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

      Main Findings:

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

      Limitations:

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

      Significance:

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

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

    1. On 2020-05-26 15:37:05, user Sinai Immunol Review Project wrote:

      Main Findings <br /> The authors describe a small cohort of 27 COVID-19 patients treated with enoxaparin or heparin in escalating doses (corresponding to clinical severity) at Sirio-Libanes Hospital in Sao Paolo, Brazil. Importantly, no control patients are included in this study. Additionally, all patients received concomitant azithromycin and a subset received methylprednisolone therapy. Patients had mean WHO score of 4.0 ± 1.2 (corresponding to moderate clinical severity) upon admittance. PaO2/FIO2 was significantly increased from 254 (±90) to 325 (±80) after 72 hours after the initiation of heparin therapy. 56% of patients were discharged within 7.3 (±4.0) days. 50% of mechanically ventilated patients were extubated within 10.3 (±1.5) days. The study reported no fatal events or bleeding complications due to anticoagulation. The authors suggest that early heparin therapy significantly improves hypoxemia and may be beneficial in the management of such patients.

      Limitations <br /> This is a small, single arm, retrospective study without controls and with concomitant confounding treatments. Therefore, no definitive conclusions can be made here.

      Significance <br /> This article adds anecdotal evidence regarding coagulability in COVID-19 patients and points to the potential for anticoagulation in the right clinical study. Given the multiple limitation, evidence herein can only corroborate previous reports demonstrating associations between elevated D-dimer and disease severity [1-3]. Additionally, this study may add to the evidence regarding mortality benefits of heparin therapy in severe COVID-19 [2, 3].

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

      Reference<br /> 1. Han H, Yang L, Liu R, et al. Prominent changes in blood coagulation of patients with SARS- CoV-2 infection. Clin Chem Lab Med 2020 doi: 10.1515/cclm-2020-0188 [published Online First: 2020/03/17]

    1. On 2019-11-30 17:00:40, user Guyguy wrote:

      EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 27, 2019

      Thursday, November 28, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,309, of which 3,191 are confirmed and 118 are probable. In total, there were 2,201 deaths (2,083 confirmed and 118 probable) and 1077 people healed.<br /> • 443 suspected cases under investigation;<br /> • 5 new confirmed cases, including:<br /> o 4 in Ituri in Mandima;<br /> o 1 in North Kivu in Mabalako;<br /> • 2 new deaths of confirmed cases, including:<br /> o 2 new community deaths in Ituri in Mandima;<br /> o No deaths among confirmed cases in CTEs;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.

      NEWS

      Three members of the Ebola Virus Epidemic response killed during an attack in Biakato, Ituri

      • Following the attack on the sub-coordination of the Biakato response in Ituri on the night of Wednesday 27th to Thursday 28 November 2019, three members of the Ebola response teams in this sector lost their lives ;<br /> • It is a provider and a driver of the vaccination committee and another driver;<br /> • In addition to these three deaths, there are 7 wounded and 6 others with psychological disorders and extensive material damage.<br /> • A good number of these teams from Biakato were evacuated in three waves to Goma. As soon as they arrived, they were greeted by a coordination team led by Prof. Steve Ahuka, general coordinator, who also visited the wounded before going to inquire about the security conditions and accommodation of evacuees. He did not fail to comfort them.

      VACCINATION

      • The vaccination commission is in mourning. A service provider and a driver of his team were killed on the night of Wednesday 27 November 2019 following attacks at the Biakato base in Ituri;<br /> • 2nd day without vaccination activity with the 2nd J & J vaccine following the disorders initiated by young people related to the security situation in Beni;<br /> • 724 people were vaccinated, until Tuesday, November 26, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,373 people have been vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.

      MONITORING AT ENTRY POINTS

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

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

      1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
      2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
      3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
      4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
      5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.
    2. On 2019-10-16 12:44:35, user GuyguyKabundi Tshima wrote:

      EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT OCTOBER 11, 2019<br /> Saturday, October 12, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,212, of which 3,098 are confirmed and 114 are probable. In total, there were 2,148 deaths (2034 confirmed and 114 probable) and 1031 people cured.<br /> 466 suspected cases under investigation;<br /> 2 new confirmed cases at CTE in Ituri in Mandima;<br /> 2 new confirmed deaths, including:<br /> 2 community deaths in Ituri in Mandima;<br /> No confirmed deaths in CTE;<br /> 3 people healed from the CTE, including 2 in Ituri in Komanda and 1 in North Kivu in Katwa;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.

      NEWS

      Organization of a press conference on the evolution of Ebola Virus Disease in Kinshasa<br /> - The Technical Secretary of the Multisectoral Committee for Ebola Virus Epidemic Response (CMRE), Prof. Jean Jacques Muyembe Tamfum chaired this Saturday, October 12, 2019 in Kinshasa a press conference during which he gave an update on the 10th epidemic Ebola Virus Disease in the DRC since its declaration on August 1 , 2018 to date;<br /> - To this end, he showed the strategies used in the response of this epidemic and spoke of the recourse to technological innovations, while recalling that the Head of State, President Félix-Antoine Tshisekedi Tshilombo, placed him at head of the technical secretariat of CMRE, with two main missions. This includes ending the epidemic as soon as possible and capitalizing on the achievements of this epidemic to strengthen the DRC's health system, starting with the three provinces affected by this epidemic;<br /> - Speaking of the evolution of the response, he reported some tangible progress, notably from July 2019, where 90 confirmed cases per week were recorded, or 15 per day, while currently there are fewer than 20 case by week, ie 1 to 3 cases per day, or even zero cases confirmed as the 05 October 2019 last. " In this period, three provinces were active (North and South Kivu, as well as Ituri), while today only the province of Ituri is affected . Today, only 9 zones are affected of the 22 recorded in July 2019, "said the technical secretary of the CMRE;<br /> - He said that for now the epidemic is concentrated in the North from where it came before revealing itself in Mangina and Mabalako in North Kivu. Hence all efforts are concentrated to put an end to this epidemic as quickly as possible;<br /> - Regarding strategies to end this epidemic, the Pof. Muyembe spoke about the change of approach that is now multisectoral and that at present, the outline of the epidemic is placed under the leadership of the presidency of the Democratic Republic of Congo with as coordinator the Prime Minister. This committee has a technical secretariat which directs the general coordination managed by Prof. Steve Ahuka and the provincial sub-coordinators of the response;<br /> - The second strategy was to maintain the motivation of the teams on the spot. This has been regularized with the support of the World Bank. An operating budget is now given to the coordination in Goma as well as all the co-ordination;<br /> - The other strategy is to give more importance to national leadership. A partnership has been built with WHO, UNICEF and MSF that support coordination in Goma. Nationals are at the forefront and partners support. This has changed a lot on the field, says Professor Muyembe;<br /> - Finally, notes the Technical Secretary, innovations have been made with this epidemic with the use of experimental vaccines, first RVSV zebov from Merck with belt vaccination which has shown its effectiveness;<br /> - " It is time to use a new vaccine, following the recommendations of the SAGE expert group that advises WHO on immunization. On May 15, 2019, this group recommended using an adjusted dose of the RVSV vaccine to prevent a possible shortage due to the fact that the epidemic lasts a long time, "Prof. Muyembe;<br /> - He added: " His second recommendation was to use a second preventive vaccine. After proposals, it is the Johnson & Johnson vaccine that presents the most data on the scientific level . He announced that the teams are prepared to give correct communication and to vaccinate the population;<br /> - He recalled that this second vaccine is used in West Africa since 2013, will also be used in Rwanda and Goma to protect the Congolese compatriots of Goma, where more than 64,000 of them cross the border daily. to go to Gisenyi and vice versa;<br /> - The first batch of the J & J vaccine, 500 000 doses can arrive in the DRC from 18 October 2019 and vaccination can begin in early November 2019 in two communes of Goma to extend later in other provinces;<br /> - The clinical trials carried out by the DRC will serve the world, since now two molecules tested are now available to break the chain of transmission during the next appearances of the Ebola virus.<br /> - " From this year, Ebola became a curable disease because we found medicines to cure the sick. It can also be avoided by immunization, especially if in both cases, one arrives in time, "concluded the technical secretary of the Multisectoral Committee for the Response to the Ebola Virus Disease Epidemic Muyembe Tamfum.

      VACCINATION

      • A new vaccination ring was opened around two confirmed cases from 10 October 2019 in the Biakato Health Area in Mangina / AS Biakato mine with low participation due to a strong community reluctance;
      • Vaccination of newly recruited front-line staff continues at Kyondo Reference Hospital and Kayna Health Zone in Bulinda, North Kivu;
      • Continuation of Local Polio Vaccination Days integrated with Vitamin A supplementation and Mebendazole deworming in 17 health zones at the Butembo antenna in North Kivu;
      • Since the beginning of vaccination on August 8, 2018, 237,165 people have been vaccinated;
      • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.

      MONITORING AT ENTRY POINTS

      • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 105,171,551 ;
      • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.

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

      1. Follow basic hygiene practices, including regular hand washing with soap and water or ashes;
      2. If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu Civil Protection toll-free number;
      3. If you are identified as a contact of an Ebola patient, agree to be vaccinated and followed for 21 days;
      4. If a person dies because of Ebola, follow the instructions for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.
      5. For all health professionals, observe the hygiene measures in the health centers and declare any person with symptoms of # Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect these health measures recommended by the Secretariat, it is possible to quickly end this 10th epidemic.
    1. On 2020-04-17 14:24:08, user Daniel Corcos wrote:

      If nothing had been done, one would have expected at least 500,000 deaths from Covid-19 in the USA in less than one year.

    1. On 2020-10-29 07:12:38, user reality tester wrote:

      orange county prevalence 12% equates to 7.6 x higher than reported? 61,000 cases reported x 7.6 = 463,000 divide by 3.1 mil population equals 15% at least as of today... add 35% of those who have innate immunity as research published in Science and Nature indicates, and OC is at herd immunity threshold... no wonder hospitalizations are decreasing on 7 day moving averages, and daily deaths likewise dropping, despite more "cases" as tallied by positive swabs ...

    1. On 2021-01-26 10:38:27, user ??u?????? ????????? wrote:

      Hi,<br /> the UK, South African and the Brazilian virus mutations can alter the results/conclusions of the study?

    1. On 2021-08-29 01:52:08, user bubba gump wrote:

      Yes, I don't believe this can possibly be accepted for publication without addressing the glaring errors and overlooked biases. It's a shame that the antivaxxers are already trumpeting this as vindication for their wrong choices.

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

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

    3. On 2022-01-06 02:01:18, user Stoichastic wrote:

      "What makes you think that mutations on the nucleocapsid are anymore stable than the mutations on the spike protein"

      Stability is a function of mutation and selection pressure, not degree of freedom to mutate. There's no selection pressure on the nucleocapsid, effectively, just the spike.

      You only need to check out VOC mutation info to see the spike is changing significantly more than nucleocapsid thanks to the vaccines.

    4. On 2021-08-26 04:22:25, user brisalta wrote:

      The paper does not clearly state which variant the subjects were previously infected with. If that data is available it may be useful to include that information.

    5. On 2021-09-02 18:28:43, user Kostas Damdas wrote:

      Who were the participants? people vaccinated in january vs people covid positive recently? immunocompromised vs healthy?

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

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

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

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

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

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

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

      The results in an under-vaccinated population is undeniable.

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

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

      Literally, that's the end of the story.

    1. On 2020-07-30 04:05:03, user Martijn Hoogeveen wrote:

      In the v5 update: results of medical findings explaining the effects of allergens/allergies on influenza/COVID-19 are included. Methodological sensitivity analyses are added by including bootstrapped correlations and controlling for autumn. Outcomes are similar and conclusions are the same.

    1. On 2020-03-26 16:04:12, user Sinai Immunol Review Project wrote:

      Title: Meplazumab treats COVID-19 pneumonia: an open-labelled, concurrent controlled add-on clinical trial

      Keywords: Meplazumab, CD147, humanized antibody, clinical trial <br /> Main findings: This work is based on previous work by the same group that demonstrated that SARS-CoV-2can also enter host cells via CD147 (also called Basigin, part of the immunoglobulin superfamily, is expressed by many cell types) consistent with their previous work with SARS-CoV-1. 1 A prospective clinical trial was conducted with 17 patients receiving Meplazumab, a humanized anti-CD147 antibody, in addition to all other treatments. 11 patients were included as a control group (non-randomized). <br /> They observed a faster overall improvement rate in the Meplazumab group (e.g. at day 14 47% vs 17% improvement rate) compared to the control patients. Also, virological clearance was more rapid with median of 3 days in the Meplazumab group vs 13 days in control group. In laboratory values, a faster normalization of lymphocyte counts in the Meplazumab group was observed, but no clear difference was observed for CRP levels.

      Limitations: While the results from the study are encouraging, this study was non-randomized, open-label and on a small number of patients, all from the same hospital. It offers evidence to perform a larger scale study. Selection bias as well as differences between treatment groups (e.g. age 51yo vs 64yo) may have contributed to results. The authors mention that there was no toxic effect to Meplazumab injection but more patient and longer-term studies are necessary to assess this.

