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

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

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

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

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

https://covid2019system.com/

On 2020-04-08 15:02:17, user Dr. Noc wrote:

I think that we have to be careful to not interpret these results the wrong way. We know that older patients are at higher risk of mortality. By selecting for patients who have recovered from disease, the patient group may be biased toward those who had stronger production of nAbs (especially in the most at-risk group).

That is to say that, although it may appear that higher titers of nAbs are correlated with the groups that tend to have more severe disease outcomes, that doesn't necessarily mean that nAbs are contributing to the severity of outcomes, but rather that they may reflect a "survivorship" type of bias.

On 2020-04-08 18:01:50, user Terry McInnis wrote:

What are LabCorp and Quest using? Are they using the same 9 probes on their PCR tests?

On 2020-04-10 20:14:05, user laurencerowe wrote:

The UK appears to be misclassified in this study as 'currently mandated'. It phased out routine BCG vaccination in 2005.

See: https://www.nhs.uk/conditio...

On 2020-04-12 00:48:21, user Oleg Gasul wrote:

I am not sure about data correctness from the countries Turkmenistan, Uzbekistan and Kazakhstan, but all of them have very small number of cases (event zero in Turkmenistan).

But if we take a look on the map http://www.bcgatlas.org/ there is information that all of them have "Multiple BCG". That I understood the BCG vaccination is carried out several times (After birth, 6-7 yrs and 15 yrs).

On 2020-03-31 05:51:15, user Dmitry Shiryapov wrote:

Very interesting and promising speculations are reflected in the article. Definitely, some amendments should be done later, in conjunction with the pandemic development in Russian Federation, as a successor of Soviet Union. In any case, the authors have revealed a fertile soil for a number of publications in the future.

On 2020-04-01 01:59:42, user T2000q wrote:

Very interesting analysis of possible correlation between COVID-19 mortality rates and countries vaccination policies. However, it would be much more convincing to see proportion of BCG-vaccinated and non-vaccinated patients, who died of COVID-19. Not sure if such vaccination data exists in different countries.

On 2020-04-02 16:41:11, user Emily MacLean wrote:

My colleagues and I are epidemiology PhD students who focus on TB, and we wrote a journal club style critique of this paper. There are serious limitations with this paper that must be taken into account when considering its findings. <br /> https://naturemicrobiologyc...

On 2020-04-03 00:18:23, user Alessandro Crimi wrote:

Interesting, but you should also correlate with geographic accessibility to airports connecting main epidemic epicenters. I suspect that that's the main factor, and the BCG policies are confounding factors. Also you should discuss in the limitations about the fact that elderly in Italy and Spain have the BCG vaccination

On 2020-05-03 18:38:20, user nomad monkey wrote:

In this chart, the circle colors indicate the BCG vaccine policy for different countries. The circle locations are plotted according to the the median age and % urbanization of the population. The circle size is proportional to covid-19 deaths per capita. As we have all noticed, the older and more urbanized populations tend to have greater per capita covid deaths (i.e. bigger circles). But notice how huge the circles are for the countries that don't do universal BCG (green & pink circles), as compared to similarly aged & urbanized northern Asian countries that have universal BCG policies (blue circles).

Ecuador strongly supports the the BCG theory, as Ecuador has comparatively high per capita covid deaths for a relatively young and less urbanized population. And Ecuador (pink circle) doesn't do universal BCG vaccination like the rest of South Amercia (blue circles).

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

On 2020-04-17 23:54:51, user David Hasenford wrote:

A lot of misguided comments here. 2.49% to 4.16% population prevalence is not "herd immunity"

On 2020-04-28 04:37:59, user Choplifter wrote:

I applaud the authors for publishing this study. It is not without its flaws, obviously you can pick apart whether the sample was reprsentative of the community given the limited way testing candidates were solicited, but it is important to get tests like this out to the public quickly rather than wait months to get statistically perfect data. I suspect the estimate of fatality rate they give is a little low, but the scale is consistent with similar studies out of NYC and elsewhere, all suggesting that the fatality rate from COVID-19 is far, far, far less than the terrifying 5% that continues to be touted on the CDC website and by people who support contined lockdowns. The real rate is likely well under 0.4%, making it worse then seasonal flu (even the historically virulent 2017-2018 flu season) but still orders of magnitude less than the 5% Armageddon numbers that were used to scare the public into accepting complete lockdowns and the widespread ruin to economies and livelihoods, that they caused.

On 2020-05-01 10:16:00, user mendel wrote:

The specificity trials on page 19 are not normal.<br /> 7 trials show 100%, with N=30,70,1102,300,311,500,99, sum 2412.<br /> The 6 remaining trials:

368/371 = 99.2% (97.7-99.8)<br /> 198/200 = 99.0% (96.4-99.9)<br /> 29/31 = 93.6% (78.6-99.2)<br /> 146/150 = 97.3% (93.3-99.3)<br /> 105/108 = 97.2% (92.1-99.4)<br /> 50/52 = 96.2% (86.8-99.5)

Pooling these, I get 896/912=98.3% (97.2-99.0).

"We use the pooled test performance based on the available information:<br /> Sensitivity: 82.8% (exact binomial 95CI 76.0-88.4%)<br /> Specificity: 99.5% (exact binomial 95CI 99.2-99.7%)"

There is no trial that has exactly 1 false positive. There are 3 <br /> trials that don’t have 99.5% in the 95% CI (4 trials if you include <br /> 1102/1102). There is no trial that falls inside the 99.2-99.7 range (one<br /> straddles it). The specifity range they’re using is an empty space <br /> between the values that the trials are actually at. This is not a normal distribution.

187 samples had loss of smell and taste in <br /> the past 2 months. This is a very specific indicator for Covid-19, ~70% <br /> of patients (well, 33,9–85,6%, depending on the study, e.g. <br /> Mons/Belgium, Heinsberg/Germany) have that, and I don’t think this kind <br /> of nerve affliction has been reported for any other common illness. Yet <br /> only 11% of these samples test positive. For the 59 more recent samples,<br /> it’s 22%.

This looks like the prevalence this study should have measured is <br /> 267/3330 = 8%, and the test failed to pick up on that. It would fail to <br /> pick up on recent infections, because they wouldn’t have seroconverted <br /> (created enough antibodies) yet, and it would fail to pick up on <br /> infections that happened too long ago (because the antibody levels would<br /> have fallen off below the sensitivity of this test). This study really <br /> needed a more sensitive test, like an ELISA, which is actually available<br /> at Standford, and is able to detect much lower levels of antibodies.

This kit has not been validated against people who had the infection a month ago.

The presence of false positives is an indication that cross-reativity <br /> with outher cold viruses exists. If you test a sample with few people <br /> who haven’t had a severe cold recently, which probably includes most <br /> samples taken of people who check into the hospital for elective <br /> surgery, or samples taken in the summer months, you get an optmistic <br /> sensitivity that does not apply to the general population in early <br /> spring.

The WHO Early investigation protocol (Unity protocol) for the <br /> investigation of population prevalence mandates the use of an ELISA <br /> test, or the freezing of samples until a time when such a test becomes <br /> available. The WHO does not endorse the use of lateral flow assays for <br /> this kind of testing.<br /> —-<br /> P.S.: No study that does not measure prevalence in the older <br /> population where the majority of deaths occurs should speak on fatality <br /> rates. This study had 2/167 positives in the age 65+ population, that’s <br /> 0.1-4.3% (95% CI), a 30-fold spread, and hardly a representative sample,<br /> since I don’t expect residents from care homes were able to attend the <br /> drive-through testing.

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

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

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

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

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

On 2020-04-24 14:40:59, user Tomas Hull wrote:

"New York antibody study estimates 13.9% of residents have had the coronavirus, Gov. Cuomo says"<br /> When false negatives were to be included - those who have undetectable levels of antibodies, mainly young population - it could mean that 30%, or more people in NY already have the antibodies...

The study as well as Dr. John Ioannidis, Dr. Jay Bhattacharya, who have gone public with these findings, stand vindicated.

https://www.cnbc.com/2020/0...

Will herd immunity be achieved by the end of summer, or earlier, as predicted by another brilliant scientist, Dr, Wittkowski? It remains to be seen...

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

On 2020-05-05 14:08:15, user buzzbree wrote:

Beyond the seroprevelance conclusions of the study which are widely discussed, another very important issue that needs to be clarified by the authors is if the study fully adhered to Good Clinical Practice (GCP) standards. It is highly concerning that in the rush to publish the study- the authors may have not done so, and there is never an acceptable reason to do this- nor would an IRB agree.

To be fully compliant with GCP the Stanford IRB really needed to be informed of the the email Jay Bhattacharya's wife (https://www.buzzfeednews.co... sent to potential subjects. The email had several erroneous statements- that the test was FDA approved (Its not) and they would know if they were now immune from COVID-19 and would know that they were <br /> free from getting sick and could no longer spread the virus. These statements could have impacted subject safety by encouraging riskier behavior (i.e. ignoring social distancing) from the study subjects if they believed that the test was FDA approved and a positive result was <br /> definitive proof of protective immunity.

In the Buzzfeed article Dr. Bhattacharya has stated that he did not know about the email or <br /> approve of it, but he still had an ethical duty to report it to the IRB when he found out. There is only one line in manuscript stating that IRB approved the study- how the IRB addressed this email should be expounded upon in final manuscript given these new issues that have come to light. If the email was kept from the IRB, and instead the authors just capped enrollment from certain areas I do not see how that is compliant with GCP. These issues as they pertain to subject safety are not discussed in the manuscript- and they really should be.

Relevant GCP sections:

"3.3.8 Specifying that the<br /> investigator should promptly report to the IRB/IEC:(b) Changes <br /> increasing the risk to subjects and/or affecting significantly the <br /> conduct of the trial (see 4.10.2).

4.10.2 The investigator should <br /> promptly provide written reports to the sponsor, the IRB/IEC (see 3.3.8)<br /> and, where applicable, the institution on any changes significantly <br /> affecting the conduct of the trial, and/or increasing the risk to <br /> subjects.2 2

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On 2020-03-16 04:22:01, user Kankoé SALLAH wrote:

Great. Impedaance model is useful when you lake data about human mobiity.<br /> https://ij-healthgeographic...

On 2020-03-19 09:12:47, user ReviewNinja wrote:

ddPCR is a great technique, and can be of value and is less dependent of PCR-effciencies.<br /> However, if you have a qPCR slope -6.3 or -6.5, that means that there is a problem with your qPCR efficiency (<50%!!!).... So, a better primer set, optimized assay conditions, ... are necessary here. <br /> Furthermore, a one-step qPCR is compared with a two-step ddPCR. RT is a very variable factor. So if you want to compare qPCR with ddPCR, almost all factors need to be kept constant (and definitely RT), which is not the case here.

On 2020-03-30 18:56:07, user Preci Genome wrote:

https://www.medrxiv.org/con...<br /> Another related papers was also published recently.

On 2020-03-20 00:15:32, user RKM wrote:

The second paragraph in bold blue in this article says it all, "yet to be evaluated."

Is it 2 days, 9 days, do you really know?

The CDC is telling us this:<br /> https://www.cdc.gov/coronav...

But research tells us something completely different:<br /> https://www.news-medical.ne...<br /> If you have problems with the following link, then click on the link above and scroll down to the link that says, “The Journal of Hospital Infection.” <br /> https://www.journalofhospit...

On 2020-03-23 03:36:38, user Sinai Immunol Review Project wrote:

Main findings<br /> The authors performed single-cell RNA sequencing (scRNAseq) on bronchoalveolar lavage fluid (BAL) from 6 COVID-19 patients (n=3 mild cases, n=3 severe cases). Data was compared to previously generated scRNAseq data from healthy donor lung tissue.<br /> Clustering analysis of the 6 patients revealed distinct immune cell organization between mild and severe disease. Specifically they found that transcriptional clusters annotated as tissue resident alveolar macrophages were strongly reduced while monocytes-derived FCN1+SPP1+ inflammatory macrophages dominated the BAL of patients with severe COVID-19 diseases. They show that inflammatory macrophages upregulated interferon-signaling genes, monocytes recruiting chemokines including CCL2, CCL3, CCL4 as well as IL-6, TNF, IL-8 and profibrotic cytokine TGF-b, while alveolar macrophages expressed lipid metabolism genes, such as PPARG. <br /> The lymphoid compartment was overall enriched in lungs from patients. Clonally expanded CD8 T cells were enriched in mild cases suggesting that CD8 T cells contribute to viral clearance as in Flu infection, whereas proliferating T cells were enriched in severe cases.<br /> SARS-CoV-2 viral transcripts were detected in severe patients, but considered here as ambient contaminations.

Limitations of the study<br /> These results are based on samples from 6 patients and should therefore be confirmed in the future in additional patients. Longitudinal monitoring of BAL during disease progression or resolution would have been most useful.<br /> The mechanisms underlying the skewing of the macrophage compartment in patients towards inflammatory macrophages should be investigated in future studies.<br /> Deeper characterization of the lymphoid subsets is required. The composition of the “proliferating” cluster and how these cells differ from conventional T cell clusters should be assessed. NK and CD8 T cell transcriptomic profile, in particular the expression of cytotoxic mediator and immune checkpoint transcripts, should be compared between healthy and diseased lesions.

