GBAP G c.1165C>T(p.Gln389Ter)<br /> 1 155206118 T GBAP C c.1142G>A(p.Cys381Tyr)<br /> 1 155209780 CGGGGGT GBAP CGGGGGGT c.203delC(p.Thr69fs)

      Add the following line to gauchian/data/GBA_target_variant_homology_region_37.txt<br /> 1 155204986 T 155184359 C c.1505G>A(p.Arg502His)

      Bibliography

      1. Toffoli, M. et al. Comprehensive short and long read sequencing analysis for the Gaucher and Parkinson’s disease-associated GBA gene. Commun. Biol. 5, 670 (2022).

      2. Tayebi, N., Lichtenberg, J., Hertz, E. & Sidransky, E. Is Gauchian genotyping of GBA1 variants reliable? medRxiv (2023) doi:10.1101/2023.10.26.23297627.

      3. Filocamo, M. et al. Somatic mosaicism in a patient with Gaucher disease type 2: implication for genetic counseling and therapeutic decision-making. Blood Cells Mol. Dis. 26, 611–612 (2000).

      4. Hagege, E. et al. Type 2 Gaucher disease in an infant despite a normal maternal glucocerebrosidase gene. Am. J. Med. Genet. A 173, 3211–3215 (2017).

      5. Pachchek, S. et al. Accurate long-read sequencing identified GBA1 as major risk factor in the Luxembourgish Parkinson’s study. npj Parkinsons Disease 9, 156 (2023).

      6. Graham, O. E. E. et al. Nanopore sequencing of the glucocerebrosidase (GBA) gene in a New Zealand Parkinson’s disease cohort. Parkinsonism Relat. Disord. 70, 36–41 (2020).

      7. Leija-Salazar, M. et al. Evaluation of the detection of GBA missense mutations and other variants using the Oxford Nanopore MinION. Mol. Genet. Genomic Med. 7, e564 (2019)

    1. On 2024-04-11 17:53:00, user eysen wrote:

      JMIR Publications and PREreview are pleased to announce our next Preprint Live Review on Friday, April 19 at 9am PT / 12pm ET / 4pm UTC which discusses this preprint

      Register Now at https://docs.google.com/for...

      The Live Review is hosted by two facilitators from the PREreview team with experience in moderating virtual collaborative review discussions. They will guide participants through a constructive discussion of the following preprint: Assessing the Incidence of Postoperative Diabetes in Gastric Cancer Patients: A Comparative Study of Roux-en-Y Gastrectomy and Other Surgical Reconstruction Techniques - by Tatsuki Onishi

      Live Review Details:

      WHEN: Friday, April 19 at 9am PT / 12pm ET / 4pm UTC

      WHO: The Live Review is hosted by two facilitators from the PREreview team with experience in moderating virtual collaborative review discussions.

      WHAT: The participants will be guided through a constructive discussion of the following preprint: Assessing the Incidence of Postoperative Diabetes in Gastric Cancer Patients: A Comparative Study of Roux-en-Y Gastrectomy and Other Surgical Reconstruction Techniques - by Tatsuki Onishi medRxiv: https://doi.org/10.1101/202...

      A review will be then written and published on PREreview.org within the following 2 weeks. Participants will have the chance to help compose the final review and be recognized as reviewing authors.

      HOW: To participate, please complete the following registration form. You will receive an email from PREReview with a link to a Zoom room and a passcode.

      More information on JMIRx-Med, the first pubmed-indexed preprint overlay journal: https://xmed.jmir.org/annou...<br /> https://xmed.jmir.org/announcements/457

    1. On 2024-05-03 15:04:37, user Tamy wrote:

      I am happy to see someone taking an interest in this horrific condition. My daughter has suffered for over 9 years and the mental toll, as well as, the physical toll it has taken on her overall well being has been life changing! Thank you for giving these sufferers some validation!

    1. On 2025-05-01 12:48:20, user Ravi Sharma wrote:

      Ladies and Gentlemen,

      in loving memory of my late, beloved mother, a type 2 diabetic since my birth, I dedicate this research to harnessing the beneficial power of gen-AI to banish GDM from the face of the earth.

      I salute my industrious and loyal research group for their dedication in this journey.

      Until our work is published and linked to this DoI, kindly cite this preprint as ...

      Edmund Evangelistaa, Fathima Rubab, Syed M. Salman Bukhari, Amril Nazir and Ravishankar Sharma. (2025). "Developing a GraphRAG-enabled local-LLM for Gestational Diabetes Mellitus." medRxiv preprint doi: https://medrxiv.org/cgi/content/short/2025.04.28.25326568v1

      With kind regards and best wishes, Ravi

    1. On 2022-01-27 21:10:24, user Siguna Mueller, PhD, PhD wrote:

      I find it difficult to see how many individuals were in each group. I may, or may not, be able to guess some proportions. For instance, Fig. 4 suggests that there were not many in the booster group, if any at all. (This is because boosters obviously were only rolled out not too long ago). Is the small peak at approx. 35 days since injection attributable to the booster group? If so, this makes me wonder if they were sufficiently many to be statistically relevant. Again, I find it hard to infer exact numbers of participants in the different groups. This info would really be helpful. Thanks.

    2. On 2022-02-14 04:09:55, user RBNZ wrote:

      "The estimates are furthermore adjusted for vaccine status of the potential secondary case interacted with the household variant, and the vaccine status of the primary case. "

      There is no information included as to how vaccination status adjusts the odds ratio.

    1. On 2022-02-03 14:15:23, user Matt Thrun-Nowicki wrote:

      Given previous studies’ evidence of a poor association between RAT results and viral culturability based on # of days after symptom onset, you guys might wanna wait to publish this paper until after those viral cultures result.

      In addition, your explanation of why booster’d HCW had higher positive RAT’s is a little baffling. If your explanation was correct, wouldn’t you expect to see the percentage of positive RAT’s among booster’d HCWers drop over time, and those of unbooster’d go up? What about confounders (like demographics of the booster’d vs unbooster’d)?

    1. On 2025-09-07 20:13:12, user S S Young wrote:

      Milojevic et al. 2014 had access to all emergency room visits for all of England and Wales for the years 2003 to 2008, over 400,000 myocardial infarction (MI) events, and over 2 million CVD emergency hospital admissions. They found no effect of CO, NO2, Ozone, PM10, PM2.5, or SO2 on heart attacks, hospital admissions, or mortality, their Figures 1 and 2.

      Milojevic, A., Wilkinson, P., Armstrong, B., Bhaskaran, K., Smeeth, L., Hajat, S. 2014. Short-term effects of air pollution on a range of cardiovascular events in England and Wales: Case-crossover analysis of the MINAP database, hospital admissions and mortality. Heart (British Cardiac Society) 100, 14: 1093-98. https://doi.org/10.1136/heartjnl-2013-304963 .

    1. On 2020-04-19 16:51:41, user Sinai Immunol Review Project wrote:

      Neutralizing antibody responses to SARS-CoV-2 in a COVID-19 recovered patient cohort and their implications

      Fan Wu et al.; medRxiv 2020.03.30.20047365; doi:https://doi.org/10.1101/202...

      Keywords

      • Neutralizing antibodies<br /> • SARS-CoV-2<br /> • pseudotype neutralization assay

      Main findings

      In this study, plasma obtained from 175 convalescent patients with laboratory-confirmed mild COVID-19 was screened for SARS-CoV-2-specific neutralizing antibodies (nABs) by pseudotype-lentiviral-vector-based neutralization assay as well as for binding antibodies (Abs) against SARS-CoV-2 RBD, S1 and S2 proteins by ELISA. Kinetics of neutralizing and binding Ab titers were assessed during the acute and convalescent phase in the context of patient age as well as in relation to clinical markers of inflammation (CRP and lymphocyte count at the time of hospitalization). Across all age groups, SARS-CoV-2-specific nAbs titers were low within the first 10 days of symptom onset, peaked between days 10-15, and persisted for at least two weeks post discharge. In contrast to spike protein binding Abs, nAbs were not cross-reactive to SARS-CoV-1. Moreover, nAb titers moderately correlated with the amount of spike protein binding antibodies. Both neutralizing and binding Ab titers varied across patient subsets of all ages, but were significantly higher in middle-aged (40-59 yrs) and elderly (60-85) vs. younger patients (15-39 yrs). However, plasma nAb titers were found to be below detection level in 5.7% (10/175) of patients, i.e. a small number of patients recovered without developing a robust nAb response. Conversely, 1.14% (2/175) of patients had substantially higher titers than the rest. Notably, in addition to patient age, nAb titers correlated moderately with serum CRP levels but were inversely related to lymphocyte count on admission. In summary, the authors show that patients with clinically mild COVID-19 disease mount a strong humoral response against the SARS-CoV-2 spike protein. Compared to younger patients, middle-aged and elderly patients had both higher neutralizing and binding Ab titers, accompanied by increased CRP levels and lower lymphocyte counts. These patients are usually considered at higher risk of severe disease. Therefore, robust neutralizing and binding Ab responses may be particularly important for recovery in this patient subset. Conversely, patients who failed to produce high nAb/binding Ab titers against spike protein did not progress to severe disease, indicating that binding Abs against other viral epitopes as well as cellular immune responses are equally important.

      Limitations

      This study provides valuable information on the kinetics of spike protein-specific nAb as well as binding Ab titers in a cohort of convalescent mild COVID-19 patients of all ages. However, similar studies enrolling larger patient numbers, including those diagnosed with moderate and severe disease as well as survivors and non-survivors, especially in the elderly group (to rule out potential bias for more favorable outcome), are warranted for reliable assumptions on the potentially protective role of Abs and nAbs in COVID-19. Moreover, longitudinal observation beyond the acute and convalescent phase in addition to stringent clinical and immunological characterization is urgently needed. <br /> In their study, Wu et al. did not measure binding Abs against non-S viral proteins, which are also induced in COVID-19 and therefore could have added valuable diagnostic information with regard to patients who seemingly failed to mount both binding and neutralizing Ab responses against the SARS-CoV-2 spike protein. Likewise, while this study excluded cross-reactivity of nAbs against SARS-CoV-1, no other coronaviruses were tested. Of additional note, neutralizing activity of plasma Abs was only assessed by pseudotype neutralization assay, not against live SARS-CoV-2. Generally, while these are widely used and reproducible assays, in vitro neutralization of pseudotyped viruses does not necessarily translate to effective protection against the respective live virus in vivo (cf. review by Burton, D. Antibodies, viruses and vaccines. Nat Rev Immunol 2, 706–713 (2002)). Further studies are therefore needed to assess the specificity and neutralizing characteristics of these Abs to test whether they could be candidates for prophylactic and therapeutic interventions. In this context, setting arbitrary cut-off values (ID50<500 vs. a detection limit of ID50 < 40) and thus classifying up to 30% of patients in this study as “weak” responders does not take into account our currently limited knowledge regarding protective capacity of these nAbs and should therefore have been avoided by the authors.

      Significance

      This preprint is arguably the first report on neutralizing and binding Ab titers in a larger cohort of mild COVID-19 patients. Assessing Ab titers in these patients is not only important in order to confirm whether mild COVID-19 elicits robust nAb responses, but also adds further information regarding the use of plasma from mild disease patients for convalescent plasma therapy as well as vaccine design in general. Future studies will need to address now whether the nAb responses generated in mild disease will be protective or (functionally) different from nAbs generated in moderate and severe disease. The findings in this study are therefore of great relevance and should be further explored in ongoing research on potential coronavirus therapies and prevention strategies.

      This review was undertaken as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2025-11-30 23:44:45, user Cyril Burke wrote:

      [Note: This is the second of several rounds of review of an earlier version of our combined manuscript, aiming to reduce ‘racial’ disparity in kidney disease. The comments were kindly offered by nephrologists, through a medical journal, and we remain grateful to them for the time and care they gave to improve our manuscript.

      We removed identifying features and included our responses, at the end of this comment. The changing title and line numbers refer to earlier versions.]

      August 3, 2022<br /> Dear Dr. Burke III,

      REDACTED.

      Reviewer #1: Cyril O Burke III et al submit a revised version of their intriguing , unusual paper.

      Overall, the paper remains extremely lengthy (the total , including clean and track versions and reply to reviewers is close to 200 pages !!) , whereas it contains relatively little original data.

      The authors speculate and comment a lot (and most of these speculations/comments will hardly be understandable by the expected audience, primary care physicians), and this will in addition distract the reader from the main key message (which is right in the opinion of this reviewer (see first round of review) and warrants more attention and studies.

      The race part is irrelevant for the key point (race does not change over time, and thus is not relevant when looking at longitudinal serum creatinine or eGFR) and should be deleted in the opinion of this reviewer. In this respect, I completely agree with the comment of reviewer 2 in the first round.

      I can not resist quoting here the reply of the authors to reviewer 2. “This manuscript could be divided into three or four short papers, increasing the likelihood that any one of them would be read. However, different groups tend to read papers about screening for kidney impairment, racial disparities, cofactors in modeling physiologic parameters, or policy proposals to encourage best practices. Despite the appeal of perhaps three or four publications, we decided to tell a complete story in a single paper, but we are open to suggestions.”

      My reply to their reply: nobody would read the current paper , even partially. Shorten, shorten, shorten please and focus on the key message.

      Reviewer #2: Thank-you, once again, for the opportunity to review this lengthy “thesis-style” manuscript which discusses some important often over-looked topics. The under-use of serial creatinine measurements and over-reliance on often erroneous eGFR measurements is an important point which is easily missed by healthcare workers with potentially serious consequences. Likewise, the misuse of racial constructs in medicine (and elsewhere) is an important point.

      I am satisfied with this re-submission and the changes which have been made to the original manuscript.