      Significance: These results seem promising as for now there are limited treatments for Covid-19 patients, but a larger cohort of patient is needed. CD147 has already been described to facilitate HIV 2, measles virus 3, and malaria 4 entry into host cells. This group was the first to describe the CD147-spike route of SARS-Cov-2 entry in host cells 1(p147). Indeed, they had previously shown in 2005 that SARS-Cov could enter host cells via this transmembrane protein 5). Further biological understanding of how SARS-CoV-2 can enter host cells and how this integrates with ACE2R route of entry is needed. Also, the specific cellular targets of the anti-CD147 antibody need to be assessed, as this protein can be expressed by many cell types and has been shown to involved in leukocytes aggregation 6. Lastly, Meplazumab is not a commercially-available drug and requires significant health resources to generate and administer which might prevent rapid development and use.

      1. Wang K, Chen W, Zhou Y-S, et al. SARS-CoV-2 Invades Host Cells via a Novel Route: CD147-Spike Protein. Microbiology; 2020. doi:10.1101/2020.03.14.988345
      2. Pushkarsky T, Zybarth G, Dubrovsky L, et al. CD147 facilitates HIV-1 infection by interacting with virus-associated cyclophilin A. Proc Natl Acad Sci USA. 2001;98(11):6360-6365. doi:10.1073/pnas.111583198
      3. Watanabe A, Yoneda M, Ikeda F, Terao-Muto Y, Sato H, Kai C. CD147/EMMPRIN acts as a functional entry receptor for measles virus on epithelial cells. J Virol. 2010;84(9):4183-4193. doi:10.1128/JVI.02168-09
      4. Crosnier C, Bustamante LY, Bartholdson SJ, et al. BASIGIN is a receptor essential for erythrocyte invasion by Plasmodium falciparum. Nature. 2011;480(7378):534-537. doi:10.1038/nature10606
      5. Chen Z, Mi L, Xu J, et al. Function of HAb18G/CD147 in Invasion of Host Cells by Severe Acute Respiratory Syndrome Coronavirus. J Infect Dis. 2005;191(5):755-760. doi:10.1086/427811
      6. Yee C, Main NM, Terry A, et al. CD147 mediates intrahepatic leukocyte aggregation and determines the extent of liver injury. PLOS ONE. 2019;14(7):e0215557. doi:10.1371/journal.pone.0215557

      Review by Emma Risson and Robert Samstein as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.

    1. On 2020-09-08 20:12:03, user Lewis Lee wrote:

      Dear authors,

      Many thanks for the interesting paper with numerous measures/analyses for controlling confounding. I'd like to ask the following:

      How valid is it to use the set of the defined ICD-10 codes for identifying COVID-19 cases? I presumed the use of U07.1 (and possibly some U07.2) may only include those who were tested for the COVID-19. I guess majority of the general population were not tested. If that's the case, most of the COVID-19 negative cases may not be truly negative but indeed unobservable (missing data) at the moment of analysis. Besides, those who did the COVID-19 tests may have already different measured/unmeasured characteristics from the non-tested population as they were not randomly/probability sampled for tests. Could this be a source of selection bias/confounding and limit the validity and generalizability of the findings?

      Many thanks and apologize if I missed some important details of the paper before asking.

    1. On 2020-04-17 21:28:07, user Daniel Shanklin wrote:

      This study abstract should be rewritten as follow: "A study of Facebook users who thought they might have COVID-19 resulted in a roughly 2.49% to 4.16% positive-test rate"

      The fact that you've extrapolated this to an entire population is confounding.

    2. On 2020-04-18 15:49:32, user DickRuble wrote:

      There are many question marks about this study re: population sampling and analysis.

      I could find no info about the manufacturer of the test. Could it be that the test/antibody is not specific enough, and detects exposure to other coronaviruses, such as the common cold? I.e. many false positives?

    3. On 2020-04-19 21:23:49, user figureitout1 wrote:

      I am not in the field and have no expertise but I think this study may have measured just the prevalence of the common cold in Santa Clara county. The ELISA assays for IgG and/or IgM antibodies are known to give false-positives due to the other Corona viruses that give us the common cold. It is known from European studies that the common cold in the winter time can cause roughly 3% positive Covid-19 ELISA tests – just about what was measured in this study. In order to get meaningful results a second test (neutralization test that is not sensitive to the common cold viruses) needed to be done on the positive samples. The scientifically correct conclusion of the study would be: the Covid-19 prevalence is between 0% and 4%. It seems irresponsible to put the study on the web and have people, including politicians, jump to hasty and possibly wrong conclusions.

    4. On 2020-04-22 03:00:50, user Eric Hadley-Ives wrote:

      I think there has been a correction on that other paper that the test getting 87% was not the same test (it was the same manufacturer) as the one used by the Stanford Sample. An earlier version of that paper did not point out this.

    5. On 2020-04-18 18:54:22, user Tomas Hull wrote:

      Germany had a similar study done published on April 9, where they combined the antibody test with the polymerase chain reaction test in active infections.

      Nature reviewed both this study, and the one from Germany, where the combined results in a population of a town of 12,000 revealed overall 15% infection rate.

      https://www.nature.com/arti...

    6. On 2020-04-19 17:20:25, user James Kalb wrote:

      Does anyone know which antibody test was used in this study? Maybe I overlooked it. I’m interested in the name of the manufacturer.

    7. On 2020-04-23 11:56:27, user Robert Ton wrote:

      Thought I already commented but don't see it, maybe waiting to be moderated still...

      I believe confirmed cases in Santa Clara as of 1 April should be 1190 (positives by sample collection date) vice 963 (positives by test result date)... By my back of a napkin calculation that drops the under-ascertainment rate to around 40-68x vice the 50-85x rate given herein.

    1. On 2021-02-06 02:50:56, user Crystal Sonia wrote:

      How accurate and reliable is this SIR model? With the mco arent the cases still increasing? How are the beta and gamma estimated? What's the sensitivity and specificity of this model?

    1. On 2021-04-07 03:09:47, user Jesse Baker wrote:

      I think Table 1 should list, for each age group and month, the actual number of cases and the number of people who were tested for Covid, as these quantities are needed to interpret the case fatality rates (CFR) given there. It is well known that the CFR generally decreases as more people are tested for the virus; the tests discover mild infections otherwise overlooked. If younger people were becoming less likely to seek testing while older people maintained their previous testing habits, this might explain at least part of the observed increase in the CFR and the bias toward younger ages.

      I’m not an expert in such matters, and concern over the new strains P.1, B.1.351 and especially B.1.1.7 extends to the USA as they begin to circulate here. The April 6 New York Times noted an increase in hospitalization among Americans under age 50 during March, but it has yet to be reflected in case fatality rates for that group.

    1. On 2020-04-02 15:17:14, user Mc Uwamwezi wrote:

      I have to say I am confused by the numbers, they say they enrolled 62 patients out of which 31 where given the HCQ treatment but then the results show outcomes for n=32 and n=32 respectively in the test and the control arms, so a total of 64??

    2. On 2020-04-09 06:55:47, user Cy Husain wrote:

      Helpful study on "best available" (read: not very good) evidence for #hydroxychloroquine. In short, this study:<br /> - Is too small<br /> - Has no control group<br /> - Only looks at a very specific patient pool<br /> - Does not consider side-effects<br /> - It's NOT a double blind study, so allows for researcher bias!

    1. On 2020-04-30 19:23:08, user Pei-Hui Wang wrote:

      This work has been published on Journal of Medical Virology ( https://onlinelibrary.wiley... ). According to the findings in this paper, we propose that antibody-based COVID-19 “immunity passports” is unfeasible.

      We agree with the opinions of Jayakrishna Ambati, Balamurali Ambati, and Benjamin Fowler that “ Passport holders and society would have a false sense of security while non–passport holders would have their civil liberties and work opportunities unwarrantedly abridged. A passport policy would also endanger lives by undercutting good hygiene and healthy behavior; those desperate to return to work or re-integrate into society would risk exposure to the virus in attempt to develop antibodies.” From Scientific American https://blogs.scientificame...

    1. On 2025-08-26 09:13:00, user Constant VINATIER wrote:

      Feedbacks about your preprint : https://doi.org/10.1101/2025.07.26.25332244

      About registration: <br /> We could not find any information about the pre-registration of your study in the pre-print. Pre-registration involves documenting the hypotheses, methods, and/or analyses of a scientific study prior to its conduct (10.1073/pnas.1708274114; 10.1038/s41562-021-01269-4). If your study was pre-registered, we strongly encourage you to include the registration number in the pre-print, ideally in the abstract make this important information easy to retrieve, as this practice enhances transparency and reproducibility. If the study was not pre-registered, this should be acknowledged as a limitation. For future studies, we recommend pre-registering on an appropriate repository.<br /> About Protocol Sharing: <br /> We did not find the protocol for your study. If you have one, we encourage you to share it as supplementary material or deposit it in a publicly available repository such as the Open Science Framework ( https://osf.io ) or Zenodo ( https://zenodo.org/) "https://zenodo.org/)") . You can then include a statement in the Methods section indicating that your protocol is openly available (e.g., 'The protocol for this study is available at (link)/ in the supplementary'). Sharing your protocol will help readers better understand your study and enable them to reproduce it if they wish to test it.<br /> About the Statistical Analysis Plan Sharing: <br /> We did not find the Statistical Analysis Plan (SAP) for your study. If you have one, we encourage you to share it as supplementary material or deposit it in a repository such as the Open Science Framework ( https://osf.io ). You can then include a statement in the Methods section indicating that your protocol is openly available (e.g., 'The SAP for this study is available at (link)/ in the supplementary'). Sharing your SAP will help readers better understand your study and enable them to reproduce it if they wish to test it.<br /> About Deviations and/or changes<br /> We could not find any information about potential deviations or changes to the protocol in your pre-print. Since such deviations are common, if this applies to your study, we strongly encourage you to include a subsection titled Changes to the Initial Protocol in the Methods' section and discuss these changes as a potential limitation of your results. If any deviations occurred during your study, please specify them in this new subsection.<br /> About Data sharing / FAIR Data<br /> We found insufficient information about your data sharing approach. Data should be findable, i.e. data are assigned a globally unique and persistent identifier (for instance there is a DOI assigned to the dataset, or data are registered or indexed in a searchable resource). Data should also be accessible, i.e. data are retrievable by their identifier and can be accessed following an open, free, and universally implementable protocol. The protocol allows for an authentication and authorization procedure, where necessary. As your data contains sensitive data, we suggest to make it Findability, Accessibility, Interoperability, and Reuse ( https://www.go-fair.org/fair-principles/) "https://www.go-fair.org/fair-principles/)") by providing some details on this procedure.<br /> About Code sharing<br /> We could not find any information about your (statistical) code. Sharing code is important for enhancing transparency and reproducibility, especially since it does not contain sensitive information. We encourage you to openly share it on a code sharing platform (Github, Codepen, CodShare, etc.) and include the Digital Object Identifier (DOI) in the Methods section. If you want more information about Code sharing https://fair-software.nl/ .<br /> Comments :<br /> Dear authors, you state that 'All data produced in the present work are contained in the manuscript,' but we cannot find any link in your preprint or supplementary materials that refers to the protocol, code, raw data, and the registration number.

    1. On 2020-04-07 22:42:22, user Christos Ouzounis wrote:

      Spain 65,082 USA 267,324, estimated peaks.<br /> Today: 141,942 and 394,182 reported.<br /> Just a week later. Stats speak for themselves.

    1. On 2021-10-15 07:29:10, user Rock Man wrote:

      "So why on earth would anyone get a vaccine if they’ve already been infected?"

      "You don’t get double immunity, or any ‘extra immunity’ at all."

      That statement is not likely true. Just as the booster trials demonstrated when mixing firsts with different brand booster, there was a benefit. The same should be true between natural immunity and natural plus vaccines.

      Re:

      "The researchers found that those who got a Johnson & Johnson shot

      followed by a Moderna booster saw their antibody levels rise 76-fold

      within 15 days, whereas those who received another dose of Johnson &

      Johnson saw only a fourfold rise in the same period. A Pfizer-BioNTech

      booster shot raised antibody levels in Johnson & Johnson recipients

      35-fold."<br /> https://www.nytimes.com/202...

    1. On 2021-11-12 10:44:25, user Ken wrote:

      The next step could be linking the TeKWP to the hospitalization rate in the ICU so to have a real time indicator on the stress that the structure can withstand in relation to the new cases

    1. On 2020-05-11 12:28:29, user Sinai Immunol Review Project wrote:

      The main finding of the article: <br /> This study analyzed the effects of the arterial hypertension and of the use of renin-angiotensin-aldosterone system (RAAS) inhibitors on mortality and recovery in patients with Covid-19. Through medical records, the authors performed a multicenter retrospective study of 3017 COVID-19 patients hospitalized within the Hackensack Meridian Health network in New Jersey. Among these patients, 52.5% presented a diagnosis of hypertension. The authors showed a significantly increase (2.7 times) of the mortality in patients with hypertension compared to Covid-19 patients without hypertension. However, when adjusted for age, the effect of hypertension in mortality decreased, as the incidence of hypertension was higher in older populations. In addition, when other clinical or demographic conditions were taken into account, no effect of hypertension on mortality was found. <br /> In relation to the RAAS inhibitors, angiotensin converting enzyme 1 (ACE1) inhibitors and angiotensin-receptor blockers (ARBs) were used in 22.8% and 18% of hypertensive patients. The use of ACE1 inhibitors and ARBs were found not to have detrimental effects and perhaps offer some protection to hypertensive patients in comparison with other anti-hypertensive agents. Hospital discharge rates were 9% higher for hypertensive patients prescribed RAAS inhibitors compared to other anti-hypertensive agents.