Relevance<br /> COVID-19 induces a robust inflammatory cytokine storm in patients that contributes to severe lung tissue damage and ARDS {1}. Accumulation of monocyte-derived inflammatory macrophages at the expense of Alveolar macrophages is known to play an anti-inflammatory role following respiratory viral infection, in part through the PPARg pathway {2,3} are likely contributing to lung tissue injuries. These data suggest that reduction of monocyte accumulation in the lung tissues could help modulate COVID-19-induced inflammation. Further analysis of lymphoid subsets is required to understand the contribution of adaptive immunity to disease outcome.

References<br /> 1. Huang, C. et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet 395, 497–506 (2020).<br /> 2. Allard, B., Panariti, A. & Martin, J. G. Alveolar Macrophages in the Resolution of Inflammation, Tissue Repair, and Tolerance to Infection. Front. Immunol. 9, 1777 (2018).<br /> 3. Huang, S. et al. PPAR-? in Macrophages Limits Pulmonary Inflammation and Promotes Host Recovery following Respiratory Viral Infection. J Virol 93, e00030-19, /jvi/93/9/JVI.00030-19.atom (2019).

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

On 2020-03-23 18:10:30, user Sinai Immunol Review Project wrote:

Summary:<br /> The authors of this study provide a comprehensive analysis of clinical laboratory assessments in 75 patients (median age 47 year old) hospitalized for Corona virus infection in China measuring differential blood counts including T-cell subsets (CD4, CD8), coagulation function, basic blood chemistry, of infection-related biomarkers including CRP, Procalcitonin (PCT) (Precursor of calcitonin that increases during bacterial infection or tissue injury), IL-6 and erythrocyte sedimentation rate as well as clinical parameters. Among the most common hematological changes they found increased neutrophils, reduced CD4 and CD8 lymphocytes, increased LDH, CRP and PCT

When looking at patients with elevated IL-6, the authors describe significantly reduced CD4 and CD8 lymphocyte counts and elevated CRP and PCT levels were significantly increased in infected patients suggesting that increased IL-6 may correlate well with disease severity in COVID-19 infections

Critical analysis:<br /> The authors performed an early assessment of clinical standard parameters in patients infected with COVID-19. Overall, the number of cases (75) is rather low and the snapshot approach does not inform about dynamics and thus potential relevance in the assessment of treatment options in this group of patients.

Importance and implications of the findings in the context of the current epidemics:<br /> The article summarizes provides a good summary of some of the common changes in immune cells inflammatory cytokines in patients with a COVID-19 infection and. Understanding how these changes can help predict severity of disease and guide therapy including IL-6 cytokine receptor blockade using Tocilizumab or Sarilumab will be important to explore.

On 2020-03-23 19:01:15, user Sinai Immunol Review Project wrote:

Summary:

Study on blood biomarkers with 80 COVID19 patients (69 severe and 11 non-severe). Patients with severe symptoms at admission (baseline) showed obvious lymphocytopenia and significantly increased interleukin-6 (IL-6) and CRP, which was positively correlated with symptoms severity. IL-6 at baseline positively correlates with CRP, LDH, ferritin and D-Dimer abundance in blood. <br /> Longitudinal analysis of 30 patients (before and after treatment) showed significant reduction of IL-6 in remission cases.

Limitations:

Limited sample size at baseline, especially for the non-severe leads to question on representativeness. The longitudinal study method is not described in detail and suffers from non-standardized treatment. Limited panel of pro-inflammatory cytokine was analyzed. Patients with severe disease show a wide range of altered blood composition and biomarkers of inflammation, as well as differences in disease course (53.6% were cured, about 10% developed acute respiratory distress syndrome). The authors comment on associations between IL-6 levels and outcomes, but these were not statistically significant (maybe due to the number of patients, non-standardized treatments, etc.) and data is not shown. Prognostic biomarkers could have been better explored. Study lacks multivariate analysis.

Findings implications:

IL-6 could be used as a pharmacodynamic marker of disease severity. Cytokine Release Syndrome (CRS) is a well-known side effect for CAR-T cancer therapy and there are several effective drugs to manage CRS. Drugs used to manage CRS could be tested to treat the most severe cases of COVID19.

Review by Jaime Mateus-Tique as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai

On 2020-03-26 02:27:01, user Cristian Orrego wrote:

Its a small sample, right, but it doesnt seem to unvalidate the study. The only thing that i think in this case (if i read it right) that could be wrongly interpreted would be the conclusion. Because the sample of the sick people was obtained in the hospitals, so maybe the O type doesnt have less chance to get the virus, but insted it has less probabilities of develop synthoms that get people into the hospitals. So maybe the virus attack them (O type) with less severity. New studies should get infected people from random tested people among the general population to confirm if the O type gets lower rates of infection or the O type gets lower rates of worsening sympthoms once infected.

On 2020-03-21 23:09:04, user Moevi wrote:

Do we have any information regarding the patient ethnicity?

Indeed, the authors have chosen to use a study published in 2015 looking at ABO distribution among the Han population in Wuhan (unfortunately i was not able to find this study). However, if my understanding of the ABO group system is correct the distribution of ABO antigen may vary a lot depending on the ethnicity.

On 2020-04-23 15:54:21, user MacS wrote:

Didn't notice this was discussed already so adding to the fray. It's well known and accepted Type O blood is also less susceptible to Malaria ( https://www.sciencedaily.co... "https://www.sciencedaily.com/releases/2015/03/150309124113.htm)") And for what it is worth, we know the Malaria drug has decent favorable results. I don't see the WHO drawing on this correlation in their study of COVID19 although they are or should have the goods on the blood type difference with Malaria and should be taking all of this into consideration in countries in Africa that have now acquired a larger group of Type 'O' blood (herd immunity?)

On 2020-03-26 05:18:54, user TreeHugginEnergyWonk wrote:

This is thrilling! People who have already been infected and cleared the coronavirus could donate their blood plasma immune factors to help those suffering more extreme cases of the disease! People could get back to work!

On 2020-03-26 18:01:31, user j2hess wrote:

The point is controlled rate of spread. This on-again off-again proposal reminds me uncomfortably of the sawtooth dynamcs of a predator-prey relationship. (The rabbits breed, coyote population grows until there are too many for the food supply, so there's a population crash of rabbits first and coyotes next.) There are other ways.

A British research group modeled the growth rate using graph theory. We're not a single uniformly-connected population; there are clusters of dense connections linked by fewer connections, and spread within is faster than spread without. The power law that results is a better fit than the standard exponential growth model.

So perhaps rather than on/off, you open up retail service businesses - hairdressers, coffee shops. You don't open the big venues - concerts, major league sports, mega-conferences. This provides a somewhat controlled spread of the virus, a more stable social environment, and less economic stress.

On 2020-03-27 12:25:01, user Boris Barbour wrote:

There is PubPeer commentary about this preprint:

https://pubpeer.com/publica...

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

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

On 2020-03-28 01:06:18, user Sinai Immunol Review Project wrote:

Summary: Analyzing the eGFR (effective glomerular flow rate) of 85 Covid-19 patients and characterizing tissue damage and viral presence in post-mortem kidney samples from 6 Covid-19 patients, the authors conclude that significant damage occurs to the kidney, following Covid-19 infection. This is in contrast to the SARS infection from the 2003 outbreak. They determine this damage to be more prevalent in patients older than 60 years old, as determined by analysis of eGFR. H&E and IHC analysis in 6 Covid-19 patients revealed that damage was in the tubules, not the glomeruli of the kidneys and suggested that macrophage accumulation and C5b-9 deposition are key to this process.

Limitations: H&E and IHC samples were performed on post-mortem samples of unknown age, thus we cannot assess how/if age correlates with kidney damage, upon Covid-19 infection. Additionally, eGFR was the only in-vivo measurement. Blood urea nitrogen and proteinuria are amongst other measurements that could have been obtained from patient records. An immune panel of the blood was not performed to assess immune system activation. Additionally, patients are only from one hospital.

Significance: This report makes clear that kidney damage is prevalent in Covid-19 patients and should be accounted for.

On 2020-03-28 20:30:39, user adycousins wrote:

In Table 1 the estimate for the UK peak daily Covid-19 fatalities is 260 and a peak date of 5th of April, however 260 people died in the last 24 hours in the UK. Events seem have overtaken this study before its even reached peer-review.

On 2020-03-30 14:54:38, user Emma Cairn wrote:

Data is not an object in itself. Data is sometimes profoundly affected by the political, social and economic environments.

1.There are differing political criteria for selecting who is tested in different countries. Some select only those with severe symptoms and some sample test over their country. Some tests are inaccurate and sometimes not enough test kits are distributed. Some testing centres are inconvenient and sometimes multiple tests to the same person are negative until nucleic acid high enough.

1. There is political variation in what constitutes a corona death. It is possible that some are only reporting it as corona if there is no underlying condition. Or in other words if some have a heart attack it is being listed as that rather than Corona. If some die out of hospital untested this is also not a Corona death.

3<br /> I suggest that if people in countries knew the true number there would be widespread panic and disruption, economic turmoil and political unrest.

Conclusion Unless standardisation of political, economic viewpoints there will be no standardisation of empirical data. Virus will only slow down when it has learnt how to live with us harmoniously.

On 2020-03-29 12:55:46, user Rosemary TATE wrote:

I'm about to submit a review for this - my first attempt on medrxiv although (as a medical statistician) I have vast experience. However, all I really needed to do was look at their Cherries checklist. It is very incomplete and missing many details of how the study was carried out. These checklists are very important and shouldn't be added as an afterthought.

On 2020-03-29 22:38:51, user Sinai Immunol Review Project wrote:

Key findings:<br /> This study investigated the profile of the acute antibody response against SARS-CoV-2 and provided proposals for serologic tests in clinical practice. Magnetic Chemiluminescence Enzyme Immunoassay was used to evaluate IgM and IgG seroconversion in 285 hospital admitted patients who tested positive for SARS-CoV-2 by RT-PCR and in 52 COVID-19 suspected patients that tested negative by RT-PCR. A follow up study with 63 patients was performed to investigate longitudinal effects. In addition, IgG and IgM titers were evaluated in a cohort of close contacts (164 persons) of an infected couple.

The median day of seroconversion for both IgG and IgM was 13 days after symptom onset. Patients varied in the order of IgM/ IgG seroconversion and there was no apparent correlation of order with age, severity, or hospitalization time. This led the authors to conclude that for diagnosis IgM and IgG should be detected simultaneously at the early phase of infection.

IgG titers, but not IgM titers were higher in severe patients compared to non-severe patients after controlling for days post-symptom onset. Importantly, 12% of COVID-19 patients (RT-PCR confirmed) did not meet the WHO serological diagnosis criterion of either seroconversion or > 4-fold increase in IgG titer in sequential samples. This suggests the current serological criteria may be too stringent for COVID-19 diagnosis.

Of note, 4 patients from a group of 52 suspects (negative RT-PCR test) had anti-SARS-Cov-2 IgM and IgG. Similarly, 4.3% (7/162) of “close contacts” who had negative RT-PCR tests were positive for IgG and/or IgM. This highlights the usefulness of a serological assay to identify asymptomatic infections and/or infections that are missed by RT-PCR.

Limitations:<br /> This group’s report generally confirms the findings of others that have evaluated the acute antibody response to SARS-Cov-2. However, these data would benefit from inclusion of data on whether the participants had a documented history of viral infection. Moreover, serum samples that were collected prior to SARS-Cov-2 outbreak from patients with other viral infections would serve as a useful negative control for their assay. Methodological limitations include that only one serum sample per case was tested as well as the heat inactivation of serum samples prior to testing. It has previously been reported that heat inactivation interferes with the level of antibodies to SARS-Cov-2 and their protocol may have resulted in diminished quantification of IgM, specifically (Xiumei Hu et al, https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.03.12.20034231v1)").

Relevance:<br /> Understanding the features of the antibody responses against SARS-CoV is useful in the development of a serological test for the diagnosis of COVID-19. This paper addresses the need for additional screening methods that can detect the presence of infection despite lower viral titers. Detecting the production of antibodies, especially IgM, which are produced rapidly after infection can be combined with PCR to enhance detection sensitivity and accuracy and map the full spread of infection in communities, Moreover, serologic assays would be useful to screen health care workers in order to identify those with immunity to care for patients with COVID19.

On 2020-03-30 02:38:57, user Sinai Immunol Review Project wrote:

Summary of Findings: <br /> -Transcriptomic analysis using systems-level meta-analysis and network analysis of existing literature to determine ACE2 regulation in patients who have frequent COVID-19 comorbidities [eg- cardiovascular diseases, familial pulmonary hypertension, cancer]. <br /> - Enrichment analyses indicated pathways associated with inflammation, metabolism, macrophage autophagy, and ER stress. <br /> - ACE2 higher in adenocarcinoma compared to adjacent normal lung; ACE2 higher in COPD patients compared to normal. <br /> - Co-expression analysis identified genes important to viral entry such as RAB1A, ADAM10, HMGBs, and TLR3 to be associated with ACE2 in diseased lungs.<br /> - ACE2 expression could be potentially regulated by enzymes that modify histones, including HAT1, HDAC2, and KDM5B.

Limitations:<br /> - Not actual CoVID-19 patients with co-morbidities, so interpretations in this study need to be confirmed by analyzing upcoming transcriptomics from CoVID-19 patients having co-morbidity metadata. <br /> - As mentioned by authors, study does not look at diabetes and autoimmunity as risk factors in CoVID-19 patients due to lack of data; would be useful to extend such analyses to those datasets when available. <br /> - Co-expression analysis is perfunctory and needs validation-experiments especially in CoVID-19 lung samples to mean anything. <br /> - Epigenomic analyses are intriguing but incomplete, as existence of histone marks does not necessarily mean occupancy. Would be pertinent to check cell-line data (CCLE) or actual CoVID-19 patient samples to confirm ACE2 epigenetic control.

