On 2021-06-05 13:55:27, user Tim Winton wrote:

Would it be possible to see the code for this?

On 2021-06-06 13:42:01, user Maryam Pahlavan wrote:

Hej, How I canrequest for dataset?

On 2021-06-10 04:54:34, user ejmah wrote:

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

On 2021-06-10 17:55:41, user Steve Johnson wrote:

It is possible that fully vaccinated participants fared better because testing for infection was done 5 weeks or more after dose 1. Are there results for partially vaccinated participants tested 5 weeks after dose 1, but free from infection in prior tests?

On 2021-06-10 17:59:48, user Aliya Amirova wrote:

Peer-reviewed and published article: https://openheart.bmj.com/c...

On 2021-06-10 20:23:12, user John Jay wrote:

Sorry if this was already mentioned, but is there a discussion of how the demographics (ie age, co-morbidities, status before care, etc.) varied between the group given 3,000mg HCQ + 1,000mg AZM and all other patients in the study?

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 2021-06-14 17:19:23, user Sherry Grace wrote:

Paper now in print! https://globalheartjournal....

On 2021-06-18 16:19:49, user Jim D wrote:

Hi, I have CLL, asymptomatic and very low count. I had the Pfizer vaccine, both doses. My arm was sore for 3 weeks after the first shot even tho I moved it around alot. On the third day after my second shot, it seemed that my shingles was reactivated, big pain, couldn't sleep. My PCP sent me to emergency for CT scan. Other than spike in white cell count, nothing showed from the scan. I shared the info about this study with PCP and Hemotology oncologist to try to get a quantitative antibody test. I have not heard back, other than those tests are extremely difficult to get. Also then with further reading, I learned that even with a quantitative test, I would not learn much since there is no standard for determining what number is safe.<br /> My question is: has there been any new info since this study was posted. Thanks. J

On 2022-01-07 04:29:43, user Cameron Cooper wrote:

Is this the study Rand Paul is quoting?

On 2022-01-07 02:59:57, user Cameron Cooper wrote:

Is this the study Rand Paul is quoting?

On 2021-06-21 17:58:22, user Greg wrote:

I will pose a very simple question. If masks worked, why wasn't the pandemic stopped in its tracks? Instead, it has played out like all outbreaks do. Masks didn't work in 1918 during the Spanish Flu pandemic, and they don't work now. Surgical masks or cloth masks were never meant to stop viruses. Why do you think workers in highly-secure biolabs wear airtight suits? Why go through all that trouble if they could just pop on a surgical mask?

The fact is, masks are simply for show. They make people feel safe and secure, but it's all theater. That's why you see people continuing to wear them even after the mandates have been lifted. They make them feel safe. It's always been about feelings, when it should've been about science.

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

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

On 2021-06-22 03:53:16, user Bob Horvath wrote:

Thank you for this paper - parents of PANS patients are grateful to see this kind of genetics work being done on PANS. May I ask:

1) What was the total number of variants meeting the criteria described (at lines 141-144 of the document for the European samples, and lines 154-158 for the U.S samples)?

2) Presumably, the list of candidate genes (described at lines 161-162) were all the genes that encompassed the variant lists in 1) above, with the possible exception of MTHC2 and BID that are mentioned as additions. What was the total number of candidate genes considered, before the list was narrowed to the 11 listed?

On 2021-07-17 14:18:34, user killshot wrote:

Make sure there is some effort to randomize according to vitamin D status! Otherwise the data is quite flawed and meaningless.

On 2021-03-13 17:08:08, user truthful melody wrote:

Honest question seeking a good faith answer:

Does anyone know why the CDC is not reporting the variant cases that were widely reported in the media from the paper?

The headline on multiple outlets was, “Houston has all the variants”.

However, these are the current numbers from the CDC:

Texas (March 11, 2021)<br /> B.1.17 Variant: 140<br /> P.1. Variant: 0<br /> B.1.351 Variant: 1<br /> Source: US COVID-19 Cases Caused by Variants | CDC

The CDC is still reporting zero P1 cases in Texas and only one B.1.351.

Since Houston is a city in Texas, and I see from the comments section here that the cases are included in GISAID, what is the discrepancy here?

On 2021-03-17 10:27:00, user Olaf Storbeck wrote:

I took the Vitamin D data from that paper but pulled the Covid-19 data myself due to severe data errors I found in the figures (very similar to the other commentors). I also corrected the Turkey Vitamin D data to that from a much better meta analysis ((Alpdemir, Medine & Alpdemir, Mehmet. (2019). Vitamin D deficiency status in Turkey: A meta-analysis. International Journal of Medical Laboratory. 10.14744/ijmb.2019.04127).<br /> The analysis in this preprint it fully dominated (beside the data errors) from the Czech data point, which is clearly an outlier and unfortuneatly not even shown in Figure 1.

When correcting the failures I got a significant correlation of Vitamin D deficiency to Covid-19 cases and deaths with p values on 0.0005 to 0.02 range.

On 2021-03-18 12:54:03, user H.C. So wrote:

This is an online calculator (intended for educational and research purposes only) based on the prediction model in this paper <br /> http://labsocuhk.ddns.net:8889/covid19/

Hon-Cheong SO

On 2021-03-20 04:41:11, user Wael wrote:

This work is immense. I appreciate the fact that the research devised 29 objective points to measure the level of Hesitancy, way to go. The methodology is really robust. I know that because I already have two publications using reliability models. In addition, the figures are clear.

On 2021-03-22 14:43:29, user tuulaojavuo wrote:

This article is erroneous. E.g. the Larson 2010 data is wrong. The results and all the major conlusions are thus erroneous.

(The Larson 2010 data has categories "symptoms" and "no symptoms" switched, that error alone changes all the results & conclusions of the study)

This article should be retracted immediately

On 2021-04-04 11:06:22, user kingmanninen wrote:

Re: Version 8; please see SUPPLEMENTARY FILE 4.

On 2021-04-07 12:36:01, user Atomsk's Sanakan wrote:

The paper is published here:

"SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic"<br /> https://www.nature.com/arti...

On 2021-04-09 19:32:45, user Dr. Nandkumar Kamat wrote:

In Indian state of Goa, with more than 3597 active cases ( cumulative 61239 cases, 845 deaths) as on April 9, Four Covid19 positive RT PCR samples taken just one day apart , in March 2021 from two males and females in same district produced four variants B.1.1.7; B.1.1.36, B.1 L452R, E484Q and B.1.1.464. The patients had no travel history. How samples taken one day apart can produce four different variants? . In four Positive samples?. What such high variant prevalence indicates? How to manage such a situation?. Any ideas? . The sequencing efforts are very slow.

On 2021-04-15 03:32:28, user Mark Czeisler wrote:

Note from the authors:

This paper was published in BMC Public Health on 15 March 2021 following peer review. Below is a link to the article, along with the PubMed citation.

https://bmcpublichealth.bio...

Czeisler MÉ, Howard ME, Robbins R, Barger LK, Facer-Childs ER, Rajaratnam SMW, Czeisler CA. Early public adherence with and support for stay-at-home COVID-19 mitigation strategies despite adverse life impact: a transnational cross-sectional survey study in the United States and Australia. BMC Public Health. 2021 Mar 15;21(1):503. doi: 10.1186/s12889-021-10410-x. PMID: 33722226; PMCID: PMC7957462.

On 2021-04-15 09:52:40, user Brendan Ruban wrote:

It's enough to make your mind spin. Credit to the authors for their excellent endeavours. We want a free thinking, critical, scientifically literate public that we can present the evidence to, and then they'll make great decisions. But we'll never have that. Even my friends who received degree level scientific education fail to assess evidence thoroughly. Quantifying how well the message will be followed is surely beyond scientific analysis being so multifaceted. The messenger, the environment, the message, the personal affect on the follower... So many factors. I am a huge fan of scientific evidence, but there are so many things in life in which we'll never gain enough lucidity from the classical scientific approach. We need another tool that is rational and thoughtful and will be respected. And perhaps we need to look into sociology and political thought to guide us. Scientific analysis and simplistic messaging cannot fill that gap in the highly nuanced, diverse world we now live in. My two cents.

On 2021-04-18 07:24:24, user Nicole wrote:

Had covid in early January 2020. Felt like death for over a week, the sickest I'd ever felt. Starting beginning of 2021 I've had "covid toe" (itchy red/painful blisters on two of my toes) and have had very dry inside of my nose for over a month that has resulted in several nose bleeds, raw scabby areas inside my nose and bloody, dry boogers 24/7.<br /> I wish more of this was shared and studied -- this affects people for a loooooong time.

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

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

On 2021-04-23 07:42:37, user The Crane Report wrote:

"The authors have declared no competing interests"<br /> Sinetra Gupta received almost £90,000 from the Georg and Emily von Opel Foundation to fund research “into the prevalence of COVID-19 in the population” in the first week of April 2020.<br /> https://www.opendemocracy.n...

On 2021-04-25 13:30:44, user Robert Saunders wrote:

Clery and colleagues state that “evidenced based treatments are available” for chronic fatigue syndrome. These are listed as Cognitive Behavioural Therapy-for-fatigue (CBT-f), Activity Management (AM) and Graded Exercise Therapy (GET).

In 2017 the US Centers for Disease Control and Prevention concluded that there are no effective treatments for CFS, after it re-examined the scientific evidence and removed CBT and GET as recommended treatments [1].

Similarly, the 2020 draft NICE guideline for ME/CFS specifically warns against the prescription of CBT and GET as treatments due to the evidence that they are ineffective and potentially harmful [2]. 89% of outcomes in studies of non-pharmacological interventions for ME/CFS have been graded as “very low quality” with a high or very high risk of bias by NICE’s independent experts. And no outcomes in any studies of CBT or GET are graded as better than “low quality” [3].

Clery and colleagues cite Nijhof et al (FITNET) [4] for their claim that “at least 15% of children with CFS/ME [sic] remain symptomatic after one year of treatment”. It should be noted that Nijhof et al used the 1994 CDC Fukada diagnostic criteria [5], which is less specific than other criteria as it does not require post-exertion malaise (PEM) as a symptom.

Evidence suggests that most people with fatigue and other persistent symptoms following viral infection will recover within 2 years with no treatment, but a minority with ME/CFS will not recover [6,7]. There is no reliable evidence to suggest that long term outcomes are any better for those who have been prescribed CBT or GET and there is good evidence to suggest that these interventions are harmful [8].

There is undoubtedly a need for children and adults with post-viral fatigue syndromes and ME/CFS to be given appropriate advice and support to manage and cope with the effects of their illnesses. However, acknowledgement of the very low quality of past studies and the evidence that CBT and GET are neither safe nor effective treatments for ME/CFS should be considered a prerequisite for any research pertaining to the provision of such services.

References:

1. https://meassociation.org.u...

2. https://www.nice.org.uk/gui...

3. https://www.nice.org.uk/gui...

4. https://www.thelancet.com/j...

5. https://pubmed.ncbi.nlm.nih...