      Minor points:<br /> 431: “creatinine inhibits several membrane transporters”. = Cimetidine

      502: “Because mGFRs have population variation as wide as sCr, with much greater physiologic variability compared to the relatively stable sCr and serum cystatin C”<br /> As mentioned previously the cited article compares the variability of sCr and cystatin C with CrCl, I agree with the authors that CrCl is a form of mGFR, however, probably one of the poorer forms and not what a reader will think of when mGFR is mentioned. In our current age of medicine when we talk about mGFR CrCl is seldom included, studies reviewing methods of mGFR will seldom include CrCl, however CrCl may be compared to one of the mGFR methods. Likewise, if a patient is sent for a mGFR, a CrCl will not be performed. In our current age of medicine mGFR refers to methods such as the clearance of iohexol, iothalamate, Cr-EDTA, inulin, DTPA, etc; the authors themselves mention this (line 539 – 540). I fully agree with the authors that mGFR is FAR from perfect and has many inaccuracies and imprecisions (which are often overlooked)- these are well published, some of which are cited in this manuscript. If the authors wish to use the current study as a source they should state the findings in a way that cannot be misinterpreted. For example: “CrCl has much greater physiologic variability than sCr and cystatin C …” – in this case the reader can determine for themselves whether they would use CrCl as a surrogate for mGFR. Alternatively, adjust the statement and use another source which has shown the variability that exists with what we currently refer to as mGFR method.

      670 – 719: As the authors specifically discuss age it would be prudent to briefly mention the short-comings, or considerations for interpretation, of serial creatinine measurements at a very young age which generally rise until late adolescence when steady muscle mass is achieved. Also note changes in creatinine and GFR from birth till 2 – 3 years.

      783 – 784: Consider re-wording the grammar makes this sentence difficult to read

      959 – 968: Note, editing has not been accepted (tracked changes still shown)

      1116 - 1121: “Using the opioid crisis as an example…. in, for example, the opioid crisis” – same sentence

      RESPONSE TO REVIEWERS:<br /> September 17, 2022<br /> Longitudinal creatinine, not ‘race’, signals pre-chronic kidney disease and decline in glomerular filtration rate

      We again greatly appreciate the reviewers for offering detailed comments and guidance, which we have endeavored to incorporate as best we could.

      Comments to the Author<br /> Reviewer #1: Cyril O Burke III et al submit a revised version of their intriguing, unusual paper.<br /> 1. Overall, the paper remains extremely lengthy (the total, including clean and track versions and reply to reviewers is close to 200 pages !!), whereas it contains relatively little original data.<br /> The authors speculate and comment a lot (and most of these speculations/comments will hardly be understandable by the expected audience, primary care physicians), and this will in addition distract the reader from the main key message (which is right in the opinion of this reviewer (see first round of review) and warrants more attention and studies.<br /> The race part is irrelevant for the key point (race does not change over time, and thus is not relevant when looking at longitudinal serum creatinine or eGFR) and should be deleted in the opinion of this reviewer. In this respect, I completely agree with the comment of reviewer 2 in the first round.<br /> I can not resist quoting here the reply of the authors to reviewer 2.<br /> "This manuscript could be divided into three or four short papers, increasing the likelihood that any one of them would be read. However, different groups tend to read papers about screening for kidney impairment, racial disparities, cofactors in modeling physiologic parameters, or policy proposals to encourage best practices. Despite the appeal of perhaps three or four publications, we decided to tell a complete story in a single paper, but we are open to suggestions."<br /> My reply to their reply: nobody would read the current paper, even partially. Shorten, shorten, shorten please, and focus on the key message.<br /> We fundamentally agree and have worked to shorten the text; to clarify our understanding that ‘race’ may change with time, location, and self-identification; and to add a Table of Contents to make the Parts more accessible to interested readers. We comment a lot because, in highly racialized societies, like the US [1,2], it can be difficult to see beyond ‘race’ without explicit speculation about other possible explanations for difference, which we understand, may or may not pan out under investigation. One hope is that all clinicians will pursue explanations other than ‘race’, but this seems unlikely. Busy medical researchers have little time to develop expertise outside their area of interest, which may explain why ‘Commentary’ and ‘Perspective’ articles have failed to inspire an ethical ban on the misuse of ‘race’ in medical research, journals, clinics, and elsewhere [3]. We do not know whether a suite of articles can meaningfully contribute to ending misuse of ‘race’, where so many scholarly articles have failed, but after perceiving little change over four decades, trying something completely different seemed (almost) rational.

      1. Nunez-Smith M, Curry LA, Bigby J, Berg D, Krumholz HM, Bradley EH. Impact of race on the professional lives of physicians of African descent. Ann Intern Med. 2007 Jan 2;146(1):45-51. doi: 10.7326/0003-4819-146-1-200701020-00008. PMID: 17200221.

      2. Betancourt JR, Reid AE. Black physicians' experience with race: should we be surprised? Ann Intern Med. 2007 Jan 2;146(1):68-9. doi: 10.7326/0003-4819-146-1-200701020-00013. PMID: 17200226.

      3. McFarling UL. Troubling podcast puts JAMA, the ‘voice of medicine,’ under fire for its mishandling of race. Stat News. 2021 April 6 [Cited 2022 August 31]. Available from: https://www.statnews.com/2021/04/06/podcast-puts-jama-under-fire-for-mishandling-of-race/ <br /> Reviewer #2: Thank-you, once again, for the opportunity to review this lengthy “thesis-style” manuscript which discusses some important often over-looked topics. The under-use of serial creatinine measurements and over-reliance on often erroneous eGFR measurements is an important point which is easily missed by healthcare workers with potentially serious consequences. Likewise, the misuse of racial constructs in medicine (and elsewhere) is an important point.<br /> Thank you for again giving time for helpful criticism and comments on our manuscript.

      A. I am satisfied with this re-submission and the changes which have been made to the original manuscript.<br /> Minor points:<br /> B. 431: “creatinine inhibits several membrane transporters”. = Cimetidine<br /> Corrected.

      C. 502: “Because mGFRs have population variation as wide as sCr, with much greater physiologic variability compared to the relatively stable sCr and serum cystatin C”<br /> As mentioned previously the cited article compares the variability of sCr and cystatin C with CrCl, I agree with the authors that CrCl is a form of mGFR, however, probably one of the poorer forms and not what a reader will think of when mGFR is mentioned. In our current age of medicine when we talk about mGFR CrCl is seldom included, studies reviewing methods of mGFR will seldom include CrCl, however CrCl may be compared to one of the mGFR methods. Likewise, if a patient is sent for a mGFR, a CrCl will not be performed. In our current age of medicine mGFR refers to methods such as the clearance of iohexol, iothalamate, Cr-EDTA, inulin, DTPA, etc; the authors themselves mention this (line 539 – 540). I fully agree with the authors that mGFR is FAR from perfect and has many inaccuracies and imprecisions (which are often overlooked)- these are well published, some of which are cited in this manuscript. If the authors wish to use the current study as a source they should state the findings in a way that cannot be misinterpreted. For example: “CrCl has much greater physiologic variability than sCr and cystatin C …” – in this case the reader can determine for themselves whether they would use CrCl as a surrogate for mGFR. Alternatively, adjust the statement and use another source which has shown the variability that exists with what we currently refer to as mGFR method.<br /> We appreciate this comment and have both added another reference and added to the text an argument for reconsidering creatinine clearance. Many hospitals and some countries lack the resources for advanced mGFR filtration markers, which are only used for research or for screening related to kidney transplants. However, most laboratories have the tools for ‘quick-creatinine clearance’ (quick-CrCl), which may be an acceptable alternative to the classic mGFRs. If confirmed, a simple and affordable quick-CrCl might allow hospitals and laboratories worldwide an alternative measurement requiring fewer assumptions for another aspect of glomerular filtration.

      D. 670 – 719: As the authors specifically discuss age it would be prudent to briefly mention the short-comings, or considerations for interpretation, of serial creatinine measurements at a very young age which generally rise until late adolescence when steady muscle mass is achieved. Also note changes in creatinine and GFR from birth till 2 – 3 years.<br /> We have added a brief discussion of the diagnosis of CKD in infants, children, and adolescents.

      E. 783 – 784: Consider re-wording, the grammar makes this sentence difficult to read<br /> Done.

      F. 959 – 968: Note, editing has not been accepted (tracked changes still shown).<br /> Done.

      G. 1116 - 1121: “Using the opioid crisis as an example…. in, for example, the opioid crisis” – same sentence.<br /> Rewritten.

      We thank you.

    1. On 2022-03-01 05:15:31, user Nun Daled Yud wrote:

      clearly serial daily or twice daily testing is needed for patients who would benefit from the early antiviral treatments particularly aged care facilities .

    1. On 2022-03-09 02:39:17, user Peter J. Yim wrote:

      Vaccine efficacy based on vaccination registries is dependent on the completeness of the registries. Any missing or improperly registered data contributes to misclassification bias: https://drive.google.com/fi...<br /> This study relies on the Citywide Immunization Registry (CIR) and the NYS Immunization Information System (NYSIIS). However, no evidence is presented for the accuracy of those registries. As such, the VE estimates from this study should be regarded as uncertain.

    2. On 2022-05-05 12:39:51, user Robert Clark wrote:

      The data shows efficacy against infection becomes NEGATIVE after one month. Imperative to found out if at longer times this also happens for hosp./deaths. Review the data to found out.

      Robert Clark

    1. On 2022-03-23 02:12:03, user Guest wrote:

      Hello authors,<br /> Thank you for submitting a preprint of this interesting study on the virome to a public domain. I have a few questions regarding your methods and materials.<br /> First, the detailed description of sample collection was great, but I could not find any internal standards for the PCR steps, DNA extraction, or isolation of VLP. These might have been stated, somewhere else perhaps, but I could not identify them. However, for sample collection, how did you determine the location and type of wounds that would be tested? Was there a specific location or depth for chosen wounds or just all types stated that were within the frames of the criteria?<br /> Secondly, the methods for sample processing and DNA extraction are excellent, but I cannot seem to find any information regarding the primers used or the number of cycles performed while analyzing 16S rRNA. I could not find the total number of sequences obtained per sample, however, the quality reading for the viral reads was in-depth and well covered. I did not find any profile or 16S normalization or a total quantification of bacterial or bacterial numbers (like qPCR).<br /> Thirdly, I did not find anything about OTU abundance corrected for variance in copy numbers or variance in genome size. I also could not find any method details regarding coverage of communities measured or if there was any comparison to the dominate to rare. One last question, what do you define as ‘deep sequencing’ regarding this study?<br /> Overall, I found this article very interesting and a good read. Thank you for providing such excellent work with the virome. I have not seen many studies regarding the effects of the virome on human healing, host interactions, or composition until recent years, but this article provides a great starting point for these types of studies.

      SHSU5394

    1. On 2022-04-07 15:07:03, user Addi Romero wrote:

      A revised, updated version has been published as a correspondence in The Lancet Infectious Diseases. A link will be forthcoming. Meanwhile, feel free to have a look at the In Press, Corrected Proof: <br /> https://www.sciencedirect.c...

      Dynamics of humoral and T-cell immunity after three BNT162b2 vaccinations in adults older than 80 years

    1. On 2022-04-29 17:03:47, user Madhava Setty, MD wrote:

      Very interesting study. From where did the data on viral copies come from? Also, the odds of seroconversion in placebo vs treatment, stated as 13.67 at a given viral copy level, doesn't seem to be reflected in the corresponding plot (B).

    1. On 2022-05-21 01:10:31, user Fritz Stumpges wrote:

      You need to provide ground level readings for this test, for your group (1) without masks. Without this base, we don't know if your methods are just producing extremely high readings across the board!

    1. On 2020-05-20 00:33:44, user SizzMo wrote:

      It appears that the methods of administration of hydroxychloroquine were doomed to fail before even being undertaken. A review of the full study reveals NO mention of zinc, and suggests that hydroxychloroquine was administered alone or sometimes in tandem with azithromycin, and primarily to hospitalized patients in very late stages of illness. The omission of zinc and administration only in late stages of disease defeat the mechanism of action by which the hydroxychloroquine protocol works

      The primary mechanism of action in the hydroxychloroquine+zinc+azithromycin protocol uses hydroxychloroquine primarily as an ionophore for zinc, which then inhibits viral replication in the cell cytoplasm. Zinc is an essential component of this protocol, and omitting zinc appears to be a fatal flaw in all of the reviewed studies and case reports in this analysis. Furthermore, this paper repeatedly refers to hydroxychloroquine being administered to hospitalized patients. The mechanism of action is the inhibition of viral replication, which reduces viral load at early stages of disease. Giving this protocol in late stages of disease when viral load is already heavy and patients are already severely ill defeats the purpose of the protocol and practically guarantees that it will not be effective. The methods reviewed in this study overlook what is known about both the mechanism of action of viral inibitors, and the synergistic function of hydroxychloroquine and zinc in viral RNA replication, making it appear that these "studies" were designed to fail.

      Clinicians employing the complete hydroxychloroquine+zinc+azithromycin protocol at early stages of disease (mild to moderate illness) are universally reporting high levels of efficacy. <br /> Additionally, researchers in an NYU Langone retrospective analysis of more than 900 patients with mild-to-moderate illness who received the protocol with or without zinc also reported significant improvements in patients who received zinc. The NYU Langone study is currently undergoing peer review, and is available at this link: https://www.medrxiv.org/con...

    2. On 2020-05-23 22:06:14, user CKComments wrote:

      The authors dismiss the finding regarding the improvement in lung health in their summary. It's messed up lungs that kill patients, so it seems worth emphasizing.

    1. On 2022-07-18 12:29:27, user Loretta Lorenz wrote:

      Quite likely many person are vaccinated and infected in various sequences. My question is, if the SARS-CoV 2 Spike protein measurement differentiated beetween spike proteins originating from a vaccine against COVID-19 and the different Spike Proteins of the various SARS-CoV-2 mutations.

    1. On 2022-07-20 16:59:17, user Tania Watts wrote:

      The authors may want to note similar findings in our paper, Dayam et al. Accelerated waning of immunity to SARS-CoV-2 mRNA vaccines in patients with immune-mediated inflammatory diseases, JCI Insight, 10.1172/jci.insight.159721 April 2022. We show anti-TNF treated patients have lower Ab responses, no neutralization of Omicron and enhanced waning of T and Ab responses to SARS-CoV-2 mRNA vaccines after 2 doses.

    1. On 2022-07-25 16:31:06, user Dr. D. Miyazawa MD wrote:

      Please also refer to previous studies.

