5,990 Matching Annotations
  1. Last 7 days
    1. On 2020-11-17 00:14:37, user Laurence Renshaw wrote:

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

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

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

    1. On 2020-04-03 12:58:04, user Kate wrote:

      How can you find a correlation in an observational study? I'm not even touching on the issue of not controlling for any confounding variable

    2. On 2020-04-04 12:23:52, user Jess wrote:

      Hi...I am a Malaysian & in Malaysia, all newborns hv been vaccinated with BCG since 1961.

      However, you can see fr the statistics that Malaysia is still struggling with Covid.

      I am sorry to inform that this hypothesis needs to be re-evaluated so as not to be over zealous over this.

    3. On 2020-04-04 14:52:54, user jwcross wrote:

      BCG is also used as intravesical therapy for bladder cancer (BC). Since BC is more common among the elderly, it would be interesting to know if BC patients and survivors treated with BCG have a higher survival than age-matched peers and BC patients and survivors who had been given alternative therapies.

    4. On 2020-04-04 19:54:04, user Paul Constantine wrote:

      The first published study on this subject was made by Dr.Mihai Netea. The distinguished researcher is an authority in citokyne storm and he based his research on a correlation of the clinical evolution of SARS 19 in countries where the BCG vaccination is compulsory, i.e. Romania, Germany, Portugal, Republic of Korea, Malaysia, Japan.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    11. On 2020-04-08 06:20:46, user Vincent Hare wrote:

      Logarithmic differences in death rates are also partially explained by the fact that UM and H income countries had the virus first; and there is a clear lag between infections and deaths - of several weeks. On top of this, lower income countries with mandatory BCG programs have also pursued more aggressive lockdowns. Both biases - lag, and lockdown - need to be factored into this analysis BEFORE the effect is tested for statistical significance. Otherwise, the comparison is more or less meaningless.

    12. On 2020-04-08 07:30:20, user Lara wrote:

      It does not appear that the authors adjusted for number of tests conducted. There is a significant difference in the number of tests conducted in high income like the US (>2 million) versus LMIC like South Africa (1700 tests). Right now it can't be assumed that BCG is protective, when the full scope of the problem is not unknown, or in other words true case load is presented.

    1. On 2020-04-04 03:15:45, user Charles Baker wrote:

      Why are some states peaking in the model almost 30 days behind all the states around them? If you look at virginia and then all the states around them they peak almost a month after. How or why would that be?

    2. On 2020-04-07 14:53:16, user Quinctius Cincinnatus wrote:

      I was glad to see the Imperial College estimate. I'm equally glad to see this work in progress. What happens if only 20% of the population is susceptible to the disease? Diamond Princess had a max of 20% (and no one did a "heat map" of the ship which boggles my mind), Italian hospital workers have a rate of 20% (assuming they have been equally exposed to the virus). We know that the Black Death didn't strike everyone, and it didn't kill everyone it struck. What was the asymptomatic rate used in this study? Did Page four doesn't relay. In Diamond Princess and the Italian village Vo, it appeared to be almost 50%. finally, did anyone look at the potential impact of weather? I suspect Wuhan had more cases than Hong Kong - one reason was the warmer climate. So, as this work in progress continues - it would be good to see those assumptions and look at those variables. .

    1. On 2020-04-04 10:47:57, user Lorenzo Sabatelli wrote:

      Hi Laura, very interesting, thanks for sharing. One thing that may be useful to account for is the differential impact of social distancing on age group mixing, e.g. that could be done by taking into account household demographic structure in Seattle and perhaps finding additional data (or making some assumptions) on the proportion of mixing between age-groups happening at the household level vs. external world. Another thing one could add is a separate group of adults with higher risk of infection and transmission accounting for health workers and other essential workers exposed to the public, e.g. apparently in Italy about 10% of currently diagnosed cases are among healthworkers, and explore the impact of transmission due to healthcare and/or other essential services (e.g. supermarkets, drugstores, etc)

      Lo.

    1. On 2020-04-06 16:17:40, user Maxim Sheinin wrote:

      Given that people dying from Covid-19 are primarily the elderly (60+), and BCG vaccine is given only in childhood, does it make sense to look at the correlation using current status of BCG vaccination? It would seem that status 60+ years ago will be more relevant. This will likely complicate the picture, as many European countries that do not mandate BCG today used to have it in the past, and conversely some other countries have introduce BCG not that long ago (http://www.bcgatlas.org/) "http://www.bcgatlas.org/)").

    1. On 2020-04-07 13:48:42, user Erin Beaver, MS, LCGC wrote:

      I am a genetic counselor. I have been following the ABO COVID19 outcome correlation. I know many are discounting the data because they can’t fathom how ABO is associated with susceptibility to a respiratory pathogen. As a genetic counselor, I started thinking in a genetic linkage type of way and looked to see what was located near ABO blood group genes on chromosome 9. It turns out there is a gene, GBGT1 that sits next to ABO blood group and so this is a relatively conserved haplotype for polymorphisms in those genes. GBGT1 encodes a glycolipid called Forssman glycolic is which is thought in humans to be a major attachment site for pathogen binding to cells. This gene is highly active in lung tissues. I find all of this interesting a something worth investigating, but as a clinical genetic counselor with no access to a research lab, I don’t have the means to investigate my theory that perhaps GBGT1 aka FS glycolipid plays a role in infection from COVID19. Thoughts? Anyone that can look at this relationship?

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

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

    3. On 2020-04-15 18:32:13, user Jaime Navarro wrote:

      There is a significant flaw in this paper's claim that Type A blood types are more susceptible to CoViD-19, and type O are less. In that the paper does not address the susceptibility of those with type B or AB blood. If as the paper suggests type O blood sees the virus as a type A antigen and so attacks the virus. Shouldn't the same happen in patients with Type B or AB? After all they would have antibodies to type A the same as type O people would.

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

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

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

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

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

      https://covid2019system.com/

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

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

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

    1. On 2020-04-17 18:50:31, user thecity2 wrote:

      The sample could be biased by a self-selection effect. People on FB who wanted to be tested because they think they had the virus at some point.

    2. On 2020-04-17 20:13:28, user AM wrote:

      thanks for the information. you did not specify if you found the IgM or the IgG antibody which would allow us to know what stage they are in on the time frame of when someone sero-converts. it would be great to conduct the same study now, or even 2 weeks from now to see the changes and the transition to herd immunity. ideally, you have kept track of all the people you tested. we could derive a wide range of conclusions from this one time test. nonetheless, thanks for taking the time to conduct these tests.

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

    3. On 2020-04-18 02:30:01, user Don Phan wrote:

      This does not appear to be random sampling. If you are using volunteers, then the sampling is not representative of Santa Clara country. What have you done to correct this? And I am not talking about demographics. The people who suspected that they had the virus would be the most likely to risk the shelter at home, drive to location, and participate.

    4. On 2020-04-18 14:03:13, user Richard Davis wrote:

      Could you guys make the data and code available for other researchers to try and replicate, now that the paper is out there?

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

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

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

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

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

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

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

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

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

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

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

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

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

    2. On 2020-04-18 19:50:29, user Oliver Van Oekelen wrote:

      "Raw data will be available in GEO."

      When will the data be uploaded? This preprint was posted almost two months ago. Would be amazing to fuel collaborative efforts across the globe and increases the impact of this work...!<br /> Thanks

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

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

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

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

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

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

      Summary:

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

      Limitations:

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

      Findings implications:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    1. On 2020-04-04 19:53:38, user VirusWar wrote:

      It is interesting study, but I'm surprised you don't talk about level of Potassium in the blood ? Did you check it ? Was there any Magnesium given to correct level of Potassium. Especially, you noted heart troubles with people having renal disease, but it is well known they have excess of Potassium which creates such heart troubles. Also, was treatment H+A stopped when QTc >=500ms ?

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

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

    1. On 2020-04-07 23:44:19, user Ronaldo Wieselberg wrote:

      I see a lot of problems with this study.

      First of all, it does not mention whether risk factors - such as hypertension or diabetes - were taken into account. The table provided for randomization doesn't show them either. Having a difference about risk factors could play a huge part in the difference - let's consider that control group had more people with pre-existing conditions, for instance, thus, the risk of evolving to a severe disease would be improved, independently of HCQ. Moreover, there is no mention of whether the four individuals who progressed to severe disease had any pre-existing conditions, needed mechanical ventilation or any other details of the "severity" - could it be a SpO2 of 92% only, accordingly to inclusion criteria.