6. https://pubmed.ncbi.nlm.nih...

7. https://pubmed.ncbi.nlm.nih...

8. https://www.bmj.com/content...

On 2021-05-04 02:06:41, user Uri Kartoun wrote:

Ref 9 actually does rely on combining structured and unstructured data elements. The paper is one of the earliest to identify NAFLD patients using EMRs - indeed it is limited, but I wouldn't write "fail to provide the full clinical picture of NAFLD" because it is not true.

On 2021-05-05 01:00:46, user Andre Boca Ribas Freitas wrote:

Unfortunately, the drop of proportion of elderly people among total of deaths is due in large part to the increase in deaths among young people!<br /> This is due to the characteristics of variant P.1, which leads to more serious cases among young people.

On 2021-05-06 12:22:51, user Steeve Asselin wrote:

The old adage I feel applies here: It is not because we can do it that we should do it...Has thoughts ever been given to the potential of such innovative process to be misused by Life Insurance Companies to increase or worse, deny life insurance to a person because that innovation "estimated" (because it is an estimation NOT a calculation) that the probability of this person to die is above 50% in the coming years...

On 2021-05-10 02:20:37, user Jogen ( G12 Student) wrote:

Good day, may I request for the questionnaire because we're currently conducting the same study and it would be a big help for us, thankyou in advance.

On 2021-05-12 06:41:10, user Mary b wrote:

may I request for the questionnaire? We are currently conducting our data gathering for the barriers in online learning that is related to your studies. Thank you in advance

On 2021-05-10 15:04:07, user Zsofi Igloi wrote:

article has been published in Emerg Infect Dis. 2021;27(5):1323-1329. https://doi.org/10.3201/eid...

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 2020-06-05 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 2020-06-26 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 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...

On 2021-06-08 17:43:19, user Jan Zo wrote:

The article was published recently in Mol Cell Ped https://doi.org/10.1186/s40...

On 2020-04-10 15:16:29, user Guilherme Araujo Lima da Silva wrote:

Hi, Do you have the code available? Is it R, Python or Julia?

On 2020-06-09 16:22:37, user Sinai Immunol Review Project wrote:

Title <br /> Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China

Keywords<br /> • Lymphopenia<br /> • Covid-19 severity<br /> Main Findings<br /> It was previously shown that more than 80% of severe COVID-19 cases presented eosinopenia, in a cohort of Wuhan [1]. In this preprint Cheng et al. aim to describe the clinical characteristics of COVID-19 patients with eosinopenia. In this retrospective and multicenter study, the COVID-19 patients were stratified in three groups: mild (n=5), moderate (n=46) and severe (n=8). All patients received inhalation of recombinant interferon and antiviral drugs, 50% of the eosinopenia patients received corticosteroids therapy compared to 13.8% of the non-eosinopenia patients according to the patients’ clinical presentation. The median age of eosinopenia patients was significantly higher than the non-eosinopenia ones (47 vs 36 years old) as well as body temperature (not significant). Eosinopenia patients had higher proportions of dyspnea, gastrointestinal symptoms, and comorbidities. Eosinopenia patients presented more common COVID-19 symptoms, such as cough, sputum, fatigue, than non-eosinopenia patients (33.3% vs 17.2%). Interestingly lymphocytes counts (median: 101 cells/ul) in eosinopenia patients were significantly less than in non-eosinopenia patients (median: 167 cells/ul, p<0.001). All patients within the severe group recovered and presented with similar numbers of eosinophils and lymphocytes compared with healthy individuals upon resolution of infection and symptoms. The results showed by Cheng et al. are similar to another study involving MERS-Cov [2], but is contradictory to the previous observation with infants infected with respiratory syncytial virus, where high amounts of eosinophils were found in the respiratory tract of patients [3].

Limitations<br /> The sample size of this study (n=59) is very narrow and could bias the observations described. The authors did not thoroughly measure potential confounding effects of or control for type of treatments, which were different across the patients. <br /> It is still unclear if SARS-COV-2 infection induces eosinopenia or eosinophilia in the respiratory tract, since all reports so far showed peripheral eosinophil counts. As eosinophils antiviral response to respiratory viral infections has been shown [4], it would be important have discussed if the high inflammatory response produced by eosinophils could contribute to the lung pathology during COVID-19, especially when vaccine candidates have been tested and could induce increased amounts of eosinophils.

Significance<br /> This study suggests that eosinophilia may be a clinical phenotype of COVID-19 that distinguishes eosinopenia patients from non-eosinopenia patients. The contribution of the present study is relevant and calls for experimental analysis to reveal the importance of eosinopenia in COVID-19.

Credit<br /> Reviewed by Alessandra Soares-Schanoski as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

1. Du, Y., et al., Clinical Features of 85 Fatal Cases of COVID-19 from Wuhan: A Retrospective Observational Study. Am J Respir Crit Care Med, 2020.
2. Hwang, S.M., et al., Clinical and Laboratory Findings of Middle East Respiratory Syndrome Coronavirus Infection. Jpn J Infect Dis, 2019. 72(3): p. 160-167.
3. Harrison, A.M., et al., Respiratory syncytical virus-induced chemokine expression in the lower airways: eosinophil recruitment and degranulation. Am J Respir Crit Care Med, 1999. 159(6): p. 1918-24.
4. Lindsley, A.W., J.T. Schwartz, and M.E. Rothenberg, Eosinophil responses during COVID-19 infections and coronavirus vaccination. J Allergy Clin Immunol, 2020.

On 2020-07-01 18:36:55, user SPARK wrote:

Reference 10 typo in pdf

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

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

On 2020-07-02 23:29:56, user Sergey wrote:

This pre-print does not have a Methods section- how did the medRxiv QC miss this?

On 2020-04-14 05:46:51, user Alexander wrote:

The same results: d-dimer>2500 (OR 6.9, 95% CI, 3.2-15.2), ferritin >2500 (OR 6.9, 95% CI, 3.2-15.2). Is it correct?

On 2020-07-12 14:20:35, user Knut M. Wittkowski wrote:

Herd immunity is not a "strategy", it's nature's way of dealing with influenza-like illnesses. Once the data is in, the models become obsolete. Herd immunity is already established in many places, including the northeast of the US (NYC) and most of Europe. Proof: There is no rebound in spite of widespread "reopening". QED

On 2020-07-13 09:29:08, user OxImmuno Literature Initiative wrote:

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

On 2021-01-28 19:31:33, user Maciek Boni wrote:

The public Github repo has been renamed: https://github.com/bonilab/...

On 2020-07-15 07:10:13, user Dr Ahmed Sayeed wrote:

Section Review comments and notes Abstract, title and references The study appears to be new and promising in the current scenario of COVID pandemic In the objectives, the authors have the aim to describe the bronchoscopic findings in COVID patients but in the method, they have forgotten to mention how the bronchoscopic findings will be studied What is the meaning of COVID19 patients? Is suspected covid19 or confirmed COVID 19 with Nasopharyngeal swab(PCR or serology or Nuclear acid amplification test) The references are recent and relevant with the inclusion of appropriate study

Introduction/background In introduction line 4, the term bronchial alveolar lavage would be more appropriate than bronchial culture The author uses the term culture repeatedly which excludes other methods like PCR, grams stain, KOH stain, AFB and would be advised to use the broader term to include other methods of detection of organisms The limitations of the study are not mentioned Methods The study subjects The age group of the patients should be mentioned and the site of covid infection? lung also needs to be mentioned The variables are defined and measured Yes the study appears to valid and reliable

Results My knowledge of statistics is very limited and it is difficult for me to comment

Discussion and Conclusions<br /> There is a grammatical error in line 2 and 5 of the discussion Suggest difficult to do suction In paragraph 3 of the discussion the reference 18 is written twice The reference in the discussion are not quoted in serial order The limitations of the study need to be explained more

Overall The study design was appropriate This study added the to the scarcity of the novel virus literature and it showed that more hospital acquired infections are common in patients with covid I did not find any major flaws in the article

full review:

Overall statement or summary of the article and its findings

The article needs some correction and rewriting with some of my suggestion<br /> Some more literature needs to be done and added to the discussion with some new references

Overall strengths of the article and what impact it might have in the respiratory field

The article appears to be promising and will definitely add to the literature of BAL in COVID which not frequently performed in fear of spreading the infection to the health care staff Culture and sensitivity will make a difference in the management of COVID ventilated patients

Specific comments on the weaknesses of the article and what could be done to improve it Major points in the article which need clarification, refinement, reanalysis, rewrites and/or additional information and suggestions for what could be done to improve the article.

More literature review<br /> More references need to be added<br /> Minor points like figures/tables not being mentioned in the text, a missing reference, typos, and other inconsistencies.

English and grammar

On 2020-05-01 04:18:35, user Dr. Anthony Burnetti wrote:

The proposed mechanism is blocking the import of accessory proteins into the nucleus that suppress the innate immune response. The dose needed to block viral replication in vitro is possibly higher than a dose that could have a positive impact on the immune response. It is still quite possible that the approved dose could have stronger effects in animals than in tissue culture.

On 2021-06-20 08:07:15, user Stephen Smith wrote:

note bottom-left panel in Fig1 needs replacing with the correct scatterplot; have tweeted the corrected sub-panel and will update PDF here shortly.

On 2020-04-16 23:17:24, user Samantha Grist wrote:

We appreciate the authors’ urgency in addressing SARS-CoV-2 decontamination for reuse of N95 filtering facepiece respirators (FFRs). In the spirit of that urgency and health impacts, we note two concerns with the current preprint that could (unintentionally) cause confusion: (1) likely mismatch between the wavelength range to which the reported UVA/B light meter is sensitive and the viral-killing UV-C wavelengths emitted by the LED High Power UV Germicidal Lamp, as highlighted by other commenters, and (2) omission of a direct comparison between the UV-C doses applied in this study and the minimally acceptable UV-C dose understood to be needed for efficacy (e.g., CDC Guidance).

We have contacted the authors Fischer and Munster via separate email suggesting that they:

1. Please check a potential mismatch between the UVGI light needed for viral inactivation and the UVA/B light meter used: The LED High Power UV Germicidal Lamp described in the Methods emits in the 260-285 nm range, as is appropriate to inactivate virus by damaging DNA and RNA. However, the UVA/B light meter (General Tools) mentioned in the Methods section is not suited to detect the virus-killing light from the LED High Power UV Germicidal Lamp. Further supporting the possibility of a sensor-source mismatch is the reported irradiance of 5 µW/cm^2, which is ~1000x lower than typically reported for effective N95 FFR decontamination [Lore et al., 2012 (1.6-2.2 mW/cm^2); Heimbuch & Harnish, 2019 (4.2-18 mW/cm^2), Mills et al., 2018 (17 mW/cm^2)].