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

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

    1. On 2022-08-04 17:25:32, user Paul Hunter wrote:

      Did you include date or week number in your model? During the study period there was a dramatic shift in the proportion of tests positive in Portugal from about 1 in 4.5 to 1 in 2 and that could explain your findings of a 3 x greater risk of hospitalisation associated with BA.5 infection irrespective of the actual risk . If you did not include week number then I think your conclusions are probably flawed.

    1. On 2022-10-05 13:49:05, user Merja Rantala wrote:

      Congrats for this preprint, it is an important summary what we know about protection of hybrid immunity and prior infection against cov19. However, I think that references and claims in the discussion should be checked. There was a sentence on page 13, first paragraph, claiming that covid survivors would have higher risk for dementia in addition to some other conditions. The reference cited was 36, which is not at all about risks for diseases after covid, but the other way around: risk factors for a severe covid outcome. So the ref need to be replaced. Moreover, we really don''t know at this stage whether risk for dementia is increased after covid or not, although has been under heavy speculation.

    1. On 2020-05-26 09:28:09, user David Sbabo wrote:

      5 counfounding factors with a p-value under 0.05, all in the same direction "higher chance of mortality for the no zinc group".

    1. On 2020-05-26 17:03:03, user Sinai Immunol Review Project wrote:

      The main finding of the article: <br /> Recent studies have diverged as to weather conditions are allied or not with the spreading of Covid-19. Through random-effects meta-regression analysis, this work aimed was to determine if elements linked to meteorology can influence SARS-CoV-2 incidence and the speed of its propagation. The number of Covid-19 patients and meteorological conditions at each Japanese prefectural capital city from January to April 2020 were collected. <br /> The results demonstrated a negative association between Covid-19 incidence and monthly mean air temperature (C) (coefficient -0.351), sea level air pressure (hPa) (coefficient -0.001) and the monthly mean daily maximum UV index (UV) (coefficient -0.001).

      Critical analysis of the study: <br /> The manuscript would benefit from a more thorough introduction and discussion of the results in the context of previous studies. The authors could explore more the results of the supplementary table 1 (wind speed, relative humidity and sunshine). The figure caption should be better detailed, explaining the characteristics of each graph.

      The importance and implications for the current epidemics: <br /> The transmission dynamics of SARS-CoV-2 depends on different factors, such as population density, demographic and clinical characteristics of the population, hygiene, local ventilation, etc., and the seasonality of SARS-CoV-2 is not yet known.<br /> The data of this manuscript suggest that higher air temperature, air pressure, and ultraviolet are associated with a lower incidence of Covid-19. Certainly, this study is a step in identifying which environmental factors can favor viral transmission.

      Reviewed by Bruna Gazzi de Lima Seolin.

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

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

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

    1. On 2020-05-28 12:04:39, user Mike Nova wrote:

      M.N.: Good study. It would be good to trace also the correlations with 1) Degree of Rat Infestations and 2) Centralised air conditioning and high power flush public toilets, producing the infectious aerosoles in these places.

    1. On 2020-05-28 16:48:14, user Megan Toohey wrote:

      So I had an antibody test that came back negative but I did have trace amounts apparently. The range was 1.4 and my result was 0.2. I did get sick for a week with severe migraine, dizzy, light headed, nausea, fever runny, nose (off and on but not bad) not really congested, no sob, or cough. Got tested twice for covid which came back negative each time. I work in a hospital so i am around covid a lot. I'm just looking for some insight on that 0.2 result. And if they mostly doing detected/not detected type testing doesn't that technically mean if its my system its been detected? I'm not a scientist, doctor, or nurse so I apologize if my question is dumb.

    1. On 2020-05-28 20:40:28, user Esmeralda R. wrote:

      Once accepted, this paper will be very important. <br /> This is a data that still in need in the community. Diabetes has been associated in many studies, but this work with 18.5K patient, from which 3.7K diabetic patients was/is in need. <br /> Real Gramas

    1. On 2020-05-29 03:44:38, user TE de la Belle wrote:

      It seems to me that there is no actual evidence that Covid-19 was ever more prevalent in the elderly than in any other age group. When testing subjects are chosen by self-selection, surely it is those suffering from the most severe symptoms who will be most likely to self-select and be tested. It is the elderly who are more likely to develop more severe symptoms to this disease. So, it is the elderly with Covid-19, suffering from symptoms, that were being tested early on, more frequently than younger people, who were more likely to have mild or no symptoms. As testing has become more prevalent and contact tracing has begun, we are testing more people with mild or no symptoms. So more young people appear in the statistics. Surely that is the most likely explanation for the shift in frequency between age groups.

    1. On 2020-05-29 06:53:23, user Chris Valle-Riestra wrote:

      This is a great contribution to our knowledge of the epidemic. It's not an ideal way of determining the IFR, obviously, and the underlying serological studies had their shortcomings, but it's a well-reasoned effort to draw conclusions based upon the best available data. From what I've been able to learn, previous highly-publicized estimates of IFR by public health authorities have mostly been based on very thin data or been no better than educated guesses.

      Critiques just point up the great need for large scale rigorously-designed programs to gather far more data empirically. If that data leads to considerably different conclusions, so be it, but right now we don't have it.

    2. On 2020-05-21 23:33:25, user Jack A Syage wrote:

      Very interesting analysis, but I have a counter argument to this. Most of these studies were conducted before the death rate peak. Deaths represent infections from about 2.5 weeks before whereas antibody measurements are current. So cases have grown by multiples by then. As a check I see the following trend in Table 3: the earliest dates show the lowest IFR's (since growing cases run way ahead of deaths) and latest dates show the highest IFR's (as cases are subsiding and catching up to deaths). So I plotted this and there is a distinct upward dependence for IFR vs. date with a Pearson coeff of 0.61 (pretty strong) and a 2-tailed, paired t-value of a staggering p = 0.00003.

      I suspect continued antibody tests for populations well past the death rate peak will start to converge on a higher value of IFR, e.g., about 1%.

      I have been doing modeling and interested in views: please check out:

      https://www.medrxiv.org/con...

      and

      syage-covid19-assessment.com

      @jacksyage<br /> https://twitter.com/jacksyage<br /> https://twitter.com/medrxiv...

    1. On 2020-05-29 18:32:49, user Sinai Immunol Review Project wrote:

      Main Findings<br /> The authors analyzed and compared the stability of viable SARS-COV-2 and SARS-CoV-1 inoculums in five environmental conditions (aerosol, copper, cardboard, steel, and plastic) by using Bayesian regression model. It was reported that SARS-COV-2 was still detected in aerosols at 3 hours, with an exponential reduction in infectious titer that was similarly observed for SARS-CoV-1. The study also concluded that both SARS-COV-2 and SARS-CoV-1 are more stable on stainless steel and plastic than cardboard and copper. Viable SARS-CoV-2 was detected up to 72 hours on stainless steel and plastic. On copper and cardboard, SARS-COV-2 was viable up to 4 hours and 24 hours, respectively, compared to SARS-CoV-1 which could be detected up to 8 hours on both material types. The half-lives between both viruses are similar, except for on cardboard.

      Limitation of the study<br /> The strain used in the study was SARS-COV-2 nCoV-WA1-2020 (MN985325.1) from the first case of 2019 novel coronavirus in the US. However, mutation throughout the course of the pandemic is inevitable and may cause unpredictable consequences on its transmissibility and disease severity. Thus, follow-up on samples from various patients in different geographic and temporal time points should be conducted.

      Significance<br /> The results support that modes of SARS-COV-2 transmission can be attributed to both aerosol and fomites, due to extended viability for hours in aerosol and up to 72 hours on stainless steel surfaces. The types of plastic, cardboard, copper, and stainless materials were selected to reflect typical hospital and household situations. It is important to compare with the SARS-CoV-1 as similarities between the two suggests methods of mitigating the pandemic by abrogating transmission both in the community and hospital.

      Review by Joan Shang as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of medicine, Mount Sinai.

    1. On 2020-05-30 02:04:01, user jeff wrote:

      Has anyone correlated the asymptomatic people to those on a low dose aspirin regiment? Are these people who have contracted and recuperated on blood thinners and low dose aspirin? Is this virus really a virus and not a bacterium? These autopsies site thrombosis! Is anyone looking into this any further?

    1. On 2020-05-30 09:02:50, user Alberto 97 wrote:

      These data should be completed and submitted to a peer reviewed journal in the field, otherwise results reported in the Table cannot be trusted as experimentally sound, even without a thorough description of the methods used in the paper. Did you address the hypothesis to expand your evidence to be reported in a full publication in a specialized journal?

      Prof A. Manzini (Roma III)

    1. On 2020-06-01 12:41:21, user Ron Conte wrote:

      SARS-CoV-1 (causes SARS) is more similar to SARS-CoV-2 (causes Covid-19) than these cold coronaviruses used in the study. SARS antibodies last 2 to 3 years ("Duration of Antibody Responses after Severe Acute<br /> Respiratory Syndrome", Emerging Infections Diseases, 13:10, 2007), and "Memory T cell responses targeting the SARS coronavirus persist up to 11 years post-infection" (dx.doi.org/10.1016/j.vaccin... "dx.doi.org/10.1016/j.vaccine.2016.02.063)").

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

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

    1. On 2020-06-04 15:25:54, user Andy Loveman wrote:

      what other factors were considered: prevalence of O-type, A-type in the population at large; and underlying health factors compared in both groups?

    2. On 2020-06-08 16:44:40, user Georg Mumelter wrote:

      Thank you! Would it be possible and interesting to further analyze the risk difference by patient age and maybe gender - is the difference especially prevalent in younger or older age, male female? Should be a farily quick and easy analysis (cluster or regression) and plot.

    3. On 2020-06-12 19:34:13, user Amr Sawalha, MD wrote:

      Nice work. The lack of association in the HLA region is very interesting given the perceived exaggerated immune-mediated response in patients with severe COVID-19. Genetic studies looking at patients with confirmed cytokine storm will be of interest in this regard, and of course a closer look at the epigenetics of immune-response genes will be of interest.

    1. On 2020-06-05 10:23:43, user Alberto M. Borobia wrote:

      This manuscript has been published in "Journal of Clinical Medicine" https://www.mdpi.com/2077-0...

      Borobia, A.M.; Carcas, A.J.; Arnalich, F.; Álvarez-Sala, R.; Monserrat-Villatoro, J.; Quintana, M.; Figueira, J.C.; Torres Santos-Olmo, R.M.; García-Rodríguez, J.; Martín-Vega, A.; Buño, A.; Ramírez, E.; Martínez-Alés, G.; García-Arenzana, N.; Núñez, M.C.; Martí-de-Gracia, M.; Moreno Ramos, F.; Reinoso-Barbero, F.; Martin-Quiros, A.; Rivera Núñez, A.; Mingorance, J.; Carpio Segura, C.J.; Prieto Arribas, D.; Rey Cuevas, E.; Prados Sánchez, C.; Rios, J.J.; Hernán, M.A.; Frías, J.; Arribas, J.R.; on behalf of the COVID@HULP Working Group. A Cohort of Patients with COVID-19 in a Major Teaching Hospital in Europe. J. Clin. Med. 2020, 9, 1733.

    1. On 2020-06-05 23:05:25, user Amy E. Herr wrote:

      *WARNING to READER*: Essential technical information is missing from this PDF which prohibits accurate interpretation and repeatability of the results.There is (1) insufficient evidence substantiating successful 'decontamination', (2) insufficient information on UV-C source and detector, and (3) insufficient information on UV-C dosing. We urge the authors to add these critical details which are represent the bare-minimum for accurate reporting and reproducibility, as further described below:

      1. Claims of “decontamination” do not align with FDA EUA guidance/terminology. FDA guidance on requesting EUAs for respirator decontamination systems define “decontamination” and “bioburden reduction” in terms of specific log-reduction values for specific classes of microorganisms. Because 6-log or 3-log reduction was not always observed or possible to be measured in this study, and no non-enveloped viruses or bacteria were tested, the results do not fall within the FDA definitions for decontamination and bioburden reduction. We suggest adjusting terminology to align with FDA EUA guidance.

      2. Critical information on UV-C source and detector is not provided. Make, model, wavelength emission spectrum, type of UV-C source (e.g., low pressure mercury lamp, LED, etc.), and dimensions of any UV-C bulbs should be reported for the source; make, model, and wavelengths detected are key parameters to report for any radiometer/dosimeter. Because UV-C decontamination equipment is not standardized and measured UV-C dose depends critically on the details of the UV-C source and detector (e.g., whether emitted and detected wavelengths match), reporting these details is critical for accuracy and reproducibility.

      3. Missing details on UV-C dose distribution across the N95. For example, where was the N95 placed within the UVGI device, relative to the UV-C source? Was the ~10% dose permeation observed across all locations on all N95 models? Providing details on characterization of UV-C dose distribution across the N95 is requisite for readers to understand whether a ‘worst-case’ scenario is being modeled.

      We thank the authors for their important research efforts on N95 decontamination during this COVID-19 pandemic & look forward to an updated/revised PDF posting.

    1. On 2020-06-06 13:55:03, user Jürgen Heuser wrote:

      Thx very much for this very helpful work!!

      I'm afraid I do not understand the term <br /> "Comorbidities marked by * are defined by hospital discharge diagnoses in combination with drug redemptions (i.e. filled prescription within 6 months prior to the test date. Of note, there is a lag of 15 days on prescription data)" <br /> when applied to diagnoses like alcohol abuse, overweight or dementia. What kind of medication prescribed would qualify a patient into those categories?

      Best <br /> Jürgen Heuser

    1. On 2020-06-06 15:50:28, user Alberto M. Borobia wrote:

      Dear Authors, congratulations for your publication. Your reference Borobia et al. is now published in JCM.