      Critical analysis of the study: <br /> The manuscript needs a better scientific writing, especially more in-depth details on the description of the patient population, clinical parameters, treatments used, other co-morbidities. The implications for COVID-19 disease of the upregulated cascade of vasoactive peptides belonging to RAAS on hypertensive patients, the relationship between the use of RAAS inhibitors on cytokine storm, plasma angiotensin II and ACE2 activity, could be better discussed. There is no information on which ARBs or other anti-hypertensive agents were used, despite being an important information given the different pharmacological characteristics of each one.

      The importance and implications for the current epidemics: <br /> While there is still uncertainty on the effect of RAAS inhibitors on Covid-19 severity in hypertensive patients, this manuscript demonstrates that ACE1 inhibitors and ARBs therapy are not detrimental, and can even be protective in hypertensive individuals. These results thus support the recommendations of the guidelines for maintaining therapy with these classes of drugs in hypertensive SARS-CoV-19 patients.

      Reviewed by Bruna Gazzi de Lima Seolin.

    1. On 2020-10-16 12:57:36, user Dieter Mergel wrote:

      This article may help to explain a finding in:

      https://www.medrxiv.org/con....<br /> Stipulating face mask wearing in Germany reduced the Covid-19 fatality rate although it did not affect the infection dynamics represented by the effective reproduction rate.

      This is the most astonishing result of a data-scientific investigation: <br /> "Correlation between daily infections and fatality rate due to Covid-19 in Germany" and<br /> fits to the findings of 45% seroprevalence in Tokyo tempting to the breathtaking speculation that: <br /> "Wearing face-masks in densely populated areas is a sort of vaccination."

    1. On 2020-04-11 07:32:16, user adss wrote:

      Injecting BCG is basically injecting controlled and weakened viruses, so that your body can create the anti-body. Usually people that have weak immune systems need to be careful not to catch the disease from the vaccine.

    2. 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.

    3. On 2020-04-01 18:41:26, user Ronald McCoy wrote:

      This totally glosses over China. Huge case numbers with universal BCG vaccination. This is a classic example fo confirmation bias. This article has more holes than a Swiss cheese factory.

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

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

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

    1. On 2020-04-23 00:06:43, user Avi B Bhagan wrote:

      The selection of the groups, does not seem random ,<br /> I don't see how this paper will get past peer review without revisions to remove about 20-25 patients from the analysis, in order to normalize the groups.

      I don't know why the study group had nearly 20% smokers while the control group had closer to 12%. That is one source of expected higher mortality in the study group,

      The other problem is the study group having the highest % of patients with complications from diabetes 30%, compared to 24% in the control group.

      And 20% Cerebrovascular disease in the study group compared to 12% in the control group

      And lastly why are patients with HIV, who would already be on other anti-viral drugs included in the study ? they should all be removed. This study has 4 patients with HIV in the control groups, and that is a blatantly dishonest move. the HIV patients who received "no medication" , would still be on HIV anti-virals , which is also a suspected treatment for COVID.

      This analysis has to be re-run, to normalize for smoking, diabetes and heart disease, and removing the 6 HIV patients..

    1. On 2020-04-24 12:11:44, user Mortal Wombat wrote:

      Okay, you did this, but why? Is it really anything other than an overfit model?

      Your original projections were off. You're never going to collect enough data for this to be falsifiable.

    1. On 2020-04-15 11:57:26, user Renato Prandina wrote:

      Duration and extent of immune protection will be critical to the novel betacoronavirus SARS-CoV-2 and will unfold in coming years. Some speculative scenarios...

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

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

    1. On 2020-06-02 15:13:39, user Sinai Immunol Review Project wrote:

      Title <br /> Serum protein profiling reveals a landscape of inflammation and immune signaling in early-stage COVID-19 infection

      Keywords<br /> • Serum Profiling<br /> • Cytokines<br /> • Protein array<br /> • CCL2<br /> • CXCL10

      Main Findings<br /> In this preprint Hou et al., analyze serological immune mediators and other proteins from individuals with early COVID-19 symptoms using an antibody microarray that detects 532 target proteins. Patients were classified as COVID-19 (n=13) or influenza (n=15) based on positive RT PCR test for SARS-CoV-2 RNA (COVID-19) or FluA, FluB, RSV RNA (all classified as influenza group).<br /> 88 up-regulated and 37 down-regulated proteins were identified by comparing COVID-19 and influenza patient groups (p-value < 0.05). Some of those up-regulated ytyl34proteins were reported before, such as IFN-????, IL-6, CXCL8, CCL2, CXCL10 and some that were not previously associated with COVID-19, such as IL-20, CCL27 and IL-21. Complement proteins C1R and C7, as well as PLG were found to be reduced in COVID-19 patients.

      After performing a correlation analysis of the differentially upregulated proteins and clinical data, the authors found a positive correlation between expression of several proteins in the CCL2 and CXCL10 signaling pathways and clinical parameters typically related to liver and renal function, myocardial injury, inflammation and infection, as well as neutrophils counts. Conversely, most of these same proteins show a negative correlation with lymphocyte counts.

      Limitations<br /> The control “influenza group” had patients negative for influenza virus but positive for RSV, and thus the nomenclature should be revised. As noted by the authors, a larger cohort should be used to validate findings. There is no multivariate analysis, and identification of independent or confounding variables. Even though several proteins were differentially expressed between the patient groups, there was significant overlap between the groups, which may preclude the use of any single protein as a biomarker. Data on clinical variables should have been included in main figure. It is unclear why the authors annotated serum proteins in cellular components. Proteins in CCL2 and CXCL10 interaction network are largely overlapping, but the authors do not emphasize it. <br /> Authors didn’t show lymphocyte and neutrophil counts. Since it is known that severe COVID-19 patients can present lymphopenia and neutrophilia, it would be important to have this information in their cohort as they are correlating protein levels with neutrophils and lymphocytes.<br /> Authors claim that CCL2 can act as an autocrine factor that promotes viral replication in infected macrophages, and cite one paper with HIV, but authors should discuss that this chemokine recruits monocytes to the site of infection and then could contribute to the increased inflammatory response related to COVID-19.

      Significance<br /> This study shows the potential use protein array to simultaneously identify many different proteins in serum of COVID-19 patients.<br /> The authors identify several differentially expressed proteins (potential biomarkers) and correlate them with clinical indices that give insights on possible therapy targets in COVID-19.

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

    1. On 2022-09-23 18:40:11, user Andre Caldwell wrote:

      This is an interesting paper, with an innovative study design which includes individuals with specific mutation and risk variants for Alzheimer's disease. <br /> I really wanted to like this paper, but after ready it in depth, just the study design is worth.<br /> 1) this study generated data in more than 1 million nuclei. After QC only 300K pass QC, meaning that more than 70% of the data was removed. when a study remove 70% of the data, it is not clear if what is left is reliable. This is very concerning indicating a large problem in nuclei extraction, batch effect or data generation.<br /> 2) the most common cell type on this study was oligodendrocytes which is totally unexpected. None of the other published studies using the technology has this finding. In fact, normally neurons is the most common cell type. This support that there is a large problem with this data.<br /> 3) the authors forgot to include a very basic comparison which is the major cell proportion vs. status. This is striking as the authors have a nice previous papers in which they do the same with deconvoluted bulk-RNA seq and single nuclei RNA-seq. No presenting this data is suspicious, as is it one the basic analyses and a good positive control.

      Besides that, the paper is difficult to follow, tries to cover many things, but fails to go in any in detail or provide any interesting results, making the study very descriptive without providing clues about disease pathogenesis.

      this paper have been as a preprint more than one year, suggesting that the authors are having problems to published these findings. May be the reviewers had several concerns.

    1. On 2021-02-13 15:15:13, user Rick Phelps wrote:

      It was noted that high degrees of in and ex leakage rates were typically observed. Were added filtration control measures taken to reduce and or control this variable. ? Others have published means by which the public can increase overall FFE using many techniques and materials.

    1. On 2020-12-08 21:22:40, user Michal Piják wrote:

      DOUBTS ABOUT THE EFFECTIVENESS OF MASS TESTING OF ASYMPTOMATIC POPULATION FOR CORONAVIRUS (SARS-CoV-2) IN SLOVAKIA

      Indeed, it might seem that the number of positive PCR tests / per day, per million inhabitants two weeks after the nationwide testing of the whole country in Slovakia has started to slowly decrease. However, this declining trend may be skewed by significantly less testing. For example data from Monday 9.11.20 show that if as many tests were performed in Slovakia as on Thursday 29.10.20 (when the highest number of positives in the second wave was reached), we should have about 3x times higher number of positives on Monday 9.11.20. cases, i.e. about 3150, instead of 1050.

      The cause of the lower number of tests is not known and one of the reasons could be the lack of RT PCR tests or staff in other days. After extensive testing with antigen tests, we had a big problem in Slovakia. This is that so far we have evaluated the situation according to the positivity of PCR tests. However, antigen testing made this situation unclear to us because people tested positive for antigens fell out of the statistics. It should also be borne in mind that lower numbers of positive cases could also be explained by the tightening of epidemiological measures and also because most of the persons with positive antigen tests were quarantined and did not undergo PCR testing.

      There is evidence that strategies based on a large number of tests may not produce the expected results. A good example is a comparison of the strategies used by New Zealand and Iceland.1-2 In both of these island countries, the first cases were identified at the end of February 2020, but each country took a different path. New Zealand was one of the few countries that openly announced a COVID-19 elimination strategy right at the beginning of the epidemic. This included a gradually strengthened system for monitoring and isolating contacts with the timely and consistent use of lockdowns and border controls. It should also be recalled that some EU countries, such as Belgium, the Czech Republic, Switzerland, France, Slovenia and the Netherlands, have had a progressive decline in the number of positives, despite the fact that they did not have any comprehensive testing of the entire country.

      Unlike New Zealand and many other countries, Iceland's strategy did not include any lockdown period, no official border closure for non-residents and negligible use of quarantine facilities. The cornerstone of Iceland's strategy was easy access to testing and mass screening, along with quarantine and contact tracking. According to data from October 21, New Zealand had 6 times fewer deaths, despite 4.5 times fewer tests than Iceland. Similarly, Slovakia, despite more than 8 times lower number of tests, had half less deaths per million inhabitants than Iceland. It should be recalled that, despite the large number of tests in Iceland, this was not a full-scale test and PCR tests were used. Taken together these findings are further evidence that nationwide antigen testing in a country with low prevalence is ineffective.

      References<br /> 1. Jefferies S, French N, Gilkison C. COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study. Lancet Public Health. 2020;5:e612-e623

      1. Murdoch, D, Gottfreðsson M. COVID-19 and small island nations: what we can learn from New Zealand and Iceland., The conversation, published, September 23, 2020, https://theconversation.com...
    2. On 2021-01-23 13:21:08, user Dušan wrote:

      "All authors declare that they have no conflicts of interest"

      Have a look at Jarcuška's organisation Euromedpro which is sponsored by GSK and Pfizer.

    1. On 2021-10-27 17:47:28, user Sir Henry wrote:

      The definition of "Severe COVID-19" did not require hospitalization and was therefore in most cases not life threatening. COVID-19 frequencies cluster at the mild end of the disease. Connecting worst-case possibilities from the definition to mortality is a red herring, because there was no mortality signal.

      HR > 125 plus fatigue and a positive lab test would have qualified as "severe COVID-19" under the study definition. That seems very similar in severity to debilitating fever.

    2. On 2021-08-11 12:11:31, user Truenorth 1960 wrote:

      I'm not sure I understand this study. While I understand this is a report that is intended for professionals, the l language is not English, it is "technobable" for lack of a better expression. For covid , these studies should have a translation into something more akin to regular English. Narrative should help understand the results. In this case I find the narrative is not helpful, it is easier to look at the tables.

    3. On 2021-09-18 19:05:19, user OBS wrote:

      These long-term results from Pfizer's clinical trial are quite informative- does anyone know of a corresponding preprint from Moderna containing their long-term (i.e. 6 months or so) clinical trial results, particularly regarding safety (total deaths, adverse events, etc.) Moderna has said it's efficacy at 6 months was 93% (a tiny bit better than Pfizer), and all 3 COVID deaths by 6 months were in the placebo group (also better than Pfizer's result of 1 COVID death with vaccine vs. 2 COVID deaths with placebo). This is not at all surprising considering that Moderna's vaccine dose is over 3x higher than Pfizer's. But what about Moderna's results for total deaths, how do they compare to Pfizer's? Surely, so many people here would like to know.

      The following is stated in an article from 3 days ago on Moderna's website:

      "Additionally, the Company shared a new analysis of follow-up through 1 year in the Phase 3 COVE study suggesting a lower risk of breakthrough infection in participants vaccinated more recently (median 8 months after first dose) compared to participants vaccinated last year (median 13 months after first dose). Manuscripts summarizing both findings have been posted to preprint servers and will be submitted for peer-reviewed publication."

      However, no such preprint from the COVE study seems to show up- does anyone know how to find it?

    4. On 2021-08-04 12:33:07, user Will Helm wrote:

      the 14+15 deaths are not vaccine related, bur are "normal demographic" deaths.<br /> A study of Pfizer for European nations based on Eudravigilance values gives a ratio of 15 vax-related deaths per million doses. We can assume it's the same thing for this study. So, for 22'000 who received the shots, statistically there's no death possible due to the jab.