Being designed for germicidal function, the LED High Power UV Germicidal Lamp would have significant output in the UV-C range and would not be expected to have significant output in the UVA/B range (280-400 nm). Put another way, the UVA/B light meter used would not be able to accurately assess the germicidal function of the LED High Power UV Germicidal Lamp, which stems from the UV-C light. It is the UV-C-specific dose that is relevant to viral inactivation, with UV-B (280-320 nm) dose providing significantly lower germicidal efficacy, and UV-A (320-400 nm) considered very minimally germicidal [Kowalski et al., 2009; Lytle and Sagripanti 2005; EPA].

1. Please clarify the total UV-C dose delivered in Figure 1, as the peer-reviewed literature points to UV-C dose of > 1.0 J/cm2 as the critical factor in N95 FFR viral inactivation treatment. Although UV-C dose governs viral inactivation, the preprint does not clearly state the germicidal UV-C dose delivered to the N95 coupons for the Figure 1 treatment times. While germicidal UV dose is the product of the UV-C irradiance and exposure time, comparison to the minimally acceptable UV-C dose of 1.0 J/cm^2 is needed. UV-C irradiance varies significantly both between and within systems, so treatment time is not an accurate characterization metric for understanding UV-C germicidal efficacy (especially when translating to a different dosing system); dose needs to be quantified directly with a NIST-traceable, calibrated radiometer matched to the germicidal wavelength range of the source. At the reported 5 µW/cm^2 irradiance, the total dose delivered during a 60 min treatment period is only 18 mJ/cm^2, greater than an order of magnitude lower than the effective 1.0 J/cm^2 UV-C dose reported in the literature for similar viruses [Lore et al., 2012; Heimbuch & Harnish, 2019, Mills et al., 2018] and current CDC guidelines for UVGI decontamination of N95s [CDC]. A UV-C dose of 1.0 J/cm^2 across all N95 FFR surfaces is understood from the literature as the minimum acceptable for N95 decontamination.

Without these clarifications we are concerned that this important study may be misconstrued by readers as indicating that either (i) very low UV-C doses are sufficient for N95 decontamination (the peer-reviewed evidence suggests that they are not), (ii) a certain UV exposure time is sufficient for N95 decontamination (dose, not time, is the critical factor) or (iii) that UV-A or UV-B are effective decontamination wavelength ranges (they are not). In the spirit of the authors’ study, our #1 concern is for the health of our heroic healthcare professionals. For additional detail from the peer-reviewed literature, please see the 2020 scientific consensus summaries on N95 FFR decontamination at: n95decon.org.

On 2020-04-20 10:54:46, user hjqq819 wrote:

It seems to conflict with this study: https://smartairfilters.com...

On 2020-05-02 21:19:54, user Javier Mancilla-Galindo wrote:

This study could have a great impact in policy making. However, even when the authors have acknowledged that serological studies will be of great importance in order to take any decisions, the authors have not commented on the impact that having non-neutralizing antibodies, especially for the persons undergoing asymptomatic or mild disease, could have on this model. Also, a sufficient and efficient cellular immune response would be granted for this model to hold true. A third factor which could affect this model is the ability of the virus to mutate into an antigenically different strain.

Even when the initial intention of the model was not to take into account these factors, it would be important to clarify that a 100% effective adaptive immune response is being assumed and that no viral antigenic variability is being considered. The authors could address what is known up to this date on these topics to strengthen the discussion and conclusions of this study and for successful publication.

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

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

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

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

On 2019-11-09 20:30:28, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT 07 NOVEMBER 2019<br /> Friday, November 08, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,286, of which 3,168 are confirmed and 118 are probable. In total, there were 2,192 deaths (2074 confirmed and 118 probable) and 1064 people healed.<br /> • 560 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new confirmed deaths have been recorded;<br /> • 1 person cured out of the CTE of Butembo;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

End of tour of the general coordinator of the Ebola response in North Kivu and Ituri

• The Epidemic Response Coordinator for Ebola Virus Disease, Prof. Steve Ahuka Mundeke, was on mission from 05 to 07 November 2019 in a few areas affected by Ebola Virus Disease in North Kivu and Ituri, to inquire about the epidemiological and security evolution of the response. During this mission, he visited some sites of the response to Beni in North Kivu, including the Mangango camp where the vaccination of pygmies took place;

• In Ituri, Prof Ahuka traveled to Biakato Mines in Mandima, Mambasa Territory, where he first reinserted three of the four cured patients he had discharged well into the Mangina Ebola Treatment Center in the area. Mabalako health center in North Kivu. He also comforted the family of the retaliating agent and journalist, murdered on the night of Saturday, November 2, 2019 in Lwemba in Mambasa territory in Ituri;

• He also chaired the daily meeting on the activities of the response in the sub-coordination of Biakato Mines;

• On his way back, the general coordinator of the riposte went to the Mangina Subcommittee, where he chaired under the trees the morning meeting in Mangina. He also visited the Health Center "Case of Salvation" which collaborates with the response and to whom he handed over a large batch of mattresses in the presence of the WHO coordinator of Mangina's sub-coordination. He again visited the Mangango camp, where the pygmies who have joined the activities of the riposte live to help the response reach all the other pygmies;

• He closed his tour of North Kivu and Ituri with a visit to the Ebola Treatment Center in Beni.

VACCINATION

• Pygmy vaccination continues in Mabalako at Mangango camp, 19/19 vaccinated pygmies;<br /> • Continuation of vaccination in expanded ring, around 3 confirmed cases on 04/11/2019 and 2 cases confirmed on 05/11/2019 and the vaccination of the biker as contacts, in Beni in five (5) areas health care, including in Butsili, Ngongolio, Tamende, mandrandele and Kasabinyole;<br /> • Since vaccination began on August 8, 2018, 248,460 people have been vaccinated;<br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS

• Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 114,626,335 ;<br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

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

On 2019-11-10 21:15:52, user GuyguyKabundi Tshima wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT 08 NOVEMBER 2019<br /> Saturday, November 09, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,286, of which 3,168 are confirmed and 118 are probable. In total, there were 2,192 deaths (2074 confirmed and 118 probable) and 1064 people healed.<br /> • 501 suspected cases under investigation;

THE LIST OF NO:

• No new cases have been confirmed;<br /> • No new confirmed deaths have been recorded;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

NOTHING TO REPORT

VACCINATION<br /> • Since vaccination began on August 8, 2018, 249,290 people have been vaccinated;<br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

MONITORING AT ENTRY POINTS<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 115.036.328 ;<br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

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

On 2019-11-27 15:46:04, user Guyguy wrote:

EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 25 NOVEMBER 2019<br /> Tuesday, November 26, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,304, of which 3,186 are confirmed and 118 are probable. In total, there were 2,199 deaths (2081 confirmed and 118 probable) and 1077 people cured.<br /> • 392 suspected cases under investigation;<br /> • 1 new case confirmed in North Kivu in Mabalako;<br /> • No new deaths among confirmed cases;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths;

NEWS

NOTHING TO REPORT

VACCINATION

• Despite the tense situation of the city of Beni, a vaccination ring was opened around the confirmed case of 24 October 2019 in the Kanzulinzuli Health Area of the General Reference Hospital;<br /> • 724 people were vaccinated with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two Health Zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,215 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.

MONITORING AT ENTRY POINTS

• Sanitary control activities are disrupted in the towns of Beni and Butembo in North Kivu province following demonstrations by the population which decries killings of civilians;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 120,825,670 ;<br /> • To date, a total of 109 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

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

On 2020-04-18 16:52:45, user novictim wrote:

Also worth considering is the timeline for treatment. HCQ proposed mode of action is not just its anit-inflammatory properties but its ability to act as a zinc ionophore. Zinc ions then interfere in viral replication. So you have to use Hydroxychloroquine early in the infection to see the maximum benefit. If you give it after lung epithelium and T-cells are already compromised, the benefit is less significant.<br /> I look forward to the trial results involving prophylaxis with HCQ and the use of it at the first signs of COVID-19.

On 2020-05-08 13:34:09, user Sinai Immunol Review Project wrote:

Title: <br /> Homologous protein domains in SARS-CoV-2 and measles, mumps and rubella viruses:<br /> preliminary evidence that MMR vaccine might provide protection against COVID-19<br /> The main findings of the article: <br /> This work aimed to determine whether measles, mumps and rubella (MMR) vaccination might provide protection against COVID-19. The authors examined: 1) sequence homologies between SARS-CoV2 and measles, mumps and rubella viruses; 2) correlations between MMR vaccination coverage, rubella antibody titers, and COVID-19 case fatality in European countries. <br /> Sequences of measles, mumps and rubella virus, which are component of MMR vaccine, were aligned to SARS-CoV-2 to identify homologous domains at the amino acid level. The Macro domain of rubella virus p150, a protease) aligned with SARS-CoV-2 Macro domain of non-structural protein 3 (NSP3), also a protease, at 29 % amino acids identity, suggest similarity in protein folding. Residues conserved in both strains include surface-expressed residues and residues required for ADP-ribose binding, and ADP-ribose 1” phosphatase (ADRP) enzymatic activity. Although the Macro domains are within a cytoplasmic non-structural protein, the authors speculate that they could contribute to vaccine antigenicity if released upon cell lysis. Measles and mumps, both paramyxoviruses, showed structural homology between their F proteins and SARS-CoV-2 spike protein. Both F proteins and spike proteins are responsible for fusion of viral and cellular membrane. The sequence identity was 20 % over a 369-amino acid region and surface-exposed residues were well conserved.<br /> The examination of historic vaccination schedules or recommendations for MMR vaccination in Italy, Spain and Germany revealed that populations who are currently in the age group of 40-49 years old in Germany, 30-39 years old in Spain, and 20-29 years old in Italy were vaccinated. However, the rubella vaccine was introduced for pre-adolescent girls and campaigns for women in child bearing age were conducted early 1970s to 90s in each countries. The latter might cover the women who are currently in the age group of 59-69 years old. If MMR is indeed protected for COVID-19 fatality, the above analysis would suggest that older populations and males are both more likely to die from Covid-19, and less likely to be seropositive for rubella specific immunity. <br /> On the other hand, analysis of anti-rubella IgG titers in moderate and severe COVID-19 patients showed increased levels of rubella IgG in severe patients. To argue that the increase in rubella antibodies in severe COVID-19 was not due to a generalized increased antibody response, the authors mentioned that there was no increase in varicella zoster virus antibody titers in a small subset of patients analyzed. While increase of anti-rubella IgM was not clearly observed in both severe and mild patients, anti-rubella IgG antibody titers were increased in patients who had been admitted for a period of less than 7 days. The authors suggest that IgG titers trend with disease burden on the basis of the shared homology between SARS-CoV2 and rubella virus.<br /> Critical analysis of the study: <br /> This study demonstrated shared homologies between SARS-CoV2 and MMR viruses that could support the hypothesis that previous MMR vaccination protects against fatality in COVID-19 patients. The authors suggested that older populations and males were less likely to be seropositive for rubella and this might be related to their higher mortality rate. On the other hand, they found that anti-rubella IgG was higher in severe patients than mild patients with COVID-19. Since there was no information about the demographics of severe and mild patients, especially the percentage of male patients and average age to analyze the relationship between severity and MMR vaccination history, the data appears inconclusive. Because of the homology in spike protein of SARS-CoV-2 and F protein of paramyxoviruses, which are important for virus entry in the host cells, measuring cross-reactive anti-measles and anti-mumps antibody titers may provide more information on whether MMR vaccination has the potential to protect against COVID-19. <br /> The importance and implications for the current epidemics<br /> The homology search for conserved domains among different virus strains and vaccine antigens may provide helpful information to develop vaccine antigens that elicit cross-reactive immunity to several viruses. While it is not clear at present if MMR vaccination reduces or not the severity of COVID-19, given the high coverage of MMR vaccination and the potential for vaccines to modulate innate immunity, this question deserves further investigation.