      Borobia, A.M.; Carcas, A.J.; Arnalich, F.; Álvarez-Sala, R.; Monserrat-Villatoro, J.; Quintana, M.; Figueira, J.C.; Torres Santos-Olmo, R.M.; García-Rodríguez, J.; Martín-Vega, A.; Buño, A.; Ramírez, E.; Martínez-Alés, G.; García-Arenzana, N.; Núñez, M.C.; Martí-de-Gracia, M.; Moreno Ramos, F.; Reinoso-Barbero, F.; Martin-Quiros, A.; Rivera Núñez, A.; Mingorance, J.; Carpio Segura, C.J.; Prieto Arribas, D.; Rey Cuevas, E.; Prados Sánchez, C.; Rios, J.J.; Hernán, M.A.; Frías, J.; Arribas, J.R.; on behalf of the COVID@HULP Working Group. A Cohort of Patients with COVID-19 in a Major Teaching Hospital in Europe. J. Clin. Med. 2020, 9, 1733.

      Best regards,

    1. On 2020-06-08 17:06:04, user Johann Holzmann wrote:

      Dear authors,<br /> Thank you for making the pre-print accessible, I read it with great interest.

      How do your findings regarding the presumptive false-positive rate of SARS CoV2 detection using RT-PCR relate with the very low RT-PCR positive rate as currently seen in many countries or regions with a very low prevalence of SARS CoV2?<br /> For example Australia runs between 30.000 to 35.000 PCR test daily for the last month and only gets around 10 positive assays per day. <br /> Other examples with a ratio of PCR assays per day to posiive assays of around 600-2000:1 are Iceland, Greece, Croatia, Thailand and certain parts of Germany (eg Sachsen-Anhalt, Mecklenburg Vorpommern) or Austria (eg Tirol).<br /> Wouldn't these data indicate a much lower false-positive rate than the one suggested in your manuscript?<br /> Thank you again for making your research accessible<br /> kind regards

    1. On 2020-06-30 12:50:48, user Dude Dujmovic wrote:

      "Secondary cases"? I think you need to precisely define what do you mean by that. The whole paper is extremely vague in what the numbers are about.

    1. On 2020-06-09 20:59:34, user Brenner Silva wrote:

      Comment:<br /> Well explained and valid analysis.<br /> Suggestions: <br /> line 203. please indicate the formula variables in the text.<br /> Possible corrections:<br /> line 147. please name the app as in "we used the COVID-19 app to"<br /> line 210. "where each is"<br /> line 213. "is defined by the"<br /> line 325. "and future work to better understand"

    1. On 2020-06-10 01:57:51, user Sinai Immunol Review Project wrote:

      Main findings<br /> To improve understanding of the cellular changes in the T and B cell compartments of COVID-19 patients, both during and after disease, Fan et al. analyzed lymphocytes isolated from the PBMCs of 4 severe COVID-19 patients (n=4), 6 COVID-19 recovered patients (n=6), and 3 healthy controls (n=3). Of note, 3 recovered patients' samples were collected 7 days after a negative SARS-CoV-2 test (recovery-early stage; RE) and absence of clinical symptoms, whereas the other 3 samples were collected 20 days after these criteria (recovery-late stage; RL). The authors used single-cell RNA sequencing and single-cell V(D)J sequencing to perform their analysis.

      The authors identified 9 classes of T cells, which included 4 sub-classes of CD4+ T cells and 5 sub-classes of CD8+ T cells. Not surprisingly, across severe COVID-19 patients, the proportion of T cells was reduced, compared to healthy controls. However, differential gene expression analysis revealed that T cells from severe COVID-19 patients highly expressed inflammatory markers, including IFNG and GZMA. Interestingly, when compared to these patients with active disease, RE samples showed significant enrichment of ICOS+ TH2-like follicular helper T cells (TFH), whereas RL samples showed a reportedly significant enrichment of a cluster identified as TH1 cells, though this result should be revisited for review (See biological limitations). These cell types were, in fact, reduced in severe COVID-19 patients. Generally, these T cells from recovering patients continued to indicate persistent activation and counter-regulation, based on expression of TCR activation-associated genes, including RNF125 and PELI1. Subsequent trajectory analyses of transcriptional dynamics indicated transition of effector CD8+ T cells to central memory T cells in RL patients. Ligand-receptor analysis revealed potential interactions between TH1 cells and CD14+ monocytes in severe COVID-19 patients. Finally, TCR sequencing identified several VJ combinations in high frequencies in severe COVID-19 patients, but not others.

      Within the B cell compartments across patients, the authors identified 9 clusters of naive B cells, 2 clusters of memory B cells, 2 clusters of plasma B cells, and a cluster of plasmablasts. Of these clusters, one, in particular, expressed genes characteristic of FCRL5+ atypical memory B cells, which have been described to be induced by viral infections. Interestingly, ligand-receptor analyses of the clusters in each group of patient samples identified different degrees of TFH cell and B cell interactions, suggesting different stages of T cell help for B cell activation. Subsequent BCR characterizations revealed the presence of homogenous monoclonal and heterogeneous clonally expanded B cell populations; the latter population exhibited an enrichment of B cell activation genes. The authors, then, compare across patients to evaluate T and B cell clonality based on V(D)J recombination analyses of RE and RL patient samples (See technical limitations).

      Interestingly, cytokine expression analysis revealed IL-6 expression by B cells. In contrast, B cells expressed IL12A in RE patients, while effector memory CD8, proliferative CD8, and CD4 T cells and plasma B cells highly expressed IL16 in RL patients. The authors report additional cytokine (and cellular) characteristics that distinguish severe COVID-19 patients and recovering patients.

      Limitations<br /> Technical<br /> A primary technical limitation is the sample size of this study for each group. There is little clinical information about the patients and no details about disease severity in patients recruited after viral clearance. For example, age and CMV status have a huge impact on the TCR repertoire, therefore clinical data on the different groups should be presented. Moreover, without additional information on the clinical management of the severe COVID-19 patients and what therapies were given to the recovering COVID-19 patients, it is difficult to compare the cellular changes in the immune landscapes of the COVID-19 patients across samples. Longitudinal analysis would have been more informative especially with regards to repertoire analysis and how expanded clones during active infections might differentiate into particular phenotypes after viral clearance.CD8 expression should have been included in the violin plots, as it is usually more robust and reliable than CD4 expression.

      Biological<br /> An immediate concern is whether the authors mis-characterized cluster 13 as a TH1 cell cluster. The cluster exhibits a low expression of CD3G and CD4. It’s neighboring clusters within the hierarchy belong to monocyte groups, so it is unexpected that a T cell subtype would be belong to their branch of the hierarchy tree. Consider also cluster 38, which shows more robust expression of CD3G and NKG7 and is arranged with the B cell group.

      In addition, the authors did not highlight or discuss expression of co-inhibitory receptors that could elucidate the heterogeneity of T cell differentiation during COVID-19. As a result, it is difficult to truly assess the activation status of the CD8+ cytotoxic T cells and whether there are features of T cell exhaustion.

      Finally, the distinction between naïve and some subsets of memory T cells by scRNA analysis can be challenging. It would be important for the authors to explore whether cluster 26, classified as a naïve CD8 T cell cluster predominant in RL group could be actually memory cells. It would have been important to show clonal diversity of the different clusters.

      Significance<br /> In summary, Fan et al. provide a comparative analysis of lymphocyte changes between PBMCs of patients with ongoing COVID-19 progression and of patients recovering from the disease. Using a combination of single-cell RNA sequencing and V(D)J recombination sequencing, the authors describe specific changes in T and B cell subpopulations over the course of early and late-stage recovery.

      This review was undertaken by Matthew D. Park as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2020-06-10 09:22:39, user alanarchibald wrote:

      Am I correct in understanding that your definition of (European) travel in the context of this study is limited to travel by persons who are normally resident in the UK and that travel by visitors to Scotland/UK is not addressed, presumably as you did not have access to the necessary samples and medical records.

    1. On 2020-06-15 01:10:48, user Serge wrote:

      There are many inaccuracies in the report that may significantly affect the conclusions.<br /> 1. Diamond Princess analysis: the mortality data (in single digits) is not sufficient for a confident estimate of the mortality per jurisdiction (for some nations there was only a single case). Moreover, most countries started universal BCG vaccination around 1950s plus the effect of WWII would likely compromise any earlier program to a significant extent. That means that regardless of the country of origin, large part of over 70 population would not be protected and thus shouldn't be considered in verification of the hypothesis.<br /> 2. Certainly there can be no expectation that the protection effect would extend equally into a very advanced age, 60 years and longer after vaccination.<br /> 3. What is meant by the statement "BCG was provided mostly in Europe"? This is plain incorrect, please check "BCG World Atlas".<br /> 4. Country analysis: was the population taken into account? It is not clear from the description of diagrams. I would advise to attempt to calculate mortality per capita, from the most current data and compare it between jurisdictions at a similar period of exposure. Note that all countries with the highest M.p.c. adjusted for the time of exposure, never had a BCG program (or equivalent as in Spain where it was provided for 18 years out of 70) there's simply not a single exception.

    1. On 2020-06-15 21:36:07, user Marm Kilpatrick wrote:

      Fantastic (but worrisome) work! <br /> Would it be possible to give the full details of the regression of infectious viral load via culturing (PFU/ml) vs RNA via qPCR? This relationship is robust and could be used as the basis for inferring infectious viral load from qPCR, but doing so in a way that explicitly incorporates uncertainty would require more details of the regression than you currently report. Specifically, if you could report the slope, intercept and residual standard error and sample size for this regression that would enable others to make maximal use of your results. Even better would be to make the individual data points from graph available and then the data could be used directly.<br /> Thank you very much for this important work!<br /> marm

    1. On 2020-06-17 13:21:18, user Jumana Haji wrote:

      Amazing experience working with this group to sort through guidelines and evaluate them for completeness while also developing a tool for future guidelines. The tool is ideal when keeping healthcare worker safety and wellbeing perspective as priorities.

    1. On 2020-06-17 20:11:26, user LB wrote:

      Zotero (a popular citation manager) says that this article has been retracted. If this is not the case, please ask Retraction Watch to correct the error.

    2. On 2020-05-18 18:01:55, user 18wheel wrote:

      I believe you're onto something here: nothing to do with infection but the response. The targeting (elderly, populations with low vitamin D uptake for various reasons) will be borne out over the seasonal change (a comparison between north of 35 and south of 35 cities in August/September cross-referenced with local fortification and diet would be most interesting)

    1. On 2020-06-18 01:00:02, user Alex Backer wrote:

      See https://ssrn.com/abstract=3... for a global study that shows case and death counts had significantly lower growth rates at higher temperatures (>14 °C) when aligned for stage in the epidemic. We then show irradiance and in particular solar elevation angle in combination with cloudopacity explain COVID-19 morbidity and mortality growth better than temperature: a reduction of mean solar elevation of 9 degrees led on average to a 2500% increase in COVID-19 case growth over the following two weeks. COVID-19 exploded during the darkest January in Wuhan in over a decade. Our results suggest transmission models should incorporate solar elevation and that the impact of UV irradiance on individual morbidity and mortality should be tested. We discuss implications for the best locations and optimal behaviors for high-risk individuals to weather the pandemic. --Alex Bäcker, Ph.D.

    1. On 2020-06-19 18:24:34, user ChrisdeZilcho wrote:

      Apparently a new study from same team shows CoV2-positive samples from savage water stored in Dec last year. Would be interesting to see the phylogenetic sequence analysis. Did virus fizzle out in Dec/Jan or was there a "quiet" transmission activity? Have there been many independent intros into Italy? Looking forward to reading the publication.

    1. On 2020-06-19 22:15:27, user Michelle Kimple wrote:

      Have you thought of performing analyses of your data by city/county size and/or population density? In the abstract you state "We did not find an association between county level prevalence of COVID-19 cases and face covering use" but when I limited the data to only counties with the 5 most populous cities, there appears to be a strong correlation. I just tweeted my analysis of your data (the county populations may not be what you used, but the city and county population ranks are correct): https://twitter.com/KimpleL...

    1. On 2020-06-21 20:05:22, user Jørgen K. Kanters wrote:

      Please note that by some (yet) unknown reason one of the authors Claus Graff is omitted from the MedRxiv page, but correctly included in the pdf file. We will submit a revision tomorrov to correct it

    1. On 2020-03-26 13:52:15, user Sinai Immunol Review Project wrote:

      SUMMARY: This study aimed to find prognostic biomarkers of COVID-19 pneumonia severity. Sixty-one (61) patients with COVID-19 treated in January at a hospital in Beijing, China were included. On average, patients were seen within 5 days from illness onset. Samples were collected on admission; and then patients were monitored for the development of severe illness with a median follow-up of 10 days].

      Patients were grouped as “mild” (N=44) or “moderate/severe” (N=17) according to symptoms on admission and compared for different clinical/laboratory features. “Moderate/severe” patients were significantly older (median of 56 years old, compared to 41 years old). Whereas comorbidies rates were largely similar between the groups, except for hypertension, which was more frequent in the severe group (p= 0.056). ‘Severe’ patients had higher counts of neutrophils, and serum glucose levels; but lower lymphocyte counts, sodium and serum chlorine levels. The ratio of neutrophils to lymphocytes (NLR) was also higher for the ‘severe’ group. ‘Severe’ patients had a higher rate of bacterial infections (and antibiotic treatment) and received more intensive respiratory support and treatment.

      26 clinical/laboratory variables were used to select NLR and age as the best predictors of the severe disease. Predictive cutoffs for a severe illness as NLR >= 3.13 or age >= 50 years.

      Identification of early biomarkers is important for making clinical decisions, but large sample size and validation cohorts are necessary to confirm findings. It is worth noting that patients classified as “mild” showed pneumonia by imaging and fever, and in accordance with current classifications this would be consistent with “moderate” cases. Hence it would be more appropriate to refer to the groups as “moderate” vs “severe/critical”. Furthermore, there are several limitations that could impact the interpretation of the results: e.g. classification of patients was based on symptoms presented on admission and not based on disease progression, small sample size, especially the number of ‘severe’ cases (with no deaths among these patients). Given the small sample size, the proposed NLR and age cut offs might not hold for a slightly different set of patients. For example, in a study of >400 patients, ‘non-severe’ and ‘severe’ NLR were 3.2 and 5.5, respectively 1.