    5. On 2021-08-05 16:37:19, user circleofmamas wrote:

      So by not being vaccinated, I am reducing my relative risk of a 'severe adverse event' by 74%. And my absolute risk to become a "case" is less than 4%, and severe COVID is 0.1%.

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

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

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

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

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

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

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

    1. On 2021-04-10 11:14:32, user John Smith wrote:

      I have been following your studies and find it fascinating, you've done an excellent job. Would be interesting to see Turkey's figures due to their rapidly rising infection rate. I see on the Economist/NYT websites they only have Istanbul figures with an undercount ration of 1.55. Is it possible to obtain the whole country's figures do you think?

      It's a shame that a lot of people look to the Worldometer site for their figures when so much of the information is incorrect/incomplete. It would be a great idea if they had a separate column showing 'total deaths including excess mortality' next to the 'total deaths' column to show a truer picture.

    1. On 2021-06-11 03:08:36, user Kel Sigmund wrote:

      1. Do you know if the relative lack of severe manifestations among the vaccinees with breakthrough covid 19 was associated with the occurrence of prior Covid 19 infection before undergoing vaccination?
      2. Do you have data on the demographics of the vaccinee recipients, especially risk factors for severe disease and age because it would be interesting to know if the vaccine truly mitigated the severity of disease or the vaccinated population is younger and healthier than most being health care workers.
    1. On 2022-01-10 10:57:41, user norsiiii wrote:

      How can you study the rate at which unvaccinated and uninfected people had gotten infected? The rate, by definition, is 0 for all of them....

    1. On 2020-04-19 15:53:35, user JGaltbna wrote:

      Nothing happens “right now”. I suggest actually reading the WH plan to reopen and what has to happen before anything is “relaxed” per policy. 3 phases, each lasting at least 14 days? Ring a bell? The only restrictions being eased now are things that should never have been restricted like walking on a beach. The danger isn’t the policy but that people ignore the policy.

    1. On 2021-01-06 17:08:20, user Jeff Boris wrote:

      I would be careful with your definition of POTS--it is not as rigorous as it should be. For adults, it really should be a relatively persistent increase of HR of at least 30 bpm in the first 10 minutes of standing after supine position, with symptoms of orthostatic intolerance, and with a history of symptoms for at least 3 to 6 months (depending on the reference). I do find the sex, race/ethnicity, and symptom distribution to be very similar to that of both our demographics article (Boris JR Cardiol Young 2018) and the Dysautonomia International-sponsored article (Shaw BH J Intern Med 2019).

    2. On 2021-01-01 08:15:38, user Forrest Weghorst wrote:

      Figure 7 would be more informative if the graphs showed symptom trajectories of Positive Tests vs. No Positive Tests (which is what all the statistical tests are comparing in the corresponding paragraph), not Positive Tests vs. Everyone (including Positive Tests).

    1. On 2020-04-03 07:50:32, user BoghosLArtinian wrote:

      In times of lethal pandemics any safe treatment that shows the slightest benefit should be tried before waiting for large scale scientific studies to be completed, to prove efficacy of treatments, and losing thousands of lives in the process.

    1. On 2020-12-15 23:02:05, user E. de Moya wrote:

      You should contact Mr. Wallukat and Celltrend, both researching autoantibodies in postviral Postural Tachycardia Syndrome (POTS) and ME/CFS. It would be interesting to see, if long-haulers also have amongst others, adrenergic and muscarinic aabs

    1. On 2020-07-22 09:51:25, user Peiying Hong wrote:

      what was the spiked SARS-CoV-2 in the recovery test? Is it the gene product or actual SARS-CoV-2? Given that the wastewater may contain SARS-CoV-2, how can recovery efficiency be determined without accounting for those SARS-CoV-2 that are already present in the sample?

    1. On 2020-04-17 22:28:49, user Whatrdafax wrote:

      What are the consequences of not making this drug available during a pandemic and large numbers of people die? The FDA has logically made an emergency approval for the use of the drug. Parallel paths are being pursued rather than letting people suffocate to death when potential cures supported by sound scientific reasoning and small clinical trials are already available. As far as fear of misuse, or people doing stupid things -those aren't valid reasons for blocking use of a life saving drug. Those are reasons why many drugs are prescription only.

      Concern for the wheels of capitalism mass producing something that might not work? If there is a competing technology that shows greater promise you have a point. But there isn't. The next best, and possible future solutions, don't have the benefit of decades of use that hydroxychloroquine has. Those drugs have to first pass the barrier of safety testing -and even then are OK'd for dying patients right to try experimental drugs.

      The one valid concern is to ramp up production to insure those already dependent on hydroycholorquine (lupus patients is one example) are not endangered. A big wad of cash to the company already making Panquil and companies making generic versions would be well spent so they can immediately boost production assuming the base ingredient supply is elastic.

    2. On 2020-04-13 14:09:18, user Ian Sinclair wrote:

      This study seems to me potentially of enormous significance. I think it would gain greater acceptance if a) the authors explain why they chose to publish before they had reached the numbers specified in the protocol (100 for TAU and 100 for 4 mg group b) they say why they did not report the results for the 2 mg per day group c) they report the actual data on coughs temperature, numbers improved on radiology examination rather than just the significance levels d) they remedy a minor error in the summary (quotes 32 cases as against 31 e) they confirm that the measures were also made by staff who were blind to allocation f) they got themselves an editor who is a native English speaker. I absolutely do not think that the authors have anything to hide but they need to cope with a Western Audience that has been trained to be ultra critical, looking among other things for investigators who stop a trial the moment that it looks to be going their way. My guess is that this was not the case in this instance and that the study was running out of subjects or the authorities were asking for results or some other event that was out of the control of those running the trial. Given the potential world importance of this trial everyone should be trying to offer constructive suggestions for its greater acceptability rather than exercising their brains on ways in which mistakes might have been made.

    1. On 2021-12-21 06:29:36, user Diego Hernandez wrote:

      I am still saddened how little seroprevelance data is available at CDPH. I had my public records request rejected 3x for Megha Mehrotra's inaccurate Seroprevelance study that was cancelled in July 2021. Cancelled due to routine blood screening cancellation yet, it was not included as part of Tomas Aragon's public health order 1 Day after canceling CDPHs seroprevelance data releases.

      I still do not have your modeling for the studies CDPH released. I doubt sending another 3 FOIAs will get me the results.

      When I asked for updating Seroprevelance studies in California beyond August 2020 you linked me back to CDC interactive dashboard.

      In August 21' you co-authored a paper with seroprevelance data back to August 2020.

      The policies issued through this pandemic are not in line with the data available. If policy is being coerced on people it has to be within reason, knowing a VE drop off can be at 90 days or sooner, why force persons into destitution of employment for refusal of vaccinations.

      The trend points toward seasonal vaccinations in late Sept and boosters in December... But that's not the policy and transparency CDPH offers the public.

      I've moved on to other topics of interest but I have lost faith in transparency at CDPH in decision making.

    1. On 2020-05-26 21:10:36, user Renato Polimanti wrote:

      Hi Rachel. Thanks for your feedback. It's a very good point. We are revising the paper to clarify this issue. It's correct that V30M is close to the cg13139646 site. However, this methylation site is assessed via a type II probe, which shouldn't be affected by the allele change. Additionally, we also see that other TTR mutations affect the methylation change at the cg13139646 site, independently from the V30M effect. Please let me know your thoughts about this.

    1. On 2020-09-08 12:00:16, user Wendy Olsen wrote:

      I noted that the assumptions going into this model are a consistent proportion of Overseas and Home students, and a similar size student body, as last year. In addition the cases arriving at UK campuses would be over half from UK Home Students. So even if the assumption of consistent proportion from Overseas turns out untrue, there is still the problem that having more UK Home students will bring more cases into the campuses. I also noted the summary, written by the authors:

      Their core estimate is that "81% of the 163 UK Higher Educational Institutes (HEIs) have more than a 50% chance of having at least one COVID-19 case arriving on campus when considering all staff and students. Across all HEIs it is estimated that there will be a total of approximately 700 COVID-19 cases (95% CI: 640 - 750) arriving on campus of which 380 are associated from UK students, 230 from international and 90 from staff. This assumes all students will return to campus and that student numbers and where they come from are similar to previous years. According to the current UK government guidance approximately 237,370 students arriving on campus will be required to quarantine because they come from countries outwith designated travel corridors. Assuming quarantining is 100% efficient this will potentially reduce the overall number of cases by approximately 20% to 540 (95% CI: 500 - 590). Universities must plan for COVID-19 cases ... and ... reduce the spread of disease. It is likely that the first two weeks will be crucial to stop spread of introduced cases. Following that, the risk of introduction of new cases onto campus will be from interactions between students, staff and the local community as well as students travelling off campus for personal, educational or recreational reasons.

      "COVID-19 has resulted in the on-campus closure of HEIs across the UK in March 2020 (1). Since that point universities have been working predominantly as virtual establishments with most staff working from home. Autumn sees the start of the new academic term with the potential return of more than 1.5 million UK and almost half a million international students (2).

      "The COVID-19 pandemic continues ... approximately 1000 new cases reported each day in the UK, 25,000 across Europe and 250,000 worldwide ((3) accessed 28/03/20). There have been a number of outbreaks of COVID-19 reported in universities in the USA (The University of North Carolina, Notre Dame in Indiana, Colorado College, Oklahoma State and University of Alabama (4)) where the national infection rate is approximately 10 times higher than the UK (3). advice ...(5, 6). However, it is currently unknown to what extent COVID-19 will be brought to campus by staff and students whether from the UK or abroad."

    1. On 2020-06-09 18:29:42, user Chris Winchester wrote:

      Would it be possible to study in your data set the quality of RCTs from different funders (e.g. commercial funders vs governmental funders, charities and NGOs)?

    1. On 2022-01-20 04:04:11, user Andrew David wrote:

      How can it be 100% effective against Delta for hospitalization or death with a confidence interval reported as 95% CI: 43.3-99.8 ?<br /> See results in the abstract.<br /> How can an estimate lie outside the confidence interval? <br /> I wish 100% could be true, but wishing doesn’t make it so. Or have math and statistics changed on account of Covid?<br /> That’s just plain sloppy.

    1. On 2020-04-16 17:51:35, user James Bell wrote:

      In the assumptions, was the ILI resulting from flu an average number or some lower number? This flu season peaked in November/December. A simple Google search reflects this through articles that were published about it at the time. If, in fact, an average ILI was used, doesn't that means the flu ILI are too high in this paper and that the overestimated value presumably belongs to COVID-19 instead? Also, since some in the media are arguing this paper "proves" we don't need the lockdown, is that really true (assuming all the assumptions in the paper are correct)? After all, we're talking about a virus for which none of us (except those who have recovered from it) have any immunity. If you have viruses with equal fatality rates, but we have herd immunity to one and not the other, doesn't common sense dictate there would be more fatalities with the latter (all else being equal)?

    1. On 2021-03-17 10:44:27, user Krisantha Weerasuriya wrote:

      If there was the opportunity, a small simultaneous blood sample from the mother to measure the COVID19 antibodies would have provided further useful information.

      Would it be possible with covering permission from the Ethical Committee to do a simultaneous blood sample for COVID 19 antibodies from mother and baby at 3 months (or the most appropriate time)?

    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 2020-04-26 13:05:40, user Bin_Pei wrote:

      Thanks for kind reminder of the reviewers, there is an unintentional editing error that we accidentally mixed the name of two cities in affliation in the original manuscript. We have submitted a revision already, there might be few days delay and we will be more careful in the future work.

    1. On 2020-04-27 04:52:01, user Krishna Undela wrote:

      It is the first information on knowledge and beliefs of general public of India on COVID-19. In this article we can understand the false beliefs / myths circulating among the general public of India about transmission of novel coronavirus and prevention and treatment of COVID-19.

    1. On 2022-01-13 13:16:50, user Zacharias Fögen wrote:

      Table S9 and S8, community median income, number of cases in <50,000 is higher in S9 than in S8, which is impossible. Same but reversed for 50,000-99,999, maybe exchanged numbers?<br /> Why in Table 3 did you use log increase for median income? that makes no sense to me, as you are using steps of 50,000 each.

      However, more importantly, <br /> Table S3: HR Age per 1y increase =1.05 , that's not plausible as COVID-19 risk increases exponentially (doubles every 6-7 years). Using a linear regression on a nonlinear variable is not a fitting model. you could have used log age.

    1. On 2021-04-20 16:21:52, user Laurie B wrote:

      Thank you for conducting this important research work and making your results available online. This information must be widely communicated. My dad received his final Retuxin infusion January 2021. Shortly after he received Covid vaccination 1 and then February 4th the second. While still following most covid precautions he had certainly let his guard down as a "fully vaccinated" person. Turns out, he was not. He is in the ICU with covid. Please pursue a press release. Please let me know how I can help disseminate your findings. Thank you for your work!

      This is how our family found out: https://www.nytimes.com/202...

      And from an ICU Doc who shared: "Rituximab specifically target cancerous B cells and helps our immune system destroy them. But B cells are the very cells that make our antibodies so his response to the vaccine is going to be muted with or without the Rituximab."