On 2021-07-12 23:16:53, user TheSailor wrote:

Did I miss the part where it was confirmed that all were fully vaccinated?

On 2020-03-05 12:08:26, user Luna Liu wrote:

DOI: 10.1002/path.1560<br /> In this article, they haven't found SARS virus in tesis but in distal convoluted renal tubule.

On 2020-05-11 01:41:57, user Sinai Immunol Review Project wrote:

Main findings<br /> The need for improved cellular profiling of host immune responses seen in COVID-19 has required the use of high-throughput technologies that can detail the immune landscape of these patients at high granularity. To fulfill that need, Chua et al. performed 3’ single-cell RNA sequencing (scRNAseq) on nasopharyngeal (or pooled nasopharyngeal/pharyngeal swabs) (NS), bronchiolar protected specimen brush (PSB), and broncheoalveolar lavage (BAL) samples from 14 COVID-19 patients with moderate (n=5) and critical (n=9, all admitted to the ICU; n=2 deaths) disease, according to WHO criteria. Four patients (n=2 with moderate COVID-19; n=2 with critical disease, n=1 on short-term non-invasive ventilation and n=1 on long-term invasive ventilation), were sampled longitudinally up to four times at various time points post symptom onset. In addition, multiple samples from all three respiratory sites (NS, PSB, BAL) were collected from two ICU patients on long-term mechanical ventilation, one of whom died a few days after the sampling procedure. Moreover, three SARS-CoV-2 negative controls, one patient diagnosed with Influenza B as well as two volunteers described as “supposedly healthy”, were included in this study with a total of n=17 donors and n=29 samples.

Clustering analysis of cells isolated from NS samples identified all major epithelial cell types, including basal, scretory, ciliated, and FOXN4+ cells as well as ionocytes; of particular note, a subset of basal cells was found to have a positive IFN? transcriptional signature, suggesting prior activation of these cells by the host immune system, likely in response to viral injury. In addition to airway epithelial cells, 6 immune cell types were identified and further subdivided into a total of 12 different subsets. These included macrophages (moMacs, nrMacs), DCs (moDCs, pDCs), mast cells, neutrophils, CD8 T (CTLs, lytic T cells), B, and NKT cells; however, seemingly neither NK nor CD4 T cells were detected and the Treg population lacked canonical expression of FoxP3, so it is unclear whether this population is truly represented.

Interestingly, secretory and ciliated cells in COVID-19 patients were shown to have upregulated ACE2 and coexpression with at least one S-priming protease indicative of viral infection; ACE2 expression on respiratory target cells increased by 2-3 fold in COVID-19 patients, compared to healthy controls. Notably, ciliated cells were mostly ACE2+/TMRPSS+, while secretory and FOXN4+ cells were predominantly ACE2+/TMRPSS+/FURIN+; accordingly, secretory and ciliated cells contained the highest number of SARS-CoV-2 infected cells. However, viral transcripts were generally low 10 days post symptom onset (as would be expected based on reduced viral shedding in later stages of COVID-19). Similarly, the authors report very low counts of immune cell-associated viral transcripts that are likely accounted for by the results of phagocytosis or surface binding. However, direct infection of macrophages by SARS-CoV-2 has previously been reported 1,2. Here, it is possible that these differences could be due to the different clinical stages and non-standardized gene annotation.

Pseudotime mapping of the obtained airway epithelial data suggested a direct differentiation trajectory from basal to ciliated cells (in contrast to the classical pathway from basal cells via secretory cells to terminally differentiated ciliated cells), driven by interferon stimulated genes (ISGs). Moreover, computational interaction analysis between these ACE2+ secretory/ciliated cells and CD8 CTLs indicated that upregulation of ACE2 receptor expression on airway epithelial cells might be induced by IFN?, derived from these lymphocytes. However, while IFN-mediated ACE2 upregulation in response to viral infections may generally be considered a protective component of the antiviral host response, the mechanism proposed here may be particularly harmful in the context of critical COVID-19, rendering these patients more susceptible to SARS-CoV-2 infection.

Moreover, direct comparisons between moderate and critical COVID-19 patient samples revealed fewer tissue-resident macs and monocyte-derived dendritic cells but increased frequencies of non-resident macs and neutrophils in critically ill COVID-19 patients. Notably, neutrophil infiltration in COVID-19 samples was significantly greater than in those obtained from healthy controls and the Influenza B patient. In addition, patients with moderate disease and those on short-term non-invasive ventilation had similar gene expression profiles (each n=1),; whereas, critical patients on long-term ventilation expressed substantially higher levels of pro-inflammatory and chemoattractant genes including TNF, IL1B, CXCL5, CCL2, and CCL3. However, no data on potentially decreasing gene expression levels related to convalescence were obtained. Generally, these profiles support findings of activated, inflammatory macrophages and CTLs with upregulated markers of cytotoxicity in critically ill COVID-19 patients. These inflammatory macrophages and CTLs may further contribute to pathology via apoptosis suggested by high CASP3 levels in airway epithelial cells. Interestingly, the CCL5/CCR5 axis was enriched among CTLs in PSB and BAL samples obtained from moderate COVID-19 patients; recently, a disruption of that axis using leronlimab was reported to induce restoration of the CD8 T cell count in critically ill COVID-19 patients 3.

Lastly, in critically ill COVID-19 patients, non-resident macrophages were found to have higher expression levels of genes involved in extravasation processes such as ITGAM, ITGAX and others. Conversely, endothelial cells were shown to express VEGFA and ICAM1, which are typical markers of macrophage/immune cell recruitment. This finding supports the notion that circulating inflammatory monocytes interact with dysfunctional endothelium to infiltrate damaged tissues. Of note, in the patient with influenza B, cellular patterns and expression levels of these extravasation markers were profoundly different from critically ill COVID-19.

Importantly, the aforementioned immune cell subsets were found equally in all three respiratory site samples obtained from two multiple-sample ICU donors, and there were no differences, with regards to upper vs. lower respiratory tract epithelial ACE2 expression. However, viral loads were higher in BAL samples as compared to NS samples, and lower respiratory tract macrophages showed overall greater pro-inflammatory potential, corresponding to higher CASP3 levels found in PSB and BAL samples. In general, the interactions between host airway epithelial and immune cells described in this preprint likely contribute to viral clearance in mild and moderate disease but might be excessive in critical cases and may therefore contribute to the observed COVID-19 immunopathology. Based on these findings and the discussed immune cell profiles above, the authors suggest the use of immunomodulatory therapies targeting chemokines and chemokine receptors, such as blockade of CCR1 by itself or in combination with CCR5, to treat COVID-19 associated hyperinflammation.

Limitations<br /> Technical<br /> In addition to the small sample size, it is unclear whether samples were collected at similar time points throughout the disease course of each patient, even with time since diagnosis normalized across patients. While sampling dates in relation to symptom onset are listed, it remains somewhat unclear what kind of samples were routinely obtained per patient at given time points (with the exception of the two patients with multiple sampling). Moreover, it would have been of particular interest (and technically feasible) to collect additional swabs from the convalescent ICU patient to generate a kinetic profile of chemokine gene expression levels, with respect to disease severity as well as onset of recovery. Again, with an n=1, the number of cases per longitudinal/multiple sampling subgroup is very limited, and, in addition to the variable sampling dates, overall time passed since symptom onset as well as disease symptoms and potential treatment (e.g. invasive vs non-invasive ventilation, ECMO therapy…) across all clinical subgroups, makes a comparative analysis rather difficult.

It is important to note that a lack of standardized gene annotation across different studies contributes to a significant degree of variability in characterizations of immune landscapes found in COVID-19 patients. As a result, inter-study comparisons are difficult to perform. For instance, an analysis of single-cell RNA sequencing performed on bronchoalveolar lavage samples by Bost et al. identified lymphoid populations that were not found in the present study. These include several enriched subtypes of CD4+ T cells and NK cells, among others. Ultimately, these transcriptomic descriptions will still need to be furthered with additional follow-up studies, including proteomic analysis, to move beyond speculation and towards substantive hypotheses.

Biological<br /> One additional limitation involved the use of the influenza B patient. Given that the patient suffered a rather mild form of the disease (no ICU admission or mechanical ventilation required, patient was discharged from hospital after 4 days) as opposed to the to authors’ assessment as a severe case, this patient may have served as an acceptable positive control for mild and some moderate COVID-19 patients. However, this approach should still be viewed cautiously, since the potential differences of pulmonary epithelial and immune cell pathologies induced by influenza compared to critical COVID-19 patients are still unclear. Moreover, it seems that one of the presumably healthy controls was recovering from a viral infection. Since it is unclear how a recent mild viral infection might have changed the respiratory cellular compartment and immune cell phenotype, this donor should have been excluded or not used as a healthy reference control.

Significance<br /> In general, this is a well-conducted study and provides a number of corroborative and interesting findings that contribute to our understanding of immune and non-immune cell heterogeneity in COVID-19 pathogenesis. Importantly, observations on ACE2 and ACE2 coexpression in airway epithelial cells generally corroborate previous reports. In addition, direct differentiation of IFN?+ basal cells to ACE2-expressing ciliated cells, as suggested by trajectory analysis, is a very interesting hypothesis, which, if confirmed, might contribute to progression of disease severity. The findings described in this preprint further suggest an important role for chemokines and chemokine receptors on immune cells, most notably macrophages and CTLs, which is highly relevant.

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

References<br /> 1. Chen, Y. et al. The Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Directly Decimates Human Spleens and Lymph Nodes. Infectious Diseases (except HIV/AIDS) (2020) doi:10.1101/2020.03.27.20045427.<br /> 2. Bost, P. et al. Host-viral infection maps reveal signatures of severe COVID-19 patients. Cell (2020) doi:10.1016/j.cell.2020.05.006.<br /> 3. Patterson, B. K. et al. Disruption of the CCL5/RANTES-CCR5 Pathway Restores Immune Homeostasis and Reduces Plasma Viral Load in Critical COVID-19. medRxiv (2020).

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 2020-03-21 14:55:55, user Alex Müller wrote:

Looking at supplementary Table 1, most of the controls had viral load qualitatively detected or the PCR was not done !!!! . Only 4 out of 16 controls had a proper measure of the viral load !!!! This is insane !

https://twitter.com/gaetanb...