      References:<br /> 1. Chuan Qin, MD, PhD, Luoqi Zhou, MD, Ziwei Hu, MD, Shuoqi Zhang, MD, PhD, Sheng Yang, MD, Yu Tao, MD, PhD, Cuihong Xie, MD, PhD, Ke Ma, MD, PhD, Ke Shang, MD, PhD, Wei Wang, MD, PhD, Dai-Shi Tian, MD, PhD, Dysregulation of immune response in patients with COVID-19 in Wuhan, China, Clinical Infectious Diseases, , ciaa248, https://doi.org/10.1093/cid...

      This review was undertaken as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2020-05-22 16:23:27, user Jim Parfitt wrote:

      It is difficult to find any discussion on this issue. I am a person who has taken NO systemic antibiotics for over 40 years. And I basically never get sick. I have been wondering how many of the severe cases of Covid 19 are in people who regularly take systemic antibiotics, and so have messed up gut flora. This is what i suspect. I would like to read the whole study; if that is possible.

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

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

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

    1. On 2020-05-24 08:36:41, user Lauren wrote:

      Accidental death rates for my age group of 30 to 39 are roughly 1 in 1000 (white female) roughly the same as COVID. I get what others are saying but this specifically addresses percent of death compared to other fatality statistics. I do think though that thr 50 or 60 age range is more likely to die of COVID IF almost everyone were to be exposed, hopefully we will not see that. This however does not include impact of COVID on black and Hispanic populations which are much higher.

    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 2020-05-26 23:26:41, user Sam Wheeler wrote:

      The medical staff can get the virus while commuting to work. Especially if you work place is the place where patients go for covid testing or treatment, so you share the bus or subway with sick patients.

    1. On 2020-05-27 01:37:02, user Keith wrote:

      Very exciting new and a likely game changer for dentists/ENTs or anyone who manipulates the mucosa of a potentially covid + patient

    2. On 2020-05-27 02:04:13, user Chintu Shah wrote:

      Interesting. I can see the oral and nasal forms becoming part of the sterile procedure process for many surgical procedures.

    1. On 2025-04-10 17:31:51, user SMR Hashemian wrote:

      At the peak of the COVID-19 crisis, when the world was gripped by fear and despair, Iran was not only battling a deadly virus but also grappling with brutal and inhumane sanctions. Economic sanctions severely restricted Iran's access to medicine, medical equipment, and vaccines, creating one of the biggest obstacles in the fight against this crisis. Yet, despite these unprecedented pressures, Iran did not surrender and, through relentless efforts, found ways to overcome these limitations.<br /> The Iranian government made every effort to bypass the sanctions through international negotiations and the creation of alternative financial channels to import the necessary medicines and equipment. These efforts, though fraught with difficulties, demonstrated Iran's resolve to save lives. Even as many countries refused to assist Iran, the nation relied on domestic capabilities and national solidarity to find solutions to the crisis.<br /> Amidst these challenges, Iran's healthcare workers stood on the front lines like unsung soldiers, making unparalleled sacrifices. Doctors, nurses, and all healthcare workers in hospitals not only played a critical role in saving countless lives but also faced significant personal risks, with many losing their lives in the process. These dedicated professionals demonstrated extraordinary commitment and selflessness, setting an example of resilience and dedication in the face of a global health crisis.<br /> But it was not just the healthcare workers who fought in this battle. Iran's scientific community also stepped up with full force. Iranian scientists and researchers, despite cruel sanctions and countless limitations, never stopped striving. They not only succeeded in producing domestic vaccines like Noora and SpikoGen, but also published numerous articles in prestigious international journals, showcasing Iran's role in advancing global science. These efforts are a testament to the fact that Iran, even under the toughest conditions, can rely on science and knowledge.<br /> The Iranian government, despite all limitations, spared no effort in controlling this crisis. From the very beginning, extensive education on health protocols was launched through the media. The public was continuously informed about health recommendations such as mask-wearing, social distancing, and hand hygiene. Even during Nowruz, one of the most important cultural events in Iran, the government encouraged people to reduce travel and celebrate at home. School and university closures, the shift to remote learning, and the reduction of workplace presence through teleworking all demonstrated the government's resolve to control the spread of the virus.<br /> These efforts, though accompanied by challenges, reflect Iran's national determination to confront this global crisis. Iran, despite all limitations, proved that it could stand firm against the toughest conditions by relying on science, sacrifice, and national solidarity. The accusations raised in this article are not only unfair but also overlook the relentless efforts of a nation. Iran fought with all its might to save lives, and that is something to be proud of.

      Seyed MohammadReza Hashemian<br /> Professor of Critical Care Medicine

    1. On 2020-04-20 15:36:38, user Philip Davies wrote:

      Interesting study, thank you.

      This is another study that attempts to ascertain if oral HCQ tablets can be of clinical use in patients more than one week into symptomatic disease, hospitalized with bilateral pneumonia and with evidence of established inflammatory reaction (cytokine storm). That's a big ask for any oral medication.

      The study is again small (both arms have less than 100 patients). The most significant outcome measured (death) is realized in very small numbers (3 and 4). The confidence levels are extremely wide.

      The are several problems with this study. There are marked differences in the two populations. The study honestly attempts to accommodate these confounding factors using a propensity score method (IPTW). Normally this method is valuable but here I can’t see that it has been well applied.

      It pays to look at the raw data. There is a significant difference (between the two arms) in the initial intensity of disease.

      At baseline (admission), HCQ arm comprises 78.3% men (>20% more of these higher risk patients than control arm with 64.9%); HCQ arm has 21.9% patients with more severe disease in the form of CT showing >50% lung affected). This is >80% more than in control arm (12.1%). HCQ arm has 90.5% patients with CRP > 40mg/l (CRP is a good indicator of impending/current severity). This is 10% higher than control arm (81.9%). HCQ arm had median O2 flow on admission = 3 litres/minute (50% higher than control arm at 2 litres / minute).

      So, at baseline, the HCQ arm had significantly more patients with severe disease than control arm. The O2 flow is actually more significant than first sight would suggest. 2 l/m is always the first step in O2 therapy. The data shows us that most patients in the control arm could hold their sats on this first step therapy. This also means they may have been OK on just 1 l/m. We don't know. But we do know that most patients in the HQN could not hold their sats at that first step and needed an increase (3 l/m ... so that's 50-300% more O2 than control arm).

      Admittedly there were other confounding factors which compromised the control arm more than HCQ arm (some chronic disease elements). But it's clear to me that disease severity was markedly more established in the HCQ arm.

      Another factor to note: the HCQ treatment was not initiated at the moment those baseline values were obtained (on admission). The HCQ was initiated within 48 hours. So let’s look again at the timelines. The median duration of symptoms at admission shows that the HCQ arm comprised patients who were further into worsening illness: they were admitted on D8 compared to control, D7. They may not have had HCQ initiated until D10.

      Then we look at outcomes: the raw data shows that the disadvantaged HCQ arm actually does better in the two most important outcomes, death and ICU admission. The HCQ delivers 12% less death and ICU admissions than the control arm. Admittedly the numbers are small so the confidence levels are very wide.

      So what does that tell us? The answer is not much. But even accepting the poorly aligned baseline for disease severity, the outcomes with their wide 95% confidence levels do deliver a mildly promising indication on the 'swingometer'. They point more towards benefit than harm when using HCQ in this advanced disease state.

      As a final comment on significant side effects (increased QT interval) from the use of HCQ. Once again, this trial used a particularly high dose of HCQ (600mg/day...right at ceiling dose for rheumatological use and much higher than the total antimalarial treatment dose). They also added azithromycin (another QT lengthening drug) to 20% of the HCQ patients. It’s not surprising at all to find such QT lengthening in a sick, more elderly population taking these medications in particularly high doses).

      Further trials should utilize conservative doses of CQ/HCQ which have been proven safe in many millions of patients.

      We don't yet know how this will pan out. We urgently need proper evidence. Statistically robust studies into prophylaxis and early intervention are likely to deliver the most interesting results.

      Dr Philip Davies<br /> Aldershot Centre For Health<br /> http://thevirus.uk

    1. On 2020-04-06 18:50:52, user Sinai Immunol Review Project wrote:

      Main Findings: Currently, the diagnosis of SARS-CoV-2 infection entirely depends on the detection of viral RNA using polymerase chain reaction (PCR) assays. False negative results are common, particularly when the samples are collected from upper respiratory. Serological detection may be useful as an additional testing strategy. In this study the authors reported that a typical acute antibody response was induced during the SARS-CoV-2 infection, which was discuss earlier1. The seroconversion rate for Ab, IgM and IgG in COVID-19 patients was 98.8% (79/80), 93.8% (75/80) and 93.8% (75/80), respectively. The first detectible serology marker was total antibody followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days-post exposure (d.p.e) or 9, 10- and 12-days post-onset (d.p.o). Seroconversion was first detected at day 7d.p.e in 98.9% of the patients. Interestingly they found that viral load declined as antibody levels increased. This was in contrast to a previous study1, showing that increased antibody titers did not always correlate with RNA clearance (low number of patient sample).

      Limitations: Current knowledge of the antibody response to SAR-CoV-2 infection and its mechanism is not yet well elucidated. Similar to the RNA test, the absence of antibody titers in the early stage of illness could not exclude the possibility of infection. A diagnostic test, which is the aim of the authors, would not be useful at the early time points of infection but it could be used to screen asymptomatic patients or patients with mild disease at later times after exposure.

      Relevance: Understanding the antibody responses against SARS-CoV2 is useful in the development of a serological test for the diagnosis of COVID-19. This manuscript discussed acute antibody responses which can be deducted in plasma for diagnostic as well as prognostic purposes. Thus, patient-derived plasma with known antibody titers may be used therapeutically for treating COVID-19 patients with severe illness.

      Reference:

      1. Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019

      doi: https://doi.org/10.1101/202...

    1. On 2020-04-23 17:27:44, user Sinai Immunol Review Project wrote:

      Presence of SARS-CoV-2 reactive T cells in COVID-19 patients and healthy donors

      Braun J et al.; medRxiv 2020.04.17.20061440; https://doi.org/10.1101/202...

      Keywords

      • SARS-CoV-2 specific CD4 T cells

      • Human endemic coronaviruses

      • COVID-19

      Main findings

      In this preprint, Braun et al. report quantification of virus-specific CD4 T cells in 18 patients with mild, severe and critical COVID-19, including 10 patients admitted to ICU. Performing in vitro stimulation of PBMCs with two sets of overlapping SARS-CoV-2 peptide pools – the S I pool spanning the N-terminal region (aa 1-643) of the S protein, including 21 predicted SARS-CoV-1 MHC-II epitopes, and the C-terminal S II pool (aa 633-1273) containing 13 predicted SARS-CoV-1 MHC-II epitopes – the authors detected S-protein-specific CD4 T cells in up to 83% of COVID-19 patients based on intracellular 4-1BB (CD137) and CD40L (CD154) induction. Notably, peptide pool S II shares higher homology with human endemic coronaviruses (hCoVs) 229E, NL63, OC43, and HKU1 that may cause the common cold, but it does not include the SARS-CoV-2 receptor-binding domain (RBD), which has been identified as a critical target of neutralizing antibodies in both SARS-CoV-1 and SARS-CoV-2. S I-reactive CD4 T cells were found in 12 out of 18 (67%) patients, whereas CD4 T cells against S II were detected in 15 patients (83%). Intriguingly, S-specific CD4 T cells could also be found in 34% (n=23) of 68 SARS-CoV-2 seronegative donors, referred to as reactive healthy donors (RHD), with a preference for S II over S I epitopes. Only 6 of 23 RHDs also had detectable frequencies of S I-specific CD4 T cells, overall suggesting S II-reactive CD4 T cells had likely developed in response to prior infections with hCoVs. Of 18 out of 68 total healthy donors tested, all were found to have anti-hCoV antibodies, although this was independent of concomitant anti-S II CD4 T cell frequencies detected. This finding mirrors observations of declining numbers of specific CD4 T cells, but persistent humoral memory after certain vaccinations such as against yellow fever. The authors further speculate that these pre-existing virus-specific T cells against hCoVs might be one of the reasons why children and younger patients, usually considered to have a higher incidence of hCoV infections per year, are seemingly better protected against SARS-CoV-2. Unlike specific CD4 T cells found in RHDs, most S-specific CD4 T cells in COVID-19 patients displayed a phenotype of recent in vivo activation with co-expression of HLA-DR and CD38, as well as variable expression of Ki-67. In addition, a substantial fraction of peripherally found HLA-DR+/CD38+ bulk CD4 T cells was found to be refractory to peptide stimulation, potentially indicating cellular exhaustion.

      Limitations

      This is one of the first preprints reporting the detection of virus-specific CD4 T cells in COVID-19 (also cf. Dong et al., https://www.medrxiv.org/con... Weiskopf et al., https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.04.11.20062349v1.article-info)"). While it generally adds to our current knowledge about the potential role of T cells in response to SARS-CoV-2, a few limitations, some of which are discussed by the authors themselves, should be addressed. Findings in this study pertain to a relatively small cohort of patients of variable clinical disease. To corroborate the observations made here, larger studies including both more healthy donors and more patients of all clinical stages are needed to better assess the function of virus-specific CD4 T cells in COVID-19. Specifically, the presence of pre-existing, potentially hCoV-cross-reactive CD4 T cells in healthy donors needs to be explored in the context of COVID-19 immunopathogenesis. While the authors suggest a potentially protective role based on higher incidence of hCoV infection in children and younger patients, and therefore a presumably larger pool of pre-existing virus-specific memory T cells, the opposite could also be the case given cumulatively increased number of hCoV infections in older patients. In this context, it would therefore have been interesting to also measure anti-hCoV antibodies in COVID-19 patients. Furthermore, this study did not quantify virus-specific CD8 T cells. Based on observations in SARS-CoV-1, virus-specific memory CD8 T cells are more likely to persist long-term and confer protection than CD4 T cells, which were detected only at lower frequencies six years post recovery from SARS-CoV-1 (cf. Li CK et al., Journal of immunology 181, 5490-5500.) Morover, no other specifities such as against the N or M epitopes were evaluated. Robust generation of virus-specific T cells against the N protein was shown to be induced by SARS-CoV-2 in another pre-print by Dong et al. (Dong et al., https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.03.17.20036640v1)"), while Weiskopf et al. recently reported preference of both CD8 and CD4 T cells for S epitopes https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.04.11.20062349v1.article-info)"). Moreover, the authors seem to suggest that some of the virus-specific CD4 T cells detected could be potentially cross-reactive to predicted SARS-CoV-1 epitopes present in the peptide pools used. Indeed, this has been recently established for several SARS-CoV-2 binding antibodies, while it was found not to be the case for RBD-targeting neutralizing antibodies (cf. Wu et al., https://www.medrxiv.org/con... Ju et al., https://www.biorxiv.org/con... "https://www.biorxiv.org/content/10.1101/2020.03.21.990770v2)"). A similar observation has not been made for T cells so far and should be evaluated. Finally, since reactive healthy donors were only tested for anti-S1 IgG, however not for other more ubiquitous binding antibodies, e.g. against M, and only a fraction of these donors was additionally confirmed to be negative by PCR, there is, though unlikely, the possibility that some of the seronegative reactive donors had been previously exposed to SARS-CoV-2.