    1. On 2021-07-05 12:11:26, user Meerwind7 wrote:

      Data from the US in 2020 showed a clear increase of cases in the southern states during summer, i.e. when and where air conditioning was the most widespread. After the summer heat, cases started to increase from North to South. Therefore, it seems quite obvious to me that air exchange is the main culprit of temperature- or weather-related changes.

      Too complicated: "A further complication is that temperature, humidity, and UV radiation plausibly affect transmission and incidence through a range of biological and epidemiological mechanisms"

      My theory could be further assessed by looking at regions or in sociological groups where installations of air conditioning are less widespread, so that people spend more time with open windows or outdoors in summer. A heatwave in temperate Europe (where air conditioning is rare in residential buildings) or in poor quarters of the US thus should not lead to increased infections, while a heat wave in US suburbs with widespread availability of air conditioning would have that effect (as long as people do not met outdoors anyway, in consideration of Covid-19). In southern Europe, air conditioning may be more widespread in urban centers, whih form heat islands, than in rural areas, so that would also drive differences,

    1. On 2021-01-22 14:40:19, user Tim Meyer wrote:

      It is understandable that the issue of the Covid-19 incidence in football (soccer) players is of general (and scientific) interest. Also, it makes sense to compare this incidence to the general population of that age. However, such comparisons have to be made in a scientifically sound manner. One of such principles - also on pre-print servers or possibly even more so on such platforms which are not peer-reviewed in advance - is the meticulous description of the methods being used. Unfortunately, crucial information about this is lacking for the article from Andersen et al. entitled „Incidence and relative risk of infection with SARS-CoV-2 virus (Covid-19) in European soccer players“.

      It is not described how the infection numbers for the 5 leagues have been obtained (i. e. uncertainty about the numerator for the incidence calculation). Also, we do not get sufficient information about how the (estimated) incidence in the general population has been assessed. In this regard, it is noteworthy that a frequently tested population like the one of the players potentially has a number of undetected infections close to zero. This is completely different in the general population where some studies point to numbers of undetected infections in the range of 75-90% with higher values in the young age groups where asymptomatic Covid-19 courses are more frequent. Due to the very short methods description it is not clear which calculations have been carried out for this study. Therefore, we have uncertainties about the numerators of both incidence calculations which makes results hard to interpret.

      When we assume (in favour of the authors´ numbers) that the number of undetected infections has been taken into account appropriately by referring to an „infection fatality rate“ from a small area in Germany (a highly questionable method from our perspective) the message would be that hygiene protocols in Germany and England work well. However, studies based on procedures like the ones in this text appear methodologically unsound and should not be published – not even on pre-print servers. Even on such pre-print platforms more thorough descriptions as well as careful interpretations (including the limitations of one´s work) are needed because otherwise misinterpretations may enter the public domain.

      Tim Meyer (Conflict of Interest: Chair of the German Task Force "Sports Medicine/Special Match Operations" which has been developing the hygiene protocol for the German football leagues; chair of the medical committees of the DFB and UEFA); Barbara Gärtner (Conflict of Interest: Member of the German Task Force "Sports Medicine/Special Match Operations" which has been developing the hygiene protocol for the German football leagues

    1. On 2020-03-24 14:01:51, user Sinai Immunol Review Project wrote:

      Main findings<br /> The authors collected data on 25 COVID-19 patients (n=11 men, n=14 women) using standard laboratory tests and flow cytometry. All patients were treated with antibiotics. Twenty-four of the 25 patients were also treated with anti-viral Umefinovir and 14 of the patients were treated with corticosteroids. 14 patients became negative for the virus after 8-14 days of treatment. The same treatment course was extended to 15-23 days for patients who were still positive for the virus at day 14. <br /> The authors found a negative association between age and resolution of infection. Patients with hypertension, diabetes, malignancy or chronic liver disease were all unable to clear the virus at day 14, though not statistically significant.<br /> Elevated procalcitonin and a trend for increased IL-6 were also found in peripheral blood prior to the treatment.<br /> A trend for lower NK cell, T cell and B cell counts in patients was also reported. B cell, CD4 and CD8 T cell counts were only increased upon treatment in patients who cleared the virus. NK cell frequencies remained unchanged after treatment in all the patients.

      Limitations of the study<br /> 73% of the patients who remained positive for SARS-CoV2 after the 1st treatment, and 43% of all patients who cleared the virus were treated with corticosteroids. Corticosteroids have strong effects on the immune compartment in blood{1}. The authors should have accounted for corticosteroid treatment when considering changes in T, NK and B cell frequencies.<br /> Assessing if IL-6 concentrations were back to baseline levels following treatment would have provided insights into the COVID-19 cytokine storm biology. Patients with higher baseline levels of IL-6 have been reported to have lower CD8 and CD4 T cell frequencies{2}. Correlating IL-6 with cell counts before and after treatment would thus have also been of interest.<br /> The report of the laboratory measures in table 2 is incomplete and should include the frequencies of patients with increased/decreased levels for each parameter.<br /> Correction is needed for the 1st paragraph of the discussion as data does not support NK cell restoration upon treatment in patients who cleared the virus. NK cells remain unchanged after the 1st treatment course and only seem to increase in 2 out of 6 donors after the 2nd treatment course in those patients.

      Relevance<br /> Previous reports suggest an association between disease severity and elevated IL-6 or pro-calcitonin concentrations in COVID-19 patients3,4. IL-6 receptor blockade is also being administered to patients enrolled in clinical trials (NCT04317092). This report thus contributes to highlight elevated concentrations of these analytes in COVID-19 patients. Mechanisms underlying the association between viral clearance and restoration of the T cell and B cell frequencies suggests viral-driven immune dysregulation, which needs to be investigated in further studies.

      References

      1. The CHI Consortium et al. Effects of Systemically Administered Hydrocortisone on the Human Immunome. Sci Rep 6, 23002 (2016).
      2. Zhao, Z. et al. Clinical and Laboratory Profiles of 75 Hospitalized Patients with Novel Coronavirus Disease 2019 in Hefei, China. http://medrxiv.org/lookup/d... (2020) doi:10.1101/2020.03.01.20029785.
      3. Chen, X. et al. Detectable serum SARS-CoV-2 viral load (RNAaemia) is closely associated with drastically elevated interleukin 6 (IL-6) level in critically ill COVID-19 patients.<br /> http://medrxiv.org/lookup/d... (2020) doi:10.1101/2020.02.29.20029520.
      4. Lippi, G. & Plebani, M. Procalcitonin in patients with severe coronavirus disease 2019 (COVID-19): A meta-analysis. Clinica Chimica Acta 505, 190–191 (2020).

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

    1. On 2020-09-04 21:26:30, user Samir Arbache wrote:

      Dear authors. Interesting essay, I am very interested in this subject. I made these injections at a specific point in the dermis of my forearm for 20 days (once a day), the skin came to ulcerate. After healing, I made a manual touch on the area but I didn't feel that the skin was hardened, so I avoided the biopsy. My question is: after the treatment of the rats, did you feel touching if the skin was hardened as morphea?

    1. On 2020-05-21 01:21:24, user Morat Gurgeh wrote:

      This whole affair has been entirely unedifying. I do not know the truth of the allegations published in Buzzfeed, but then neither does anyone else commenting here, on Twitter and elsewhere. There are a lot of people, including senior academics, who should be ashamed of their behaviour.

      Turning to the central controversy, it is entirely possible and indeed likely for different populations to have different IFRs. The fact that the IFR in NYC appears to be significantly higher than reported here does not “debunk” this work and indeed is not even inconsistent with these results.

      NYC was hit early by the virus, when protocols for managing infected patients were still developing and mistakes were made. In addition, those most susceptible to COVID-19 (e.g. the old) were much less likely to be voluntarily shielding. Catastrophic errors have been made in many countries in care homes. So the likelihood of those over 80 being infected was likely much higher than in this study. Given the incredibly steep fatality gradient with age, this alone could explain the IFR differences.

      I think the main take home message of this paper is this: the lives of healthy, working age people should return largely to normal while those groups identified at elevated risk should continue to shield. Amongst the young, we should treat infection by SARS-CoV-2 as more akin to measles than Ebola.

      We need most of the healthy, young population to develop what immunity they can to this virus so that we can properly protect those most susceptible.

    1. On 2020-04-08 15:07:01, user Georgeta Vaidean wrote:

      Interesting paper. Good to see adjustment for 16 covs. and sens analysis. Any chance to add data on COPD, Lung cancer, CHD? both prevalence and mortality rates? particularly longitudinal figures (against historical background). Data are likely available, even at county level.

    1. On 2021-04-25 15:33:39, user Tam Hunt wrote:

      This study is conflating deaths with covid with deaths caused by lockdown measures bc it employs the UK standard definition of a covid deaths as follows:

      In the UK, all-cause death by 28-days post confirmation of SARS-CoV-2 infection is the standard definition of SARS-CoV-2 mortality,8 so we used death from any cause as the primary outcome. In sensitivity analysis restricted to people diagnosed with SARS-CoV-2 a minimum of 28-days prior to the censoring date, and logistic regression with deaths censored beyond 28-days the results were consistent.

    1. On 2021-11-28 19:40:54, user Robert van Loo wrote:

      44 relevant new variants up till now and on average some 2 per 10 million cases. Did we only see 220 million cases globally? I would think more with over 5 million deaths and an IFR of 0.6 %. I have papers and also WHO stating the reported 260 million cases is factors lower than the real number of infections. With over 5 million reported deaths and an IFR of 0.6 % the real number of infections would be over 800 million cases. The number of relevant new variants per 10 million cases would then be about 4 times lower. Of course if reported cases always underreport to the same extent the extrapolation of reported cases to new variants would not change. Still important to make the distinction as the underreporting factor is hugely variable.

    1. On 2020-10-28 17:53:21, user Sam Wheeler wrote:

      It it so that non-vaccinated hospital personnel are forced to wear a mask almost all the time to prevent flu, so the protection of flu vaccine is even greater than this study tells?

    1. On 2020-05-14 10:44:33, user Dom Mcelhinney wrote:

      In the at risk group for covid19 almost 50% of population are being treated for Hypertension and Hypercholesterolaemia. Can you explain why you have been unable to list this as a possible comorbidity.

    1. On 2021-05-27 04:54:05, user rusbowden wrote:

      Not satisfied with my response from 11 hours ago being nearly as curt as what I responded to, I've come up with a list of links for anyone who wants to be up-to-date on how we have come to know about the efficiacy of wearing face masks. My hunch is that most readers here do not need it, but for anyone unfamiliar, it just seemed too vital to let lie.

      Each article below includes the knowledge that masks are used to lessen aerosol transmission. What gets covered is what we know about how effective different types of masks are, how they should be worn. We also know how double masks help, what the research shows us there, and which mask should go on top, things like that. A recent article scientifically addresses Texas' executive orders, the harm done. But the final one, is the link to the the report that I was quoting from a day ago, that seriously undercuts this study.

      Many readers will already recognize some if not most of the links. All of them need to be explained by anyone who wants to now say that all the science we've had and have been developing for over a year has been hogwash, that tjhousands of researchers have not know what they are talking about, that we now know none of it had veracity. We don't just go back to flat earth, because someone writes a research paper. Here they are:

      To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic<br /> https://www.ncbi.nlm.nih.go...

      Masks Do More Than Protect Others During COVID-19: Reducing the Inoculum of SARS-CoV-2 to Protect the Wearer<br /> https://link.springer.com/a...

      Will an imperfect vaccine curtail the COVID-19 pandemic in the U.S.?<br /> https://www.ncbi.nlm.nih.go...

      Could masks curtail the post-lockdown resurgence of COVID-19 in the US?<br /> https://www.ncbi.nlm.nih.go...

      Effectiveness of Face Masks in Preventing Airborne Transmission of SARS-CoV-2<br /> https://www.ncbi.nlm.nih.go...

      Maximizing Fit for Cloth and Medical Procedure Masks to Improve Performance and Reduce SARS-CoV-2 Transmission and Exposure, 2021<br /> https://www.cdc.gov/mmwr/vo...

      Impact of Public Health Education Program on the Novel Coronavirus Outbreak in the United States<br /> https://www.frontiersin.org...

      Assessment of the COVID-19 Vaccine Program: Impact of the No Mask Mandate Executive Order in the State of Texas<br /> https://www.medrxiv.org/con...

      What factors have determined how well countries have done in responding to the pandemic?<br /> https://richardswsmith.word...

    2. On 2021-07-05 03:07:56, user dmit77 wrote:

      Studies on masks show that masks are not only ineffective against virus spread but that cloth masks in particular actually increase chances of getting infected.

      Here's one

      The results showed that there were no difference between wearing cloth masks, medical masks and no masks for incidence of clinical respiratory illness and laboratory-confirmed respiratory virus infections. However, a large harmful effect with more than 13 times higher risk [Relative Risk = 13.25 95% CI (1.74 to 100.97) was observed for influenza-like illness among those who were wearing cloth masks [19]. The study concluded that cloth masks have significant health and safety issues including moisture retention, reuse, poor filtration and increased risk for infection, providing recommendation against the use of cloth masks

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

    3. On 2021-08-17 15:31:41, user robert brown wrote:

      Your response is with a study that once again gets the setup wrong. The majority of a masks effective capacity is with exhaled breath. When droplets exit your mouth or nose they are contained in large droplets easily captured by masks. As those particles spread out much of the water evaporates leaving only a thin shell that can pass through the mask in larger numbers. A mask prevents this by 1 getting those droplets quickly and 2 by creating a humid environment behind the mask which slows the evaporation rate allowing for more time for particles to be captured. If you wanted to study this effect you would need the following. A control group with no masks. Another group that could be from the study you linked. And finally a group consisting only of people using masks only interacting with other people using masks. Otherwise the conclusions might as well read we tested one aspect of a multiprong system and found that one aspect did not hold up well on its own and thus conclude the entire system taken as a whole is bad. Something the study you linked is very self aware of. From its limitations section. "Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others." Far from being double blind as it states itself there is no blinding involved and no assessment of spreading covid. And even says so for a change.