      The paper does not describes clearly the evaluation criteria. How was measured the cough? Was it dicotomic (have cough/don't have any cough)? How could you determine whether the pneumonia "improved"? Was it accordingly to the presence/absence of infiltrates on X-Rays, or % of lungs compromised in CT-scan? Thus, calculating a significative p value for subjective criteria is really, really a difficult point.

      It does not states, as well, the symptoms duration prior to admission and start of the intervention. People who had, for instance, 10 days of symptoms before looking for a physician could have fewer days of symptoms than another individual who looked for medical assistance with two days of symptoms - and there is no mention about this.

    1. On 2020-04-12 05:17:40, user John Roberts wrote:

      Cytodyn’s drug Leronlimab is proving effective in treating the cytodyne storm and getting severe Covid patients off of ventilators.

    1. On 2020-04-12 08:33:12, user tsuyomiyakawa wrote:

      Thanks, everyone, for your precious comments.

      1. We are examining the potential confounders, which includes the ones mentioned here.

      2. As Rosemary mentioned, BCG is an attenuated version TB and, indeed, big protective effect of TB prevalence against COVID-19 exists. We will incorporate the data in the next version.

      3. We obtained the data from the web site of European Centre for Disease Prevention and Control, and are re-analyzing the growth of spreading in a more quantitive manner. Basically, there are significant effects of BCG/TB against COVID-19 growth, which will replace the data shown in Figure 3.

      4. Regarding the tourists from China, according to a survey, the top 10 destination countries of China’s out bound countries are Japan, Thailand, South Korea, Indonesia, Singapore, Malaysia, Australia, UK, New Zealand, and Maldives, and 9 out of 10 of them are the ones with extremely low COVID-19 cases and deaths (4 or lower deaths per million) , as of April 13th, which makes it unlikely that the Traveling activity from China matters. This will be added to the discussion. Also, we evaluated the number of international arrivals in each country and it did not essentially affect the results (almost at all).

      5. As for masks and green tea, they cannot explain 1) the differences between Eastern Europe and Western Europe and 2) low COVID-19 indices in Africa, South America and South East Asia. We may consider their potential effect, once we can get any good statistics representing those things, but so far, we set priority low for these potential confounders.


      Anyway, we will upload next version sometime in next week and it will be appreciated if you could keep providing us critical comments, which will greatly improve our manuscript. Thank you!

    1. On 2020-04-12 13:23:51, user Joe Gitchell wrote:

      Thank you to the authors for taking the time and effort to report these findings in the midst of confronting the challenges from managing the COVID19 pandemic. Please stay safe!

      And it is with humility that I make a request to them to do two things with their data on tobacco use. The first I think should be pretty straightforward, the second will depend on the specificity available within the Epic records:

      1) In Tables 1 and 2, can you please break out "Never" and "Unknown" in to separate categories; and

      2) In these tables and in other analyses, can you please break out "tobacco use" at least in to combustible (cigarettes, cigars, cigarillos, hookah, etc) and noncombustible (smokeless tobacco, snus, vaping) categories?

      Thank you. I also found your use of CART/decision-tree analysis really helpful, btw.

      Joe

      Disclosures:<br /> My employer, PinneyAssociates, provides consulting services on tobacco harm minimization on an exclusive basis to JUUL Labs, Inc., a manufacturer of nicotine vaping products. I also own an interest in an improved nicotine gum that has neither been developed nor commercialized.

    1. On 2020-04-13 00:38:02, user Craig wrote:

      The safety of HCQ alone has already been proven. It's the efficacy, both as prophylaxis and as treatment, that needs to be studied.

      Studying HCQ in combination with a drug that is already known to have adverse cardiac effects seems like a study designed to produce data with a negative bias.

    1. On 2020-04-13 13:45:53, user Rosemary TATE wrote:

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

    1. On 2020-04-14 08:27:08, user Lisa Kane wrote:

      Can the authors comment on the role air conditioning and/or building/residence heating may have played in the cooler cities?

      That is, are cooler, measured city temperatures actually proxies for warm, indoor temperatures?

    1. On 2020-04-14 14:03:10, user Chris Pericone wrote:

      The death data in table 3 are the reverse of what is described in the results section. I assume the high and low dose columns were mistakenly switched in that table?

    1. On 2020-04-15 14:34:21, user Bio wrote:

      I have several issues with this study:

      1. I find not including time as a factor in the model bewildering. After all, time is the single most important factor for the number of cases for most of the countries in the model. The model is only log(cases) ~ population + temperature. But for example, in half a month's time, population and temperature won't change much, while the number of cases could increase several fold for some countries. Time is a critical factor to model and is more important than temperature and population. Not including time, the model in the paper cannot be stable. Basically as time changes, your conclusions likely will change.

      2. Many other important factors were not considered. For example, at what point of COVID-19 growth is each country at? If one compares March 14 to March 27, China's numbers are not much different while USA and many other countries have quite different numbers on those 2 days. The model cannot be stable due to this as well (time + point during growth). Also what about containment policy causing slower growth? Effects from such important confounding factors were not considered in the model.

      3. There are many other smaller issues such as USA cases were mostly in Northeast, with latitude clearly higher than the one used to represent USA. In China, the cases happened in many provinces with vastly different latitude/temperature but all cases counted at one latitude/temperature. Moreover, the vast majority of the cases happened in China during Jan/Feb while you used late March temperature to represent them. Inaccuracies like these seriously impact modeling latitude/temperature as a continuous variable. Excluding countries with small population but high case rate as outliers is also questionable, given that you modeled population size already.

      Fig. 7 could benefit from being plotted also for 2/29, 3/14, 3/21. Interpretation of Fig. 7 could instead be that it showed 2 groups of countries/latitudes that reflects the temporal sequence of events rather than temperature: COVID-19 started in China, spread to South Korea and Italy, then Europe and America as they trade/travel often and happen to all be cold countries; then in March COVID-19 picked up in southern hemisphere and tropical area and still going. It's likely time and policies that helped Australia case rate be relatively low instead of temperature, because the spread of COVID-19 is still early there and they learned from other countries to control the spread from early on.

      Therefore I do not believe the paper provided convincing evidence for temperature-dependency of COVID-19.

    1. On 2020-04-15 18:51:04, user Greg Lambert wrote:

      The study seems to incorrectly use a UVAB meter instead of a UVC meter to measure the exposure from their UVC lamp, consequently their UV exposure readings are wrong(low).

      From the study:

      "Ultraviolet light. Plates with fabric and steel discs were placed under an LED high power UV germicidal lamp (effective UV wavelength 260-285nm) without the titanium mesh plate (LEDi2, Houston, Tx) 50 cm from the UV source. At 50 cm the UVAB power was measured at 5 u W/cm2 using a General UVAB digital light meter (General Tools and Instruments New York, NY)."

      Their lamp emits effective UV wavelength of 260-285nm but a General UVAB meter only measures from 280 to 400 nm with a calibration point of 365nm.

      A

    2. On 2020-04-16 01:47:35, user 777Rampage wrote:

      I have the following questions and issues on their testing of UVC LED.<br /> 1. In the article it states that General Tools UVAB digital light meter was used. Is that the UV513AB meter? If so, that monitoring probe is only able to measure UVA&B, not C. <br /> 2. If using General Tools UV512C meter, that probe's spectral range is 220 to 275 and it is used to measure low pressure mercury UVC lamp, not UVC LED.

    1. On 2020-04-15 23:59:04, user Mark .Minnery wrote:

      The average time between symptom onset and randomisation was 16.6 days. Could the authors discuss the implications of this potential confounder. Was the long time before treatment because of delay between symptoms and presentation at hospital?

    2. On 2020-04-16 09:05:11, user Stef Verlinden wrote:

      Please study the paper thorougly before jumping to conclusions. Standard of care means that (most of the) patients were also treated with lopinavir-ritonavir, arbidol, oseltamivir, virazole, entecavir, ganciclovir and/or interferon-alpha.

      The autors also did a post-hoc subanalyses with patients who did not get other medications other than HCQ in the treatment group or nothing in the SOC group. And, for what it is worth, here they found ‘a significant efficacy of HCQ on alleviating symptoms’.