Importance/Relevance:<br /> - Study implies vulnerable populations have ACE2 upregulation that could promote CoVID-19 severity. Shows important data-mining strategy to find gene-networks associated with ACE2 upregulation in co-morbid patients. <br /> - Several of the genes co-upregulated with ACE2 in diseased lung might play an important role in CoVID-19 and can be preliminary targets for therapeutics.<br /> - If in silico findings hold true, epigenetic control of ACE2 expression could be a new target for CoVID-19 therapy with strategies such as KDM5 demethylases.

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.

On 2020-04-01 22:22:34, user Sui Huang wrote:

Nice, important work. Question: Mechanical ventilation has been associated with increase of ACE2 expression in the lung post-mortem. Do you find support for this previous finding in your data?

On 2020-03-30 11:14:51, user Mark Pepin, PhD wrote:

The statement claiming "positive effects" of ARBs on morbitity/mortality is invalid given the nature of their study design. It should claim association only.

On 2020-04-29 19:07:05, user Sinai Immunol Review Project wrote:

Keywords: SARS-CoV-2, ACE-2, Renin-angiotensin system, Hypertension

Main findings: The authors analyzed clinical data obtained from COVID-19 patients and categorized them based on the antihypertensive drugs they were taking. They then investigated its association with morbidity and mortality of pneumonic COVID-19 patients. ARBs were found to be associated with a reduced risk of pneumonia morbidity in a total of 70,346 patients in three studies. They found that in the elderly (age>65) group of COVID-19 patients with hypertension comorbidity, the risk of severe disease was significantly lower in patients who were on ARB anti-hypertensive drugs prior to hospitalization compared to patients who took no drugs. Also, through their meta-analysis of the literature, the authors reported that ARB anti-hypertensive drugs were associated with a decreased risk of severe disease in elderly COVID-19 patients.

Critical Analyses:<br /> 1. Retrospective study with large potential for confounder bias. <br /> 2. Their inference that ARB is better than other anti-hypertensive drugs is based on literature met-analysis.<br /> 3. P-values could not be computed for some subsets because of very low/no patients in these categories(ref to table-1;ACEI, thiazide and BB)

Relevance: Anti-hypertensive ARB drugs taken by COVID-19 patients prior to entering the hospital may be associated with improved morbidity and mortality of pneumonia in elderly COVID-19 patients although confounders may bias results.

Reviewed by Divya Jha, PhD and edited by Robert Samstein, MD PhD, as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

On 2020-03-30 21:51:40, user Preci Genome wrote:

Digital PCR appears to be a very powerful tool to diagnose the infection of COVID-19.

On 2020-03-31 10:08:01, user Darren Dahly wrote:

There is now a statistical review for this paper here: https://zenodo.org/record/3...

On 2020-03-31 20:27:36, user Andrew Singer wrote:

Can the authors please check the validity of the first reference that is cited. It does not report SARS-CoV-2 in stool. It is a paper on: "Elagolix for Heavy Menstrual Bleeding in Women with Uterine Fibroids"

A second comment is that you state: 17 patients (23.29%) remained positive in feces after viral RNA was undetectable in respiratory tract, however, there were only 39 patients that initially tested positive for viral RNA in the stool, so it should be 17/39 (43.58%). Yes?

On 2020-03-31 22:30:20, user Aaron wrote:

While the author claims that "The data suggest that at least two strains of the 2020 SARS-CoV-2 virus have evolved during its migration from Mainland China to Europe", no such data is presented or referenced. The title of the piece should be changed to reflect that this is a hypothesis, not a finding established by any analysis found within the paper.

On 2020-04-01 18:24:50, user Editor wrote:

Were there any sex differences in mortality, as was seen in China?

On 2020-04-02 09:24:44, user Ákos Török wrote:

What do you think about this? If we pool an aliquot of e.g. 5 samples (collect swabs from 5 different persons in the same tube with transfer medium.) then extract RNA, then pool 10 such RNA samples? This would result in 50X pooling.

On 2020-04-02 10:24:38, user ansgarjohn wrote:

The output seems similiar to what Michael Levitt has observed. Here Netherland (growth rate slowing by 1% per day is the guesstimate) https://sinaas.blogspot.com...

On 2020-03-31 18:56:14, user Igor H. wrote:

I would suggest verifying the calculations. Data for Colorado do not fit.<br /> Here is the comparison of actual reported hospitalizations and your prediction for 3/18-3/29:

First column after date are actual hospitalizations (not new per day but all covid hospitalized patients on the day) reported by Colorado Dept of Public Health - https://covid19.colorado.go... - and the right column is your predicted "allbed_mean" which is supposed to be “Mean covid beds needed by day” (I assume that you mean number of beds needed on the particular date, not a cumulative number from the beginning – patients get discharged or die)

3/18/2020 26 158<br /> 3/19/2020 38 186<br /> 3/20/2020 44 268<br /> 3/21/2020 49 323<br /> 3/22/2020 58 455<br /> 3/23/2020 72 573<br /> 3/24/2020 84 716<br /> 3/25/2020 148 882<br /> 3/26/2020 184 1069<br /> 3/27/2020 239 1294<br /> 3/28/2020 274 1542<br /> 3/29/2020 326 1841

When I look closely, Allbed_mean on the day is the sum of (admis_mean) from the beginning to that day.

This is how you project ***new*** admissions (admis_mean) for the same time period:

69<br /> 28<br /> 88<br /> 56<br /> 137<br /> 124<br /> 149<br /> 178<br /> 209<br /> 242<br /> 278<br /> 317

This is also hugely overestimated and the numbers more resemble TOTAL number of hospitalized patients on the day.

Also, spotcheck for New York State does not match. See attache https://uploads.disquscdn.c... d images (prediction and actual reported number this morning)<br /> https://uploads.disquscdn.c...

It appears that (Allbed_mean) is only correct if 100% of cases need hospitalization, which is not the case in the US (it was the case in China). So, actual number of beds needed seems to be 20% of the predicted number, which much more closely corresponds with reported data.

Igor Huzicka

On 2020-04-02 22:35:05, user Yuri Utsunomiya wrote:

The companion app to this manuscript can be accessed at: https://www.theguarani.com.br/<br /> The source code is available at: https://github.com/adamtait...

On 2020-04-27 17:01:13, user Paul Floto wrote:

It should be worthy of research to examine whether copper compounds are as toxic to the virus causing COVID-19 as they are to poliovirus. Since the toxicity level of copper to humans is already well established, if a lower level is effective against viral protease, then drug development could be quite rapid.

A letter that appeared online recently in the New England Journal of Medicine demonstrated that the COVID-19 virus had a shorter life span on a copper surface than on many other materials.

Since copper has an essential role in human health, it might be possible that the growth of the COVID-19 virus is impacted by the copper level in the host organism. Copper levels vary significantly by diet, and are significantly reduced by even small quantities of molybdenum in the diet.

Widely varying rates of infection and death might be explained by variation in typical copper levels in the diet which would influence serum level of copper in blood and tissue. Has any measurement of serum copper level been made in patients with differing response to COVID-19 infection?

On 2020-06-05 13:21:52, user Arnar Palsson wrote:

Reference 6. Falconer D, M.T. Introduction to Quantitative Genetics, (London, 1996).

Has two authors, Douglas S. Falconer and Trudy F.C. Mackay

On 2020-04-29 17:12:43, user Deirdre wrote:

It isn't clear whether you are aiming to predict mortality or identify causal risk factors. There is a difference, they have distinct approaches. The title for the final figure is confusing, instead of "Survival by symptom onset", do you mean "Risk of mortality"? There are limitations in BMI as a proxy for total fat mass in elderly populations that may be underestimating the relationship of obesity, and is a notable limitation.

On 2020-05-01 00:11:26, user Dr. Amy wrote:

Most interesting differences from the Mexico cohort are that pregnancy is not a significant increased risk factor, and immunodeficiency isn’t specifically mentioned. Pretest probability (if you will) of obesity in U.K. 27.8%, 36.2% US, Mexico 32.4% so that could artificially lower comorbidity of obesity in U.K.

On 2020-05-05 17:25:01, user Hannah Sally wrote:

Are all patients included in the study, patients whom were admitted because of COVID-19 or does this cohort also include patients whom were admitted to hospital for other reasons but concurrently were diagnosed in hospital with COVID-19? I may have missed something, but not sure if this is clear in the methods. This could impact the overall hospital admission mortality statistic.

On 2020-05-04 00:32:57, user Lynn wrote:

I did not notice any specific outcome related to the asthma patients. Did I miss something?

On 2020-05-04 11:11:16, user Will Jones wrote:

What was the median number of days between admission and death?

On 2020-04-30 04:10:22, user Tom Turek wrote:

So.. how much Vit D3 is good? To get the optimum blood level of Vit.D3 of 60nano gms/mL of blood,we need either 5 minutes of sun a side, between 10am and 2pm in the lower latitudes. Longer time for darker skins.. or supplement with 8000IU of D3/d, BUT at t his high dose´ also Vit. K2 to stop calcium pumping into artery walls. )Ignore the outdated, idiotic RDA of 800iu of D3.. and avoid the synthetic, toxic D2 in nearly all multis.

On 2020-04-30 13:54:19, user Charles R. Twardy wrote:

Nice. As A. Kumar notes in Twitter, this is productive engagement rather than just critique.

Note: The result in the abstract & discussion seems to combine two estimates from the results section: the [0.27%, 1.72%] unweighted estimate and the [0.49%, 3.21%] using the original authors' re-weighting. Not sure if this is copy/paste error or deliberately using widest range.

On 2020-04-30 16:31:03, user Dr SK Gupta wrote:

Authors have reported the high prevalence of Mycobacterium Tuberculosis infection in Covid19. Authors have tried to portray not only the Higher prevalence of MTBI but also more severe and rapid progression of disease. However, since their findings are not in tune with observational data on the subject all across the world. Rather corona infection has been found to be low in South East Asia, Africa and other places where the tuberculosis is rampant. Also burden of Covid-19 has been highest in United States and Europe where the prevalence of Tuberculosis is low.

These Observations have prompted the scientist to look for the role of BCG vaccination/ past TB infection in prophylaxis and treatment of Covid 19.

Authors have erroneously relied upon use of Interferon gamma release assay (IGRA) to diagnose MTB Infection using a kit X.DOT-TB kits (TB Healthcare, Foshan, China). Not much has been described in article about the methodology used in these kits, but as the name suggests probably it is T-spot test which measures the number of IFN-?-secreting T cells via an enzyme-linked immunospot (ELISPOT) assay.<br /> Two types of IGRAs available, the QuantiFERON-TB Gold In-Tube test and the T-SPOT.TB blood test. Though both these tests are approved by the Food and Drug Administration as indirect tests for TB infection (including active disease) when used in combination with other medical and diagnostic evaluations. Since aging leads to a decline in the strength of immune responses, it is also argued that these tests loose their sensitivity with advancing age.

Overall Interferon gamma release assay (IGRA) has a poor sensitivity and specificity for the diagnosis of Tuberculosis.<br /> In patients with Non Tuberculous Mycobacterial Disease specificity of only 74% for infection and a relatively high indeterminate rate was found for QuantiFERON®-TB Gold(QTF) test assay with a sensitivity of 81.7 %. Hence the test is not able to discriminate between tuberculosis(TB) and non-tuberculous mycobacterial (NTM) disease with high degree of specificity.

The problem gets compounded even more in countries like China and India where the prevalence of TB is high and use of Tuberculin Testing and BCG vaccination is a routine and such cases have all the likelihood of being labelled as positive despite no active disease.<br /> Contrary to current practice Authors have also not used the available gold standards to define active TB based on either a positive Mycobacterium culture or a positive TB polymerase chain reaction/Gene expert/CBNAAT.

Not only that present investigators have also not describe any base line x-ray lung findings like cavitation, fibro-infiltration, lymph node enlargement, Spirometry based poor Lung function suggestive of tuberculosis in patients with positive MTBI or active tubercular disease which may have contributed to the rapid progression of superimposed pneumonia of Covid 19 in these patients.

In Covid-19 disease pathogenesis initially it is the role of Innate immunity mediated by Neutrophils Macrophages which mount a protective response. In tuberculosis Cell mediated immunity or the adaptive immunity involving T cells and B cells is at work. This has prompted world scientists to look for the role of BCG in treatment and prophylaxis of Covid-19. BCG Vaccine for Health Care Workers as Defense Against COVID 19 (BADAS) (NCT04348370) in USA and Brace trial by an Australian University are such attempts.

The current study needs the support of larger data which doesnot seem to be coming from other countries like India where TB is rampant. Till now the observations don’t support the hypothesis of increased susceptibility of TB patients for Covid-19 nor are there any indicators of more severe/ rapid progression of disease in patients with TB infection.