      Significance

      Quantification of virus-specific T cells in peripheral blood is a useful tool to determine the cellular immune response to SARS-CoV-2 both in acute disease and even more so post recovery. Ideally, once immunogenic T cell epitopes are better characterized, tetramer assays will allow for faster and more efficient detection of their frequencies. Moreover, assessing the potential role of pre-existing virus-specific CD4 T cells in healthy donors in the context of COVID-19 pathogenesis will be of particular importance. The observations made here are also highly relevant for the design and development of potential vaccines and should therefore be further explored in ongoing research on potential coronavirus therapies and prevention strategies.

      This review was undertaken by V. van der Heide as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2020-06-24 11:34:40, user Renzo Huber wrote:

      This is a nice review that might also be valuable to the field of layer-fMRI. <br /> I think the manuscript might benefit from an additional brief discussion of the related laminar connectivity findings from non-invasive human fMRI studies:

      -> layer-dependent connectivity in Fig. 6 and 7 of the following study: <br /> Huber L, Handwerker DA, Jangraw DC, et al. High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. Neuron. 2017;96(6):1253-1263.e7. doi:10.1016/j.neuron.2017.11.005

      -> layer-dependent connectivity with gppi in this study: <br /> Sharoh D, Mourik T van, Bains LJ, et al. Laminar Specific fMRI Reveals Directed Interactions in Distributed Networks During Language Processing. PNAS. 2019:1907858116. doi:10.1101/585844

      -> layer-dependent hierarchical connectivity discussed in this study: <br /> 1. Huber L, Finn ES, Chai Y, et al. Layer-dependent functional connectivity methods. Prog Neurobiol. 2020:in print. doi:j.pneurobio.2020.101835

    1. On 2020-06-05 17:35:30, user wbgrant wrote:

      Dark-skinned people living in Spain are at an increased risk of COVID-19 due to lower vitamin D production from solar UVB. This effect probalby explains the finding for Sub-Saharan Africa and the Caribbean. Not sure about Latin America, where rates are very high in several countries. See:<br /> Grant WB, Lahore H, McDonnell SL, Baggerly CA, French CB, Aliano JA, Bhattoa HP. Evidence that vitamin D supplementation could reduce risk of influenza and COVID-19 infections and deaths. Nutrients 2020, 12, 988. https://www.mdpi.com/2072-6...<br /> and references thereto at scholar.google.com<br /> as well as this response<br /> Grant WB, Baggerly CA, Lahore H. Response to Comments Regarding “Evidence that Vitamin D Supplementation Could Reduce Risk of Influenza and COVID-19 Infections and Deaths”. Nutrients 2020, 12(6), 1620; https://doi.org/10.3390/nu1...

    1. On 2020-06-06 01:33:13, user David Hood wrote:

      I think the "39.5% of cases seeking medical consultation in primary care settings" may be overly conservative in the model for a parameter representing getting medical advice, as it is based of influenza in the 2018 'flu season (a fairly typical year). We know from the ESR influenza surveillance site that healthline historically (I don't know the period for what they determine historical) get around 40000 Influenza like illness calls a year, and for the period from the week of 14/2 to 29/5 there are historically around 10000 ILI calls. In 2020, for the period from the week of 14/2 to 29/5, there were around 26000 ILI calls. Even allowing for false positive worries from anxious people boosting call numbers, it suggests that people seeking official advice about ILI is dramatically higher in 2020 (which I also acknowledge is not the same as visiting a primary care location about an ILI, which is the 39.5% figure, but the official advice was to ring Healthline, who were presumably advising testing/ isolation/ primary health as appropriate)

    1. On 2020-06-08 14:35:52, user Francesco Rossi wrote:

      Dear Dr.Streeck, <br /> is it possible, with your experimental approach, giving an estimate of the percentage of people hospitalized and treated in ICU?<br /> The theoretical model supporting lockdown was published by Ferguson and collaborators in The Imperial College report 9 (https://www.imperial.ac.uk/..., hereafter ICR9). In this reports, authors extimated that in Covid-19 epidemic “optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over.” (ICR9). Therefore they concluded that “epidemic suppression is the only viable strategy at the current time.” (ICR9). They focused their prediction on UK and US, but they claimed that their prediction could be applied to other high-income countries (ICR9).<br /> However the model they proposed is controversial for several reasons (https://retractionwatch.com... ; https://pubpeer.com/publica... "https://pubpeer.com/publications/227C0B09C78E146F96F7D679348BF7#)").<br /> May be possible to extimate the percentage of people of Gangelt that would be hospitalized and treated in ICU over the total citizen of Gangelt extimated to be infected with SARS-COV2, according to the parameters used in table 1 of ICR9 reports (which are taken from Verity et al., 2020, https://www.thelancet.com/p...? "https://www.thelancet.com/pdfs/journals/laninf/PIIS1473-3099(20)30243-7.pdf)?")<br /> The parameters are “Under the China case definition, a severe case is defined as tachypnoea (>=30 breaths per min) or oxygen saturation 93% or higher at rest, or PaO2/FiO2 ratio less than 300 mm Hg.7 Assuming severe cases to require hospitalisation (as opposed to all of the patients who were hospitalised in China, some of whom will have been hospitalised to reduce onward transmission), we used the proportion of severe cases by age in these patients to estimate the proportion of cases and infections requiring hospitalisation.” (Verity et al., 2020)

    1. On 2020-06-30 15:59:24, user Dr. Hans-Joachim Kremer wrote:

      Very good trial.<br /> It is interesting that the analysis by days since symptoms onset (<=7 vs. >7) appeared to be as discriminative as the main analysis or the subgroup analysis by respiratory support. Then, the onset of symptoms was strongly correlated with type of respiratory support. Hence, it would be interesting which of both (days since symptoms onset or respiratory support) was more discriminative, i.e. the independent predictor of efficacy of dexamethasone.

    1. On 2020-07-02 13:57:50, user Dr. Amy wrote:

      It would be useful to see how obesity and A+ blood type change the HLH genetic expression. This paper has extremely useful clues toward targets to reduce severity.

    1. On 2020-06-11 13:53:48, user peter tofts wrote:

      please include: 1.) what type of corticosteroid was used (meythyleprednisolone) 2.) the dose (?1mg/kg or other v pulsed) duration etc... 3.) timing: the authors mention timing around 7 days from onset of symptoms- also Delay respect to Sx 13+/- 4.2 so I suppose maybe 6 days +/- 4 into their hospitalization? interesting paper thankyou

    1. On 2020-07-03 19:26:50, user Jun Wan wrote:

      Dr. Anthony Fauci warned this Tuesday (https://www.youtube.com/wat... "https://www.youtube.com/watch?v=m5l5UGS9ngc)") that a new strain of the coronavirus was found to be dominant around the world which was published the past Sunday by the Cell (https://www.cell.com/action... "https://www.cell.com/action/showPdf?pii=S0092-8674%2820%2930820-5)"). The new strain G614 they referred is the exactly same as what this paper identified associated with the mutation A23403G (group A). In addition to the mutation on Spike (614), another mutation C14408T on ORF1ab (P4715 changed to L4715) was also reported by this paper which co-occurred with the mutation on Spike (614). Both can become the features of these strains. Indeed, the paper combined both together to name them as strain GL (G614+L4715) or DP (D614+P4715). Their results suggest "that the GL strain of SARS-CoV-2 might become much more stable and prevailing than DP identified from Wuhan-Hu-1 after 6-month evolution and transmission." Actually, when you read the paper carefully, you may find more novel interesting findings discussed in their work.

    1. On 2020-07-07 20:00:16, user Ron Conte wrote:

      The article above assumes that ivermectin works as an inhibitor, and therefore compares approved dose to IC50. But the results of clinical studies (Chowdhury et al. ResearchGate; Rajter et al. medRxiv) suggest that ivermectin works in some other way, i.e. not as an inhibitor that would depend upon concentration.

    1. On 2020-07-11 14:17:56, user DMelanogaster wrote:

      I understand that this study was done just to explore safety, not efficacy, but doesn't the finding that mortality rates were not decreased in those infused with the antibodies in such a large sample indicate that the antibody treatment was not at all useful for severely ill patients?

    1. On 2020-05-01 23:43:12, user Sinai Immunol Review Project wrote:

      Title A single-cell atlas of the peripheral immune response to severe COVID-19<br /> Wilk, A.J. et al. MedRxiv ; doi:10.1101/2020.04.17.20069930

      Keywords<br /> scRNAseq; Interferon-Stimulating Genes (ISGs); Activated granulocytes

      Main Findings<br /> The authors performed single-cell RNA-sequencing (scRNAseq) on peripheral blood from 6 healthy donors and 7 patients, including 4 ventilated and 3 non-ventilated patients. 5 of the patients received Remdesivir.

      scRNAseq data reveal 30 gene clusters, distributed among granulocytes, lymphocytes (NK, B, T cells), myeloid cells (dendritic cells DCs, monocytes), platelets and red blood cells. Ventilated patients specifically display cells containing neutrophil granule proteins that appear closer to B cells than to neutrophils in dimensionality reduction analyses. The authors named these cells “Activated Granulocytes” and suggest them to be class-switched B cells that have lost the expression of CD27, CD38 and BCMA and acquired neutrophil-associated genes, based on RNA velocity studies.

      SARS-CoV2 infection leads to decreased frequencies of myeloid cells, including plasmacytoid DCs and CD16+ monocytes. CD14+ monocyte frequencies are unchanged in the patients, though their transcriptome reveals an increased activated profile and a downregulation of HLAE, HLAF and class II HLA genes. NK cell transcriptomic signature suggests lower CD56bright and CD56dim NK cell frequencies in COVID-19 patients. NK cells from patients have increased immune checkpoint (Lag-3, Tim-3) and activation marker transcripts and decreased maturation and cytotoxicity transcripts (CD16, Ksp-37, granulysin). Granulysin transcripts are also decreased in CD8 T cells, yet immune checkpoint transcripts remain unchanged in both CD8 and CD4 T cells upon SARS-CoV2 infection. The frequencies of memory and naïve CD4 and CD8 T cell subsets seem unchanged upon disease, though gdT cell proportions are decreased. SARS-CoV2 infection also induces expansion of IgA and IgG plasmablasts that do not share Ig V genes.

      Interferon-signaling genes (ISGs) are upregulated in the monocyte, the NK and the T cell compartment in a donor-dependent manner. ISG transcripts in the monocytes tend to increase with the age, while decreasing with the time to onset disease. No significant cytokine transcripts are expressed by the circulating monocytes and IFNG, TNF, CCL3, CCL4 transcript levels remain unchanged in NK and T cells upon infection.

      Limitations<br /> The sample size of the patients is limited (n=7) and gender-biased, as all of them are men.<br /> The activating and resting signatures in monocytes should be further detailed. The authors did not detect IL1B transcripts in monocytes from the patients, though preliminary studies suggest increased frequencies of CD14+ IL1B+ monocytes in the blood of convalescent COVID-19 patients[1].<br /> Decreased NK cells, B cells, DCs, CD16+ monocytes and gdT cells observed in peripheral blood might not only reflect a direct SARS-CoV2-induced impairment, but also the migration of these cells to the infected lung, in line with preliminary data suggesting unchanged NK cell frequencies in the patient lungs[2].<br /> The authors identified platelets in their cluster analyses. Recent reports of pulmonary complications secondary to COVID-19 describe thrombus formation that is probably due, in part, to platelet activation[3, 4]. A targeted characterization of the platelet transcriptome may thus benefit an increased understanding of this phenomenon.<br /> The transcriptome of the Activated Granulocytes should be further detailed. As discussed by the authors, IL24 and EGF might be involved in the generation of the Activated Granulocytes, though these cytokines are poorly represented in the blood of the patients. The generation of these cells should therefore be further investigated in future studies.

      Significance<br /> The authors show a SARS-CoV2-induced NK cell dysregulation, in accordance with previous studies[5]. Alongside the upregulation of ISGs in NK cells, these findings suggest an impaired capacity of the NK cells to respond to activating signals in COVID-19 patients. The unchanged expression of immune checkpoints on CD4 and CD8 T cells suggest distinct SARS-CoV2 dysregulation pathways in the NK and the T cell compartments. In particular, the downregulation of transcripts encoding for class II HLA but not for the HLA-A, -B, -C molecules in monocytes suggest an impaired antigen presentation capacity to CD4 T cells, which should be further investigated.<br /> The authors provide preliminary results suggesting an age-related activation of the monocytes in the COVID-19 patients. Future studies will be needed to evaluate if the age impacts the involvement of the monocytes in the cytokine storm observed in COVID-19 patients.

      References<br /> 1. Wen, W., et al., Immune Cell Profiling of COVID-19 Patients in the Recovery Stage by Single-Cell Sequencing. MedRxiv, 2020.<br /> 2. Liao, M., et al., The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing. MedRxiv, 2020.<br /> 3. Giannis, D., I.A. Ziogas, and P. Gianni, Coagulation disorders in coronavirus infected patients: COVID-19, SARS-CoV-1, MERS-CoV and lessons from the past. J Clin Virol, 2020. 127: p. 104362.<br /> 4. Dolhnikoff, M., et al., Pathological evidence of pulmonary thrombotic phenomena in severe COVID-19. J Thromb Haemost, 2020.<br /> 5. Zheng, M., et al., Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cell Mol Immunol, 2020.