      What also could be of interest is that patients treated with HCQ showed a significantly higher reduction of CRP. One of the proposed MOA for HCQ is an anti-inflammatory one.

      All in all a very weak study from wich not much can be concluded

    1. On 2020-04-15 22:33:38, user suradip das wrote:

      Very interesting work. I have some questions -<br /> 1. Page 15 (Table 1): C-Reactive Protein is an indicator of cardiovascular disease. It is interesting that the authors chose to conduct the study in a population where 86% of all the patients had high CRP.<br /> 2. Out of the 84 patients receiving HCQ (90.5% having CRP>40mg/l and 45.2% having cardiovascular diseases) only 3 patients died (3.6%). In comparison, the group which did not receive HCQ but had similar weight proportions of high CRP and CVD saw 4.1% mortality.<br /> To summarize, there appears to be no significant difference in mortality rates when patients with CVD and COVID-19 are treated with HCQ versus a placebo.

    1. On 2020-04-16 21:55:50, user Sinai Immunol Review Project wrote:

      Title:<br /> Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou, China<br /> The main finding of the article: <br /> This study analyzed immune cell populations and multiple cytokines in 31 patients with mild/moderate COVID-19 (ave. 44.5 years) and 25 with severe COVID-19 (ave. 66 years). Samples from patients with fever and negative for the SARS-COV-2 test were used as control. At inpatient admission, total lymphocytes number was decreased in severe patients but not in mild patients, whereas neutrophils were increased in severe patients. CD4+ and CD8+ T cells were diminished in all COVID-19 patients. CD19+ B cells and NK cells were decreased in both mild and severe patients, however, severe patients showed a notable reduction. These data might suggest a profound deregulation of lymphocytes in COVID-19 patients. Further analysis showed significant increases of IL-2, IL-6, IL-10 and TNF? in blood of severe patients at the admission. Sequential samples revealed that IL-2 and IL-6 peaked on day 15-20 and declined thereafter. A moderate increase of IL-4 was seen in mild/moderate patients. Thus, elevation of IL-2, IL-6 can be indicators of severe COVID-19.<br /> Critical analysis of the study: <br /> There is no information on when the patients were assessed as severe or mild/moderate, at inpatient admission or later. The authors could have analyzed the correlation between immune cell population and cytokine levels to see, for example, if severe lymphopenia correlated to higher elevation of IL-2.<br /> The importance and implications for the current epidemics:<br /> While similar findings have already been shown, the data corroborates alterations in circulating adaptive and innate immune cell populations and cytokines, and its correlation to disease severity. The increase of IL-2 and IL-6 at the admission might an indicator to start intensive therapies (like convalescent serum) at an early time.

    1. On 2020-04-18 20:25:12, user Scott Howell wrote:

      Conceptually this study and its conclusions are patently false. Internal endogenous hormone levels do not equate to exogenously administered androgens. Perhaps a read of Morgentaler's saturation model would enlighten the authors. A statement that long-term elevated free testosterone levels causes prostate cancer does not align to either the saturation model or the use of bipolar androgen therapy at supraphysiologic doses to treat prostate cancer. There is a big jump from Mendelian randomization to nuances in physiology and what occurs in practice. Just like secondary data analysis of insurance claims to establish risk should be banned or at least relegated to their limitations, these type of studies drawing conclusions outside of the scope of the data should be relegated to their limitations or even less.

    1. On 2021-08-11 09:40:50, user Joao Martins wrote:

      Incredible! Violation of the underlying assumptions of the test used in this article!

      From its ref (10), Tajima's original proposal of D' test:<br /> "Assumption: In this paper we consider a random mating population of N diploid individuals and assume that there is no selection and no recombination between DNA sequences."

      Tajima's D' applies to "random mating populations of diploid individuals": do RNA-viruses fit in this description?

    1. On 2021-08-12 12:38:42, user Peter Colin wrote:

      Has there been any analysis of vaccine effectiveness in (1) persons who tested positive for Covid prior to vaccination, versus (2) persons who did not test positive prior to vaccination (negative and/or untested)?

    1. On 2021-08-18 15:39:23, user Lincoln Sheets wrote:

      This analysis seems to present a paradoxical finding, that there is an inverse relationship between early deaths from cancer and early deaths from CVD. If high animal-source diets lead to more early deaths from cancer, does that make it impossible for those same persons to die early from CVD? This is a detailed big-data study that deserves reivew, publication, and expansion by additional researchers.

    1. On 2021-08-23 04:17:45, user Anon wrote:

      How about selection bias? Vaccinated people take covid more seriously which would lead to less infections.Not to mention this study was before Delta took over so the results are irrelevant

    1. On 2021-08-26 11:13:46, user Fran Braga wrote:

      There's an English mistake in the interpretation section "Interpretation". The sentence "Coronavac vaccinees above 55 years" is repeated

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

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

    1. On 2021-07-12 02:43:41, user Jennifer McDonald wrote:

      Dr Conly et al, I read your pre-print with interest. I have a few clarifying questions.

      First, given the demonstrated viral stability on hospital equipment/PPE, I am curious why there was no attempt to collect virus directly from used PPE. Does the pre-publication contain the full list of objects/equipment sampled, including those with negative results?

      Second, can you elaborate on the sampling method used to obtain the positive cultures off hands? Were these samples collected at random or immediately following a cough into the hands? Regarding the hand transfer experiment, were the hands washed in culture medium immediately following the transfer? Was this experiment attempted with a longer duration between cough-handshake and handshake-culture?

      Thank you for clarifying,<br /> Jennifer McDonald, MD, Ottawa

    1. On 2021-07-13 02:15:24, user ?0 wrote:

      Will note that absolute risk reduction between vaccinated and unvaccinated is 0.32%. The authors’ claims that the vaccines prevented death are not supported by the evidence provided, which is correlated in nature, not causative.

      A good paper on this issue: https://www.ncbi.nlm.nih.go...

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

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

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

      mu = 1.7/100;

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

      R0 = 4;

      bN = R0*alfa;

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

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

      for k = 2:1:numel(t)

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

      end

      T_steps = T/dt;

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

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

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

      end

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

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

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

      end

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

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

    2. On 2020-05-27 01:46:56, user Dario Palhares wrote:

      I congratulate you from this preprint. Since 2014, in Bioethics, we have questioned quarantine measures as a simple excuse for the State to get absolutist; a State of Exception. Never in history has quarantine shown any effectiveness in reducing, modeling or preventing a single epidemics. I guess you´ve got interesting feedback here in order to aprimorate you work when published. Anyway, I would like to ask (if not beg) you to analyze data from some other European countries: Portugal, Greece, Netherlands, Belgium, and in USA, to split data by state/region: NY, NYC, Florida, California.

    1. On 2021-07-15 07:57:35, user John Lambiase wrote:

      What's truly interesting is that no one is talking about Fructose and refined sugar activating long term NLRP3 inflammasome in the Monocyte which reprograms the monocyte on a path of inflammation and upregulation of Reactive oxygen species which lowers nitric oxide in Endothelium. Sars CoV-2 seems to have a knack of exploiting and exacerbating this chronic inflammation in patients leading to an acute medical malody.

      What deactivates NLRP3 inflammasome? Olive Oil, Melatonin, Vitamin D Fish Oil, Resveritrol, Quercetin etal. Been taking doses of Oleic Acid for months because of all the research I was finding. Cashews high in Oleic Acid. If this all comes down to Anti Oxidants vs Oxidants then medicine is going to have serious explaining to do. Unfortunately that would never get out.

    1. On 2021-07-15 13:36:08, user Merlin Khoo wrote:

      This laboratory study seems to indicate the need for a booster 3rd jab based on the latest variant as the virus mutates further and further from the original wild type

    1. On 2021-07-16 09:27:55, user ??? wrote:

      There's recently published article presenting the application of brain temperature rhythm in outcome prediction after traumatic brain injury. This paper should be cited.<br /> "Kuo, L.-T.; Lu, H.-Y.; Huang, A.P.-H. Prognostic Value of Circadian Rhythm of Brain Temperature in Traumatic Brain Injury. J. Pers. Med. 2021, 11, 620. https://doi.org/10.3390/jpm..."