Dr S K Gupta <br /> Senior Consultant Physician <br /> Secretary Community Health Care Foundation<br /> Dr Prabhat Prakash Gupta <br /> Dr Mrs Praveen Gupta

References:<br /> 1.Comparison of the Sensitivity of QuantiFERON-TB Gold In-Tube and T-SPOT.TB According to Patient Age Won Bae,Kyoung Un Park,Eun Young Song,Se Joong Kim,Yeon Joo Lee,Jong Sun Park,Young-ae Cho,Ho Il Yoon,Jae-Joon Yim,Choon-Taek Lee,Jae Ho Lee <br /> Published: June 3,216 https://doi.org/10.1371/jou...<br /> 2. Sensitivity of the QuantiFERON-TB Gold test in culture-verified NTM disease and TB in a Danish setting Thomas Stig Hermansen, Vibeke Østergaard Thomsen, Pernille Ravn <br /> European Respiratory Journal 2012 40: P426; DOI:<br /> 3. https://clinicaltrials.gov/...<br /> 4. 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<br /> doi:10.1093/jac/dkaa114<br /> 5. Covid-19 coronavirus pandemic. https://www.worldometers.in...<br /> 6. 1. Mehta P. Mc Auley DF, brown M et al. Covid-19, consider cytokine storm syndromes and immunosuppression. Lancet. 2020. doi.org/10.1016/S0140-6736(...

1. Roitt I, Brostoff J, Male D. Immunology (Fifth Edition). Philadelphia: Mosby; 1998. ?

2. Wang L, Cai Y, Cheng Q, Hu Y, Xiao H. Imbalance of Th1/ Th2 cytokines in patients with pulmonary ?tuberculosis. Zhonghua Jie He He Hu Xi Za Zhi. 2002; 25 (9) : 535-537. ?

3. Collins FM. Cellular antimicrobial immunity. Crit Rev Microbiol. 1979;7:27–91. ?

4. Bretscher PA. An hypothesis to explain why cell-mediated immunity alone can contain infections by ?certain intracellular parasites and how immune class regulation of the response can be subverted. ?Immunol Cell Biol. 1992;70:343–351.

On 2020-05-01 01:23:45, user DAEYOUNG LIM wrote:

It's not clear how you did the following in your paper regarding the Google Mobility Reports data:<br /> "We aggregated these points to get a single mobility index per day for each trend chart."

On 2020-05-02 14:17:05, user ??? wrote:

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

On 2020-05-03 20:07:28, user PatriotsNE wrote:

This is the ONLY model 95% confidence interval gets SMALLER at one to three months out. You'd expect greater uncertainty for forecasts months out, but this model is the opposite (greater uncertainty in short-term, but less uncertainty in the long-term forecasts, with 100% certainty of zero cases in July.

On 2020-05-06 15:16:10, user Sinai Immunol Review Project wrote:

Summary: Using peripheral blood samples collected from 8 COVID-19 patients with moderate to severe acute respiratory distress syndrome (ARDS), the authors showed that COVID-19 patients exhibit lower CD3+ T cell counts as well as increased CD4:CD8 ratio. In addition to population analysis, PBMCs were stimulated with three pools of either overlapping peptides of SARS-CoV-2 spike (S) protein or HLA Class II or I predicted epitopes covering all viral proteins except S designed to activate CD4 and CD8 T cells, respectively. While stimulation of PBMCs with all three peptide pools led to detection and activation of SARS-CoV-2 specific CD4 and CD8 T cells, spike (S) peptide pool elicited the strongest response, indicating that the S surface glycoprotein is a strong inducer of both CD4 and CD8 T-cell responses. Phenotyping of activated T cells (CD4+CD69+CD137+ or CD8+CD69+CD137+) showed that the majority of activated CD4 T cells were central memory T-cells (CD45RA- and CCR7+) while activated CD8 T cells were mostly effector memory T cells (CCR7-) and terminally differentiated effector T cells. Cytokine analysis of cell culture supernatants from PBMCs stimulated by S-peptide pool led to a strong production of Th1 cytokines IFN?, TNF? and IL-2. Lastly, the authors profiled the kinetics of both humoral and cell-mediated response in four different time points using ELISA of virus-specific serum IgG and quantifying expression of cell surface markers induced by S peptide pool activation. Throughout the patients’ stay at the ICU, both levels of virus-specific IgG antibodies and frequencies of virus-specific CD4 cells increased significantly over time.

Limitations: A couple of additional assays done in parallel could have further strengthened the paper’s findings. Simultaneous profiling of cytokines from PBMCs could have easily answered whether these T cells which are capable of producing Th1 cytokines upon activation are indeed producing them in patients. Furthermore, it would have been informative to have added a couple of functional exhaustion markers (i.e. PD-1, Tim-3, etc.) and compare their expression between pre- and post-activation by S peptide pool—thereby addressing the effect of functional exhaustion in T cells reported in severe COVID-19 patients. Follow-up studies investigating which epitopes out of the S protein peptide pool elicited the most potent T-cell response would have yielded informative results for possible vaccine design efforts against the spike protein. Lastly, comparing the quality of virus specific T cells immunity between patients in ICU (the focus of the study) and patients with mild /moderate disease would have been very informative.

Significance of the finding: For the most part, the study design has been well established to answer the following questions: a) are there T cells reactive to spike (and other HLA-reactive) protein of SARS-CoV2 even in cases of COVID-19 with moderate to severe ARDS (which has been characterized with lymphopenia)? b) what are the phenotype and cytokine profile of CD4 and CD8 T cells upon activation? Answering these questions do advance the field’s understanding of T cell response to COVID-19 and add to much-needed effort to devise a vaccine against SARS-CoV2. Building on this article’s findings, perhaps future studies could perform mechanistic assays the function of T cells from COVID-19 patients in the context of systemic inflammation (i.e. adding IL-1, IL-6, TNF? in the culture media) as well as correlating epitope-specific immune response of patients with their clinical severity.

Review by Chang Moon as part of a project by students, postdocs and faculty at the<br /> Immunology Institute of the Icahn school of medicine, Mount Sinai.

On 2020-05-07 12:01:23, user Alex Cranberg wrote:

The authors’ conclusion about being far from herd immunity is based on the questionable assumption that the population is homogeneous. If population has variation in susceptibility herd immunity may be close or even reached. https://www.medrxiv.org/con...

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

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

On 2020-05-09 21:33:19, user christopher starling wrote:

What positive HCQ evidence does anyone have that provides usable scientific data and answers the same questions being asked here?

On 2020-04-24 23:54:28, user Gunnar V Gunnarsson wrote:

The conclution that HC causes higher risk of death is basically wrong due to a huge sampling bias. The problem lies in the fact that once people went on ventilators they where given HC or HC+AZ. This re-categorised the patients by increasing the number of high risk patients in the HC and HC+AZ groups making the No HC an invalid control group.

Before ventilation the statistics was like this: (Table 4 in paper)

HC: 90 - 9 (10.0%) deaths - 69 (76.6%) recover - 12 (13.3%) onto ventilation HC+AZ: 101 - 11 (10.9%) deaths - 83 (82.2%) recover - 7 (06.9%) onto ventilation No HC: 177 - 15 ( 8.4%) deaths - 137 (77.4%) recover - 25 (14.1%) onto ventilation

We see that death-rate is about the same for all groups but HC+AZ seams to have the highest recovery rate but it might not be statistically significant.

Now once people hit ventilation the re-categorisation occurs. More patients where given HC and HC+AZ which moved them from the No HC group to the HC or HC+AZ group. These groups therefore have a much higher % of ventilation patients because they where given the drugs after they hit ventilation.

The following data can be derived from the paper but is not presented:<br /> Once people hit ventilation we have the following results.

HC: 19 - 18 (95%) deaths - 1 (11%) recover HC+AZ: 19 - 14 (73%) deaths - 5 (27%) recover No HC: 6 - 3 (50%) deaths - 3 (50%) recover

If you compare these 2 tables, you see that 25 patient with No HC reach ventilation. Once they reach ventilation, 19 of these where give HC or HC+AZ, thereby moved from the No HC group to the other two. 79.5% of all patients reaching ventilation died so arguably 14 patients that died where moved from the No HC group to the other 2 groups only once they reach the much higher risk state.

Here are the number of people per group that got ventilation:

HC: 97 - 19 (19.6%) got ventilation HC+AZ: 113 - 19 (16.8%) got ventilation No HC: 158 - 6 ( 3.4%) got ventilation

So the conclusion that HC causes more death is basically wrong. All it shows is that people that need ventilation are more likely to die.

On 2020-04-29 16:09:10, user Serge Rdo wrote:

the response is i this article

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

On 2020-05-10 12:03:31, user Zn2 plus wrote:

This preprint is now published : https://doi.org/10.3390/bio...

On 2020-05-12 20:31:26, user Erwan Gueguen wrote:

The methodology used raises several questions:

• Why were 6 patients with a negative PCR included in a study on Sars CoV2, which means we don't even know if they have the disease? They should have been excluded from the study.

• In Figure 1 describing the flowchart of the studied population, Patients were divided into 2 groups. A HCQ + AZI group (n = 45), and an "other regimen" group (n = 87). It is very strange to find in this "other regimen" group patients who have not all undergone the same treatment. For example, there are 9 patients who also took HCQ+AZ but for a shorter period of time before transfer to ICU or death, 14 patients who took lopinavir/ritonavir, and even 28 patients who took AZI alone. This group is therefore not a control group since patients who have taken the same drugs are in the two groups being compared.

• Following the description of these 2 groups, we discover figure 2 which compares not these 2 groups but 3 groups. The "other regimens" group was divided into 2 groups AZI (n=26) and SOC (n=61) (SOC = standard of care which includes no targeted therapy, or lopinavir/ritonavir or treatment received <48h until unfavorable outcome (transfer to ICU or death). Why 2 patients were removed from the AZI group? (figure 1 n=28, but n=26 in figure 2). Figures suggest that 2 patients from the AZI group were placed in the SOC group. This could change the statistical analysis of the data. It is essential that the authors clarify this point because the results are not publishable as they stand.

• Finally, table 1 shows 2 groups. Statistics are made on 2 groups but actually also on 3 groups for the therapeutic data (see table 2).

Conclusion: The study suffers from numerous methodological biases that make it difficult to interpret the data. The groups are not equivalent and the control group is made up of an agglomeration of patients who have undergone different treatments including HCQ+AZI treatment. It seems to me indispensable that the authors clarify the points raised before a submission to a peer-reviewed journal. I hope that the above comments will enable them to improve their study.

On 2020-05-13 08:14:17, user Erwan Gueguen wrote:

The methodology used raises several questions:

• Why were 6 patients with a negative PCR included in a study on Sars CoV2, which means we don't even know if they have the disease? They should have been excluded from the study.

• In Figure 1 describing the flowchart of the studied population, Patients were divided into 2 groups. A HCQ + AZI group (n = 45), and an "other regimen" group (n = 87). It is very strange to find in this "other regimen" group patients who have not all undergone the same treatment. For example, there are 9 patients who also took HCQ+AZ but for a shorter period of time before transfer to ICU or death, 14 patients who took lopinavir/ritonavir, and even 28 patients who took AZI alone. This group is therefore not a control group since patients who have taken the same drugs are in the two groups being compared.

• Following the description of these 2 groups, we discover figure 2 which compares not these 2 groups but 3 groups. The "other regimens" group was divided into 2 groups AZI (n=26) and SOC (n=61) (SOC = standard of care which includes no targeted therapy, or lopinavir/ritonavir or treatment received <48h until unfavorable outcome (transfer to ICU or death). Why 2 patients were removed from the AZI group? (figure 1 n=28, but n=26 in figure 2). Figures suggest that 2 patients from the AZI group were placed in the SOC group. This could change the statistical analysis of the data. It is essential that the authors clarify this point because the results are not publishable as they stand.

• finally, table 1 shows 2 groups. Statistics are made on 2 groups but actually also on 3 groups for the therapeutic data (see table 2).

Conclusion: The study suffers from numerous methodological biases that make it difficult to interpret the data. The groups are not equivalent and the control group is made up of an agglomeration of patients who have undergone different treatments including HCQ+AZI treatment. It seems to me indispensable that the authors clarify the points raised before a submission to a peer-reviewed journal.

On 2020-05-13 14:21:49, user Sinai Immunol Review Project wrote:

Main Findings: <br /> Given the urgent need for diagnostic testing for COVID-19, this study uses enzyme-linked immunoabsorbent assay (ELISA) to measure serum antibody levels against recombinant spike protein ectodomain as well as its receptor binding domain (RBD) to angiotensin-converting enzyme (ACE2). Twenty RT-PCR confirmed COVID-19 patients as well as 99 healthy donors were tested for IgG titers in their serum. Antibodies to spike protein ectodomain were detected in 17 out of 20 patients, of which 5 showed borderline levels. 15 out of 20 patients tested positive for antibodies against spike RBD, of which 7 indicated borderline levels. These findings suggest that while majority of COVID-19 patients develop antibodies against the RBD, some patient responses may target other epitopes of the spike protein. Furthermore, they show that circulating antibody levels (ie: positive vs borderline) do not correlate with clinical severity or recovery from COVID-19. Strikingly, 1 patient who recovered did not have detectable IgG antibodies against RBD, suggesting a potential role of cellular immunity in the clinical resolution of COVID-19. In addition, they report that 4 out of 10 healthy donor serum collected since January 2020 tested positive. This indicates that apparently healthy individuals may be asymptomatic carriers, which underscores the importance of developing effective methods for community wide testing.