On 2021-07-24 06:42:21, user itellu3times wrote:

Need to compare with background - what is the vaccination rate for Houston, during the period of the study? This may completely dominate the purported findings.

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 2020-05-14 16:32:24, user Anita Bandrowski wrote:

"Hi, we're trying to improve preprints using automated screening tools. Here's some stuff that our tools found. If we're right then you might want to look at your text, but if we're not then we'd love it if you could take a moment to reply and let us know so we can improve the way our tools work. Have a nice day. Specifically, your paper (DOI:10.1101/2020.02.15.20023457); was checked for the presence of transparency criteria such as blinding, which may not be relevant to all papers, as well as research resources such as statistical software tools, cell lines, and open data.

We did not detect information on sex as a biological variable, which is particularly important given known sex differences in COVID-19 (Wenham et al, 2020).

We also screened for some additional NIH & journal rigor guidelines:<br /> IACUC/IRB: not detected ; randomization of experimental groups: not detected ; reduction of experimental bias by blinding: not detected ; analysis of sample size by power calculation: not detected .

We found that you used the following key resources: cell lines (1) . We recommend using RRIDs so that others can tell exactly what research resources you used. You can look up RRIDs at rrid.site

We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

More specific comments and a list of suggested RRIDs can be found by opening the Hypothes.is window on this manuscript, direct link https://hyp.is/d1D3uI-sEeqy...<br /> References cited: https://tinyurl.com/y7fpsvzy"

On 2020-10-13 21:45:00, user Isaque Silva wrote:

The author was a past consultant of two companies that manufacturers hydroxychloroquine and yet consider himself enable, in a competing interest statement, to make such conclusion?? You must be kidding me.

On 2020-03-24 23:10:14, user Godfree Roberts wrote:

JANUARY 1 seems awfully late, if we are to believe multiple health officials:

Coronavirus may have been in Italy for weeks before it was detected. Test results worry experts as new cases emerge in Nigeria, Mexico and New Zealand Lorenzo TondoLast modified on Wed 18 Mar 2020 10.57 GMT. The Guardian

"The new coronavirus may have circulated in northern Italy for weeks before it was detected, seriously complicating efforts to track and control its rapid spread across Europe. The claim follows laboratory tests that isolated a strain of the virus from an Italian patient, which showed genetic differences compared with the original strain isolated in China and two Chinese tourists who became sick in Rome." https://www.theguardian.com...

NEXT ITEM: Massimo Galli, professor of infectious diseases at the University of Milan and director of infectious diseases at the Luigi Sacco hospital in Milan, said preliminary evidence suggested the virus could have been spreading below the radar in the quarantined areas.

“I can’t absolutely confirm any safe estimate of the time of the circulation of the virus in Italy, but … some first evidence suggest that the circulation of the virus is not so recent in Italy,” he said, amid suggestions the virus may have been present since mid-January.

The beginnings of the outbreak, which has now infected more than 821 people in the country and has spread from Italy across Europe, were probably seeded at least two or three weeks before the first detection and possibly before flights between Italy and China were suspended at the end of January, say experts.

The findings will be deeply concerning for health officials across Europe who have so far concentrated their containment efforts on identifying individuals returning from high risk areas for the virus, including Italy, and people with symptoms as well as those who have come in contact with them.The new claim emerged as the World Health Organization warned that the outbreak was getting bigger and could soon appear in almost every country. The impact risk was now very high at a global level, it said.“The scenario of the coronavirus reaching multiple countries, if not all countries around the world, is something we have been looking at and warning against since quite a while,” a spokesman said.symptoms.https://www.scmp.com/news/china/sci...

On 2020-03-25 03:16:39, user Sinai Immunol Review Project wrote:

Main findings: Antibodies specific to SARS-CoV-2 S protein, the S1 subunit and the RBD (receptor-binding domain) were detected in all SARS-CoV-2 patient sera by 13 to 21 days post onset of disease. Antibodies specific to SARS-CoV N protein (90% similarity to SARS-CoV-2) were able to neutralize SARS-CoV-2 by PRNT (plaque reduction neutralizing test). SARS-CoV-2 serum cross-reacted with SARS-CoV S and S1 proteins, and to a lower extent with MERS-CoV S protein, but not with the MERS-CoV S1 protein, consistent with an analysis of genetic similarity. No reactivity to SARS-CoV-2 antigens was observed in serum from patients with ubiquitous human CoV infections (common cold) or to non-CoV viral respiratory infections.

Analysis: Authors describe development of a serological ELISA based assay for the detection of neutralizing antibodies towards regions of the spike and nucleocapsid domains of the SARS-CoV-2 virus. Serum samples were obtained from PCR-confirmed COVID-19 patients. Negative control samples include a cohort of patients with confirmed recent exposure to non-CoV infections (i.e. adenovirus, bocavirus, enterovirus, influenza, RSV, CMV, EBV) as well as a cohort of patients with confirmed infections with ubiquitous human CoV infe<br /> ctions known to cause the common cold. The study also included serum from patients with previous MERS-CoV and SARS-CoV zoonotic infections. This impressive patient cohort allowed the authors to determine the sensitivity and specificity of the development of their in-house ELISA assay. Of note, seroconversion was observed as early as 13 days following COVID-19 onset but the authors were not clear how disease onset was determined.

Importance: Validated serological tests are urgently needed to map the full spread of SARS-CoV-2 in the population and to determine the kinetics of the antibody response to SARS-CoV-2. Furthermore, clinical trials are ongoing using plasma from patients who have recovered from SARS-CoV-2 as a therapeutic option. An assay such as the one described in this study could be used to screen for strong antibody responses in recovered patients. Furthermore, the assay could be used to screen health care workers for antibody responses to SARS-CoV-2 as personal protective equipment continues to dwindle. The challenge going forward will be to standardize and scale-up the various in-house ELISA’s being developed in independent laboratories across the world.

On 2021-04-12 19:59:24, user Rui Seabra wrote:

The article was published at: http://dx.doi.org/10.3389/f...

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 2021-05-15 22:46:36, user sam wrote:

Here is the journal article

https://royalsocietypublish...

On 2020-04-22 23:23:26, user Eric Solrain wrote:

"It was also reported that the maximum outdoor air supply was operated during the quarantine<br /> period." Is this 100% fresh air with no return? The referenced article (https://www.jstage.jst.go.j... ) notes that 100% fresh air is the norm, but for energy efficiency cabins are reduced to 30%. Full economizer mode (at 100% fresh air) is also a common energy saving measure.

On 2020-06-22 23:20:07, user Charles Warden wrote:

Hi,

Thank you very much for putting together this pre-print and database for Polygenic Risk Scores.

I took a quick look at the website, but it is possible that I might have overlooked something:

Is there currently a way to apply these scores to your own samples (and see the distribution of scores from other samples that have been tested)? If not, is this something that you plan to add in the future?

I have done some testing with PRS percentiles, but I wasn't very impressed with what I have tested so far:

http://cdwscience.blogspot....

So, I was curious how these other scores might compare.

Thank You,<br /> Charles

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

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

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

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

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

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

Minor points:

Provide p-value on the graphs.

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

On 2020-06-29 16:23:37, user David Eyre wrote:

Until an updated version is posted by medRxiv - you can find the version with the figures displayed correctly here - https://unioxfordnexus-my.s...

On 2020-07-02 20:44:39, user Joel Silveira wrote:

All of this may be due to 5-HT (serotonin) resulting from platelet degranulation, including NET.

On 2020-07-14 06:27:42, user jaswinder singh maras wrote:

Please read and suggest

On 2020-04-17 18:38:09, user Marm Kilpatrick wrote:

Can you please provide a more detailed breakdown of the ages of those sampled and the general pop? Grouping 19-64 year-olds obscures a potentially enormous amount of variation. It's also not clear why you didn't adjust estimates for age. The justification appears to be that your sample sizes were too small. Without adjustments for age it's not clear how one can make an accurate estimate of fatality ratios given the substantial age effects for COVID-19.<br /> Can you also present the results by age group (with finer age groupings - e.g. decades or 5yr incements)?<br /> Could you also present results based on prior symptoms? It seems quite likely that individuals w/ COVID-19 symptoms would be more likely to be recruited into study.<br /> Could you report the sensitivity results for your known samples at Stanford by IgG and IgM like you present the manufacturer data? This would help the reader understand the discrepancies.

Finally, it seems likely that socio-economic status of Facebook users and non-facebook users likely differs. It doesn't appear that you collected this data and yet it seems like it could significantly influence the results. Can you discuss this issue in Discussion?

Thanks!<br /> marm

On 2020-04-17 19:58:00, user John Ryan wrote:

50 out of 3,300 study participants tested positive for antibodies. This is actually a very low number given that lead researcher Dr. Eran Bendavid has been floating the notion that herd immunity has already been achieved in California, which is why the mortality rate is so low. Dr. Bendavid wrote an opinion piece in the WSJ on March 24 arguing that the case prevalence is much higher than revealed by testing and based on that analysis, the U.S. would see a maximum of between 20K & 40K deaths. We will pass that upper level this weekend.

This study did not have a random sample but a convenience sample drawn from Facebook users, many of whom believed they had already had CV-19. Lots more research to be done before any sweeping conclusions are drawn.

On 2020-04-18 02:41:54, user Andy wrote:

Based just on the 50x number, many places in New York already have herd immunity. Everyone in Westchester (currently 2,253 cases per 100,000 people) should already have it.

https://www.nytimes.com/int...

Based on the 85x number, more than everyone in New York City (currently 1,458 cases per 100,000 people) also already have it.

As noted in the paper, "bias favoring those with prior COVID-like illnesses seeking antibody confirmation [is] possible."

The bias has to be very very significant, if you think about why anyone would venture out to risk exposure to be tested during the state's Stay At Home order. In other words, if you do not believe you have been exposed previously, why would you even go -- I wouldn't.

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

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

On 2020-04-19 00:58:33, user dixon pinfold wrote:

If you read between the lines of the final paragraph of the Discussion, you can perhaps guess at some of the motivation behind the study.

No other antibody seroprevalence studies had been started in the US prior to this one, and the study's authors may have thought that it was high time, somewhat-dubious antibody tests and barriers to random sampling be damned.

On rare occasions, owing to a sense of urgency, the farmer may think it necessary to plant a crop despite the ground not really being prepared.

If others are white-hot with indignation at the very idea, it's their right, and from their side of it they are probably correct. For my part, I'm less than sure.

On 2020-04-19 05:23:12, user John Dixon wrote:

This may be stupid, but if the ad specificies what the test is for, then doesn't that render it immediately unrepresentative? If it says it's for Covid-19, then won't people be more likely to go who have had cold or flu symptoms recently and are worried they may have had it? And so the sample pool would tend to have more positives than a purely random selection of the population. Therefore the study would underestimate the fatality rate. Am I missing something? To get a random sample, wouldn't you have to leave out any specifics of what the test is for?