    1. On 2021-07-22 18:02:23, user Andriy Kolesnyk wrote:

      1260 times at which point on timeline? Delta is faster (4 days vs 6), and in case of measuring the viral load at 6th day we can receive the result 1260 times bigger for Delta. Becouse Delta has 2 days more for multiplying the viral load.

    1. On 2021-07-22 18:39:09, user Bernie Mulvey wrote:

      Did you check which genes are driving the "synapse organization" enrichment? The clustered protocadherin locus is GWAS significant in, I believe, all of these disorders. Several of those 20-some genes have ontology terms including "synapse organization" (which is true of these genes). However, the density and complex transcriptional regulation of these along with LD results in several PCDH genes being associated to variants by QTLs and so forth. Just sharing to be cautious, as this phenomenon has spoiled many a moment of ontologic excitement in my own work.

    1. On 2021-07-26 17:27:59, user Fortu Nisko wrote:

      The research should not use PCR or tests derived of PCR for assessing 1-Infection 2-infectiousness 3-illness. If the research depends on flawed data, at its root, then, the conclusions drawn will be no better. First establish what you are actually looking for - an intact viral particle that can be cultured. Further, establish that each supposed transmission be verified using such a method. And, de4fine the actual illness that is supposed to be directly associated with the pathogen you are looking for; that means a syndrome of acute severe respiratory distress. Not a cough or a wheeze; not a fever; not a symptom that is applicable to many other potential causes. So make the causal relationship front and center. Specifically identify and test for the particular causal agent; specifically verify illness caused by that causal agent. Failing that, your research will be for nothing specific - not for a specific infection, not for a specific transmission, not for a specific malady. This should be noted in the strenghts/weakness portion of any research paper produced from your efforts.

    2. On 2021-07-26 17:44:49, user Fortu Nisko wrote:

      From expected results.

      We intend to present the evidence in three distinct packages: study description, methodological quality assessment and data extracted. We intend on summarising the evidence and drawing conclusions as to the quality of the evidence.

      Fair enough. A ruthlessly non-politiccal assessment of the quality of scientific evidence will be the most significant portion of the research. Perhaps you might add to the discussion portion of your research paper the impact of basing policy on evidennce that does not meet the standard for policy-grade evidence. This is a very important discussion. Policy-makers seem to be ignorant of the standards necessary to draw conclusions that then can translate into sound policies for public health. They seem to have fallen into the trap of self-perpetuating policies that become untethered from an assessment of the quality of evidence.

      Wishing you luck and good fortune in your pursuit of a worthy goal re quality of evidence.

    1. On 2021-07-30 05:51:51, user Raja Mugasimangalam wrote:

      The views expressed in this article do not necessarily represent the views of the DHSC JCVI NIHR or WHO. TW, HS, IH, JB, EJK, KS, JV, TLV are employees of AstraZeneca. <br /> should I need to say anything more?

    1. On 2021-07-30 16:47:26, user Kirsten Elliott wrote:

      There seem to be at least three reviews based on the same literature search, so I'm posting similar comments on each of them.

      The search strategy for this review has not been adequately reported as there is not enough information in the appendix to replicate the search in any database, as it hasn't been made clear which fields were searched. It is therefore not compliant with PRISMA 2009 or PRISMA 2020 reporting standards. Furthermore, from what has been reported it appears that relevant search terms and subject headings have not been included, meaning that it is likely relevant papers have been missed.

    1. On 2021-07-31 20:00:31, user I. Bokonon wrote:

      In Table S5, among participants receiving placebo, why are the surveillance time (0.265) and n2 (736) for the positive baseline SARS-CoV-2 status group greater than the sum of those values shown for the 3 positive subgroups (0.264 and 735)?

    2. On 2021-08-01 14:47:19, user Nir Tsabar wrote:

      In the 'Disposition of Participants' chart, the numbers of participants who 'Entered open-label follow up' (lowest items) and those of 'Withdrawal after Dose 2' do not add up to those 'Received Dose 2'. <br /> There seem to be missing 583 participants in the Placebo group and 1258 in the Pfizer BNT162b2 group.<br /> Moreover, a clear statement regarding the possibility of unknown deaths in the randomized groups may be very important.

    3. On 2021-08-02 22:47:42, user drwambier wrote:

      Please revise: "No new serious adverse events assessed as related by investigators were reported after data cut-off for the previous report."

      Previously reported: 2 deaths (BNT162b2) vs 4 (placebo), with zero deaths related to COVID19 in each arm. Death (any cause) is the main SERIOUS ADVERSE EVENT (SAE), and a higher number was reported, please revise accordingly.

      "During the blinded, controlled period, 15 BNT162b2 and 14 placebo recipients died; during the open-label period, 3 BNT162b2 and 2 original placebo recipients who received BNT162b2 after unblinding died. None of these deaths were considered related to BNT162b2 by investigators. Causes of death were balanced between BNT162b2 and placebo groups (Table S4).”

      Since you are reporting the 6 months data, please consider rephrasing to the full numbers: "18 deaths on BNT162b2 versus 16 deaths on the placebo (including the 2 deaths after receiving BNT162b2)." It is also important to specify the denominator for each group. It is unclear what is the total number of patients were followed-up for full 6 months, and how many were lost to follow-up (survivor bias?).

      "Cumulative safety follow-up was available up to 6 months post-dose 2 from combined blinded and open-label periods for 12,006 participants originally randomized to BNT162b2. The longer follow-up for this report, including open-label observation of original BNT162b2 recipients and placebo recipients who received BNT162b2 after unblinding, revealed no new safety signals relative to the previous report”.

      If 3 deaths happened in the BNT162b2 group until 1 month after Dose 2 during the blinded period and 5 in the placebo group, the new deaths after that month were: 15 for BNT162b2 and 11 for placebo (including the 2 deaths after receiving BNT162b2). Please verify if this is correct, if it is, please state specifically as this might be considered a safety signal.

      200 HIV patients data is still not disclosed. I understand that this is per protocol. However, we ask to please disclose the current HIV+ data, since many are receiving the shots under EUA without data of their subgroup analysis.

      Plus, assuming that those are in the 22,166 patients of BNT162b2 and 22,320 of placebo:<br /> Considering the “scenario of all patients followed, without unknown outcomes”:<br /> RR for death is 1.1328 (.5778-2.2208). An increase by 13% of all cause mortality in 6 months of follow-up including the part of vaccinating the placebo arm.<br /> The ages and gender of deaths would be informative for safety since populations were balanced by randomization please add a table with such information.

      Current data suggests that within 6 months of follow-up, BNT162b2 does not reduce all-cause mortality. There is a signal that it might increase all-cause mortality. <br /> Assuming that it would be difficult for investigators to access if deaths were related to BNT162b2 since myocarditis or heart-related side effects were initially thought to be unrelated to BNT162b2, also no previous signals of thrombosis were reported.

      Causes of death were assumed to be “Cardiac Arrest” or other "unknown" descriptions. There is even a “death” as cause of death on the table… "dementia?" For future trials or third injection, an active screening for myocarditis (Serum Cardiac Troponin T and Creatine Kinase–MB), and thromboembolic events would be prudent, specially in the >65 y.o. population, which may be more vulnerable to momentary reduction of cardiac muscle function through inflammation.

      As this was a healthy population (not treatment of COVID-19, etc), and deaths were rare. <br /> It seems that all-cause mortality was indeed more common than deaths by COVID-19 in the current manuscript, thus, they cannot be left aside from the trial results discussion. Please discuss specifically about the comparison of COVID-19 deaths in the control group vs the relative increase of deaths detected in the BNT162b2 group and how putting those numbers in the balance.

      About COVID-19 related deaths, the score was expected: 2 deaths on placebo (“COVID-19”) and 1 death in Vaccine ("COVID-19 pneumonia”). <br /> With the current safety data, caution is warranted, since the number to harm in the best scenario points that approximately 100 deaths could be attributed to the vaccine for every 1M fully vaccinated, if the increase in all-cause deaths is not a noise of low numbers.

      "Safety monitoring will continue per protocol for 2 years post-dose 2 for participants who originally received BNT162b2 and for 18 months after the second BNT162b2 dose for placebo recipients who received BNT162b2 after unblinding.”