      Credit<br /> Reviewed by Bérengère Salomé and Zafar Mahmood as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai

    1. On 2020-05-04 18:15:10, user Dr SK Gupta wrote:

      High Dose Chloroquine with Poor patient selection are the culprits- not the drug <br /> Investigators were over enthusiastic in using a higher dose of chloroquine in elderly patients. In China National Health and Care Commission officially included the Chloroquine as medical agent on 19 Feb 2020 to be used in corona virus treatment plan. The dose of 500mg of chloroquine twice a day was decided following in vitro studies EC50 values, PBPK modeling and mice RLTEC data projected on Human beings (1). <br /> The initial recommended dose of 500 mg of chloroquine phosphate salt twice per day can quickly approach danger thresholds with sustained use at the maximum course of 10 days (Total chloroquine base 6gm). The lethal dose of chloroquine base in adults is about 5g. In China, On Feb 26, 2020, the treatment guidelines were revised, shortening the maximum course to 7 days to keep the total dose of chloroquine base 4.2 gm much lower than toxic dose (2). <br /> Elderly population is particularly prone to chloroquine toxicity especially at high doses. It is unfortunate in present study, that a base line ECG was not done to measure the QTc interval because the drug should be avoided if the QTc was more than 500ms especially in patients with severe disease prone to develop myocarditis due to primary disease Covid-19 per se(3). On the contrary we find that the higher dose regimen included Older age population with mean [SD] age, 54.7 [13.7] years vs 47.4 [13.3] years with more heart disease (5 of 28 [17.9%] vs 0) as compared to lower dose regimen. We in India having hige experience of using the drug would refrain from using such high doses.<br /> Gao et al reported results from more than 100 patients demonstrated that chloroquine phosphate is superior to the control treatment: in inhibiting the exacerbation of pneumonia, improving lung imaging findings, promoting a virus-negative conversion, shortening the disease course. Severe adverse reactions to chloroquine phosphate were not noted in the aforementioned patients (4). <br /> Poor patient selection and use of toxic doses of chloroquine seems to have brought disrepute to a promising drug. More studies are required before condemning the drug in present indication of Covid 19<br /> References:<br /> 1. Wang M, Cao R, Zhang L, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res 2020; 30:269–71<br /> 2. COVID-19: a recommendation to examine the effect of hydroxychloroquine in preventing infection and progression Dan Zhou, Sheng-Ming Dai and Qiang Tong J Antimicrob Chemother doi:10.1093/jac/dkaa114

      1. Cardiovascular risks of hydroxychloroquine in treatment and prophylaxis of COVID-19 patients: A scientific statement from the Indian Heart Rhythm Society<br /> Aditya Kapoor, Ulhas Pandurangi,Vanita Arora, Anoop Gupta, Aparna Jaswal et al. Indian Pacing and Electrophysiology Journal, https://doi.org/10.1016/j.i...

      2. Gao J, Tian Z, Yang X. Breakthrough: chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies. Bioscience Trends 2020; 14:72–3

    1. On 2020-04-17 23:52:12, user Daniel H Vlad, PhD wrote:

      Dear Author, <br /> I appreciate your efforts to shed light on this very important topic but I believe the article has a major bias, which is indeed mentioned in the article.<br /> "Other biases, such as ... bias favoring those with prior COVID-like illnesses seeking antibody confirmation are also possible. The overall effect of such biases is hard to ascertain. "

      I think this is a very serious bias and let me explain why. It's very likely that your Facebook ads attracted a fair number of participants that were concerned they may have been infected with Covid-19. People who had experienced Covid-like symptoms in the recent past were more likely to pay attention to your Facebook ad and were also more likely to enroll in your study. Therefore your sample is not random.<br /> Let's make some reasonable assumptions. Let's assume that 10% of your sample, or 333 participants had Covid-19 like symptoms in the past and were seeking antibody confirmation. I believe this percentage is very reasonable. <br /> According to California statistics, approximately 25% of people tested for Covid-19 test positive. It could be very reasonable to assume that 15% of these 333 participants seeking antibody confirmation had been indeed infected. So that will equal to 50 positive participants, or the entire number of antibody test positive participants in your sample.<br /> The example above proves that this bias is a valid concern. Your entire list of 50 antibody positive participants could have been participants seeking antibody confirmation.

      There are several ways to remove the bias:<br /> a. You mention in the article that you asked survey participants if they had prior clinical symptoms. You should try to exclude all participants that had symptoms (fever, chest pressure) similar to Covid-19 this year. This will indeed exclude all people that were ill, not only those who replied to the add to seek antibody confirmation. However, it will give you insight into the percentage of silent Covid-19 carriers, which is a question as important as the question you are trying to answer, and in a way equivalent. And the results will be unbiased. <br /> b. Attempt to adjust for this bias. Calculate the percentage of participants in your sample who experienced Covid-19 symptoms and compare this with reasonable epidemiological data. Calculate a weight and apply it to your sample in addition to your zip-sex-race weights.

      Regards, Daniel H. Vlad, PhD.

    2. On 2020-04-18 17:13:58, user Animesh Ray wrote:

      I do not believe these conclusions. A crucial control for the estimate of false positive detection by their method is grossly inadequate. This manuscript should not have seen the light of the day in this form, let alone be published even in a pre-print format because of the sensitivity of the topic.

      Here is the reason: The common cold coronaviruses that could potentially cross-react to existing pre-COVID19 IgM/IgG are quite prevalent in the population. To address this, the authors tested 30 pre-COVID19 sera.

      Given an unadjusted detection rate of 2.8% seropositives in post-COVID-19 samples, if all were false positives, they needed to test, for 99% confidence, a MINIMUM of log(0.01)/log(0.972) = 162 pre-COVID19 sera of similar demographics (age/sex/location).

      Instead, they tested only 30!

      [They do cite the kit validation data by the supplier/vendor as having tested 371 negative samples--this is as spurious an argument as stating that a q.RT-PCR kit produced x frequency of true negatives by the supplier and therefore we don't need to do the appropriate control in our experiment!! This statement has no place in a scientific publication other than trying to obfuscate the real weight of the lack of sufficient control to determine the false positive rates.]

      On this basis I cannot attach any value to this report.

      These false conclusions, given the current pre-print version, are dangerous because they could be naively interpreted to imply a lesser morbidity of COVID19 than the current numbers otherwise suggest.

      I fear that this pre-print will now be used by the public media and sections of political interest groups to advocate for lesser stringency in COVID-19 pandemic control than desirable, and might lead to unfortunate loss of lives.

    3. On 2020-04-21 15:33:02, user ?????Ozymandias????? wrote:

      I'm just an undergrad with no expertise, but based on Bayesian logic, when the sensitivity of a test isn't perfect, and given the low prevalence of a trait in a population, won't the test tend to elicit enough false-positives to cloud the results?

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

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

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

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

      Why is there no ELISA for ORF8?

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

    1. On 2019-10-10 12:11:25, user GuyguyKabundi Tshima wrote:

      EPIDEMIOLOGICAL SITUATION

      EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT OCTOBER 06, 2019<br /> Monday, October 07, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,205, of which 3,091 are confirmed and 114 are probable. In total, there were 2,142 deaths (2028 confirmed and 114 probable) and 1006 people healed.<br /> 363 suspected cases under investigation;<br /> 1 new confirmed case at CTE in North Kivu at Oicha;<br /> No new confirmed deaths<br /> 2 people healed from Butembo CTE;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

      NEWS

      7 people healed from Ebola Virus Disease released Monday at Komanda CTE<br /> - A total of 7 people cured of Ebola Virus Disease were released on Monday October 7th at the Ebola Treatment Center (ETC) in Komanda. ;<br /> - This is 4 people from Mambasa and 3 cases from Komanda Health Zone to whom discharge certificates were given by the director of this Ebola Treatment Center<br /> - This certificate of discharge bears as inscription: "On the date of issue of this document the bearer of this certificate does not present any risk of contaminating other people, because his test was negative for the Ebola virus disease. He / she is thus DECLARE GUERI (E) . His current state of health is not a danger to the community. That is why he / she can return to his household and his professional environment to continue the daily activities. The family, the community and the authorities are asked to welcome him to promote his social integration ".

      VACCINATION

      • Continuation of vaccination around the confirmed case of 04 October 2019 in the Tenambo Health Area in Oicha, North Kivu;
      • Continuation of the vaccination of newly recruited front-line staff at the General Reference Hospitals of Katwa and Kyondo in North Kivu;
      • Since vaccination began on 8 August 2018, 234,693 people have been vaccinated;
      • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

      MONITORING AT ENTRY POINTS

      • Since the beginning of the epidemic, the total number of travelers checked (temperature increase) at the sanitary control points is 103,167,809 ;
      • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

      1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
      2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
      3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
      4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
      5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.
    2. On 2019-10-17 18:36:39, user GuyguyKabundi Tshima wrote:

      EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS OF OCTOBER 15, 2019

      Wednesday, October 16, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,227, of which 3,113 are confirmed and 114 are probable. In total, there were 2,154 deaths (2040 confirmed and 114 probable) and 1038 people healed.<br /> 530 suspected cases under investigation;<br /> 3 new confirmed cases, including:<br /> No cases in North Kivu;<br /> 3 in Ituri in Mandima;<br /> 1 new confirmed death, of which:<br /> 1 community death in Ituri in Mandima;<br /> No confirmed deaths;<br /> 2 people healed from the CTE in Ituri in Mambasa;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

      NEWS

      The state of play of the response at the center of an interview in Goma between the Technical Secretary of the CMRE and the United Nations Emergency Coordinator for Ebola<br /> - The Technical Secretary of the Multisectoral Committee on Epidemic Response to Ebola Virus Disease (ST / CMRE), Prof. Jean Jacques Muyembe Tamfum, granted a hearing on Wednesday, October 16, 2019 in Goma to the United Nations Emergency Coordinator for Ebola;<br /> - During their meeting, the two personalities discussed the state of play of the response to the 10th Ebola Virus Disease outbreak and the security situation in the areas affected by this epidemic;<br /> - It should be noted that the 10th Ebola epidemic has been taking place in the Democratic Republic of the Congo in areas of armed conflict, particularly in the provinces of North Kivu and Ituri, for more than a year;<br /> - Some time before this meeting, the technical secretary of the Multisectoral Committee for the Response to the Ebola Virus Disease Epidemic (ST / CMRE), Prof. Muyembe Tamfum, who is currently staying in Goma, North Kivu to inquire about the evolution of the response, chaired the morning meeting of the general coordination of the Ebola response to the epidemic.

      Pygmies at Mahombo camp in Mambasa territory in Ituri pledge to fight Ebola Virus Disease

      • The pygmies residing in Mahombo camp located more than 30 minutes walk from the main road from the village Nyangwe in the territory of Mambasa in ITURI, pledged Tuesday, October 15, 2019 to fight against Ebola by raising alerts with teams of the response;<br /> This commitment is the result of awareness raising by the Community Risk and Commitment (CREC) teams for 79 pygmies about the generalities of the Ebola virus disease, its methods of prevention and contamination;<br /> Pygmies have, for this purpose, asked for hand washing kits to break the chain of transmission of the Ebola virus in their respective communities.

      VACCINATION

      • Since vaccination began on 8 August 2018, 238,700 people have been vaccinated;
      • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

      MONITORING AT ENTRY POINTS

      • The Governor of North Kivu, Carly Nzanzu Kasivita accompanied by a strong delegation, visited Maboya Control Points (PoCs) in Kalunguta and Kangote in Butembo in North Kivu Province;
      • The providers of the Mususa Point of Control (PoC) in Butembo, North Kivu, in collaboration with the Ndondo Primary School and the Kyambogho School Complex, participated in a mass sensitization session (travelers and riverside population) under the theme " All Eliminate Ebola Virus Disease "on International Handwashing Day;
      • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 106.625.956 ;
      • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

      1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
      2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
      3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
      4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
      5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.
    3. On 2019-11-17 04:20:48, user GuyguyKabundi Tshima wrote:

      EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT NOVEMBER 15, 2019<br /> Saturday, November 16, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,292, of which 3,174 are confirmed and 118 are probable. In total, there were 2,195 deaths (2077 confirmed and 118 probable) and 1070 people healed.<br /> • 517 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths of confirmed cases have been recorded;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.

      NEWS

      Goma opens leadership capacity building workshop for Ebola epidemic response to Ebola Virus Disease.

      • The coordinator of the epidemic response to Ebola Virus Disease in North and South Kivu Province and Ituri, Prof. Steve Ahuka Mundeke, opened this Saturday, November 16, 2019 in Goma North Kivu a workshop on building the capacity of actors involved in the response against Ebola;<br /> • For four days, participants, coordinating and sub-coordinating officers from the response, the Ministry of Health, the World Health Organization (WHO), national security, CDC and DFID will be equipped with management skills epidemics before, during and after the tenth epidemic of Ebola Virus Disease, especially in the event of any outbreak;<br /> • According to Prof. Ahuka, this workshop will not only benefit this epidemic, but will help, through acquired skills, to cope with other epidemics or other crises in a collective and individual way. " Each participant will be able to use these skills in his daily life ," he concluded;<br /> • This training for the response officers, from 16 to 20 November 2019, is organized by the Ministry of Health in collaboration with WHO with funding from UKaid from the British people.

      VACCINATION

      • 93 people were vaccinated with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two Health Zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 252,835 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine complements the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this outbreak, manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. It has recently been approved.

      MONITORING AT ENTRY POINTS

      • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 117,333,420 ;<br /> • To date, a total of 112 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

      1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
      2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
      3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
      4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
      5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.
    4. On 2019-11-30 16:39:58, user Guyguy wrote:

      EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 26, 2019<br /> Wednesday, November 27, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,304, of which 3,186 are confirmed and 118 are probable. In total, there were 2,199 deaths (2081 confirmed and 118 probable) and 1077 people cured.<br /> • 366 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths among confirmed cases;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.