On 2020-04-19 18:41:29, user Dean Karlen wrote:

The authors are reporting incorrect confidence intervals because they to not correctly treat the unknown false positive rate. Use the manufacturer data for false positives (2 out of 371 known negatives) to give the posterior probability for the false positive rate (fpr) which is proportional to Binomial(2, 371, fpr). With this, calculate the 95% CL interval using the exact approach (Neyman). The correct interval, for the unadjusted case is:

[0.00% - 1.53%]

The authors report an incorrect interval for this case: [1.11% - 1.97%].

Because the unadjusted case is such a simple problem to interpret, there is only one correct treatment to produce the 95% central confidence interval. Done correctly, and reporting the correct intervals, this paper would not gain any attention at all. Please ignore this paper. It is only getting attention because the authors made serious mistakes in the analysis. The authors should retract this erroneous paper.

Python code with this calculation will be provided to anyone on request. I have contacted the lead author, pointing out their error in statistical analysis. I have received no response.

On 2020-04-20 07:07:53, user clever trevor wrote:

The Achilles heel of this study is the specificity of the serology test.

On the manufacturer's own data, they tested 371 blood samples stored from the pre-COVID era, and got 2 false-positives.

False positives are real problem on population testing. if on that crude data they over-estimate the prevalence of sero-positivity by 0.66%points, that throws the whole calculation into doubt.

the authors did their own testing for specificity, but on only 30 samples, and, inexplicably, those 30 samples were from hip-surgery patients. Hip surgery patients tend to be old, *and* therefore they tend to have generally lower circulating levels of immunoglobulin,

https://www.ncbi.nlm.nih.go...

so a cohort of hip-surgery patients is *the wrong group* to look at if you want to stress-test the specificity of your assay.

This study needs to be repeated with much stronger specificity evidence in the assay.

On 2020-04-21 06:51:43, user Vladimir Lipets wrote:

Well, from statistical/math perspective there are significant errors in results interpretation.Based on calibration experiment (2 FP of 271), authors assumed that FP range is very low. However, it is incorrect, obviously. And I’m not the first one who point out about this mistake.

Since calculating posterior probabilities combining Binomial distribution seems to be little bit tricky, I spend 15 minutes and did Monte-Carlo experiment as follows: A) Randomly selected FP probability in range 0-1% B) Simulated 270 experiments with FP probability chosen C) If exactly 2 FP results were obtained, then the main test of 3300 iteration was simulated. Steps A,B,C where repeated 1M times, to get the results. (well be glad, if somebody corrects me, if there are mistakes in this approach)

Finally, I got FP distribution which estimates probability of having more than 50 FP in 3300 (random?) candidates is about 20%. Too high... Having more than 40 is 33%

It is very confusing that these results are wrong, considering the importance of these results to the… well, whole world!

On the other hand, significant infection rate, still remains maximum likelihood.

Moreover, for me, hypotheses of higher infection rate, still seems very reasonable, let’s wait for more studies to come. As far as I understood, author want to repeat this experiment in NY

P.S. I think,I will wait for these results even more then for last episode of GoT. I hope it will not be disappointing, like this one ))

On 2020-04-22 00:40:03, user Unko J wrote:

It's nice to read below what essentially IS the 'peer-review' for this pre-print online paper! I wish I had read these comments last night before having a heated debate with my fellow quarantinees. My point was how could these possibly be 2%-4% of the population that is positive and yet Santa Clara has only 83 deaths? These divergent sets of data can't really exist in one universe, unless either we're wildly wrong about either a) the mortality rate or b) how many people can be asymptomatic and test positive with an Ab test. So yeah, between cross-reactivity against non-Covid antibodies and other false positives, I think we've decided to reject this paper. And aren't some of the authors the same on both papers?

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

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

Friday, July 19th, 2019

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

.167 152 Vaccinated persons

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

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

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

On 2020-04-18 06:11:39, user Sergey Morozov wrote:

The manuscript provides the readers with the results of retrospective analysis of different regimens of treatment of SARS-Co-V2 infected patients in a single centre in Wuhan, China.<br /> Despite several limitations, properly discussed by the authors, the described results are very actual and may impact clinical practice as COVID-19 pandemic has not yet reached its peak in most of countries, no universal and highly effective treatment was found, whereas some of the proposed remedies showed their efficacy in-vitro only. The study is methodologically correct. However, if possible, I would suggest to add the information on whether selection criteria for study population were applied (all patients admitted to the hospital and who received interferon (IFN), IFN+ Umifenovir (ARB), or ARB treatment, or only some of them).<br /> The authors convincingly proved that inhaled IFN-?2b affect 2 major ways of pathogenesis, namely, viral replication and host's immune response (IL-6), while effects of ARB remain questionable.<br /> A pilot nature of the study requires confirmation of the results in randomized controlled multicentre trials with greater number of patients enrolled. Still, at the present state it may let to avoid waste of the financial sources to the treatment regimens that seem to have poor clinical effect. <br /> Minor remark: please, consider avoidance of the use of the trade name of investigated product (arbidol), if possible. The paper is very well-organized, every statement is logical, weighed and supported with objective grounds.<br /> COI statement: I have no conflict of interest in the regard to this review.

On 2020-04-18 15:24:11, user Robert Clark wrote:

This is potentially a bombshell report, of especial importance for health care workers, showing 100% protectiveness against COVID-19 using interferon. A flaw in the report though is that while it gives a total number of health care workers who didn't take the drug contracting COVID-19, it doesn't compare that to the total of all health care workers. So we can't make the comparison in percentage terms of how many on interferon who contracted the disease (0% according to this report) compared to those not on interferon who contracted it.

Robert Clark

On 2020-04-19 05:52:47, user AlanCarrOnline wrote:

So a single 14 day lockdown is not enough. How many went on to develop symptoms in the next 14 days?

On 2020-04-19 15:29:27, user Tom Grys, PhD wrote:

Unless I'm missing something, there are concerns about the methods used to infer Viral Load. A linear regression is NOT appropriate for Ct. Each 3.32 cycles is 10x more. They need a log regression, or assign a dummy value to their LOD and calculate using relative numbers. Maybe the authors can clarify the methods to help us better understand the data? I am willing to believe the conclusions (Biology never fails to surprise us), but the data must be shown a different way to make it more clear whether VL correlates with anything.

On 2020-04-19 09:51:55, user Arne Elofsson wrote:

Just a note (from Arne): It is clear that our predictions for Sweden (done a week ago) were quite wrong (as it earlier models), the exponential increase in deaths in Sweden has not materialized. This will be made clear in a revised version - along with further analysis.

On 2020-04-19 12:52:50, user David Steadson wrote:

The model uses a base of 200 cumulative deaths for March 31 to calibrate. FHM data as of today (April 19) reports 329 cumulative deaths for that date, a figure 64.5% higher - and that data is still subject to change, with 2 deaths being added as recently as yesterday. The doubling time used is also inaccurate based on more up to date date, though not as significantly.

Recalibration would appear necessary.

On 2020-10-26 17:59:08, user Meng-Ju Wu wrote:

Hi! It is interesting to read the paper in discussion for EVs to differentiate ALS from healthy and diseased groups. And I want to share my thought on the study.

I think the main contribution of the study includes the purification of EVs with the nickel-based isolation compared to the conventional methods that makes the analysis of specific EV parameters highly sensitive and reliable. If the EVs are reliably differentiate ALS patients from healthy and diseased group, clinical assessment with the blood test will significantly shorten the diagnosis time for ALS and that the treatment may be started as early as possible. In addition, if biomarkers are available to detect ALS patients, it means that we can develop the treatment specific to ALS using their unique properties. Patients can avoid costly and lengthy process of ALS diagnosis.

I have two questions considering the methods. First, why was the supernatant from human plasma diluted in filtered PBS once but the serum from mice required 10 times for dilution? Second, what was the temperature and humidity condition for the incubation of activated charged agarose beads in NBI? I think the time to use the obtained serum would be the limitation of this approach. The content of the EVs might be changed if the centrifuged plasma samples are not immediately used. Such compositional change may be subject to the storage condition and the degradation rate of each specific proteins. It may also vary among species. Therefore, a specific time period to analyze the plasma should be strictly regulated.

In general, I think there are no major grammatic or spelling errors. However, the content may be modified in order to make it more logical and convincing to read. In the introduction part, I think it is important to summarize how is ALS diagnosed clinically. If the readers are informed that electrophysiologic diagnosis takes longer time and effort and make the diagnosis, they would appreciate the value of blood test to detect suspected ALS patient in prodromal state. In the last paragraph of the introduction, it is not reasonable to mention that the study results suggesting EVs are food biomarkers. It should be mention in the discussion or conclusion section. In the material section, the time of patient inclusion was missing. In the animal model, the paper should mention why only female mice with SOD1G93A and male mice with TDP-43Q331K were studied. Also, the timing to study the two different genes as well as the number of the mice were concerning to interpret the results. I want to suggest making a visual diagram on the machine learning technique. You did a great job in comparing the difference between ultracentrifugation and NBI using EV-like liposomes. As such, I want to suggest applying the same comparison onto the animal model to test the reliability of the using the NBI method alone in the paper. The results and the discussion are well-written and consistent with the tables and figures provided

On 2020-04-21 21:15:32, user Iyad Sultan wrote:

Patients who are sicker are more likely to get HQ or HQ+AZ and are more likely to die. Those who got the combination were 50% likely to get mech vent. The only message is that combination is superior and NO HQ alone. Otherwise, this is a biased study that misses the point - sorry!

On 2020-04-22 00:35:27, user Eric H wrote:

The Hazard Ratio confidence intervals in Table 5 of the report shows that the findings of this study are not significant. That plus the uncertainties in the Propensity Score Matching method make it even worse. I noticed the HCQ group contained a substantially higher proportion of high blood pressure and diabetic w/complications than the control group. Worst of all, they apparently did not interview even one doctor to ascertain the range of Tx criteria used.

On 2020-04-23 02:46:06, user Raspee wrote:

(1) There appears to be a statistically significant imbalance in the arms with regard to disease severity.

“However, hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease, as assessed by baseline ventilatory status and metabolic and hematologic parameters.”

The base line pulse oximetry data and baseline line absolute lymphocyte count (Table 2) - indicates a statistical difference at p = 0.024 - the subjects that received hydroxychloroquine had a worse baseline respiratory status - and a worse absolute lymphocyte count p = 0.021.

This is an inherent bias in the design that has not been adequately addressed. The analysis should compare treatment in subjects with the same disease severity.

(2) If we look at table 4 - (HC + AZ) - 82% were discharged without ventilation vs. 77% discharged without ventilation both in the HC and non- HC group - Apparently the HC + AZ group did better than the other two groups.

This is supported by the observation that the adjusted HR for ventilation is 0.43 (0.16 - 1.12) - It was better than the control arm with regard to disease progression and no different than the control for death.

So in patients that were sicker at baseline, HC + AZ appears to have had a better outcome - than the other two groups - with regard to being discharged without requiring an ICU admission.

(3) Please provide a better justification to exclude the 17 women Please go back and perform the analysis including the 17 women.