Limitations: <br /> The authors cite a study in their introduction that demonstrates minimal cross reactivity of antibodies between SARS-CoV and SARS-CoV-2 patients suggesting a specific antibody response for each disease. However, their study showed that five out of 89 serum samples collected from healthy donors between 2017 to 2019 tested positive for antibodies against spike protein ectodomain, and acknowledge a possible cross reactivity from prior exposure to other strains of coronavirus. This result also stands in contrast with other recent studies*. Understanding whether or not there is indeed such cross reactivity would be important for interpreting their results and designing vaccines against this specific virus. Furthermore, their thresholds for determining positivity versus borderline antibody levels are arbitrary and can significantly influence the outcome of their assay. It will be critical to obtain a larger cohort to further validate the robustness of their thresholds for determining circulating antibody levels.

Significance: <br /> This study establishes a straightforward assay in testing for circulating antibodies against spike protein in the serum of COVID-19 patients. This is important not only for surveying the population for people with immunity, but also improves sensitivity for diagnosis when combined with RT-PCR. In addition, their finding of a patient who recovered without detectable antibodies against spike protein RBD provides important insights to designing therapies for COVID-19.

Reviewed by Joel Kim as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

References:<br /> *Amanat, F., et al. A serological assay to detect SARS-CoV_2 seroconversion in humans. medRxiv preprint (2020)

On 2020-05-15 15:29:20, user Irving Kushner wrote:

Finding a low serum vitamin D concentration does not necessarily indicate vitamin D deficiency. There is now abundant evidence that vitamin D is a negative acute phase reactant – that is, its serum concentration falls during inflammatory states, as do albumin, transferrin, zinc and iron concentrations, in contrast to C reactive protein (CRP), which is a positive acute phase reactant.https://www.ncbi.nlm.nih.gov/pubmed....

This conclusion is supported by several lines of evidence: vitamin D levels have been found to be decreased in a number of inflammatory states. https://www.ncbi.nlm.nih.go..., https://www.ncbi.nlm.nih.go...<br /> Vitamin D levels fall following a variety of inflammatory insults, such as surgical procedures. https://www.ncbi.nlm.nih.go..., https://www.ncbi.nlm.nih.go..., https://www.ncbi.nlm.nih.go...<br /> And, as the authors indicate, it is well recognized that serum CRP and vitamin D levels are inversely associated. https://www.ncbi.nlm.nih.go..., https://www.ncbi.nlm.nih.go...

There is really nothing new in this study. The abstract states that they used CRP levels as a surrogate for vitamin D levels. So what they actually found was that higher CRP levels are associated with the risk of severe COVID-19. We knew that already.<br /> From Maria Antonelli and Irving Kushner, Case Western Reserve University

On 2020-05-19 00:53:07, user Sinai Immunol Review Project wrote:

Main Findings:

An unusually high incidence of Kawasaki disease was reported in a pediatric center for infectious diseases in France. This is a rare post-viral vasculitis that was been associated with several viruses in the past, including coronaviruses. The authors reported 17 cases over a period of 11 days, in contrast to a mean of 1 case per 2-week period in 2018-2019. <br /> Polymorphous skin rash and bulbar conjunctival injection were the most frequent criteria for diagnosis of Kawasaki disease. The patients had a median age of 7.5 years (range 3-16); 65% (n=11) presented with shock syndrome, and 70% of the patients (n=12) had concomitant myocarditis. All patients had high inflammatory parameters, including leukocytosis with a predominance of neutrophils, and high levels of C-reactive protein, procalcitonin and interleukin-6. Compared to past descriptions of Kawasaki disease, this cohort had an 8-fold increase in procalcitonin level, what suggests a particularly strong post-viral immunological reaction to SARS-CoV-2 as compared with other viral agents. <br /> Remarkably, although the study was conducted in France, 59% of the patients were originally from sub-Saharan Africa or Caribbean islands, and 12% from Asia, pinpointing a possible genetic predisposition or a travel-associated exposure. <br /> In 82% of the cases, IgG antibodies for SARS-CoV-2 were detected, suggestion an association with coronavirus disesase 2019 (COVID-19). RT-PCR testing for SARS-CoV-2 was positive in 41% of the patients. Although only 6 patients had recent history of an acute respiratory infection, in 9 cases there was history of recent contact with family members displaying respiratory symptoms. However, all patients had gastrointestinal symptoms prior to the onset of Kawasaki disease signs.<br /> All patients were treated with intravenous immunoglobulin (IVIG) and aspirin. Some received concomitant corticosteroids (n=3) and/or broad-spectrum antibiotics (n=14). Admission to intensive care unit (ICU) was necessary in 13 cases. A total of 5 patients had IVIG resistance. Regarding the outcome, 5 patients had not yet been discharged by the time the manuscript was published.

Limitations:

This was a single-center study with a very short follow-up period of 11 days. The information about the total number of paediatric patients that tested positive for SARS-CoV-2 in this center/region during the reported period is missing. That could help to draw conclusions about the incidence of Kawasaki disease-like inflammatory syndromes in children after SARS-CoV-2 infection. Additional to the genetic predisposition hypothesis, information about potential travel-associated exposures should be discussed in the manuscript due to the apparent difference in incidence between racial groups. Furthermore, although the prevalence of COVID-19 in Europe is currently very high, an association between SARS-CoV-2 and the reported outbreak of Kawasaki disease needs further studies to determine causality.

Significance:

The temporal association between the COVID-19 pandemic and the results of RT-PCR and antibody testing suggest a causal link between Kawasaki disease and COVID-19. At the time of this writing, while this is not the first description of Kawasaki disease-like inflammatory syndromes in association with COVID-19, it is the largest published cohort. Kawasaki disease should be evaluated as part of the spectrum of post-viral immunological reactions in COVID-19 convalescent children. These findings should prompt a high degree of vigilance among all physicians, and preparedness in countries with a high proportion of children of African and Asian ancestry during the COVID-19 pandemic. The World Health Organization (WHO) has recently developed a case report form and encouraged physicians to report all suspected cases.

Reviewed by Alvaro Moreira, MD as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai

On 2020-11-20 19:44:06, user StephenSela wrote:

Can I see a real MRI/Xray picture of the damage from someone who actually has this

On 2020-11-21 23:33:56, user VirusWar wrote:

Dr Soumya Swaminathan, Scientific chief of WHO explained on ECCVID conference that in Solidarity trial, hydroxychloroquine (HCQ) was widely used in Standard of Care group, despite rules said it should not. She said they had to do some "adjustment" but this doc don't talk about this issue or any adjustment.

Dosage of Hydroxychloroquine is also far too high and patients in that group are worse at entry than the one in supposed "control" group.<br /> There is a big issue in mortality graph over time in Figure 2a for remdesivir : death rate at 28 days is supposed to be 11% but graph shows it at 13%

It is odd to compare HCQ against HCQ

On 2020-11-25 16:37:17, user Duke Pham wrote:

The main flaws of #solidarity #study can be found here : <br /> https://c19study.com/solida...

HCQ dosage very high as in RECOVERY, 1.6g in the first 24 hours, 9.6g total over 10 days, only 25% less than the high dosage that Borba et al. show greatly increases risk (OR 2.8) [1].

Authors state they do not know the weight or obesity status of patients to analyze toxicity (since they do not adjust dosage based on patient weight, toxicity may be higher in patients of lower weight).

KM curves show a spike in HCQ mortality days 5-7, corresponding to ~90% of the total excess seen at day 28 (a similar spike is seen in the RECOVERY trial).

Almost all excess mortality is from ventilated patients.

Authors refer to a lack of excess mortality in the first few days to suggest a lack of toxicity, but they are ignoring the very long half-life of HCQ and the dosing regimen - much higher levels of HCQ will be reached later. Increased mortality in Borba et al. occurred after 2 days.

An unspecified percentage used the more toxic CQ. No placebo used.<br /> [1] c19study.com/borba.html<br /> death, ?19.0%, p=0.23

According to scientific studies, #hydroxychloroquine is efficient against #covid19. <br /> This website lists all the studies (positive or negative) : www.c19study.com. <br /> Majority of the 181 studies show a reduced #mortality and #severity in the disease with patients treated with #HCQ.

On 2020-12-02 16:52:31, user Benjamin Speich wrote:

This was an interesting article, thanks for posting it!

On 2020-12-03 18:13:15, user Nicholas Lewis wrote:

In general the reasoning and modelling in the original (July<br /> 29, 2020) paper seemed sound to me., in fact I thought it was an excellent<br /> paper. The revised (October 29, 2020) version of this paper makes the argument about<br /> varying heterogeneity rather more clearly than did the original version,<br /> although I found the explanations rather too sketchy in some places.

However, it appears to me that – if I understand it<br /> correctly – the revised version introduces some unsupported and unreasonable changes<br /> in assumption, which should be reversed.

In particular, the argument that short term overdispersion has<br /> an effect on the overall epidemic dynamics is insufficiently explained and not substantiated.<br /> It is far from obvious why that should be the case, although superspreading<br /> events may affect its very early stages.

Persistent heterogeneity is quantified by reference to the<br /> characteristics of contact networks, which "are remarkably robust"<br /> and set the value of nu at approximately<br /> 1, implying lambda = 3 (page 6 of the October 29 version). It is accordingly illogical to work on the basis that an individual's number of contacts changes significantly over time, which is what your Eq.[20] and related assumptions appear to imply. In the<br /> absence of such changes, the assumed original susceptibility gamma distribution<br /> will remain gamma distributed with unchanged CV (but lower mean) as the<br /> epidemic progresses [Montalban and Gomes arXiv:2008.00098v1]. No evidence is<br /> given that, by the time that there is sufficient data to model the evolution of<br /> the epidemic, any initial heterogeneity overdispersion will affect the inferred<br /> epidemiological parameters.

One way the supposed 'short term overdispersion' effect could<br /> arise is if a person who is highly connected and, as a result, becomes infected<br /> early in the epidemic thereafter tends thereafter to have fewer contacts, so<br /> that his inability (after recovering) to infect others has less effect on<br /> slowing the future epidemic, while other (uninfected) people on average have<br /> more contacts than previously. However, such an assumption would seem<br /> unjustifiable, save perhaps to a small extent, given the robustness of contact<br /> networks.

I accept that such an effect could perhaps arise from (say) week-to-week<br /> fluctuations in the number of contacts someone has, with their being more<br /> likely to be infected during a week with an unusually high number of contacts,<br /> and possibly being more likely to have more contacts in their following<br /> infectious period. I think that may be what the paper is arguing, although if<br /> so it is not very clearly explained. But, if so, surely that would apply<br /> throughout the epidemic wave rather than being time varying? In connection with<br /> this, you state (page 6) that delta-lambda(t') decreases with time, but it is<br /> not clear to me from Eq.[19] why it should do so, given that there is (and<br /> should be) no assumption that the delta-alpha_i values decrease over time.

Further, the change to assuming zero, rather than modest,<br /> biological heterogeneity in susceptibility is unjustifiable and should be<br /> reversed. Given that individuals vary as to their immune system memory and general<br /> effectiveness, due to differences in age, genetic factors, health status and<br /> life history, they are bound to vary in their ability to resist infection by<br /> SARS-CoV-2, as stated in the July 29 version. The assumed level of biological heterogeneity in susceptibility in the July 29 version, of lamba_b = 1.3, was – as stated<br /> there – a conservative level. It should be reverted to.

On 2020-12-05 18:54:57, user Zed wrote:

Dear authors,

I'm pretty sure your preprint is now somewhere under peer-review, but I was wondering what are the main difference between your meta-analysis and Fiolet et al (https://www.clinicalmicrobi... "https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(20)30505-X/fulltext)"). It looks pretty similar or at least going in the same way.

Thanks :)

On 2020-12-11 10:13:56, user Marina Pollán wrote:

Please, notice that a new version of this paper, including additional information, has been accepted and published in the British Medical Journal:<br /> doi: 10.1136/bmj.m4509<br /> Prof. Marina Pollán in the name of all the authors

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

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

There are several methodological problems in this study.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On 2020-12-21 18:08:41, user Michael Schrader wrote:

Very helpful study.<br /> Just a short comment on table: With 35 patients, precision is not better than +- one patient, corresponding to +-2.9 %. It is thus confusing to claim percentages with 4 digits like 97.12 %.

On 2020-12-24 07:31:39, user K Cornwell wrote:

Well done on your study. It is because of doctors who go the extra mile in the fight against this terrible virus. That we find that some of our medicines which may have been around for many years are having a significant impact on the treatment and recovery times. Let hope that the vaccines are enough to create some immunity across the countries and the treatment algorithms improve with better research.

On 2020-12-25 16:40:49, user Mukesh Bairwa wrote:

A novel topic chosen for systematic review and meta-analysis have medical implication for developing countries. The research question and search strategy is very clear and understandable. The results are quite impressive that M health intervention is helpful to improve the maternal and child health indicators in developing countries. The methodology is crisp and concise and readable. The work included the important parameters related to maternal and child health indicators. However, I suggest authors to include many other relevant parameters in future work.

On 2021-01-03 22:32:54, user Rodger Kram wrote:

Overall, I find this analysis to be interesting and well-conducted.

I would add Hunter et al. to the list of papers reporting improved running economy with neoteric Nikes. <br /> https://www.tandfonline.com...

Iain's treadmill was a bit slippery in the Vaporflys and I bet that accounts for their slightly lower savings.

minor points: <br /> Line 26 tongue in cheek: I know Joyner is prescient but how did he know in 1985 that he would be fascinated in 2019? Likewise for Hoogkamer 2017.