      Was all the control group crossed-over to BNT162b2 post-unblinding? If so, please state and give the reasons why it was decided to do so. If there is no placebo arm for a safety control comparison, this safety monitoring will only be important if extreme flags happen: such as unexpected high number of serious adverse events emerge.

    4. On 2021-08-06 12:28:32, user Sven wrote:

      So we have only 2 "covid deaths" in the placebo group and 1 in the vaccinated group, for a total group of about 44000 persons and a period of half a year? Regarding "all-cause deaths", we have 14 (placebo) vs 15 (vaccine). Covid death was extreme rare, so that it had no impact on death rates, i.e. the vaccine did not yield any significant benefit in preventing deaths in the study population. From only 3 covid deaths we cannot derive any statistical data! Where is the evidence for the statement, that the vaccine is preventing covid deaths?; this study is certainly not able to show that. Moreover, as the placebo group is vaccinated already, it is also not possible to get this data in future from this study.

    5. On 2021-08-06 15:18:01, user Robert Clark wrote:

      It is notable that the number of deaths six months after the vaccine is not reduced. This might be because the number of deaths due to COVID overall is percentage-wise too small for a difference to show up in this trial.

      A question I have is specifically for the elderly cases. Is the number of deaths or life-threatening events higher, lower of the same for that case?

      Robert Clark

    1. On 2021-08-02 01:30:33, user Paul wrote:

      Hasn't the CDC indicated that data says people who get the vaccine are just as likely to get the virus and be just as contagious as those who don't take the virus? That means that to 70% of the population getting the virus, or even 100% will not lead the herd immunity since the vaccines fight the virus in the blood after it has reproduced in the throat. What is the point in a vaccine with 50% effectiveness it still makes you five times as likely to develop serious symptoms compared to one with 90% effectiveness. Being vaccinated does nothing for the common good, only for the individual good of reducing symptoms. At the rate the Philippines is spreading the virus it will take 100 years to burn itself out with or without the vaccines. It seems to me the best way to deal with it is to vaccinate as many as possible to prevent symptoms and then open the economy and remove the mask mandates so the virus will burn itself out quicker. It is a tough decision to make but I have known many more who died do to being unemployed and not able to afford their maintenance medicines during the lockdowns than who have died from COVID

    1. On 2021-08-06 21:20:16, user MotherGinger wrote:

      This is at the stage of calculating CFR where we were with the initial wild SARS-Cov2 in February 2021. That is, we have no idea how many cases there actually are, because most people aren't getting tested.

      Testing was extremely common prior to mass vaccination, but post-vaccination, most people no longer bother to get tested as soon as they have symptoms, most institutions (colleges, healthcare, etc.) stopped requiring weekly testing for those with proof of vaccination, most institutions requiring immediate tests for participation (sports, travel, etc.) stopped requiring it for those with proof of vaccination, and the CDC, among other public health bodies, announced they would stop collecting stats for asymptomatic cases in the vaccinated.

      That means the denominator for the CFR for VOC-202012/1 ("Delta") is completely unknown, just as it was in February 2020 for the wild virus, when it was estimated at 3.5% or higher, at least an order of magnitude higher than it turned out to be.

      Unfortunately, this study doesn't yet allow us to compare apples to apples.

    1. On 2021-08-07 15:14:47, user A Call for Honesty wrote:

      What a number of critics ignore in their comments is that there are really poor countries that have a very, very limited supply of expensive medicines. If they have a good supply of Ivermectin, like one I know well, a caring doctor would not hesitate to try this medicine. I have had family that were quite ill with covid and responded very well to ivermectin. If their GP was in the US, UK or some other EU country, he would quite likely have his license withdrawn at the behest of politicians and academic experts who are not working with patients at the coal face. Less doctors in these situations would mean even more suffering and deaths.

    1. On 2021-08-08 14:35:35, user Yaakov Kranz wrote:

      Hi I'm curious was this study taking into acount the Delta variant?<br /> Did anything cahnge since then with regards to the Delta variant?<br /> Thanks!

    1. On 2020-05-26 20:36:45, user C'est la même wrote:

      A lack of sequencing data limits the conclusions of this study. Suggestion that individuals were reinfected by the same strain is not confirmed due to lack of specificity of the serological testing. There is far greater genetic diversity of these strains compared to SARS-2. Just like influenza, subsequent infections in the few years following an infection are due to exposure to different strains, or similar strains but with significant drift in key antigenic proteins.

      Immunological memory is not dependent on high levels of circulating antibodies and hence the antibody kinetics do not tell us very much about long term immunity. The observed kinetics are similar to many other infections/vaccines and primarily reflect plasma cell kinetics, not memory-B-cell functions. So long as a small population of memory T-cells and B-cells are maintained, long term immunity will be maintained.

      I strongly suggest that a strong worldwide vaccination approach will be effective, even if at worst, there is significant genetic variation that requires annual vaccinations.

    1. On 2020-05-26 21:50:22, user Sam Wheeler wrote:

      Good paper, I downloaded the pdf.

      We still don't have the answer: what if an adult has taken the BCG shot very recently. There are clinical trials that will answer this question, hopefully soon.

      In many countries, medical doctors refused to prescribe BCG vaccines to adults even before covid-19, and pharmacies don't stock the vaccine at all. In which countries can an adult easily buy a BCG vaccine, and in which countries it is nearly impossible?

    1. On 2020-05-27 02:53:57, user Divalent wrote:

      Are case data the date that test results were reported to the public, or the date the lab determined the test result, or the date of test sample was taken, or the date of first symptoms? (I'm trying to get a handle on what sewage detection tells us, and how it can be used. I.E., how much of the 7 day offset is due to asympt shedding, vs test-processing delays vs test result reporting delay, vs time from sympts to time of test.)

    1. On 2020-05-27 08:45:44, user Thomas Wieland wrote:

      Thanks for your comment! Unfortunately, there is no explicit behavioral measurement that could be used. However, there are some other findings which imply behavorial changes before the German "lockdown" started: Surveys show an increasing awareness towards SARS-CoV-2/COVID-19 in February/first half of march (e.g. the Ipsos survey of February 2020). Moreover, the German Robert Koch Institute (RKI) documented an "abrupt" and "extremely unusual" decline of other respiratory diseases (with shorter incubation period, such as influenza) from the beginning of March (calendar week 10). See the corresponding RKI paper (EpidBull 16/2020, page 7-9). These findings imply a more cautious behavior (staying at home when sick, physical distancing to strangers e.g. in public transport, thorough hand washing, carefully cough and sneeze etc.). Well, also hoardings started in the middle of February, which is, of course, an indicator for awareness towards the Corona threat (though hoarding is not desirable or even "rational"...)

    1. On 2020-05-29 08:49:02, user David Cadrecha wrote:

      Similar study in Spain shows a 20% reduction in the number of deaths per day social distancing started earlier.

      Looking at different countries and regions, a strong correlation between late intervention and number of fatalities is found.

      It should work for any country and tells that every single day of anticipation reduces deaths by roughly 20-25% (in the absence of other preventive actions)

      “LA PRÓXIMA VEZ DEBEMOS ACTUAR ANTES. Impacto de la precocidad de las intervenciones por Covid-19”

      https://t.co/TWfpDklLfo

    1. On 2020-06-01 09:16:36, user ??? wrote:

      Dear Colleague

      I am Jaehun Jung, the corresponding author of the paper.

      HIRA in Korea conducted a database update on May 15 that included 1,000 confirmed cases and over 150,000 controls. We will revise the manuscript based on a more detailed case definition and medication history.

      Preliminary analysis showed that most of the drugs presented in our study did not show any statistically significant effects. If you are using our research results in systematic review or meta analysis, be sure to consider this.

      Thank you

    1. On 2020-06-02 10:57:42, user Bruce Nelson wrote:

      The sample unit was the household. One person was tested per household. But SARS-CoV-2 is clustered by household, leading to possible underestimate of prevalence?

    1. On 2020-06-04 00:53:02, user Bruce Zweig wrote:

      The sentence ‘Our findings showed that only 4.22% of the overall population received 5ARI anti-androgen therapy’ should say ‘male patient population’ instead of ‘overall population.’

    1. On 2020-06-04 08:18:20, user Abderrahim Oussalah wrote:

      It could be insightful to have adjusted effect sizes for the GWAS after considering body-mass index and other potential risk factors (e.g., therapy with angiotensin-converting enzyme inhibitor / angiotensin receptor blocker) as covariates in the models?