(4) What were the doses of azithromycin and hydroxychloroquine administered? How are the different doses and dose regimens adjusted in the analysis? Not everyone in the HQ and HQ + AZ groups were dosed in the same fashion. Is there a minimum number of doses that you used to include them in the treatment groups?

(5) If the control group had less severe illness at presentation, it stands to reason that the mortality rate would be lowest in the control group.

(6) Was there a sub analysis looking at impact of secondary bacterial pneumonia - which occurs in 5-15% of moderate to severe COVID-19 patients? Were the antibiotics utilized the same over the 3 cohorts or were they different?

(7) How many patients were on ace inhibitors and/or angiotensin receptor blockers? Were these medications balanced in the 3 arms? What about corticosteroid use in the 3 cohorts? Was corticosteroid use balanced?

(8) Please go back and re-run the analysis with an additional 14 days of COVID-19 data (using April 25th cut -off) as your sample size will undoubtedly be greater and we would expect that the HQ + AZ group will now have a p value < 0.05. for discharge without ventilation.

(9) Please include length of stay in your analysis as well

(10) Please include readmission rates to the hospital in your analysis

On 2020-04-21 23:29:37, user Sinai Immunol Review Project wrote:

Title: Factors associated with prolonged viral shedding and impact of Lopinavir/Ritonavir treatment in patients with SARS-CoV-2 infection?<br /> Keywords: retrospective study – lopinavir/ritonavir – viral shedding

Main findings:<br /> The aim of this retrospective study is to assess the potential impact of earlier administration of lopinavir/ritonavir (LPV/r) treatment on the duration of viral shedding in hospitalized non-critically ill patients with SARS-CoV-2. <br /> The analysis shows that administration of LPV/r treatment reduced the duration of viral shedding (22 vs 28.5 days). Additionally, if the treatment was started within 10 days of symptoms onset, an even shorter duration of virus shedding was observed compared to patients that started treatment after 10 days of symptoms s onset (19 vs 27.5 days). Indeed, patients that started LPV/r treatment late did not have a significant median duration of viral shedding compared to the control group (27.5 vs 28.5 days). Old age and lack of LPV/r administration independently associated with prolonged viral shedding in this cohort of patients.

Limitations:<br /> In this non-randomized study, the group not receiving LPV/r had a lower proportion of severe and critical cases (14.3% vs 32.1%) and a lower proportion of patients also receiving corticosteroid therapy and antibiotics, which can make the results difficult to interpret.<br /> The endpoint of the study is the end of viral shedding (when the swab test comes back negative), not a clinical amelioration. The correlation between viral shedding and clinical state needs to be further assessed to confirm that early administration of LPV/r could be used in treating COVID-19 patients.

Relevance:<br /> Lopinavir/ritonavir combination has been previously shown to be efficient in treating SARS [1,2]. While this article raises an important point of early administration of LPV/r being necessary to have an effect, the study is retrospective, contains several sources of bias and does not assess symptom improvement of patients. A previously published randomized controlled trial including 200 severe COVID-19 patients did not see a positive effect of LPV/r administration [3], and treatment was discontinued in 13.8% of the patients due to adverse events. Similarly, another small randomized trial did not note a significant effect of LPV/r treatment [4] in mild/moderate patients. A consequent European clinical trial, “Discovery”, including among others LPV/r treatment is under way and may provide conclusive evidence on the effect and timing of LPV/r treatment on treating COVID-19.

1. Treatment of severe acute respiratory syndrome with lopinavir/ritonavir: a multicentre retrospective matched cohort study. - PubMed - NCBI. https://www-ncbi-nlm-nih-go.... Accessed March 30, 2020.
2. Role of lopinavir/ritonavir in the treatment of SARS: initial virological and clinical findings. - PubMed - NCBI. https://www-ncbi-nlm-nih-go.... Accessed March 30, 2020.
3. Cao B, Wang Y, Wen D, et al. A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19. New England Journal of Medicine. March 2020. doi:10.1056/NEJMoa2001282
4. Li Y, Xie Z, Lin W, et al. An Exploratory Randomized, Controlled Study on the Efficacy and Safety of Lopinavir/Ritonavir or Arbidol Treating Adult Patients Hospitalized with Mild/Moderate COVID-19 (ELACOI). Infectious Diseases (except HIV/AIDS); 2020. doi:10.1101/2020.03.19.20038984

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

On 2020-04-22 03:57:44, user IanM wrote:

Hi,<br /> Could you explain how you performed your quantitative RT-PCR?<br /> Also, could you comment on whether a recombinant or plaque purified version of each virus carrying a mutation of interest may increase the strength of these in vitro observations? Cheers!

On 2021-09-16 10:11:35, user kdrl nakle wrote:

The paper claims significant increase of virulence yet many epidemiologists in the US would claim that is not the case with any of the variants. Which is true?

On 2021-08-20 12:21:27, user Jodi Schneider wrote:

Additional breakthrough infection data (from states that are collecting more info than the CDC is expecting) could be useful for comparison and contextualization in discussion. https://www.kff.org/policy-...

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

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

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

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

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

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

On 2021-08-23 10:32:30, user ingokeck wrote:

Dear authors, I have a problem following your comparison between vaccinated cases and non-vaccinated cases. I understand how you select the vaccinated cases with your flowchart (thank you for providing one, this really helps to understand!), but I don't understand how you create the non-vaccinated controls. If you simply add up all non-vaccinated cases, you will get a huge bias towards non-vaccinated cases, as the vaccination campaign was still ongoing during your analysis period. So you will need to account for the differences in exposure, i.e. for a vaccinated case in week 10 which got infected in week 8 you need to look at the dose2 percentage even 2 weeks earlier, i.e. week 6 to normalize the exposure risk between vaccinated and non-vaccinated persons. It would be interesting to see the result. If you can share the anonymized raw data, I may be able to help.

On 2021-08-25 12:07:48, user Prof. W Meier-Augenstein, FRSC wrote:

What other than the difference in antibody titer post-vaccination and post-infection is the take-home message of this study? Surely, the decline in antibody titer per se months after vaccination or primary infection is not a surprising finding but could be expected? Antibodies have a finite life-span given by their Ig specific half-life (for example 21 days for IgGs). In the absence of a subsequent challenge (e.g. by a secondary infection) antibodies formed in response to the challenge posed by vaccination or primary infection will have all but cleared from serum after 6+ months. Furthermore, the difference in antibody titer between mRNA vaccinated and SARS-CoV-2 infected could not have come as a big surprise either considering mRNA vaccination results in expression of spike-protein “only” which means in contrast to a viral infection host cells are actually not infected and do not reproduce copious amounts of the virus which will take longer to fight and clear from the body than the spike protein. For the same reason, macrophages (phagocytes) are unlikely to be involved in the mRNA vaccinated group to the same degree as they are in the group infected by the virus. The natural decline of IG antibodies produced in response to the mRNA vaccine does not offer an exclusive explanation for breakthrough infection. Instead, breakthrough infection occurring 146+ days post vaccination are most likely the result of a “perfect storm”, an unfortunate coincidence of the higher virulence of the Delta variant of <<7 days incubation time, the associated higher viral load produced, and the fact the production of neutralising antibodies by B-memory cells takes up to 4-5 days to reach its peak.

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

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

On 2021-08-26 14:57:06, user JK wrote:

Is anyone really surprised by this?

On 2021-08-28 11:49:17, user Doug Truitt wrote:

So if one lives in Kentucky previous infection is less protective than vaccination - https://www.cdc.gov/mmwr/vo... - and if one lives in Israel previous infection is more protective than vaccination (this study). I'd be interested in discussion as to why these two studies are at odds with one another.

On 2021-08-29 05:35:10, user some_guy wrote:

Is there any variable control?

The first question that pops into my mind is: are we comparing the same populations?

People who were first vaccinated are disproportionately old people with weaker immune systems, more likely to be infected anyways. I wonder how much does this impact the results.

On 2021-08-30 07:37:30, user 4qmmt wrote:

This paper has one major flaw that is not discussed: We know for certain who was vaccinated and of those, 199 had symptoms. Though 8 of the matched recovered had symptoms, they were assumed to have been infected because of a + PCR test in the past, which as we all know produces tons of false positives (Israel's Ct is 35-40). In fact, the paper's own data shows that of the 238 PCR+ in the vaccinated cohort, only199 were actually positive, i.e., symptomatic = ill, and in the recovered cohort, of 19 PCR+, only 8 were symptomatic, suggesting at least 60% false positives. Thus, while the number of vaccinated is certain, the true number of previously infected is at most 8, but could in fact be 0, as the Cleveland Clinic study found.

In fact, last weeks' MoH data in Israel shows that 73% of PCR + tests are on people with no symptoms, i.e., not infected. So this paper is actually saying that the risk of infection for vaccinated vs. recovered is between 27X to Infinite X.

On 2021-09-01 03:04:45, user bgoo2 wrote:

To all the people commenting on this article who have no idea how to critically evaluate study methodology.... let's just skip over the lack of control variables and omission of addressing the Santa's naughty list of biases.

Let's just get right to the bones of it... while you are searching for your "natural immunity" as opposed to vaccination (how did that go with Polio, by the way? And Tetanus? And Rubella? And Hepatitis? ... hint: those vaccines came out before the Twitter era) ... where the FAHQK do you intend to keep the millions of symptomatic infected people who require hospitalization while they recover?

How did that work out in 2020? How is that working out now? Every whack job shouting about natural immunity doesn't seem to acknowledge that to get there... you have to sacrifice a whole lot of people who would've otherwise been protected by a vaccine.

Alabama USA has less than 5 million people. 38% of the population is double vaccinated as of August 31. Nearly 2500 people are in hospital with mild to severe Covid symptoms.

Ontario Canada has 15 million people. Triple the population. 67% double vaccinated. Less than 350 hospitalized.

We can repeat these comparisons across the globe. The results of this years' vaccination program is completely undeniable.

The results in an under-vaccinated population is undeniable.

Thankfully, each day, the percentage of unvaccinated grows smaller and smaller.

And it is very quickly isolating who the remaining lunatics are in your community. (hint: they're ironically usually the ones who clearly have trouble saying NO to refined carbohydrates)

Literally, that's the end of the story.

On 2021-09-04 14:10:39, user criticalscientist wrote:

It is likely that emergence of the Delta variant, which has 10 mutations in the spike protein, is due to leakiness of the mRNA vaccines based on the single spike antigen. I more worry about the Mu variant that appears to be completely resistant to monoclonal antibodies. Time to develop new vaccines using multiple viral proteins or develop an "attenuated" virus mimicking natural immunity.