Line 42 (13) is a great paper but an odd reference here, Tung et al. would make more sense.<br /> Line 53 "led to" assumes cause-effect, horse before cart<br /> Line 82 doesn't really matter here but such directional hypotheses make 1-tailed tests legit. I am a proponent of directional hypoths<br /> Line 177 "moderated" seems like the wrong word here. plus "strongly moderated" seems like an oxymoron. like "mildly enthusiastic"<br /> Line 188-189 "average" but then "median" values are given.<br /> Line 209 cold temps too!<br /> Line 281 where does 1.5% come from? I thought the mean was 2%?<br /> Line 284 I would have provided (X%) in addition to the 4minutes since previous sentence was about %,

Line 301 I list my consulting to Nike on relevant papers, it would seem AJ should do so on this paper.

Ref (11) is 2020 not 1985

On 2021-01-05 14:01:12, user Lianna Martin wrote:

Hiya - I had suspected covid 11th March and still can barely smell. My nasal passage more recently has become painfully crusted up coinciding with most things with a strong smell coming across like bleach or petrol to me. Taste comes and goes. I can live with symptoms, but would love to be part of a study...

On 2021-01-06 12:33:57, user C'est la même wrote:

The authors state that there were 25 cases of GBS in London during the sampling period, which would lead to an estimated occurrence rate of 0.82 GBS cases per 1000 COVID-19<br /> infections.<br /> Yet they discount this by citing a claim that 17.5% of individuals London had been infected by that time. We now know that estimate was wildly inaccurate.<br /> Serological survey data collected by the ONS found that prevalence in London was just under 0.4% around that date (https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.07.06.20147348v1)")

Which works out to around 36,000 people in comparison to the 26,784 PCR confirmed cases. <br /> This would lead to an estimated occurrence rate of ~0.6 GBS cases per 1000 COVID-19 infections which certainly seems suggestive of an association.

The authors also performed genomic analyses to rule out molecular mimicry due to epitope similarities.

I'd like to draw attention to the fact that many of the known viral triggers of GBS also do not have evidence of molecular mimic epitopes, instead suggesting other mechanisms of generating autoimmunity including the co-capture hypothesis, (http://www.pnas.org/content... "http://www.pnas.org/content/114/4/734)"), given that spike protein interactions with gangliosides have already been characterised in a substantial number of publications to date.

As such, while the lower population incidence during the observed period is compelling, that data alone is not enough to rule out the association of GBS with SARS-CoV-2, given the impact of lockdown measures on other infectious causes that happen to have lower infectivity (basic reproduction number) than SARS-CoV-2.

On 2021-01-09 09:39:25, user Dr. Sebastian Boegel wrote:

This is a wonderful study. Congratulations. I am very honoured that you used my tool, seq2HLA. As seq2HLA also output HLA gene (and allele) expression (normalized to RPKM and the coounts), i am wondering why you additionally used AltHapAlignR for obtaining read counts for HLA genes. Did you experience any issues with seq2HLA? If yes, i am happy to help. <br /> All the best for you and keep up the great work,

Sebastian

On 2021-01-10 10:09:41, user Disqus wrote:

Gandini S et al. updated their previous preprint without, however, resolving the<br /> methodological problems, that is the errors already highlighted and the<br /> arbitrariness of most of the conclusions (see comments for the previous version<br /> here https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.12.16.20248134v1)").<br /> In particular in this second version the sample of public institutions increase from 81.6% to 97% of total, for a total of 7,376,698 students, thus it is not clear how on such large numbers one can hope to obtain significantly different or significantly more reliable results from such an update.

On the other hand Gandini et al. seem to have realized how their analyses suffer from the biases of an ecological study (page 13) though it is incomprehensible how the proposed additional analysis for the Veneto region only can significantly relieve the problem.

There are still also some gross errors here and there, e.g. although the authors have updated Table 8 by adding the (useless) absolute range of the number of tests per institution, the problem of standard deviations remains, certainly the result of a calculation error being compatible with negative values in the number of tests (e.g. 9-13 = -4 which would represent the lower limit for 1 standard deviation for the number of tests, see Student index case – Kindergarten row)

Finally, once again in spite of the medRxiv warning, Gandini et al. seem to consider it as a sort of personal press agency, a springboard to relaunch their studies without having to wait for the peer review, so much so that on the fb page of the first author (Gandini S.) a link to the article promptly appeared, the day after it was published on medRxiv

On 2021-01-12 17:22:08, user Ann Marie Miller wrote:

Can any one tell me if the Herpes 6/7 loads could cause a false positive Hep. C test, during a flare up? Thank you!

On 2021-01-15 14:29:13, user Serge Richard wrote:

Would you please inform the financial Interest Links between these authors and the pharmaceutical compagnies involved in the drugs refered to ?

On 2021-01-16 00:11:22, user Sandrine_G ???????? ???????? wrote:

All the people involved and mentioned above have the duty (and the obligation, for the French) to declare their conflicts of interest. Make them obey the law. Thank you !

Toutes les personnes impliquées et citées en haut ont le devoir (et l'obligation, pour les français) de déclarer leurs conflits d'intêret. Obligez les à respecter la loi. Merci

On 2021-01-15 20:36:01, user Yves Muscat Baron wrote:

Could changes in the airborne pollutant particulate matter acting as a viral vector have exerted selective pressure to cause COVID-19 evolution? Medical Hypotheses DOI: 10.1016/j.mehy.2020.110401Reference:YMEHY

On 2021-01-17 17:03:45, user kdrl nakle wrote:

Extremely important result. Shows aerosolization of the virus when it can be cultured from less than 0.5 micron particles, these are definitely aerosol size.

On 2021-01-19 15:51:45, user Alter Ego wrote:

In the text it is written: "LamPORE reliably detected SARS-CoV-2 to 20 copies/ml of sample. SARS-CoV-2 reads were detected in the 0.2 copies/ml sample but this was below the threshold for calling as positive sample in LamPORE but were not detected via RT-qPCR (Table 1, Figure 3)." - I assume that with "sample" the original saliva or NP sample is meant. If this is true the assay would be amazing .... my question: ins't there an error and it should be written 20 copies/microliter ... and also 0.2 copies/microliter. This would better fit to the rather low sensitivity of the assay in Figure 4 and an overall performance that is rather on the lower side of other LAMP reports where generally a cut of of approx CT=30 has ben reported (corresponding to approx 20'000copes/millilitre. This Figure is otherwise consistent with the idea that the N2 priers are much better than the E1 and ORF1ab primers....

On 2021-01-19 18:29:14, user Monika J. wrote:

As a Slovak citizen I can tell your that they are NOT telling the whole truth. Your can fact check my every single word.<br /> They claim that the testing was not obligatory... NOT TRUE<br /> People where forced to attend this mass testing. Prime minister admitted that they forced us to do this on the Press conference. Our Human rights where oppresed. Without negative test certificate your couldnt go to work, bank, post Office, all shops denied you to enter their premises. All services where denied to your without certificate. Even some doctors refused to treat patients without cerificate. You could only go to grocery store, pharmacy and drugstore without certificate. There were some exceptions, but not important. Some employers called the police on employees who wanted to go to work (they where healthy, had no symptoms) but didnt hlave the certificate. A lot of employees were fired, because they refused to get tested.

Lets talk about the study. They claim that they have participant conset.... NOT TRUE we havent sign anythig. Nobody informed people what kind of test they are using, who will hlave their samples afterwards, who will procesed their personal information..yes they hlave our personal numer and wrote some information from our ID....we dont know which information they collected.

Thay claim that tests where done ONLY by profesionals.. NOT TRUE. Tests where done by non medical personnel too - in some cities - those people braged about it on Facebook. There is NO name of person who tested you. You can not check if this person <br /> is profesionall or not.<br /> In some cities testing was done outside. People where forced to stand for multiple hours in lane just to get tested, in rain, and low tempersture...<br /> I could continue on and on and on....<br /> Now they are going to do the second round od this mass testing. They are again FORCING us to do it Once again. The second round is even worst than the first one. Now they want us to stand in lane to get tested in -10 to -15°C.<br /> Now the police will be controlling us if we have the certificate or not. If your will not have the certificate you will get a fine. And they will oppresed our human rights again. Segregstion od people to two categories is called apartheid and it is illegeal....this is what they are doing. They are creating second category people. First category Has certificate and Can live relatively normaly. Second category is treated like garbage.

On 2021-01-24 11:43:28, user Zdenko Ontek wrote:

I have to express myself as a citizen of the Slovak Republic. Several points in the research conditions do not agree with reality. Test subjects did not sign informed consent or instruction. It is also untrue to claim that testing was voluntary. The Government of the Slovak Republic created direct and indirect pressure, for example, through employers, who conditioned the entry of their employees into the workplace by passing testing. I note that the translation is machine, so I apologize for the English. Affected citizen of the Slovak Republic.

On 2021-01-21 15:04:47, user CB Bass wrote:

Been saying this for 9 months but Ignored by all MSM outlets. Our published study found that the culprit in the cytokine storm and Covid severity is IL-6. Guess what else? Your gut bacteria- specifically Bifidobacterium regulate IL-6. This is why we are not seeing severe cases of covid in children. They have much higher concentrations of Bifidobacterium in their guts than adults do and it down regulates IL-6 which is pro inflammatory, while up regulates interferon and IL-10 which are anti inflammatory.

Also a study coming out of Hong Kong university last week not only confirmed what our Initial study and discovery showed, it found that patients with Covid severity had deficiencies in Bifidobacterium.

Here is a summary of our study if you’d like to read more on how IL-6 plays a major role in Covid severity in high risk individuals.

https://www.worldhealth.net...

On 2021-01-22 21:53:47, user Takashi Nakano wrote:

The article was peer-reviewed and published on JMIR in November, 2020. <br /> Nakano T, Ikeda Y<br /> Novel Indicator to Ascertain the Status and Trend of COVID-19 Spread: Modeling Study<br /> J Med Internet Res 2020;22(11):e20144<br /> URL: https://www.jmir.org/2020/1...<br /> DOI: 10.2196/20144<br /> PMID: 33180742<br /> PMCID: 7708296<br /> https://www.jmir.org/2020/1...

On 2021-01-27 10:19:32, user Fred wrote:

I am not convinced of the data. Eg for Germany it is presumed that only about 1 of 10 infections is detected. The data I know from Germany say this number ist only 2-4 . So the IFR for Germany would not be O.2% but at least o.4 or even near to 1 %

On 2021-01-29 18:28:35, user hlritter wrote:

The stated 51% reduction in daily incidence reflects only that half as many cases occurred in the second 12 days as in the first 12. But that does not take into account the fact that the curves don't begin to diverge until 6 days into the second 12-day interval. What's important is the improvement in incidence that occurs after immunity develops, not after the halfway point to some arbitrary date. It appears that only about 1/6 as many new cases occurred in the 6 days after the onset of relative immunity at Day 6 as occurred in any 6-day interval prior to this. This supports an efficacy in the range of 80%-85%, not 51%.

On 2021-02-06 06:12:34, user Scott Huffman wrote:

So what exactly was the n value in the non-vaccinated group, and what was the n value in the vaccinated group? How was a positive case defined? Was it merely a positive PCR test, or was it an actual symptomatic case where a person was sick? And importantly, what was the average cycle rate of the PCR testing? What is the Absolute Risk Reduction? What's the NNT? These are legitimate questions that must be asked. The answers should be very simple.

On 2021-01-31 18:53:06, user Timotheus123 wrote:

This is clearly not a serious study. No apparant controls for age or comorbidity, no random assignment of treatment or control, an "inverse probability of treatment" adjustment.. etc etc.

And yet a strong conclusion debunking ivermectin?

This is NOT science.

On 2021-02-01 15:59:31, user Victoria Gates wrote:

What about the studies done by the FLCCC Front Line COVID-19 Critical Care Alliance? They present strong evidence to the contrary.

On 2021-02-02 16:30:41, user Martha Albertson wrote:

This is a poorly-designed study that looked at very few trials of ivermectin. The authors picked the studies that portrayed ivermectin in the worst light and ignored the many studies showing that ivermectin is a safe and effective treatment for Covid-19. I wonder who funded this study. Ivermectin is so much more effective than the expensive treatments promoted by the pharmaceutical industry. I can't imagine this biased study will survive peer review.

On 2021-02-02 22:45:20, user Elizabeth McNally wrote:

We are running similar ELISA assays after vaccination and not seeing this same robust IgG response. I would like to see more data prior making any recommendations about deviating from the vaccination protocols followed in the clinical trials.

On 2021-02-10 17:50:30, user Humanitarian wrote:

This is a wonderful application of science for common good, I love it. One question is the mass spectrometer affordable and portable to be useful in a surgical environment? It may be early, how much it would cost a surgery department to buy?

On 2021-02-14 17:53:25, user Bruce Aronow wrote:

Is Children's National seeing a recent rise in MIS-C cases and do you think this variant may be responsible?

On 2021-02-27 07:05:42, user jeromee5000 wrote:

published

doi

10.22034/jzd.2021.43762.1097

On 2021-03-03 01:17:29, user Dawn Christine Khan wrote:

I am a covid survivor, and said the same. 95 symptoms was incomplete. <br /> I had 150. This is the most comprehensive Long Haul research I have seen. I recommended it for CDC/NIH publication. Community NEEDS this!! May I receive a text or spreadsheet list of symptoms and categorization used? for more information http://www.linkedin.com/in/...