      NEWS

      Closure of training of Ebola Rapid Response Teams in Goma

      • The Ebola response coordinator for the Ebola response to operations, Dr. Luigino Mikulu, closed on Wednesday 27 November 2019 the training of Rapid Response Teams (RRTs), composed of units of the Armed Forces. (FARDC) and the Congolese National Police (PNC), on the Ebola virus disease that took place in Goma, capital of North Kivu Province from 22 to 26 November 2019;<br /> • For Dr. Luigino, this team is the first in the Rapid Response Teams to be composed of elements from other sectors, such as those of the Ministries of Defense and Security and the Ministry of the Interior;<br /> • This training aligns with the vision of the Technical Secretariat of the Multisectoral Ebola Virus Disease Response Committee (ST / CMRE), through the overall coordination of the response, to expand its mixed and multidisciplinary teams available and able to intervene 24 hours a day, 7 days a week and everywhere, where they will be deployed, not only for the response to this epidemic to Ebola Virus Disease, but also for other epidemics;<br /> • This training was a pride for WHO to accompany the Ministry of Health in order to capitalize the capacity building of FARDC and PNC units in public health;<br /> • The participants, in turn, reassured the overall coordination of the response, the Ministry of Health and all those who contributed to the delivery of this training, particularly to WHO and all facilitators, to be faithful disciples in the field by putting into practice all the notions learned during these sessions;<br /> • At the end of this training, the thirty participants, including the facilitators, received a participation certificate.

      VACCINATION

      • Despite the tense situation of the city of Beni, a vaccination ring was opened around the confirmed case of 24 October 2019 in the Kanzulinzuli Health Area of the General Reference Hospital;<br /> • 724 people were vaccinated, until Tuesday, November 26, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,247 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.

      MONITORING AT ENTRY POINTS

      • Sanitary control activities are disrupted in the towns of Beni and Butembo in North Kivu province following demonstrations by the population which decries killings of civilians;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 121,159,810 ;<br /> • To date, a total of 109 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

      1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
      2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
      3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
      4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
      5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.
    1. On 2020-04-18 21:04:02, user Katri Jalava wrote:

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

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

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

    1. On 2020-02-28 08:19:07, user iraq2010 wrote:

      hi sir,<br /> Please share data for the purpose of developing the algorithm.I am a researcher in the field of deep learning especially in classification and CNN algorithms..<br /> Thanks for help the world

      falahgs07@gmail.com

    1. On 2021-10-17 14:04:46, user BouncingKitten wrote:

      The article mentions "All data is available in the supplementary file" but doesn't provide a link to the file.

      Could you update the paper with a link to the supplementary file please?

    1. On 2020-03-08 10:12:04, user Mikko Salervo wrote:

      Hi,

      I might have missed it, but I could not find any details of the sensitivity analysis considering the february 1st outlier. It looks like the outlier has a considerable effect on the estimated trend between jan. 23- feb. 01, which might lead to an overestimation of the effectiveness of the centralized quarantine measured in comparison to the less rigorous measures during jan. 23-feb. 01.

    1. On 2020-03-13 16:56:55, user Brian Reed wrote:

      This is an important contribution to the literature. I have a few questions, the answer to which might make it even more valuable and better able to evaluate the rates of transmission as an effect of age. I take these mostly from carefully table 3 and table 1, but also from the 'transmission characteristics' subsection of the results section.

      Of the 1298 close contacts, it appears only 1155 actually had tests come back.

      There is evidently substantial overlap between the household (HH) contacts and the meal contacts, which makes sense. Certainly the travel contacts in general are coming back much lower. The question is, where do the age groups stratify within these. I would imagine by far the close contacts with 0-9 and 10-19 are much more likely in the HH, as well as the "often" category" of contact frequency, as there is a much less likelihood of having co-travel and co-non household meals with kids for the substantial majority of your initial cases (except for maybe the 4 who were kids). I suspect this may skew the conclusion that the rates of transmission for these two younger age groups are similar to older groups. I suspect likewise that the substantial portion of the travel negatives are with older age groups. I think performing the age analysis, or at least presenting the data, for each age group for the HH, travel, meal, and contact frequency subgroups would be helpful. I am aware that the n for some of these subgroups might be too low to allow for a real analysis, but then that is part of my point...<br /> Also, there is a substantial gender difference in those infect among close contacts, with females having a far greater % infection rate (almost double!). Similarly to the age effects, stratifying this gender ratio by age as well as close contact type would be of benefit.

      I hope you find my comments constructive and can address them. I still think children may be somewhat more resistant, although less so than before i read this preprint, and would like to know if I should adjust my view further still.

      Thanks!

    1. On 2021-07-22 18:07:27, user Ken Jacobie wrote:

      What was the average age and INNATE IMMUNE SYSTEM STATUS of these 167 person in this study? How many were CHEMOTHERAPY recipients etc...

    1. On 2020-05-14 15:31:20, user Emanuel Papadakis wrote:

      At the statistical level there are two major flaws: What are you using the chi-sq test for? You test a hypothesis. State the hypothesis. Your data for families B and C show rather random infections. Given the 14 day window of symptoms and the date of the start of the lock down the members of the B and C families may have been infected randomly outside of the restaurant. Also, why are the stories of all of these people accurate? You do have something to say but since you do not state the two hypothesis for which you test. Also your table at the end violates the assumptions for the test. The main assumption is independence and these people belong to families so the number of patients in total, namely 5 does not constitute 5 independent cases. Honestly, you try to establish causality and this is difficult because you have families. But your work despite these setbacks is interesting at the exploratory level. But you have no statistical significance as you treat your data because tests can be applied under certain conditions.

    1. On 2021-11-04 03:14:20, user Hiromichi Suzuki wrote:

      We thank you for your comments, The reagent was currently approved in October, 2020. We changed the year of approval from 2021 to 2020, which is the mistake of description.

    1. On 2020-03-28 22:38:39, user Sinai Immunol Review Project wrote:

      Summary of Findings: <br /> - Prospective cohort of 67 patients, clinical specimens taken and follow-up conducted. <br /> - Viral shedding, serum IgM, IgG antibody against NP evaluated and correlated to disease severity and clinical outcome <br /> - Viral RNA levels peaked at 1 week from febrile/cough symptom onset in sputum, nasal swabs, and stool samples. Shedding ranged from 12-19 days (median ranges) and was longer in severe patients. <br /> - IgM and IgG titers stratified patients into three archetypes as ‘strong vs weak vs non-responders’. Strong responders (with higher IgM/IgG titers) were significantly higher in severe patients.

      Limitations (specific for immune monitoring <br /> - Patient cohort is small for such a study and no individuals who were asymptotic were included; thus we cannot clearly interpret antibody titer associations with disease severity without "immunity" response.<br /> - Not clear if stool RNA captured from live infection in intestine/liver or from swallowed sputum. Transmission electron microscopy (TEM) carried out on sputum samples as proof of concept, but not stools. TEM unreasonable for actual clinical diagnosis. <br /> - Several patients had co-morbidities (such as pulmonary and liver disease) that were not accounted for when tracking antibody responses. Viral kinetics and IgM/IgG titers in subsets of patients with underlying conditions/undergoing certain medication would be informative.

      Relevance (specific for immune monitoring) <br /> - Three archetypes of antibody response to SARS-CoV-2 with different disease progression and kinetics is useful to stratify patients, and for future serological tests.

      • Strong spike-IgG levels often correlate with lymphopenia and CoVID-19 disease severity (https://doi.org/10.1101/202... ), similar to macaque studies in SARS (1). It would be critical to see if anti-NP or anti-Spike IgG antibodies for SARS-CoV-2 also elicit similar detrimental effects before clinical use.

      References: <br /> 1. Liu L, Wei Q, Lin Q, Fang J, Wang H, Kwok H, et al. JCI Insight 2019; 4(4): pii: 123158. <br /> Doi: 10.1172/jci.insight.123158

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

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

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

    1. On 2020-06-04 17:10:24, user Mandy Lyons wrote:

      "only 37.4% of suspected SARS-CoV-2 patients seroconverted"<br /> 1) What are the criteria for suspected SARS-CoV-2 patients?

      2) Do these suspected cases have SARS-CoV-2, or do they have an infection which mimics SARS-CoV-2?<br /> 3) Is the test testing for the test? I.e. is there something functionally different in the infection causing presumed cases which, if it actually is SARS-CoV-2, would cause the antibody test to be inaccurate?<br /> 4) Is there another illness circulating which mimics SARS-CoV-2 which has heretofore not been identified?<br /> 5) Is there any follow-up or investigation on these negative antibody cases in both the confirmed and suspected cases?

    2. On 2020-05-11 08:25:11, user M.E.Valentijn wrote:

      The assumption that a neutralizing antibody IgG titer of 160 is sufficient to produce immunity may be overly optimistic, as it's based on a case study of one recovered patient who had mild symptoms - and her titer was much higher on Day 20 after symptom onset, reaching 1,280.

    1. On 2020-06-07 05:04:06, user Marm Kilpatrick wrote:

      This is a very interesting study. There are several important details that aren't clear from the methods and data presented that would help in understanding the patterns:<br /> 1) When were household individuals tested for viral RNA? After the first person in the household became asymptomatic? If children are less likely to be symptomatic, they could be the primary case but not tested until after they infect their household member and that person develops symptoms which could be quite a long time after the child was infected (at the least, an average of 5.5 days after being infected). Given that sensitivity by swab decreases quickly with days since symptom onset, this by itself could lead to an underestimate of infection in children.<br /> 2) Are there data on viral loads? This would help greatly in supporting or refuting the potential infectiousness of children.<br /> Thank you,<br /> marm

    1. On 2020-06-07 17:05:34, user Dr Shyamapada Mandal wrote:

      Dear authors,<br /> Nice presentation; but before lockdown I, India adopted some containment measures that are required to be reflected in your work. Plus the current situation is different. <br /> Thanks,<br /> Dr. Shyamapada Mandal, University of Gour Banga, Malda-732103, West Bengal.

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

      The authors fail to declare potential COI.

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

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

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

    1. On 2020-05-07 04:29:09, user Paul Bollyky wrote:

      Interesting paper but it's not clear to me what link there is to hyaluronan in these data. Hyaline membranes are made up of dead cells, surfactant, and proteins - not HA. HA staining and other specific tests would be need to be done to support the argument that HA is present and responsible for the disease manifestations of COVID-19.

    1. On 2020-05-07 21:12:07, user helgarhein wrote:

      Would you please link the outcomes of covid illness (mild, severe, death) to 25(OH)D? I imagine lowest vitamin D levels linked to worst outcomes, like in other studies. Thanks

    1. On 2020-05-08 13:26:30, user Jamie Rosenblum Lichtenstein wrote:

      Thanks for the contribution. In your abstract, you state " 5875-9738 more deaths in New York State (168-213% more) (95% CI (14502, 18365) vs. 8627 COVID-19 deaths)." "(168%-213% more) should either be "(168%-213% of expected)" or "(68-113% more)". I would argue that the former is clearer.

    1. On 2020-05-08 19:29:54, user vinu arumugham wrote:

      Here's why famotidine works.

      Immunological mechanisms explaining the role of IgE, mast cells, histamine, elevating ferritin, IL-6, D-dimer, VEGF levels in COVID-19 and dengue, potential treatments such as mast cell stabilizers, antihistamines, Vitamin C, hydroxychloroquine, ivermectin and azithromycin

      https://doi.org/10.5281/zen...

      My comment posted in the Annals of Internal Medicine:<br /> Please see comments section:<br /> https://annals.org/aim/full...

    1. On 2020-05-08 22:29:12, user Jessica wrote:

      This reports a high proportion of isolated BA families with putatively causal large effect alleles. This proportion is higher than expected for families with isolated BA but not necessarily higher than expected for families with syndromic BA. It would be helpful for the authors to provide further detail about the specific ascertainment criteria and phenotyping performed on each proband and their parents, as well as whether any families were multiplex, especially for those with biallelic candidate variants, and if that family history is consistent with the mode of inheritance reported for each family's candidate gene.

    1. On 2020-05-11 14:50:43, user Quant wrote:

      I published an article Apr 26th with a similar theme that may interest readers. I described this as a Jensen's Inequality effect. It can apply to any source of heterogeneity including population density. Its good to see progress like this paper towards a more nuanced understanding of the turning point of an epidemic. <br /> https://www.linkedin.com/pu...

    1. On 2020-05-11 18:13:35, user Dianelos Georgoudis wrote:

      The IFR is very sensitive to the age distribution of a country, so the same model can produce an IFR varying from 0.3% for Pakistan to 1.4% for Italy (and 0.6% for the world). So I don't understand what the 0.75% value in this paper even means.

    1. On 2020-05-12 15:25:42, user Francois Alexandre wrote:

      I believe that there is another major limitation for this work, that should be at least acknowledge by the authors in the study limitation section: the R0 of 3.1 they used in the study is the R0 calculated at the beginning of the lockdown in France. Yet, the R0 during the middle of March, in the ascending phase of the outbreak, could be very different at that time. The authors state that this R0 is consistent with those observe in China during the ascending phase of the outbreak during January. However, R0 of a given virus is usually not stable across region and time (depending on several factors not restricted to temperature, such as humidity, weather, natural immunity due to vitamin D...). For example, the other human coronavirus have a R0 below 1 during summer in France, but the R0 increases during winter. And they also have different dynamics with some peaking in november, while some peaking in February. Furthermore, in early March, some observations in other countries (Brazil, West Africa) have underlined lower transmission rates compared with that observed in the countries located in the latitude 25-55° (Europe, USA). Therefore, serious doubts exist that the R0 of March will still be the same at May in France after the lockdown, without taking into account the potential unknown natural dynamic of the outbreak that has been masked by the lockdown and other procedures to slow the outbreak.

    1. On 2020-05-12 17:11:33, user Sui Huang wrote:

      Hi Anne (et al) - nice, heroic work! 2 quick questions as this work inspires similar approaches for scaling up community testing...:<br /> (1) Have you examined longer transports, more than the 5hrs @RT, and on ice, or even frozen for a longer time?<br /> (2) Have you tried to skip the RNA isolation step and do qPCR directly in the saliva as others have done?<br /> Thank you