On 2021-09-09 04:36:47, user Salvatore Chirumbolo wrote:

Dear Colleagues, my congratulations for this valuable and excellent paper. With a Colleague of mine, Sergio Pandolfi (Rome) we too addressed the topic of natural immunized subjects against SARS-CoV2 (see Pandolfi S, Chirumbolo S. On reaching herd immunity during COVID-19 <br /> pandemic and further issues. J Med Virol. 2021 Sep 7. doi: <br /> 10.1002/jmv.27322. Epub ahead of print.) but we highlighted also the controversial issue of the immunization route, i.e. mucosal versus intramuscular, I mean sIgA-B cell mediated respect to a DC-mediated immunity towards the IgGs production, with obviously different B-cell memory. Do you think that this is one of the major differences between immunized vs vaccinated people? And if serum anti-RBD IgGs are the only clue for evaluating immunized people, why a "certain" discriminating attitude exists towards natural immunized subjects respect to vaccinated ones?

Many thanks in advance<br /> Regards<br /> SC

On 2021-09-09 13:13:01, user Wolfgang Birkfellner wrote:

sorry, the comment referred to another paper ... my bad ...

On 2021-09-10 07:18:00, user Jim Ayers wrote:

I hate to ask a dumb question but did the study include people with long haul covid and people who died? Quoting the study '46,035 persons in each of the groups.' The fraction of a percent who died or the few percent who have long covid who may feel too sick to participate in a study could invert the study if not accounted for since they have been weeded out of the cohort and need to be adjusted for. This study could be 100 percent wrong if the up to 20% who have long haul covid aren't participating.

On 2021-08-28 18:17:03, user Squid Pro Crow wrote:

Despite the fact that I have no formal medical training, I think that I now have the real life experience to knowledgeably comment on this. My wife and I both had our second doses of the Phizer just under 5 months ago. Also my daughter and son-in-law had the Pfizer shots about 3-1/2 or 4 months ago. At the end of a 3 day stay of 2 grandkids i began to get a cough and slight fever, and lost my sense of smell and taste. So I got tested and it was positive, My wife has a cough and body aches and will be tested today. My daughter and son-in-law (in their low 40's) are also experiencing mild symptoms and will be tested today. The kids, of course had very minor symptoms for about a day, and are completely fine. So, assuming that the adults test positive, it seems evident that the delta strain does indeed spread rapidly and easily, and the vaccine(s) may not be as effective against it. HOWEVER, I feel that at my age, with asthma and possibly COPD history, I would be much worse off had I decided against the vaccine, as my symptoms are very mild now, except for the chest congestion that I have (which is already better) that I also get from just about every cold.

My main concern is that there is not enough focus on theraputics, and major health providers like Kaiser just expect even their at-risk patients like me to just sit at home and wait to see if their lips turn blue and they can't breathe, and make it to an E.R. for a company that is usually proactive about health care, this is just stupid. An apparently, this is the norm. There are some treatments that are effective if taken early, but our government and the health system that follows their dictates are afraid to prescribe safe drugs off-label that are semi-proven to be very helpful, like ivermectin, which I managed to get from a nearby Dr. It seems to be helping clear it up even faster--my sense of smell is even starting to come back.

On 2021-09-05 04:24:28, user Adriana Perez wrote:

Regrettable the matching of the groups requires to use conditional logistic regression for the analysis which the authors did not do otherwise they would have written it. The lack of control in the matching indicates that the results can not be trusted.

On 2021-08-26 10:17:10, user Ollie wrote:

This might be an interesting approach. However, something is worrying me:<br /> 1/ The first equation in this paper "r*dr/dt = ..." is not derived, just presented as a citation from a book consisting of 304 pages. A book that is not readily accessible lest one borrows or buys it. The reader thus cannot understand the validity of this equation. The number of open and close brackets is not equal, which implies that the citation is incorrect. Further, it is a pity that parameter e_s(T_a) in the equation is explained in a slightly sloppy manner by omitting the subscript a for T in the text.<br /> 2/ The second equation is stated by the authors, rather than derived from hypotheses. A derivation seems relevant here, as the intuition of the reader (at least mine) tells him or her that the relationship between evaporated volume and surface area reduction of spherical drops is only linear for evaporation that causes very little radius decrease, or in other words: only for evaporation (dV) where dR<<r, where="" dv="the" evaporated="" volume,="" r="the" initial="" radius="" of="" a="" droplet,="" and="" dr="" the="" change="" of="" r.="" if="" this="" intuition="" is="" correct,="" it="" should="" be="" evaluated="" why="" the="" indicator="" air="" drying="" capacity="" is="" indeed="" relevant,="" as="" it="" is="" likely="" that="" in="" a="" given="" timeframe="" for="" some="" drops="" who="" evaporate="" only="" slightly="" dr<<r="" indeed,="" but="" for="" other="" droplets="" dr="R" (complete="" evaporation).="">

On 2021-08-26 16:24:55, user Felix Poppelaars wrote:

This preprint has now been published in the peer-reviewed journal Scientific Reports:<br /> https://pubmed.ncbi.nlm.nih...

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

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

On 2021-09-05 11:40:00, user OverSpun wrote:

The term "infected" appears to translate in this article to the presence of virus (detectable SARS-Cov2 at Ct<25) rather than the presence of the disease (i.e clinical manisfestions of COVID-19). Chronic carriers of other pathogens such as Staphylococcus are sometimes referred to as "not infected".

Beyond the cellular pathophysiology of bacteria vs virus, this is more than linguistic trivia because it challeges the assumption that SAR-Cov-2 asymptomatic carriers are in a transient subclinical state rather than chronic carriers. If such chronic carriers exist, are they more likely to have been vaccinated or obtained their partial immunity from a live virus infection, i.e. an acute case of COVID-19?

The following quote from this article highlights the importance of determining if mRNA vaccines have the potential to create chronic carriers: <br /> "Notably, 68% of individuals infected despite vaccination tested positive with Ct <25, including at least 8 who were asymptomatic at the time of testing."

Clinical management and public health policy require confirmation that all asymptomatic carriers are eventually clear of SARS-Cov-2 and any causative relationship between the vaccine and such carrier state is well undestood.

On 2021-08-29 16:06:28, user Paul Wolf wrote:

I wonder if the infectiousness of the delta variant could be a blessing in disguise, if it dominates over other, potentially more dangerous variants.

On 2021-08-29 19:50:51, user Yvonne wrote:

Based on Pfizer (6 month) study, the vulnerable started getting vaccinated on a great scale in February (USA) if you add 6 months that would put that vaccinated population at August, therefore the question would be asked, once the 6 month time frame of those vaccinated within a specific period, be deemed “unvaccinated” come August? With increasing spike cases/hospitalization in August (USA) and the term “unvaccinated” being used, who are within the description of “unvaccinated”, those never getting a vaccine? Or would the term include those who were vaccinated and now have passed the 6 months? I think August would be more of a complete study, if the term “unvaccinated” group is clearly defined. That would require maintaining that data, tracking the expiration of the 6 months when those vaccinated are spiking in cases. While this is helpful, the public should be shown how the spikes are increasing in August for full transparency and even comparison.

The next spike of population vaccinated in April 2021 (USA) will hit the 6 month cycle in October. Therefore December will show if the spikes in November are from that vaccinated group.

On 2021-08-31 15:57:16, user leoniehaimson wrote:

Did you project what weekly testing of 100% of students would achieve in terms of infection reduction?

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

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

On 2021-09-07 15:50:49, user Zach wrote:

Im confused if it doesn't reduce death significantly statistically and increases serious adverse events by double. Why is this being pushed as effective or safe? This data proves both to be wrong. If your chance of death is unchanged and your hospitalization rate is nearly doubled it literally makes no sense to take this. What am I missing?

On 2021-09-09 11:59:48, user Mohammad Ali wrote:

Please find the published version here: https://link.springer.com/a...

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

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

On 2021-12-06 16:42:17, user Kristi Leach wrote:

Sociology student, here, currently writing a paper on issues with the online vax schedulers and the whole idea of using them. I would like to respectfully suggest that you consider focusing on other mechanisms in addition to the city's vax distribution strategy. On March 28, we were only 6 days into phase 1B+ and 50 days into Protect Chicago Plus. Meaning shots had been available to people in Plus neighborhoods much longer than it had been available to most other residents, unless we're suggesting it would have been appropriate to divert from nursing homes, jails, and healthcare workers. That's outside of my expertise, but as a lay person, it's unconvincing. I'm piggybacking on my advisor's findings that we are neglecting the social safety net as COVID mitigation https://www.newsweek.com/wh... For example Not to mention other efforts such as contact tracing and masking. Dr. Parker mentions the lack of hospitals in Black and Brown neighborhoods.

On 2021-12-09 20:54:49, user El Fabsterino wrote:

Interesting stuff. The sample sizes are very, very small, though. I'd refrain from using p-values here at all. I'm not sure the suggested statistical test (Student's t-test) to test for differences in the means is even applicable here. The original data is clearly not normally distributed and transformed into a 0/1 Bernoulli-variable by defining an arbitrary threshold.

On 2021-12-25 13:45:26, user Blister wrote:

Interesting that most evidence used to support boosting against omicron is in vitro. If anyone has a study that shows real clinical benefit to boosting with these legacy vaccines please share. This paper is being cited by authors as supporting the use of legacy virus boosters as opposed to a new generation variant booster.

On 2021-12-11 13:48:37, user Patrick Gérardin wrote:

The paper has been accepted for publication by Travel Medicine and Infectious Disease. Attached the URL towards the publication: https://www-sciencedirect-c...

On 2021-12-13 18:28:05, user Kristen wrote:

I just stumbled across this and I wonder what impact the Mullen's norms have to do with this drop. The Mullen norms are over 20 years old and many of the VR stimuli are very outdated and are not recognizable to children born in recent years. I always prefer to give the Bayley or WPPSI if I can given this issue. It looks like there has been an overall downward trend in Mullen scores in your sample. I know you wouldn't be able to go back and compare as easily, but I wonder how the COVID-19 babies would fare on a measure with more updated norms. Bayley-4 has been freshly updated and would capture those born during the pandemic.

On 2021-12-15 06:28:56, user Robert Clark wrote:

From the article:

We used two-month periods as our basic time interval for defining the sub-cohorts, but combined months 12 to18 for the Recovered cohort and omitted months 8 to 10 for the Vaccinated and the hybrid cohorts due to the small number of individuals.

And also:

Typically, infection rates among recovered or vaccinated individuals are compared to the infection rate among unvaccinated-not-previously-infected persons. However, due to the high vaccination rate in Israel, the latter cohort is small and unrepresentative of the overall population; furthermore, the MoH database does not include complete information on such individuals. Therefore, we did not include unvaccinated-not-previously-infected individuals in the analysis.

Frankly, I don’t think the researchers are being completely open about the real reason they aren’t including the unvaccinated/uninfected in their study. The vaccination rate in Israel is about 80%. At a population of 9 million, that would mean 1.8 million unvaccinated. Obviously they could get high statistical significance with that many people.

I think the real reason is they would find the same as what was seen in the UK and in Sweden, post 6 months the vaccine effectiveness is worse than being unvaccinated to begin with.

Stunning after this length of time so many countries are refusing to present this data. They’ll collect the data up to 6 months and find the vaccine has waned to having no effectiveness in comparison to the unvaccinated. But except for Sweden and the UK, they refuse to go beyond that point.

Robert Clark