    1. On 2020-09-14 23:14:12, user arkancide_is_real wrote:

      When are we going to see the data associated with this project? Source code merely shows how to generate output.

      The data should be openly available, given the supervising author's history.

    1. On 2021-09-01 09:50:45, user Till Bruckner wrote:

      This paper usefully highlights and quantifies the scarcity of randomised trials of NPIs. Providing a precise definition of NPIs and more details on inclusion/exclusion criteria might add value.

      A potential weak point is the claim that "it is unlikely that we have been unaware of pertinent results of further NPI trials, given their substantial impact on current debates and scarcity of the evidence." This appears to assume that all NPI trials were either (a) registered in a trial registry or (b) reported in the academic literature.

      There may have been experiments meeting the inclusion criteria that were run by government bodies and research units such as "nudge units" that were neither registered nor made public in academic formats.

      Performing a grey literature search and/or reaching out to key informants outside academia who may be able to comment on the likelihood of such research having been performed would help to provide assurance that no relevant studies have been missed, and strengthen the conclusions of the paper.

      Till Bruckner

    1. On 2020-09-07 23:07:20, user Louis Rossouw wrote:

      In the case if South Africa:<br /> * The reported deaths are very much undercounted.<br /> * The economist excess deaths figure includes drops in accidental deaths and other things. Please have a look at https://www.samrc.ac.za/rep... that tries to adjust for moving parts.

    1. On 2020-05-15 12:51:43, user Melimelo wrote:

      Thanks for this interesting analysis and plausible explanation! Another plausible explanation is that countries with endemic malaria have a better public health system than wealthier countries. I have been impressed with the excellent work done in the region of Maradi, Niger to rapidly investigate and isolate cases, test, and do contact tracing, despite extremely limited means. They’re very strained and could use support but they’re doing an amazing job, better than we are in the U.S.

    1. On 2021-05-23 07:26:54, user disqusWVOR wrote:

      Fig.2 pg.25 graph indicates ~5% grade 3 (severe) systemic adverse effects with NVX 2nd dose vs. <1% with placebo. How was this addressed in the article other than pg.13 "similar frequencies of severe adverse events (1.0% vs. 0.8%)"?

    1. On 2020-03-27 13:07:45, user Guido Marco Cicchini wrote:

      Very interesting. However my gut feeling is that a rock solid <br /> analysis will only be possible once the full history of contagion within<br /> the ship is tracked down. For instance people of the crew who work on <br /> the maintenance of the mains ervices of the boat (such as cooking and <br /> cruising) share little space with the people crusing and relaxing. As it<br /> is likely that these workers are young, this cast a whole new <br /> interpretation on the number of contagion within the younger ages <br /> ranges.

      Second point is that the number of deaths (fortunately) <br /> has been quite low. This poses a bit of an issue if one wants to <br /> extrapolate from this data. One viable option which has been proposed by<br /> several people in these days it has been to rely on the data of people <br /> with severe symptoms who needed ICU. Typically they are higher and thus <br /> enable more solid conclusions. IMHO the paper could be more solid if <br /> also this metric were included. <br /> Lastly, out of curiosity it <br /> would be interesting to compare the number of fatalities in Diamond <br /> Princess in February to those of other cruising boats (say during Feb <br /> 2019) across the world. I assume that these are quite lower (it is <br /> unlikely that there are more than 5 deaths across 3000 people in a few <br /> weeks of time).. yet it could be interesting. If stats for one months <br /> are too low and unreliable one may want to enlarge the sampling period <br /> to six-months

    1. On 2020-07-06 15:38:39, user Alexander Pearlman wrote:

      why is placebo sterile saline soln.--and not formulated with lipids as the mRNA-LNP (scrambled) drug product? is this a safety concern? or expect immunog. sig. from a scrambled construct?

    1. On 2020-06-29 01:07:28, user Dr. D. Miyazawa MD wrote:

      This is the revised second edition.

      Our hypothesis in this study is that face mask-wearing rates may be a significant factor for COVID-19 mortality, that obesity and old age are currently identified as the most relatively-independent factors for COVID-19 mortality, and that these three factors may be strong enough to "predict" mortality using means including Lasso regression to a considerable extent.To show the independence or causality of each factor, a multiple regression with a number of factors added to exclude confounding would be necessary, but that was not the goal of this study. Other studies aiming to identify predictors, or to show the independence of the factors of interest, for the difference among countries have done multiple regression analyses with a number of factors, but since the mechanism is currently largely unknown, the selection of factors other than the factors of interest would be close to random, making it of little significance to prove the true independence of the factors of interest.

    1. On 2021-09-11 13:25:33, user J Jones wrote:

      What you clearly dont understated is that the injection DOESNT PREVENT YOU FROM CONTRACTING COVID OR FROM SPREADING IT. Where is this misinformayion coming from?

    2. On 2021-09-11 16:11:54, user NativeCalifornian wrote:

      The vaccine only purports to protect vaccinated persons from getting a more serious case of the virus...it does NOT purport the prevention of onward transmission.<br /> From the FDA.Gov website: "Most vaccines that protect from viral illnesses also reduce transmission of the virus that causes the disease by those who are vaccinated. While it is hoped this will be the case, the scientific community DOES NOT YET KNOW if Comirnaty will reduce such transmission." "While the vaccine may not prevent infection, symptoms or transmission of the virus from person to person, it is effective in preventing hospitalization and death."<br /> https://www.fda.gov/vaccine...

    1. On 2020-10-29 06:19:38, user Marm Kilpatrick wrote:

      This is a very nice study. Unfortunately, two pieces of information are missing that make it very difficult to build on this study or compare it to the vast data on viral loads over time that are available from other studies:

      1) the date of symptom onset for the 13 symptomatic patients. Can you indicate this date of symptom onset on the figure with the individual viral loads (Supp Fig 13)?

      2) a conversion of viral loads from Ct values into copies per swab. This could be done either by re-running the samples with standards on the plate, or by simply running some standards with known copies. I am aware that this relationship (Ct-viral copies) can vary from machine to machine and even a little from run to run on the same machine, but without this conversion the Ct values in this study can't be compared to other studies that used different assays, machines, etc. Given that you were willing to use Ct scores from the Florida labs in your analysis (with the relationship in Figure S5) it seems like it would be possible to run a few standards and at least get an estimate of what viral loads you observed in copies/swab.

      Adding these two aspects to your paper would greatly enhance its value for the broader scientific community.

      A third component which may be much more difficult for most samples, but might be possible would be to indicate the likely day of infection if this can be inferred from case investigation. This would allow the data to be even more informative in mapping the relationship of viral load back to the day of infection.

      Thank you,<br /> Marm Kilpatrick

    1. On 2022-01-17 19:49:07, user AW wrote:

      Some errors in text and tables I’m afraid. In text you report the IRR for men <40 years as “7.60 (2.44 - 4.78)” for 3rd dose for Pfizer which clearly is nonsensical -looks you have used the 95%CI for second dose repeated in error. And you have reported the number of events as * for 3rd dose Pfizer in men under 40 years in table rather than number - should have a numerical value.

      Given these are probably the most important impactful data you present it’s a bit embarrassing to not get this right - but shows why peer -review is needed (and makes me wonder what else might be incorrect)

    1. On 2020-05-02 04:43:05, user Ilya Zakharevich wrote:

      Thanks! This is the first potentially meaningful text on such stats I have seen so far. However, there are some (possibly significant) apparent problems too… (Below, I only address points about false-positivity rates.)

      The presentation: for your Table 2 (and other related presentations), would not it be more clear if you add a row “Pre-Covid” before the row “1–5 day”?

      “Samples from UCSF and ZSFG were assigned a random well position in one of four 96-well plates.”

      I suspect this is not clear enough. The crucial question for estimating the seropositive population is the “degree of double-blindness” of mixing the 108 pre-CoVid samples among the other samples. Can you be more explicit about this? (Separately for ELISA and the rest, if possible.)

      “Binomial exact 95% confidence intervals were calculated for all estimates.”

      With 14 different schemes tested, this is a very questionable choice. Basically, for laymen in statistics (which, in my experience, probably covers >99.9% of potential readers), only the 99.74%-confidence intervals can be useful. (Here 5%/14?0.357%.)

      The people who understand the pitfalls of using 95%-confidence with 14 schemes could also be interested in 95%-confidence numbers — but these numbers would just create an unneeded confusion among the overwhelming majority. (As this XKCD shows.)

      “Four assays … maintaining >95% specificity.”

      Sigh… Do you understand the expected number of outliers with 14 groups? Especially when you, essentially, say “<=5 false-positive samples per group”?!

      “We based minimum sample size calculations on expected binomial exact 95% confidence limits.”

      I think 108 samples is ruefully small for any reliable conclusion. (As your numbers, and 99.64%-confidence intervals show.) I do not see any way than to start with >=1,000 samples (with one method), or >=3,000 (with 14 methods, as you use).

    1. On 2021-08-27 23:57:15, user Chris Woolley wrote:

      Is your sample biased? A snowball sample has reported that the nurses have worked more hours than normal. Isn’t it human nature to over-exaggerate hours worked. Would it have been better to just get the factual data from the hospitals if possible?

      Just looking at the nurses that worked 31-40 hours. 1/3 worked more than contracted and 15% of these claimed to have high stress. Does this not mean that only 5% of full time workers have had extra stress during COVID? Shouldn’t that be the headline?

    1. On 2020-07-14 04:46:01, user AJ wrote:

      Interesting paper. Gives an important view of CD8 physiology following infection. As expected, but not reassuring- the CD8s are more differentiated on a background of lymphopenia. Concerning to say the least.

    1. On 2020-01-27 17:59:25, user robertinventor wrote:

      Just to say the author of this paper tweeted that they now estimate it as 2.5 95% CI 2.4, 2.6 for R0 which would change all the projectons.

      This version says 3.8 (95% confidence interval, 3.6-4.0),

      Likely those confidence intervals need revising to, if it changes so much with an extra day of data. It is a non peer reviewed preprint.

      https://twitter.com/JonRead...

    1. On 2020-02-19 22:23:35, user hvoltbb wrote:

      There is a typo in the abstract "The updated basic reproductive number was found to be 2.12 on average with and a 95% credible interval of [2.04, 2.18]. ".<br /> It should be "and with". I was typing so fast on my laptop that words switched places. It will not get fixed in the second version, because the revision has already been uploaded.

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

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

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

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

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

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

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

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

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

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

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

    1. On 2021-08-13 10:28:43, user Amorphis wrote:

      Hey Astrid,

      I am a bit confused about this article. Majority think that vaccines are there to make sure your body has a decent amount of antibodies ready before the relevant infection so you can fight it off quicker. Meaning the main objective of the vaccine would be the prevention of severe ilness / hospitlization.

      But I am confused as to how a vaccine could prevent an infection from spreading? Say, as someone that had 2x dose vaccine, i contacted a person with covid-19 infection. At this point through air and by shaking hands with him and moving my hand to my mouth, face, eyes etc. i also get infected. Right here, how exactly does the vaccine protect the person from NOT getting the virus from the infected person?

      Certainly I am not a doctor but I did some reading on pathology and immunology related subjects.

      This article didn't make sense to me.

    1. On 2022-06-19 06:47:59, user TIGER-GNP wrote:

      Hearing Loss is among the top non-communicable disorders, in prevalence and YLDs - and yet it is forgotten again from multi-disorders studies. Please include hearing loss!

    1. On 2021-12-14 14:10:03, user Ergellegre wrote:

      We would all benefit for this proposition to be widely considered for replacing the current 'crude' model adopted in the UK to assess risk level. The fundamentals are well established, irrefutably so.

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

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

      Prof A. Manzini (Roma III)

    1. On 2020-04-11 18:07:45, user Aaron Gasaway wrote:

      Scientists and medical researchers: please look into whether it's dust that is sometimes allowing the virus to become "aerosolized." I've read a little about dust particles carrying influenza, so it seems plausible. Also, the recent Chinese study showed higher concentrations on the floor (where dust would fall). Dust as the vehicle would also explain it being found in AC vents. Central Air units suck up a huge amount of dust and some of it makes it through the filters and back out into the air.

      Of course none of this means the moisture in exhalations or coughs couldn't also be the vehicle. On the whole it would seem not to be spreading enough for normal exhalations to be the primary vehicle, although it seems from the Washington choir episode that with enough force behind the exhalations, it could be.

      I am sorry if this question about dust seems amateurish or crackpot. I just don't know if anyone qualified is looking into this possibility, so thought I should post it here.

    1. On 2020-09-22 22:58:23, user Stephen D wrote:

      It would be useful if you included "modelling" or "computer simulation" in your title. I've never been able to understand why so many advocates of draconian approaches to this virus have such a 'thing' against choirs and singing. Is there a lot of that going on where you live?