On 2020-10-31 00:01:20, user Joe Feist wrote:

It is funny that the CDC has issued a statement that wearing masks to filter smoke particles around the california fires isn't recommended because the smoke particles are too small. Yet the particles are at least twice the size of the covid 19 virus particles. Can you offer any explanation?

Also what do you mean exactly when you say ultra-fine particles? What size ranges?

On 2020-11-02 00:38:07, user Md Mokhlesur Rahman wrote:

The peer-reviewed version of this paper has been accepted and published online. You can find the paper at the following link.

https://www.mdpi.com/2071-1...

On 2020-11-03 20:27:05, user SteveH wrote:

Vitamin D levels do not decline quickly enough to explain the October surge. https://www.hindawi.com/jou...

On 2020-11-06 09:08:27, user Maksim wrote:

This is a nice point. “ plasma levels of total catechins are at submicromolar level, which is below the effective dose in many in vitro studies, tissue dispositions could be much higher “ (DOI: 10.5772/intechopen.74190). Besides, in the throat (during tea consumption) catechins levels could be much higher, though for a short period of time. (The latter is just a speculative idea to think about).

On 2020-11-17 00:14:37, user Laurence Renshaw wrote:

Apart from one sentence, this paper does not discuss deaths that are not directly attributable to the disease - for example, it does not appear to consider future deaths caused by the massive economic downturn as a result of people staying at home and businesses failing or downsizing.<br /> So how can it predict that people born in 2020 will expect to live 1 year less? People born in 2020 will certainly not die from Covid19, and the paper does not discuss anything else that could affect their life expectancy.<br /> Even for the over-65 group, how can a 0.1% population fatality rate (let's say that's 0.3 or 0.4% over over-65's) bring down their future life expectancy by several percent?<br /> This paper is very short on methods and data, and very long on conclusions.<br /> It also dismisses the impact of what it refers to as 'harvesting', and claims that few of the Covid19 deaths would have died soon - this contradicts all other studies that I have seen.<br /> It may well be that life expectancy, for those not killed by Covid19, will be reduced for decades to come, due to the economic and social impacts of the virus and our reactions to it (lockdowns and other restrictions), but deaths from the virus itself (a one-time loss of 0.1% of the population, with the vast majority over 70) can only have a tiny impact on life expectancy.

On 2020-11-17 21:24:47, user George wrote:

The two leading comorbidities associated with COVID-19 mortality, SCD and kidney disease, are mechanistic causes of selenium deficiency. Selenium deficiency is associated with hemolysis in SCD and has been strongly associated with mortality and other outcomes in 4 COVID-19 studies so far. High-dose sodium selenite infusion is safe and well-tolerated in dialysis patients.<br /> Vitamin D and dexamethasone both alter selenoprotein expression, and thus may be ineffective if selenium is deficient.

On 2021-09-13 14:36:27, user Chadwick wrote:

It is incredibly odd that the study authors provide us copious odds ratios but never the number of participants in each condition with each outcome. It's absence is quite strange.

On 2021-08-26 08:55:34, user William Richard Dubourg wrote:

Because of the voluntary nature of testing, testing rates as an outcome measure are on their own unreliable. There is reason to think the propensity to get tested is different between the vaccinated and infected groups. You need a model to predict testing propensity.

Your Table S1 does not match the text. Odds ratios and CIs are different.

My main concern relates to underlying health status. The infected group will exclude people who have previously died from COVID. The vaccinated group will not. Thus, there is reason to believe the infected group will have better underlying health status than the vaccinated group. This might explain why there were marginally more hospitalisations (a better and less biased outcome measure) in the vaccinated group than the infected group.

It should also be noted that there was no difference in deaths between the two groups.

Your conclusions about the beneficial effect of infection vs vaccination are therefore unwarranted.

On 2021-08-27 14:34:28, user Jonathan Bennett wrote:

Does this mean I should be allowed to travel anywhere, given I have prior infection, and people who are merely vaccinated should be subject to tight restrictions?

On 2021-08-27 15:57:52, user Jacky wrote:

The study does not account for survivor bias (i.e., those who got COVID and died; however, hardly anyone--probably nobody--who got a <br /> vaccine died); the estimates they report are confounded and not <br /> interpretable. Also, it does not account for time differences of when <br /> the person was vaccinated and when when the person got COVID. If most <br /> individuals were vaccinated say 6 months ago and they are compared <br /> individuals that got Delta recently, then of course the latter will have<br /> more antibodies than the former (antibodies will wane in both groups). <br /> Thus, this study has sever methodological challenges.

On 2021-08-29 03:38:56, user julie kemp wrote:

I've heard many different reports , and most agree , that if you recover from Covid 19 your immunity is greater than a vaccinated person. A lab test would prove it. I had the vaccines, my friend had the Covid 19 virus, and doesn't want the vaccine. Why can't she just have a lab test to check her immunity ,and that should suffice.If she's immune. why force her to take a vaccine.??

On 2021-08-29 08:15:47, user Jeroen Boschma wrote:

The group of unvaccinated persons are truly survivors of their first infection, this means that many of the weak and problematic health cases have died during their first infection and are no longer present in that group. If Covid has a mortality of 1.5%, then this subgroup is 240 cases for the 16000 large group. However: all those cases of weak and problematic health who likely die from an unprotected infection are still present in the group of SARS-CoV-2-naïve vaccinees. So a selection was done where the most vulnerable persons were taken out of the unvaccinated group (death), but that selection is not done in the vaccinated group simply because it is not possible to predict at forehand who will die from an unprotected Covid infection. Although the groups are finally selected on equal risk factors, the above observation will always introduce a huge statistical bias.

I am quite sure that the group of cases found in the 'vaccine' group are largely those persons who would have died from an unprotected Covid infection. Because those persons are by definition not present in the unvaccinated group (they died during the first infection) you can explain the number of cases in both groups precisely by the above described mechanism. The conclusion then is that the found cases have nothing to do with 'better resistance due to an earlier infection'.

EDIT: I see now below that William Richard Dubourg made the same comment about the deaths due to Covid. I had problems with my Disqus account and could not post for a couple of days. Moreover: yesterday I saw 0 comments below this article while today suddenly comments appear that are 3 days old. Strange behavior....

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

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

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

On 2021-09-01 10:08:16, user Jonh Peter wrote:

About Graphene’s health effects summarised in new guide (European Commission Feb.2015)<br /> At the level of the whole body, the authors indicate that there are two main safety factors to consider regarding exposure to CNTs and graphene. The first is their ability to generate a response by the body’s immune system; the second is their ability to cause inflammation and cancer.

On 2021-08-19 07:37:44, user dixon pinfold wrote:

The bulk of these comments cover in a more or less cogent manner the various ways the survey results could be wrong—the portion, that is, concerning respondents who reported holding doctoral degrees. No one questions the other findings, which are all congenial to ordinary educated prejudices.

Few are dissatisfied with the survey's respondents having self-selected, which I view as the chief problem with it. I am inclined to say quite flatly: Not a random sample, not valid. But then, if self-selection were the main objection in these comments, all the education-category results would fall under similar doubt, not just one. Is that why this objection seems not to have occurred to many?

I read anxiety and indignation into the tone of most of the comments. I confess to a slight doubt about the depth of their sincerity. I feel quite certain that if the survey showed a mere 1% of doctorate holders were vaccine-hesitant, the commenters would instead be saying "See? The more educated you are, the less likely you are to be vaccine-hesitant" and would express at least qualified approval of the survey.

Needless to say, these are mere opinions of mine. I should be interested to hear other people's.

(N.B. I myself have received two Moderna doses and mention it to establish my bona fides, not wishing to be pilloried for a lack of it.)

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

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

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

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

On 2021-08-23 17:44:20, user Olga Matveeva wrote:

Very interesting paper, however, I can't find supplementary material.

On 2021-08-25 00:35:16, user Andrew Huang wrote:

Can I check, if my body weight is 67 kg, I need to take : Honey 67gms per day Nigella Sativa - 12,060mg = 80mg/day ? Quite a large amount of honey based on this.

On 2021-08-27 06:09:19, user William Brooks wrote:

This is interesting paper showing that the first three states of emergency (SoE) and GoTo campaign didn't have much effect on the fluctuation on K. However, rather than conclude that the medical system is at no risk of collapse and the government should copy Texas and Florida and eliminate all business restrictions, the author calls for stricter border measures, lockdown, and more tests for healthy people despite it being clear for over a year that "Rapid border closures, full lockdowns, and wide-spread testing were not associated with COVID-19 mortality per million people" [1].

Since Covid's case fatality rate in Japan is now close to 0.1%, it's hard to see the point of spending even more time, money, and effort copying testing strategies that have been ineffective even in advanced countries like Germany [2] and Denmark [3].

[1] https://doi.org/10.1016/j.e...<br /> [2] https://www.ncbi.nlm.nih.go...<br /> [3] https://doi.org/10.1101/202...

On 2021-08-29 20:06:25, user Peter A McCullough wrote:

Most in this area of China are vaccinated. Authors please confirm all these Delta cases were fully vaccinated. Data likely congruent with Chau et al in Lancet.

On 2021-08-29 21:48:43, user philipn wrote:

Thank you for this great trial!

I shared some of my thoughts in this twitter thread here: https://twitter.com/__phili....

RAAS components: preprints notes no impact of treatment on measured RAAS components. In studies I've read (non-COVID), ARBs raise Ang II (see e.g. https://pubmed.ncbi.nlm.nih...; "https://pubmed.ncbi.nlm.nih.gov/10082498/);") idea is less AT1R binding => more Ang II. But the trial found no impact on even Ang II with treatment.

Preprint doesn't mention how many participants had RAAS components measured, so maybe it wasn't enough for significance. But the preprint does give significant p-value for an association with baseline. In the above non-COVID study showing ARBs raise Ang II, n=12 wasn't enough for significance with 50mg losartan (but was for the other ARBs; 50mg losartan pictured as open diamond in Figure 4).

If argument is treatment was dosed to block AT1R sufficiently but had no impact on RAAS components, why Ang II isn't higher in the treatment group is an interesting question?

The preprint looks at PK data in n=7, "consistent with..maximal AT1R blockade." Earlier in preprint, "yielding an expected 70% inhibition of AT1R." 70% inhibition doesn't appear in citation (https://pubmed.ncbi.nlm.nih... mentions 77% at trough with 100mg bid).

In this paper (https://pubmed.ncbi.nlm.nih... "https://pubmed.ncbi.nlm.nih.gov/11392465/)") 50mg od losartan looks like ~35% in the peak window. In https://pubmed.ncbi.nlm.nih..., 50mg again looks like ~35% at peak (open diamonds in Figure 3).

I was unable to find a study that tests exactly 50mg bid losartan and looks these proxies for % AT1R blockade.

I think the preprint authors may be getting the 70% figure from an earlier citation, https://pubmed.ncbi.nlm.nih..., Fig 3 and ~205 ng/mL EXP3174 (median C_6h) => ~70% according to figure. It seems this argument is based on PK in this n=6 study. The PK study uses SBP response to Ang II but looks pretty different from https://pubmed.ncbi.nlm.nih....

https://twitter.com/__phili... - side by side figures are illustrative

Compare the ~50mg losartan (open diamonds in right figure, from https://pubmed.ncbi.nlm.nih... "https://pubmed.ncbi.nlm.nih.gov/10082498/)"). Looks like ~35% at peak vs ~70%. The graphs look pretty different.

The authors of the ~35% study address this difference, stating:

"The antagonism produced by 50 mg of losartan (ie, 35% to 45% blockade of AT1 receptors) was also weaker than expected on the basis of previous results of studies using 40 mg of losartan. To explain this difference, one must consider that in our study, the placebo had no effect on blood pressure response to exogenous Ang II, whereas it blunted the effect of Ang II by almost 20% in Christen et al’s6 study. Thus, if one corrects for the placebo effect, the percentage of inhibition obtained in the 2 studies is comparable."

So once the PK study’s placebo response is adjusted, results are similar. So isn’t the value ~35%, not 70%? Would be consistent with other studies, showing proxies for % blockade being around ~35% for 50mg losartan rather than 70%. I also wonder if “Labeled Ang II %” figures may be a better proxy for % AT1R blockade than SBP (less prone to placebo etc)?

--Philip Neustrom

On 2021-08-30 22:37:50, user Dave Kavanagh wrote:

Will C.1.2 be the next pandemic wave of Covid to sweep the globe and will this potential vaccine resistant variant pose a greater problem to the WHO when considering the sharing of information to the general masses?

On 2021-08-31 03:11:22, user Judy Friend wrote:

when will this report be fully peer reviewed and when will we have more information. also how often are variants actually coded in these countries for genome sequencing

On 2021-08-30 22:44:45, user Rachel Ezzour wrote:

Is the follow up study available yet?

On 2021-08-31 19:11:00, user Andy Loening wrote:

I think this is a thought provoking model. However, I think there are some major flaws with the model (as I understand from the pre-print manuscript) that severely limit the interpretation of the results.

The biggest flaw I see is:<br /> 1) "Case-investigation of potential contacts is not conducted." So the "no testing" cases have NO contact tracing, which makes this not at all a far comparison. If they included contact tracing/testing (status quo), I would believe most (or all) the difference between their "testing" and "no testing" lines would go away.