    2. On 2020-06-05 07:12:39, user Matthias Hübenthal wrote:

      Thanks to Ellinghaus et al. for sharing these interesting results. The authors utilized rs8176747, rs41302905 and rs8176719 to predict ABO blood types. Combinations of the inferred blood types then have been used to predict case/control status employing logistic regression. Alternatively, one could base the prediction on a genetic risk score incorporating the ABO SNPs. Boxplots of the risk scores could then be used to illustrate group-wise differences. However, for completeness association results for the ABO SNPs should be reported and discussed.

    1. On 2020-06-04 09:47:03, user Malcolm Semple wrote:

      Dear Authors, Great paper, well written. Your reference Docherty et al as unpublished. This is now published in BMJ : Docherty Annemarie B, Harrison Ewen M, Green Christopher A, Hardwick Hayley E, Pius Riinu, Norman Lisa et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study BMJ 2020; 369 :m1985

      Did you identify distinct symptom clusters as we did?

      Wishing you well

      Calum<br /> CI ISARIC4C & CO-CIN

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

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

    1. On 2020-06-05 20:23:05, user Steve S wrote:

      It is good to see this strange weekly cycle being addressed by the research community. The hypothesis that contracting on the weekend because human behavior changes on these days—set by our arbitrary definition of time (a week)—sets the trend of the weekly cycles in viral metrics (cases reported and deaths) is appealing. However, it seems a tad odd to me that the explanation of the death rate being weekly is completely dependent on it having a cycle that is divisible by a week, i.e., 14 days is two weeks. If say the death rate peaked at 10 days instead, then you would expect interference patterns between previous weeks to create something analogous to beat frequency in sound, where there would be several irregular peaks within in a week and the weeks could look different from each other. 14 days would therefore have to be a perfect coincidence, which just seems unlikely... but still possible I guess. I'm a neuroscientist not an epidemiologist, so forgive my ignorance, but are there examples of other infectious diseases that have weekly trends. Are the cases reported and death rates also weekly in these cases?

    1. On 2020-06-06 15:24:15, user wbgrant wrote:

      The analysis of data from European and perhaps other countries is problematic for a couple of reasons. One is that the 25OHD concentrations used may not be appropriate for those who develop COVID-19 due to age mismatch or not being for winter.<br /> Another is that life expectancy, an index for the fraction of the population that is elderly, has a stronger influence on COVID-19 rates than does 25OHD. See this preprint<br /> Kumar V, Srivastaa A. Spurious Correlation? A review of the relationship between Vitamin D and Covid-19 infection and mortality<br /> https://www.medrxiv.org/con...<br /> I verified their findings by using more recent case and death rate data.

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

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

    1. On 2020-06-08 02:08:18, user Simin wrote:

      Hello from Istanbul, <br /> Not a science person but just a concerned human being. <br /> I have a question if I may. <br /> The water basin siphons mentioned in the article, are they only restroom siphons or does the research include the siphons of the kitchen basins too? <br /> The reason for my question is to figure out if the grocery cleaning habits maybe ended up any virus particles in the kitchen sinks.

      Thank you for all your efforts and kind reply if possible.

      Simin

    2. On 2020-06-12 04:50:15, user Paul_Vaucher wrote:

      Dear authors,

      Thank you for this interesting article of major interest. I find the process and research question to be most relevant. I however have a few questions that remain open to understand how the study could come to the conclusion that aerosols and surfaces were not important vectors of covid-19.

      1. What is the external validity of the results for making inferences over infectiousity on the entire period people could be carriers of the disease? In this study, most participants had already been in quarantine for 5 days. Repeated sampling has shown viral load to be optimal in the upper airway system 2 days before and 2 days after symptoms appear. Viral load from nasal and throat swabs drop to a rate where viral culture becomes difficult from 8 days onwards. Most of the study participants were probably beyond that point and were therefore not expected to be very infectious in the first place. If existant, infection through secondary contact and aerosols are however more likely when viral loads are high. It therefore seems difficult from the collected data to infer that household infection through these vectors are unlikely at all times.<br /> 2) When comparing risks from different surface types, how do authors justify the use of chi2 statistics with a sample smaller than 200 and all positive cells with less than 5 cases? In this condition, type 2 errors are very high and this test should not be used under this condition. The number of positif tests are too low to be able to answer the question of whether different surface types are more or less potential vectors of the disease.<br /> 3) Statistical inference assumes independence between measures. This is clearly not the case as a median of 9 samples were taken from each household. Statistical methods should therefore account for these clustering effects. However, the sample size is probably too small for this and a pure descriptive approach without inference could be more relevant.<br /> 4) Could we have any indication on viral load from throat swabs in household cases? If their viral loads were low, we wouldn’t then expect contamination to happen anyway. In two of your 21 housholds, there were apparently not a single case with a positive PCR. This might suggest viral loads to have been too low for any form of infection to have occurred in these households. It seems important to document to what extent each household had at least one person who could infect the air and surfaces.<br /> 5) Likewise, to document risks of infecting the air, were any samples from direct breathing taken from cases Within each household? This seems important as we would theoretically not expect ambient aerosols to be present in aerosols if viruses were difficult to find from air breathed out from cases.

      This study investigates an important question. I am however not convinced the method used truly answers the question as the public seems to understand it. Their is indeed room for misinterpretation and for the public to consider contact and air contamination not to occur at any time.

      To avoid any overinterpretation, it seems important to clarify that this study only tests risks of air and surface contacts days after people have been placed in quarantine when we don’t suspect them to be very infectious anymore.

    1. On 2020-06-08 13:40:04, user bvwredux wrote:

      Exine. The outer layer of the pollen, it is incredible stuff. Also the "remnants of the tapetal cells" found in the nooks and crannies of the exine layer. Either or both of them may be potently anti-viral for the corona virus -- that's my speculation. There is little pollen in bat caves. See https://www.ncbi.nlm.nih.go...

    1. On 2020-06-08 20:18:31, user itdoesntaddup wrote:

      I did my own empirical research along these lines for local authorities in England, finding a power law relationship between cases reported by Public Health England and population density, summarised in this chart, made before there was a change in the testing regime:

      https://datawrapper.dwcdn.n...

      I was inspired to put it together through being a long term observer of the output of the Santa Fé Institute (including some of the papers written by Luís Bettencourt under their aegis). I found that Geoffrey West had published a short note there on the same topic a few days later:

      https://www.santafe.edu/new...

    1. On 2020-06-10 19:55:05, user Sebastian Rosemann wrote:

      Dear authors,

      this is an interesting overview-study. However, many questions concerning the quality of the data and a systematical question arise.


      Systematical

      How do the authors assure that the uniform reporting delay of ~10 days reflects the real pandemic curve by e.g. comparing published reproduction rates against the rates used to estimate the effects of NPIs? How do the authors deal with overestimating certain NPIs when comparing their impact rates to local observations?

      For the german numbers we have the following discrepancy:<br /> The estimated reproduction number is based on reported cases using a delay of ~10 days from infection to confirmation. This seems not appropriate as a study from germany and the discussion around it shows.<br /> If simply using the reported cases curve one may get wrong drop rates for NPIs.<br /> This Science-study first used the reported cases:

      https://science.sciencemag....

      As stated by the authors in a technical note the drop-rates are quite different if one uses the real epi-curve with exact symptom-onset (if available):

      https://github.com/Priesema...

      Figure 19 shows a model based three-change-point approach and the impact.<br /> Figure 16 shows the same model fitting the curve with reported cases.<br /> Mind the drop rate of the first invention (which was cancellation of gatherings > 1000).

      The reproduction numbers in this study lead to a totally different conclusion as changes in R are not correct and gatherings < 1000 as first NPI are not introduced correctly which gives the closing of schools an overestimated impact.

      A closer look at the reproduction number of the netherlands reveals the same.<br /> Drops are visible but not in this intensity:<br /> https://www.rivm.nl/documen...


      Data quality

      A look around intervention dates in different countries brings up questions concerning the quality of these data. Some of the findings to discuss are the following:

      Belgium:<br /> Large gatherings were effectively cancelled since around march 10th and 13th<br /> https://en.wikipedia.org/wi...