    1. On 2025-11-30 16:49:17, user Cyril Burke wrote:

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

      We removed identifying features and will include our responses in a subsequent comment. The changing title and line numbers refer to versions prior to our medRxiv preprints.]

      April 1, 2022<br /> Screening for early kidney disease and population health using longitudinal serum creatinine

      Dear Dr. Burke III,

      REDACTED.

      Reviewer #1: Burke et al submit a somewhat unusual paper, devoted to a topic of potential major clinical relevance, and as yet understudied.

      General comments

      1. The thesis of the authors, that using the baseline serum creatinine of a given patient would potentially improve the earlier diagnosis of kidney disease, even in the normal range, is in line with the experience of this reviewer, who always retrieves , whatever the difficulty of reaching that goal, past results of blood tests, and uses them as a way to date the onset of kidney disease, sometimes with important prognostic implications.

      2. Yet, the authors do not provide data strongly supporting their thesis. For instance, when looking at case 2, should the last point (the most recent one) be omitted, there would be very little evidence supporting progressive early kidney disease.

      3. The claim that the statistics fit the data better when all points are used (page 9,11) should not come as a surprise. Using thresholds instead of the full range of values has long been known to be more powerful for statistical analysis. But fitting the data does not equal to a high positive predictive value!

      4. A key question is whether in a real world context, the earlier diagnosis of kidney disease would be possible, without too much background noise from intercurrent illness (functional), drugs (NSAIDS, etc..). In other words, would the specificity (or PPV) of the suspicion of early kidney disease be reasonable enough to catch the attention of clinicians

      5. Even though there has been improvement in the standardization of measurement of serum creatinine (IDMS), the comparability of results measured by different labs remains suboptimal, at least in the experience of this reviewer, and medical shopping is not uncommon, making the availability of all previous results in the same graph a logistical challenge.

      Specific comments

      1. The authors should mention that the USPTFS decided a month ago to revisit the question of screening for kidney disease in high risk groups (page …)

      2. Even though ESRD has a legal meaning in the USA, not very relevant to the topic of this paper about early kidney disease, the authors should stick to the nomenclature proposed by a recent KDIGO consensus conference (see Levey et al. Nature Reviews in Nephrology ). In particular, use kidney failure instead of ESRD/ESKD. When the topic is glomerular filtration, use that wording instead of kidney function (page…)

      3. The authors allude to the concepts of prediabetes and prehypertension. But this reviewer points to the fact that the levels used to define those entities are currently “generic” , rather than based on previous values in an individual subject. Please discuss.

      4. The authors repeatedly mention in the discussion section evidence that even small increases in serum creatinine have prognostic significance. This has indeed been known for decades but is a different topic: AKI . Admittedly, there is growing evidence that AKI and CKD are linked. But that the stability of a biological parameter is prognostically best is all except surprising: the same is true for body weight, mood, blood pressure etc…

      Reviewer #2: Thank-you for the opportunity to review this work which highlights the importance of monitoring serum creatinine over time and how this can be a useful tool in detecting possible CKD. This is an important topic as the use of sCr on its own is certainly under-utilised and changes are often missed because they don’t fall into a predefined category.

      MAJOR CONCERNS

      “Choi- rates of ESRD in Black and White Veterans” doesn’t fit with the rest of the paper including the title; the introduction and conclusion also don’t adequately address this portion of the paper. It feels disjointed from the main point of discussion which is the use of sCr in screening “pre-CKD”. This section and discussion should be removed and possibly considered for another type of publication.

      Cases 1 - 3, (lines 93 – 122): where are these cases from? There is no mention of ethics to publish these patient results, which appears to be a clear ethics violation. If so, these cases should be removed and patient consent and ethical approval obtained to publish them.<br /> The authors describe the reasons for not obtaining an ethics waiver for this secondary data analysis. Despite this, the relative ease of obtaining an ethics waiver for secondary data analysis usually means that this is done regardless.

      The message of the article and data representation is unclear: do the authors wish to show that sCr is superior to eGFR in this “pre-CKD” stage, should both be used together? Do the authors wish to convey that a “creatinine blind range” does not exist? Or is the aim to demonstrate that continuous variables should not be interpreted in a categorical manner?

      MINOR CONCERNS

      ABSTRACT<br /> Vague<br /> Doesn’t give a clear picture of the study

      INTRODUCTION<br /> 51 – 57: needs to state that these stats are from e.g. the US. The authors should consider adding international statistics to complement those from the US.

      68: reference KDIGO guidelines, state year

      75 – 77: is this reference of the New York Times the most appropriate?

      82: within-individual variation not changes (this is repetition of the point made in lines 425 – 427, but should match the language)

      82 – 84: reference? If this is a question it should be presented as such

      84: “normal GFR above 60” = guidelines (including KDIGO) do not refer to 60 as normal GFR, 60 – 89 is mildly decreased. (see line 126)

      93: avoid the use of emotive words such as apparently (also in line 428)

      94: “Not meeting KDIGO guidelines”: KDIGO 2.1.3 includes a drop in category (including those with GFR >90). This would appear to include some of the cases listed. Additionally, albuminuria should have been measured for case 2 and 3.

      97: “progressive loss of nephrons equivalent to one kidney”: this is based on a single creatinine measurement.

      93 – 122: Could any of these shifts be explained by changes in creatinine methodology or standardisation of assays, especially over 15 – 20 years (major differences between assays existed before standardisation and arguably still exist with certain methods).<br /> It would be useful to see a comparison between serial sCr and eGFR measurements on the same figure. There appears to be significant (possibly more pronounced) changes when eGFR is used. As line 87 mentions changes in eGFR may be as useful (and in some situations more useful) than changes in sCr alone.

      127 – 142: should there be separate charts for males and females, the differences in creatinine between males and females needs to be discussed somewhere in the paper. Similarly, is this suitable for all ages?

      162 – 163: rephrase

      METHODS<br /> 185 – 193: aim belongs in the introduction, can be adjusted to complement paragraph 178 – 182.

      196 – 205: reference sources

      224 – 247: not in keeping with the rest of the article or title and conclusion

      RESULTS<br /> If eGFR is treated as a continuous variable does inverted sCr still have higher accuracy?

      As mentioned, the section on ESRD in black and white veterans doesn’t fit in with the rest of the article.

      DISCUSSION<br /> As mentioned, section 4.1 doesn’t fit in with the rest of the article. As the authors note the correlation between illiteracy and CKD is likely not causal.

      387: erroneous creatinine blind range. The data presented does not show this is erroneous there is still a relative blind range. A distinction must be made between a population level “blind range” and an individual patient’s serial results. The data and figure 4 in particular demonstrate the lack of predictive ability of sCr above 40ml/min compared to below 40ml/min at a population level. For an individual patient this “blind range” is more relative, and a change in sCr even within the normal range may be predictive. (Note: the terminology “blind range” is problematic).

      399 – 400: “rose slowly at first and then more rapidly as mGFR decreased below 60” this refers to a relative blind range. Whether these slow initial changes can be distinguished from analytical and intra-individual variation is the question that needs to be answered before we can say a “blind-range” doesn’t exist for an individual patient.

      425 - 432: sCr is indeed very useful when baseline measurements are available. eGFR remains useful when baseline sCr is not available or when large intervals between measurements are found.

      425: low analytical variation- if enzymatic methods are used

      428: avoid the use of “apparently”

      430: reference 56 compares sCr and sCysC with creatinine clearance NOT with mGFR, this does not prove that mGFR has greater physiologic variability. Creatinine clearance is known to be highly variable (partially due to two sources of variability in the measurements of creatinine: serum and urine).

      The limitations of sCr for screening should also be discussed: differences in performance and acceptability between enzymatic and Jaffe methods (still widely used in certain parts of the world), the effect of standardizing creatinine assays (an important initiative but one that could also produce shifts in results around the time of standardization- see cases), low InIx means that once-off values are exceedingly difficult to interpret, is a single raised creatinine value predictive (or should there be evidence of chronicity): similarly are there effects from protein rich meals, etc (The influence of a cooked-meat meal on estimated glomerular filtration rate. Annals of Clinical Biochemistry. 2007;44(1):35-42. doi:10.1258/000456307779595995)

      CONCLUSION<br /> The discussion recommends using SCr above eGFR while the conclusion recommends the NKF-ASN eGFR for use in pre-CKD and ASC charts. While the use of both together in a complementary fashion is understandable- this needs to be congruent with the discussion, aims and results.

    1. On 2020-07-02 20:38:30, user Aiman Tulaimat wrote:

      Another aspect of this study that I am still pondering is the decreasing response from high in ventilated patient, to moderate with some respiratory support, to none on no oxygen. Could the observed effect of dexa be limited to its ability to reduce ventilator induced lung injury (PMID: 27383928, PMID: 23451215, PMID: 24439582), especially that dexa is the least effective steroid in reversing the genetic activation in patients with viral pneumonia (https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.05.06.20076687v1.full.pdf)"). The study has not reported much of the ventilator data, particularly adherence with low tidal volume-low plateau pressure strategy.

      Aiman Tulaimat<br /> Pulmonary, Critical Care, and Sleep Medicine<br /> Cook County Health<br /> Chicago, IL USA

    1. On 2020-08-20 01:45:02, user giorgio capitani wrote:

      How it can be proved without any doubt that the virus present in the aerosol actually infects a person? it can present but be harmless. Where is the evidence of the actual trasmission of the infection? the presence in the aerosol is not evidence of the transmission of the virus it's another pair of shoes. Or somebody can be infected and others not. How can you tell one thing from the other? they are two different moments: the presence of the virus in the aerosol, the actual transmission of the virus.

    1. On 2020-05-05 03:43:04, user Sinai Immunol Review Project wrote:

      A possible role of immunopathogenesis in COVID-19 progression

      Anft M., Paniskaki K, Blazquez-Navarro A t al.; medRxiv 2020.04.28.20083089; https://doi.org/10.1101/202...

      Keywords

      • SARS-CoV-2 spike protein-specific T cells

      • COVID-19

      • adaptive immunity

      Main findings

      In this preprint, 53 hospitalized COVID-19 patients, enrolled in a prospective study at a tertiary care center in Germany, were assigned to moderate (n=21; light pneumonia), severe (n=18; fever or respiratory tract infection with respiratory rate >30/min, severe dyspnea, or resting SpO2 <90%), and critical subgroups (n=14; ARDS, sepsis, or septic shock) according to clinical disease. Moderately and severely ill patients with a PCR-confirmed diagnosis were recruited within four days of clinical onset, whereas critically ill patients were enrolled on average within 14 days of diagnosis on admission to ICU. To account for the overall longer hospital stay in ICU cases prior to inclusion, repeated blood samples were obtained from moderately and severely ill donors within eight days post recruitment. For 10 out of 14 ICU patients, no follow up blood samples were collected. At recruitment as well as on follow-up, circulating lymphocyte counts were below reference range in the majority of enrolled COVID-19 patients. Relative frequencies were significantly reduced in critically vs. moderately, but not vs. severely ill individuals, with substantially lower NK as well as CD8 T cells counts, and a concomitant increase of the CD4:CD8 T cell ratio in ICU patients. Basic phenotypic and immune cell subset analysis by flow cytometry detected lower frequencies of central memory CD4 T cells as well as reduced terminally differentiated CD8 Temra cells in critical COVID-19. Moreover, a decrease in activated HLA-DR+ CD4 and CD8 T cells as well as in cytolytic CD57+ CD8 T cells was observed in critical vs. severe/moderate disease. Similarly, frequencies of CD11a+ CD4 and CD8 T cells as well as CD28+ CD4 T cells were lower in critically ill donors, indicating a general loss of activated bulk T cells in this subgroup. In addition, a reduction of both marginal and transitional CD19+ B cells was seen in patients with severe and critical symptoms. Of note, on follow-up, recovering severe COVID-19 patients showed an increase in bulk T cell numbers with an activated phenotype. Importantly, SARS-CoV-2 spike (S)-protein-specific CD4 and CD8 T cells, identified following stimulation of PBMCs with 15-mer overlapping S protein peptide pools by flow-cytometric detection of intracellular CD154 and CD137, respectively, were found in the majority of patients in all COVID-19 subgroups at the time of recruitment and further increased in most subjects by the time of follow-up (antiviral CD4 >> CD8 T cells). Most notably, frequencies of both antiviral CD4 and CD8 T cells were substantially higher in critically ill patients, and virus specific CD4 and CD8 T cells in both critically and severely ill subgroups were shown to produce more pro-inflammatory Th1 cytokines (TNFa, IFNg, IL-2) and the effector molecule GzmB, respectively, suggesting an overall increased magnitude of virus-specific T cell inflammation in the context of more severe disease courses. Furthermore, frequencies of antiviral CD4 T cells correlated moderately with anti-S-protein IgG levels across all patient groups.