Other flaws I see<br /> 2) As a previous comment pointed out, they assume an initial rate of infections coming into the school at ~10-20-fold greater rate then actually infection rates. Similarly the 1 new case coming into the school per week may be too high.<br /> 3) They don't seem to build in any allowance for the ~36-48 hrs it would take a RT-PCR test to get a positive result back. The model doesn't seem to take any of this delay in testing results into account. This would obviously blunt the positive effects that surveillance testing would have.<br /> 4) They seem to treat their student population as a single classroom of 500 kids, and do not take into account that kids (even in the pre-covid days) are mostly segregated into their classrooms for the majority of the day.<br /> 5) There are no error bars provided for the model. Presumably the model has randomization within it, so there should be some variation in the outputs, it would be interested to see what the spread of the outputs are to gauge the significance of the findings.

I would be really interested in the results of this manuscript if it was redone with more appropriate assumptions. My guess is that there would be a much smaller difference between the surveillance and non-surveillance groups.

On 2021-09-01 17:09:10, user Elle Tigre wrote:

Why did you choose the 2016-2017 period to monitor? Why not 2018-2019, respectively?

On 2021-09-01 21:33:26, user Paul wrote:

In reviewing your study's hospitalization rates by age group (your Figures 3 A, B and C), it shows that peak hospitalization rates per 100k in the unvaccinated population to be at about 12-13 for ages 18-49; about 35-40 for ages 50-64; and about 80-90 for ages 65+. These peaks happed mid to late April.

The hospitalization rates by age group during the worst peak of COVID in late December 2020, before the vaccines were available, were as follows (per the CDC COVID-NET data, week ending 1/9/21): 9.6 for ages 18-49; 28.4 for ages 50-64; and 71.9 for ages 65+.

Under the theory that the risk of hospitalization from COVID in the unvaccinated population did not change dramatically from December 2020 to May 2021, seems hard to explain how unvaccinated hospitalization rates were 20-30% higher in April/May peak vs. December peak when overall deaths were 6 times higher in December. I understand you cannot compare the deaths between the two periods because of vaccines, but it seems there is a disconnect between your study’s unvaccinated hospitalization rate and the hospitalization rate before the vaccines were available.

Would be interested to know if your study’s unvaccinated hospitalization rate was compared to hospitalization rates during periods when the vaccine was not available to test for reasonableness. Also would be interested to know if it is possible that your study under reported the number of hospitalizations in the vaccinated population (for example, how confident were you in matching the IIS vaccination patients to the COVID-NET hospitalized patients, how likely are providers to report a COVID vaccine to their state’s IIS database, are different provides more or less likely to report vaccines to the IIS, were any smaller follow-up surveys performed on hospitalized patients to see if their reported vaccine status is consistent with what you assumed in your study, etc.).

On 2025-10-12 13:03:25, user Ceejay wrote:

There are many other plausible mechanisms than antigenic imprinting for the "counter-intuitive" result, some vaccine-related, but others such as nutritional state and prior flu or indeed C19 exposure. May be too late for this paper, but my belief is that all such investigations should include measured Vitamin D status. The effect of Vit D on respiratory tract infection resilience is well known, and particularly over the winter months covered in this study, vitamin D titre will naturally fall due to reduced sun exposure. In similar vein, those who decline flu vaccination may adopt a significantly different health regime to those accepting vaccination, obviously not terribly easy to capture. But one I think you could capture is the C19 and C19 shots status, since I would imagine many of those tested might have taken part in your earlier studies. Those declining a flu shot could easily coincide with those declining a C19 shot. It all certainly shows vaccination science is complex.

On 2021-12-03 00:34:25, user Sulev Koks wrote:

This manuscript is under review at Experimental Biology and Medicine.

On 2021-12-07 10:40:57, user S. von Jan wrote:

I feel that some of the assumption that go into the model calculation are overestimated, others are underestimated, and some important further information is not considered. I am referring specifically to v (vaccine uptake), s (susceptibility reduction) and b (relative increase in the recovery rate after a breakthrough infection).

The authors assume a vaccination rate of 65% for the period between 11.10 and 7.11. For the sake of transparency, I think it should be mentioned in the study that in Germany an underestimation of the vaccination rate of up to 5 percentage points is assumed (1), perhaps this should also be considered in the scenarios. Moreover, the recovered cases are not mentioned at all, do they not play a role for the model?

For s in the "upper bound" scenario, a 72% efficacy of the vaccination in Germany is assumed (2), this figure comes from the German Robert Koch Institute (RKI) and is calculated based on the vaccination breakthroughs in Germany, i.e., it only includes the number of symptomatic cases in Germany. The RKI writes on the estimated vaccine effectiveness: "The values listed here must therefore be interpreted with caution and serve primarily to classify vaccination breakthroughs and to provide an initial estimate of vaccine effectiveness" (3, own translation). The vaccine effectiveness estimated here refers to the effectiveness of vaccination against Covid 19 infections with clinical symptoms, not against infection in general. However, there are indications that infections are more often asymptomatic in vaccinated persons ("vaccinated participants were more likely to be completely asymptomatic, especially if they were 60 years or older"(4)), and vaccinated people in Germany must rarely participate in Covid 19 tests. The RKI points out that vaccination would considerably reduce transmission of the virus to other people but assumes that even asymptomatically infected vaccinated people can be infectious: "However, it must be assumed that people become PCR-positive after contact with SARS-CoV-2 despite vaccination and thereby are infectious and excrete viruses. In the process, these people can either develop symptoms of an illness (which is mostly rather mild) or no symptoms at all" (5, own translation). So is the effectiveness of vaccination against symptomatic infections in this setting relevant when it comes to the role of the vaccinated/unvaccinated to the infection incidence?

In the "lower efficacy" scenario, s is given as 50% to 60% based on an English study. This percentage corresponds to the data from another study, which estimates the effectiveness of the Biontech/Pfizer vaccination against infection as 53% after 4 months in the dominant delta variant (6). Would this number not be more plausible for the "upper bound" scenario? The "lower efficacy" scenario could then be calculated with an efficacy of 34%, for example, as suggested by another study on infection among household members (7).

If we consider b, "an average infectious period that is 2/3 as long as this of unvaccinated infecteds" is assumed. This figure seems reasonable based on the available information on the faster decline of the viral load in vaccinated persons. However, there are statements, for example by Prof. Christian Drosten in an interview with the newspaper “Die Zeit”, that make this effect seem less significant: "The viral load - and I mean the isolatable infectious viral load - is quite comparable in the first few days of infection. Then it drops faster in vaccinated people. The trouble is, this infection is transmitted right at the beginning. I'm convinced that we have little benefit from fully vaccinated adults who don't get boostered" (8, own translation). Moreover, there is another issue that is not mentioned in the paper at all, but which I think should be taken into account: Unvaccinated people in Germany have to test themselves much more frequently than vaccinated people (e.g., at the workplace) due to the 3G rules (9, this means vaccinated, recovered or tested). Children and adolescents have a testing frequency of 3 rapid tests a week (10). Even if the effectiveness of the rapid Covid 19 tests for asymptomatic infections should be 58% (i.e., only 58% of infected persons are correctly identified as positive) (11), a test rate of 2 to 3 tests per week would still reduce the duration during which an unvaccinated person is infectious and not in quarantine. This consideration is not included in the model calculation.

Overall, it appears that several central parameters were underestimated or overestimated in the model calculation: The vaccination rate is actually higher, the effectiveness of vaccination against infection is certainly lower than the figure given in the “upper bound” scenario, and the period in which infected persons infect others is shortened for unvaccinated persons by 3G regulations, since they have to go into quarantine if they test positive. As a result, the contribution of the unvaccinated to the infection incidence in Germany is likely to be strongly overestimated in the model calculation, especially in the “upper bound” scenario.

(1) https://www.rki.de/DE/Conte... <br /> (2) For adolescents, s is even estimated at 92%, without explicit data being available here.<br /> (3) https://www.rki.de/DE/Conte.... <br /> (4) https://www.thelancet.com/j...<br /> (5) https://www.rki.de/SharedDo... <br /> (6) https://www.thelancet.com/j... <br /> (7) https://www.thelancet.com/j... <br /> (8) https://www.zeit.de/2021/46... <br /> (9) https://www.bundesregierung... <br /> (10) https://taz.de/Schulen-in-d... <br /> (11) https://www.cochrane.de/de/... This overview work does not yet refer to the delta variant.

On 2020-05-30 07:55:21, user Irene Petersen wrote:

You seem to conflate the risk of getting exposed (and thereby infected) and the risk of dying with covid19. However, these risks may vary substantially and therefore we would need a two-step approach to obtain meaningful predictions. For example, age and ethnicity are strong predictors for exposure while diabetes and obesity are strong predictors of mortality once you are infected.

On 2020-06-23 13:30:40, user Ralph Hawkins wrote:

Analysis of the RECOVERY trial pre-print data, looking only at non-ventilated patients together, not stratified by oxygen use. There is NO DEMONSTRABLE TREATMENT BENEFIT.<br /> Dex treated 360/1780 (20.2%) vs standard care 787/3836 (21.6%) p=0.2427

On 2020-06-23 19:20:17, user addie wrote:

The article states that patients receiving mechanical ventilation were ten years younger than those not receiving respiratory support - this implies that ventilators were being rationed? Can the authors speak to this.

Thank you.

On 2020-06-25 15:01:25, user Kirielson wrote:

I think this paper is fine, my question I would have for the authors: Did you attempt to evaluate if the patient could relay back those risks to you through any metric? Finding a way to see if a patient understands it by evaluation may see how effective one is over the other while looking at their preferneces.

On 2020-06-26 16:13:44, user Veli VU wrote:

the authors do not detect SARS-CoV-2 in samples from 2019 March. Rather, they do detect IP2/IP4 resembling SARS-CoV-2. Whatever virus it is it does not have the E and N1/N2 of SARS-CoV-2. Fluctuations in qRT-PCRs even in 2020 samples -different sewers- are way too high to trust the reliability of the RT-PCRs. However, their approach is amazing. I hope they use a metagenomic approach to sequence to sewers rather than doing an RT-PCR assay, which doesn't look very rigorous.

On 2021-06-04 13:42:50, user fauxnombre1 wrote:

Help me understand. The cumulative dose is not a product of the duration of treatment? Patients receiving treatment longer have a better survival rate?

On 2020-06-06 05:51:49, user Tim Lee wrote:

The possible relationship between A blood type and COVID-19 progressive respiratory failure.

Endemen et al (2020) found that progressive respiratory failure in COVID-19 is linked to hypercoagulability.21 This conclusion is supported by cohort studies that found hypercoagulability and a severe inflammatory state in COVID-19 patients 22,23 . Type A blood increases the risk for thromboembolic events.25 Viral infections activate the blood coagulation system.29

It may be that all factors that increase your risk for hypercoagulation increase the risk for progressive respiratory failure in COVID-19. One factor that has caught my attention is mercury. It is ubiquitous and known to cause hypercoagulation. (26-28) For more info please read my note on the topic https://www.qeios.com/read/...

1. Endeman H, Zee P van der, Genderen ME van, Akker JPC van den, Gommers D. Progressive respiratory failure in COVID-19: a hypothesis. Lancet Infect Dis. 2020;0(0). doi:10.1016/S1473-3099(20)30366-2

2. Panigada M, Bottino N, Tagliabue P, et al. Hypercoagulability of COVID-19 patients in Intensive Care Unit. A Report of Thromboelastography Findings and other Parameters of Hemostasis. J Thromb Haemost JTH. Published online April 17, 2020. doi:10.1111/jth.14850

3. Spiezia L, Boscolo A, Poletto F, et al. COVID-19-Related Severe Hypercoagulability in Patients Admitted to Intensive Care Unit for Acute Respiratory Failure. Thromb Haemost. Published online April 21, 2020. doi:10.1055/s-0040-1710018

4. Ellinghaus D, Degenhardt F, Bujanda L, et al. The ABO blood group locus and a chromosome 3 gene cluster associate with SARS-CoV-2 respiratory failure in an Italian-Spanish genome-wide association analysis. medRxiv. Published online June 2, 2020:2020.05.31.20114991. doi:10.1101/2020.05.31.20114991

5. Groot Hilde E., Villegas Sierra Laura E., Said M. Abdullah, Lipsic Erik, Karper Jacco C., van der Harst Pim. Genetically Determined ABO Blood Group and its Associations With Health and Disease. Arterioscler Thromb Vasc Biol. 2020;40(3):830-838. doi:10.1161/ATVBAHA.119.313658

6. Worowski K. The Hypercoagulability in Mercury Chloride Intoxicated Dogs. Thromb Haemost. 1968;19(1/2):236-241. doi:10.1055/s-0038-1651201

7. Lim K-M, Kim S, Noh J-Y, et al. Low-Level Mercury Can Enhance Procoagulant Activity of Erythrocytes: A New Contributing Factor for Mercury-Related Thrombotic Disease. Environ Health Perspect. 2010;118(7):928-935. doi:10.1289/ehp.0901473

8. Song Y. [Effects of chronic mercury poisoning on blood coagulation and fibrinolysis systems]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi Zhonghua Laodong Weisheng Zhiyebing Zazhi Chin J Ind Hyg Occup Dis. 2005;23(6):405-407.

9. Antoniak S. The coagulation system in host defense. Res Pract Thromb Haemost. 2018;2(3):549-557. doi:10.1002/rth2.12109

On 2020-06-07 21:50:15, user Wei Gu wrote:

Peer reviewed version at Clinical Infectious Diseases:

Clinical Infectious Diseases, ciaa599, https://doi.org/10.1093/cid...<br /> Published: 21 May 2020<br /> https://academic.oup.com/ci...