      Bulgaria:<br /> 10 out of 28 regions closed on march 4th<br /> https://www.bnr.bg/en/post/...<br /> General closage happended on march 13th<br /> https://en.wikipedia.org/wi...

      Germany:<br /> Gatherings > 1000 were effectively cancelled since march 9th, one week before closing schools.<br /> https://en.wikipedia.org/wi...<br /> Closing schools was announced on march 13th but startet on march 16th.

      Finland:<br /> https://www.reuters.com/art...<br /> Mainly closed since march 18th.

      This list is open and does only include a few finding that should be discussed or taken into account in the estimation. However, i know that inventions are not always clearly clear to categorize. But this should be more reflected by untercertainties in estimations.

    1. On 2020-06-10 21:37:52, user La-Thijs Mokers wrote:

      HCQ isn't even the active component in the andecdotal cases of succesful treatment. You have to administer the HCQ together with a zink-supplement, else nothing will happen for sure. Also you need to get the timing right; this suggested treatment will only work during the early stage of infection, when viral load is relatively low. Herein HCQ merely functions as ionophore for the Zn2+ ions ( https://www.ncbi.nlm.nih.go... ), so that they can easily pass the cellwall into the cell, where they will inhibit viral replication ( https://www.ncbi.nlm.nih.go... ). Nothing fancy to it if you know how to use freaking google. Ofcourse loads of misleading studies will be continued published - like the recent Lancet drama of Mehra et al -, leaving out zinc and testing ridiculously high dosage of HCQ on very ill patients with a sky high viral load. No wonder you get a negative result if your research setup is designed to fail like that.

    1. On 2020-06-11 03:51:09, user kpfleger wrote:

      I echo Helga Rein's request for data on vitamin D levels of COVID-19 patients in your data. I emailed Ben Goodacre and the OpenSafely team email address suggesting this on May 14 but have received no response. The data implicating low vitamin D levels as causally worsening severity of COVID-19 infection is now very compelling. For a 1-page summary of the facts with links to supporting sources see: http://agingbiotech.info/vi...

      The world needs a dataset with n=10,000+ examining vitamin D levels in COVID-19 patients.

    1. On 2020-06-11 18:36:28, user Ruth Kriz wrote:

      This is consistent with my findings in other chronic infections that about 55% have PAI-1 or Leiden Factor V mutations that prevent them from up regulating their Thrombin/anti-thrombin complexes or elevated Lipoprotein (a) that binds with tPA when inflammation triggers the clotting pathway.

    1. On 2020-06-12 15:42:05, user DFreddy wrote:

      I miss mental health as risk factor. Every human also has a mind and a body. We know from piles of evidence that the mind impacts physical health too. I hope it will be included in a future analysis. Seems very elemental to do, no?

    1. On 2020-06-14 12:52:28, user Nayo57 wrote:

      Best recent seroprevalence studies from NYC and Bergamo yield roughly 1500 deaths/100k infections or a crude IFR of 1.5%. With Germany's crude IFR of about 4.5%, the total number of infected would be around 3 times the official estimate. We have to await age-stratified data to refine this estimate.

      On the other hand, CFR for medical staff in Germany as reported by RKI is about 0.15% vs 0.2% for age-groups 20-60 years when adjusted to gender-mix in medical staff. This would put the underreported fraction of cases in the range of about 30%.

    1. On 2020-06-19 06:18:19, user Kato Peterson K wrote:

      This is an interesting study Nicholas, looking forward to you coming up with a harmonised country specific manual to guide nutrition education and counselling for T1DM in Uganda

    1. On 2020-05-20 09:31:25, user Reks wrote:

      Two comments and one question:<br /> 1. I think your reference 26 got mixed up? ( here: In a recent systematic review we concluded that the evidence in favour of face mask use outside of hospital was weak. 26)<br /> 2. The measures data are not entirely accurate: face masks were made mandatory in Poland on April 16th<br /> 3. Assume that countries tended to close down schools at roughly same epi stages. Your models, however sophisticated, would not be able to tease out the effects of school closures and any limiting factors that are inherent in the course of this epidemic, let's call them "natural" factors for want of a better term. Or would they? If not, should you mention that in the limitations? Can you perhaps check if this is likely to be the case (i.e. closures or other measures tending to be introduced at similar stages across quite a few countries)?

    1. On 2020-05-20 19:25:43, user Christian Gibbs wrote:

      Please note the dislaimer at the top of the article:

      This article is a preprint and has not been peer-reviewed. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice.

    1. On 2020-08-02 18:17:55, user iVX Engineering wrote:

      Why on earth they used such dangerously high dosing (800mg per day is the daily max according to FDA, with most other studies using 400) 2400mg dose in the first day? This is a toxic dose. What is these doctors trying to do, intentionally poison patients? Who reviewed the ethics of doing this and why was this allowed? And why are there no comments in the paper justifying this extremely high dosing? In addition to this there needs to be a portion of the discussion addressing how potential toxicity from high doses may have influenced the results.

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

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

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

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

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

    1. On 2020-08-02 00:11:16, user Michael Verstraeten wrote:

      I would like to make also a suggestion. <br /> 1. Calculate the amount of people infected in the whole population on the highest result of your research, by age category. (That's a simplification since there are also other relevant factors then age, like comorbidity factors but ok). <br /> 2. Add to this amount the results from the positive PCR-tests in the hospitals until that moment (Also a problem since there is a % of false negative results, but ok) <br /> 3. Estimate the amount of patients whit a general problem who were refused to get a blood test due to a suspicion of Covid - 19 and were not admitted to the hospital (if possible). And add them to the grand total. <br /> 4. From there on you can make an estimate based on the weighted average evolution of the deaths from de date corresponding to the testdate pn (a few days later then the test dates). It seems to be a relatively good assumption to consider that de evolution of the infections will be relatively equal to the evolution of the deaths / age category. <br /> 5. There is one problem however: we are not sure about the exact amount of deaths due to Covid. 73 % of people deceased in the care homes were not diagnosed and the tests have a big error margin. And diagnoses are maybe wrong due to extended diagnose protocols. Maybe it would be a good idea to calculate an average on the evolution of deaths and hospital admissions. Even if the latter depends on the admission policy.

      Even with the uncertainties and the quite big error margin, maybe it will be possible to come with such an exercise closer to the real number of the infected population.

    1. On 2020-08-05 12:20:29, user Per Sjögren-Gulve wrote:

      Have the authors tested whether the sample of incubation days is normally distributed or not? If not, it is more appropriate to present the range of the observed values than to report 95% CIs. The latter requires that the parameter is normally distributed (the arithmetric mean is equal to the median).

    1. On 2020-08-05 17:49:59, user Dieter Mergel wrote:

      Note from the author:<br /> Error in Figure 4 and Figure 5.

      Fatality rates leT2000 in Figure 4 and lT18 in Figure 5 have to be shifted by 18 days to earlier dates. Fatality rate lT20 has to be shifted by 20 days to earlier dates.

      Updated version will be available shortly.

    1. On 2020-08-13 12:21:29, user Justin Cotney wrote:

      These Cq values are at the very unreliable end of the instrument's detection range. Most biologists and in my own lab do not trust Cq values greater than 35. The instrument will usually report a number even in negative controls as was seen in their table. Performing a melt curve analysis after the PCR reveals if it is the product you were expecting or spurious amplification. Please show qpcr traces and melt curves.

    1. On 2020-08-17 14:11:29, user Aaron J. Courtney wrote:

      Is the mask modeling based upon a surgical mask? Have you rerun the model assuming everyone wore N95s? Any eye protection to guard against conjunctiva infection? What factor did aerosol transmission, particularly fecal and urine aerosolization in community rest rooms, account for infectivity calculus? (recall Hong Kong high rise apartment building SARS-CoV-1 outbreak caused by faulty plumbing)

    1. On 2020-08-17 14:30:16, user Ciron Soauv wrote:

      This study was cited in a nice powerpoint (link below) made by the Dr.<br /> Wanderson Oliveira from Brazil Ministry of Health, titled "scientific<br /> evidence of pandemic impact". It is being circulated on WhatsUp, together<br /> with videos from Dr. Ioannidis from Stanford, who suggests mortality rates are<br /> around 0.1%. Unfortunately, many people in that country, where more than 100,000<br /> people died of COVID, minimises the pandemic impact justifying it with those<br /> pre-prints. Noted, no fault on the authors – they are the ones that need to get<br /> “immune” to misrepresentation.

      https://www.sinprolondrina....

    1. On 2020-08-20 15:31:30, user Matt Price wrote:

      6 people had antibodies to SARS CoV2 prior to departure, 3 of whom had neutralizing antibodies (i.e., much more potent). Of the 3 who didn't have neutralizing antibodies, all developed symptoms and became PCR+ during the trip. I have a few comments for the authors, that I think would be helpful to address (unless I missed it):

      1. Did those 3 without neutralizing abs later develop neutralizing antibodies?
      2. Were they (as someone below suggests) the carriers who might have brought the virus on board, since PCR does have a high rate of false negatives (i.e., failing to detect virus when in fact it is there)? This might be difficult to test, as you don't have samples during the trip...
      3. How many of the 104 with positive PCR and later seroconverted developed neutralizing antibodies (i.e., is it common that everyone develops potential immunity?)

      Very nice work.

    2. On 2020-08-21 13:41:13, user CodeJ wrote:

      While it is great that we have some concrete evidence that being infected/testing positive for antibodies gives you protection, how long does protection last? Is it 3 months? Is it 1 year? Is it lifelong? I want to know when these three Ab+ individuals were actually exposed to the virus, though I acknowledge that this information could be difficult to obtain. Based on what we know about SARS and common cold causing coronavirus strains, this protection may be short-lived. These questions needs to be answered before the pandemic can truly be over and an effective vaccination strategy can be developed, but we obviously need more time to answer these questions, as well.

      Also, while the studies of the neutralizing antibodies are promising, there is no evidence that the neutralizing antibodies they detect actually protect people from getting reinfected, as T cell response also seems to be important, which is highlighted by other studies. Additionally, are these antibodies present in serum getting to the mucosal sites of infection they need to be in order to protect? Importantly, this study does underscore the need to test the therapeutic and prophylactic potential of monoclonal Abs directed against the virus (i.e. the NP protein or S) that can perhaps be derived from these neutralizing Abs present in convalescent individuals.

    1. On 2020-08-21 09:47:26, user David Simons wrote:

      Hi,

      It looks like this may already be formatted for submission but you may want to revisit the inclusion of Qi (reference 16) in particular.

      The relevant pre-print has only dichotomised smoking into current and non-current smokers. The authors do not make clear that non-current smokers are never smokers. I've found this difficult to mannage in our own work so we do not include them in meta-analysis if there is no explicit never smoker category. It is unclear from your manuscript how you manage this.

      Kind regards,

      David

    1. On 2020-08-23 18:52:01, user Michael Shodell wrote:

      Greatly enjoyed this paper as the logic, assumptions, and<br /> analyses are very-well described and readily followed. This also enables good critical assessments<br /> of the range of confidence to place in the numbers at which the author<br /> arrives. HOWEVER – by ignoring<br /> everything other than the sedentary in-flight, non-perambulating and generally<br /> observant passengers (see excerpts below), the author may have missed the<br /> greatest risk areas of flying.

      For instance, when disembarking at the destination, the more<br /> crowded the plane (eg. a plane with middle seats occupied), the riskier this<br /> part of travel. I can tell you from recent<br /> experience that for up to 10 minutes passengers crowd the aisles awaiting disembarking<br /> and, being the flight conclusion, often with masks at half-staff or barely<br /> covering the face at all.

      Probably similar consideration for use of toilets and aisle<br /> movement during the flight.

      106 We focus on a particular passenger who is traveling<br /> alone, and assume that the primary

      107 infection risk for this passenger arises from other<br /> passengers in the same row. We further

      108 assume that additional risk arises from passengers in<br /> the row ahead and row behind. For two

      109 reasons, we treat the risk posed by other passengers as<br /> negligible …

      … we treat the risks associated with boarding

      119 the aircraft, leaving the aircraft, visiting the<br /> lavatory, and touching surfaces in

      120 the passenger cabin, as second-order effects.

    1. On 2020-08-24 17:34:34, user Muhammad Shoaib Akhtar wrote:

      Seems good work. However, biochemical analysis of remedesivir inside body is an important aspect and must be focused as well.

    1. On 2020-08-25 17:13:15, user Benjamin Kirkup wrote:

      Despite some discussion and speculation about the diversity of the strains in a single patient at the start of one local outbreak, I don't see any data or analysis reflecting on the measured viral diversity of SARS-CoV-2 within any of the clinical samples; nor an analysis of whether that can be used to tie individuals together via the minor populations, for example [https://www.biorxiv.org/con...]. Instead, each sample is reduced, mapping to reference, to a consensus genome or partially covered consensus genome. Is there a way you could address the potential for minor populations in the samples; and leverage that for greater resolution in the transmission analysis?

    1. On 2020-08-25 19:43:48, user Allan H. SMITH wrote:

      Some readers may be misled by the title and abstract of this paper into thinking the Covid-19 epidemic is under control.

      Dr. Bhatia acknowledged that I was a reviewer, and I have been reviewing drafts of the paper and providing comments along the way. It is good to see work on epidemiological data concerning Covid-19. More is needed if we are to learn from the tragic mistakes which have been made in responding to the outbreak.

      My reason for writing this comment is that I fear it may appear to some that this paper indicates that the epidemic has been under control since early March. The confusion may arise from misunderstanding the term “epidemic growth rate”. If there were a sequence of 1,2,4,8,16,27 one could state that the epidemic growth rates has declined in the last period because the last number is 27, and not 32 which would be expected with a continuing doubling of rates. In fact, the greatest increase in this sequence is in last period, going from 16 to 27, an increase of 11 compared to the previous largest increase of 8. So, stating that the epidemic growth rate is declining does not mean the epidemic is under control.

      In fact, the epidemic in the United States charges on and is out of control. You can see evidence for this in Figure 1a in Dr. Bhatia’s paper. Hospital admission rates are mostly much higher than in early March, and many places have evidence of a resurgence in July.<br /> Mortality data give clear evidence of the catastrophe being experienced in some countries, especially the United States, Brazil, Peru, and India. The Johns Hopkins Coronavirus website gives excellent tracking graphs. https://coronavirus.jhu.edu/data/cumulative-cases You can get the death numbers by clicking in the dropdown box on the left. The top line in the graph is for the United Sates. You can see the curve seemed to start to flatten, but it has taken off again. I think this can reasonably be termed a public health catastrophe. Mortality rates like these have not occurred in any other developed nation, and they could have largely been avoided.

      To conclude, I thank Dr. Bhatia for his paper and extensive work analyzing the data, and for sharing it with me.

    1. On 2020-08-26 12:22:50, user Keir Philip wrote:

      A typo has been noted in table 3, which currently reads "No risk of cross infection", but should read "potential risk of cross infection"

    1. On 2020-08-29 05:11:06, user Daniel Connelly wrote:

      The practitioners at our office in NJ have been prescribing HCQ +zinc + azithromycin or doxycycline to newly diagnosed symptomatic Covid-19 patients since March. Our sample size is small and includes nursing home patients. To date, all patients improved rapidly, usually within 24 hours. The were zero hospitalizations, zero deaths and no reported side effects.<br /> The import number from the study is only 7.6% of outpatients were prescribed the drug. This could be because they were asymptomatic at the time and did not need it or it could be because of the oppressive political climate that suppressed the use of this life saving drug in New Jersey.

    1. On 2020-08-30 22:20:50, user JimboKatana wrote:

      Is the virus truly decreasing in virulence or is it following the phenomenon of decreased severity that occurs with viruses in the summer?

    1. On 2020-09-06 08:30:14, user Aporia wrote:

      No matter how you criticize the data- every argument still places these estimates FAR lower then what the media has been pushing . Add to that Dr Ioanidis's talks - we did this by being pushed into a panic- the total years of life lost this season due to Covid is on par wt a flu, but the lockdown will cause REAL LIVES LOST - via deaths of despair (suicides, crime, od etc)

    1. On 2020-09-06 14:23:35, user Knut Wittkowski wrote:

      The hypothesis of two strains in my manuscript, starting in the March 31 version, was confirmed in a July 2 paper in Cell. Korber (2020) identified two strains, D614 and G614, of which G614 is more virulent and arrived in Europe first in Italy.<br /> https://doi.org/10.1016/j.c...