      Limitations

      In general, this is a well executed study and most of the observations reported here pertaining to overall reduced bulk T cell frequencies (along with lower NK and other immune cell counts) as well as diminished numbers of T cells with an activated phenotype in ICU vs. non ICU COVID-19 corroborate findings in several previous publications and preprints (cf. https://www.jci.org/article... https://academic.oup.com/ji... https://www.nature.com/arti... https://www.medrxiv.org/con... https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.04.17.20061440v1.full.pdf)"). Notably, in contrast to many previous reports, the prospective study by Anft et al. enrolled a relatively larger number of COVID-19 patients of variable clinical disease (with the exception of mild cases). However, there are a few weaknesses that should be addressed. Most importantly, the choice of statistical tests applied should be carefully revised: e.g. comparison of more than two groups, as seems to be the case for most of the figures, requires ANOVA testing, which should ideally be followed by post-hoc testing (despite the somewhat confusing statement that this was conceived as an exploratory study). Given the overall limited case numbers per clinical subgroup, trends even though they might not reach statistical significance are equally important. Similarly, some statements are overgeneralized and should be adjusted based on the actual data shown (e.g. the authors continue to refer to gradual reductions of activated T cell subset numbers in moderately vs. severely vs. critically ill patients, but for the majority of data shown substantial differences are apparent only in ICU vs. non-ICU patients). Moreover, it would be helpful to include representative FACS plots in addition to explanatory gating strategies provided in the supplemental document. There are also several inconsistencies regarding the order of data presented here (e.g. in the main manuscript, Fig S5 is chronological referred to before Fig S4) as well as pertaining to relevant technical details (according to both the main manuscript and the gating strategy in Figure S5, virus-specific CD4 T cells were identified by CD154 expression; however, in figure legend S5 virus-specific CD4 T cells are defined as CD4+ CD154+ CD137+). Additionally, from a technical point of view, it is somewhat intriguing that the percentages of virus-specific T cells identified by expression of CD154 and CD137, respectively, following peptide simulation seem to differ substantially from frequencies of CD154+ or CD137+ INFg+ virus-specific T cells. Assuming a somewhat lower extent of cellular exhaustion in the moderate COVID-19 group, one would expect these cell subsets to mostly overlap/match in frequencies, therefore suggesting slight overestimation of actual virus-specific T cell numbers. In this context, inclusion of positive controls, such as CMV pp65 peptide stimulation of PBMCs from CMV seropositive donors, in addition to the already included negative controls would also be helpful. Moreover, in view of the observation that virus-specific T cells were found to be increased in critically ill ICU over non-ICU patients, a more stringent characterization of these patients as well as assessment of potential associations with clinical characteristics such as mechanical ventilation or death would add further impact to the findings described here. Finally, this study is limited to anti-S protein specific T cells. However, evaluation of N and also M-protein specific T cell responses are likely of great interest as well based on current knowledge about persistent M-protein specific memory CD8 T cells following SARS-CoV-1 infection (cf. https://www.microbiologyres... "https://www.microbiologyresearch.org/content/journal/jgv/10.1099/vir.0.82839-0)").

      Significance

      In addition to reduced frequencies of activated bulk T cell numbers, the authors report an enhanced virus-specific T cell response against S protein epitopes in critically ill COVID-19 patients compared to severely and moderately ill individuals, which correlated with anti-S protein antibody titers (also cf. Ni et al.: https://doi.org/10.1016/j.i... "https://doi.org/10.1016/j.immuni.2020.04.023)"). This is an important observation that mirrors previous data about SARS-CoV-1 (cf. Ka-fai Li C et al.: https://www.jimmunol.org/co... "https://www.jimmunol.org/content/jimmunol/181/8/5490.full.pdf)"). Furthermore, in accordance with a recent preprint by Weiskopf et al. (https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.04.11.20062349v1.full.pdf)"), virus-specific CD4 T cells were found to increase in most patients over time regardless of clinical disease, whereas antiviral CD8 T cell kinetics seemed slightly less pronounced. Moreover, in the majority of moderately and severely ill cases, virus-specific T cells against the S protein could be detected early on - on average within 4 days of symptom onset. Longitudinal studies including larger numbers of COVID-19 patients across all clinical subgroups are therefore needed to further evaluate the potential impact of this observation, in particular in the context of previously described pre-existing memory T cells cross-reactive against human endemic coronaviruses (cf. https://www.medrxiv.org/con... https://journals.sagepub.co... "https://journals.sagepub.com/doi/pdf/10.1177/039463200501800312)").

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

    1. On 2025-02-12 20:00:36, user Aron Troen wrote:

      Review Part III

      Results and Discussion<br /> Quantity of food trucked in: No source is cited for the figure of a pre-war baseline of 150-180 food-transporting trucks per day. This number is inconsistent with Israeli and UN sources. According to a document published in June by the Food Security Cluster, only 23% of UN recorded incoming goods to Gaza (not including fuel) before 7 October were food or food production inputs ( https://fscluster.org/sites/default/files/2024-06/Gaza%20imports%20and%20food%20availability%2015_may_V2%202.pdf) "https://fscluster.org/sites/default/files/2024-06/Gaza%20imports%20and%20food%20availability%2015_may_V2%202.pdf)") . If one is to rely on those UN statistics, the pre-war monthly average of trucks carrying food into Gaza was 2,288 (an average of approximately 100 trucks per working day in a normal month). Another UN source is the OCHA online Gaza crossings dashboard according to which during Jan-Sep 2023 a total 27,434 trucks carrying food entered Gaza, representing a monthly average of 3,048 trucks. <br /> The comparison in Figure 1 between the mean daily number of trucks for each week during the war with the "pre-war number of food-carrying trucks" per working day is highly misleading since it assumes that the number of working days remained steady. The distortion is significant because between 21 October and 5 May the crossings were open almost every day, as opposed to the 5-day work week in the period before the war. The following chart shows the monthly figures of UNRWA and COGAT compared to the monthly pre-war average of 2,288 trucks carrying food.

      Compare it with Figure 1 from the article, which tells an entirely different story for the same period (blue columns represent trucks carrying food) in which is all but one week at the end of April the number of trucks carrying food was below the pre-war average:

      Contribution of different food sources [to the northern and southern regions] (Table 1 & Figure 4)<br /> The result and discussion devote substantial attention to the relative distribution of food between the northern and southern regions. The governates designated as North and South Gaza are not explicitly defined. The only explanation for how the author determined the distribution of food deliveries between Northern and southern-central Gaza is as follows:<br /> "Until Israel re-opened the northern Erez and Erez West crossings, trucks had to leave south-central Gaza to resupply the north. We reconstructed the number of these trucks over time based on published information and data shared by WFP. As no data on content were available, we simulated their caloric equivalent by repeatedly sampling from the empirical distribution of calories per truck obtained from the UNRWA dataset (see below and Figure S1, Annex). The remaining trucked food was attributed to the south-central region."

      The breakdown of that amount between northern and central-southern Gaza is based on an incomplete dataset (Commodities Received.xlsx) that appears to be missing the bulk of supplies by the private sector, appearing in the COGAT data ( https://gaza-aid-data.gov.il/main/) "https://gaza-aid-data.gov.il/main/)") , and which provided a significant share of supplies to the north. The dataset shows that during January and February 84 trucks were delivered to the north (according to the Logistics cluster). According to the same file, during March and April there only 20 private sector trucks delivered aid to the north. However, according to COGAT, deliveries to the north at that time were carried out mostly by the private sector, which are not fully covered by UN data. The flow of aid within Gaza and its regional distribution is difficult to ascertain. Media sources have provided conflicting reports from different sources. But they underscore the need to clarify precisely how the study assigned the regional food supply. For example, a story by the Associated Press from February 28 2024, reported that the UN had not been involved in aid deliveries to the North that month. According to one of COGAT's reports, during the first half of March they "facilitated over 150 aid trucks to the north" ( https://gaza-aid-data.gov.il/media/qtvbs5u0/humanitarian-situation-in-gaza-cogat-assessment-mar-15.pdf) "https://gaza-aid-data.gov.il/media/qtvbs5u0/humanitarian-situation-in-gaza-cogat-assessment-mar-15.pdf)") . In addition, COGAT claimed in a tweet from March 25 that UNRWA had not submitted a single request for delivering food to northern Gaza in six weeks ( https://x.com/cogatonline/status/1772316633605812511) "https://x.com/cogatonline/status/1772316633605812511)") . Thus, the methodology for determining the distribution of aid between northern and southern-central Gaza appears to be flawed since it almost entirely disregards aid deliveries by the private sector, which had a significant share of the total deliveries to the north during that period. Findings and conclusions that are contingent on this issue cannot be fully evaluated until this is corrected.

      Main findings

      The authors insinuate that the shortfall in the adequacy of food aid is solely due to intentional Israeli actions. For a subtle example of this the authors write that “Patterns in the diversity and caloric value of food trucked-in suggest that humanitarian actors may not have optimised the selection of what aid was allowed into Gaza.”. The food diversity findings suggest the humanitarian actors, who are responsible for deciding what is supplied to Gaza may not have optimized the selection of the aid. However, the use of the word “allowed” insinuates that the fault for this lies with Israel. The correct word should be “delivered”. Israel is responsible under international law for facilitating the entry of humanitarian aid. It is not responsible for selecting, procuring or delivering the aid. The fact that there was a considerable decline in food availability the first months of the war should not be surprising. Israel did not initiate the war, and should not be expected to have in place the logistics capacity for providing food to over 2 million conflict-affected people immediately after a strategic surprise attack. These major efforts, facilitated by the international community acting together with Israel, eventually yielded results as demonstrated by the study’s findings (eg. “a steep increase in food availability occurred from late April 2024, coinciding with the reopening of crossings into northern Gaza, and by June acute malnutrition prevalence appeared to be relatively low…”. [As noted above, “reopening” is a misleading term for the conversion of the Hamas-damaged Erez crossing from a pedestrian to a trucking terminal].

      Similarly, one might ask why the Hamas failed to prepare for the needs of the Gazan civilian population under its governance, while it demonstrably prepared meticulously for the attack that was intended to provoke retaliation.

      The authors seem intent to find Israel alone at fault, to encourage political pressure on Israel. They criticize “operations to deliver food via air or sea [as] cost-inefficient and a poor substitute for diplomatic pressure to merely reopen crossings”, stating in passing that “the 230M USD cost of the JLOTS operation [43] was higher than the entire humanitarian aid budget for the Central African Republic in 2024”. A back of the envelope calculation examining this assertion, and using WFP statements that their “emergency response [in Gaza] requires USD 740 million to provide support for up to 1.1 million people monthly” ( https://www.un.org/unispal/wp-content/uploads/2024/04/WFP-Palestine-Emergency-Response-External-Situation-Report-18-23-April-2024.pdf) "https://www.un.org/unispal/wp-content/uploads/2024/04/WFP-Palestine-Emergency-Response-External-Situation-Report-18-23-April-2024.pdf)") , shows that USD 740 per 1.1 persons monthly translates to 22.4 dollars per person per day. This means that the cost of the air-dropped food was only 29% higher than the delivery of land-based humanitarian food-aid. Thus, an equally plausible alternative interpretation of the resource expenditure might be that the air and sea operations, involving cooperation of USA, Jordanian, Israel and other Arab militaries to assist the Palestinian civilian population, could be considered a valuable attempt to circumvent the challenges to land-based humanitarian aid-operations during fierce fighting between Hamas and the IDF, as well as a means of exerting diplomatic pressure on the combatants. The policy implications and cost effectiveness of political pressure to increase food influx via land crossings are not obvious.

      Comparing the resources allocated by the international community to the Palestinian population versus the long list of other pressing humanitarian crises, out of proper concern for emergency-affected civilian populations, is indeed a vexed question. Clearly, a critical and balanced discussion of this issue is beyond the scope of this paper. However, if one insists on raising this important question, one might also question the efficiency of the billions of dollars donated to Gaza over the past decade by the international community, including from UNRWA, and how the funds, which were intended for civil and humanitarian development, were misappropriated by Hamas for a massive military buildup to the attack including the construction of hundreds of kilometers of military tunnels and the stockpiling tens of thousands of rockets and launchers, embedding them in their civilian population ( https://www.wsj.com/world/middle-east/hamas-gaza-humanitarian-aid-diverted-cf356c48; https://govextra.gov.il/unrwa/unrwa/#:~:text=Update%206%2F8%2F24%3A,massacre%20are%20credible%20and%20true; https://www.nytimes.com/2024/12/08/world/middleeast/hamas-unrwa-schools.html?unlocked_article_code=1.f04.lcW3.n2kj8akEfM-M&smid=nytcore-ios-share&referringSource=articleShare; https://www.atlanticcouncil.org/blogs/new-atlanticist/how-to-reform-unrwa-to-improve-palestinian-lives-and-israeli-security/) "https://www.atlanticcouncil.org/blogs/new-atlanticist/how-to-reform-unrwa-to-improve-palestinian-lives-and-israeli-security/)") .

      Limitations

      The authors acknowledge several of the more obvious limitations and assumptions described above. However, they minimize or arbitrarily dismiss these weaknesses and proceed to make tendentious interpretations in support of their preferred policy implications. For example, they write that they relied heavily on a single UNRWA dataset “which appears highly complete and well-curated” without explaining how they make that subjective and unsupported assertion. The authors are demonstrably aware of the controversy and limitations of the data, yet they feign ignorance and avoid placing the data in the context of the known controversy writing that the data “may be biased by systematic under- or over-reporting UNKOWN TO US”. This knowingly downplays and misrepresents the CERTAIN under-reporting of UNRWA trucking data which the official disclaimer states clearly on the online dashboard and in the dataset that they provide for review: “We [UNRWA] are unable to provide comprehensive monitoring of cargo for the following reasons: i) safety and security concerns, which continue to prevent UN staff from maintaining constant presence at Kerem Shalom, therefore severely impacting our ability to cross-reference UN cargo, and record data from INGO, Red Cross and commercial trucks, and ii) delays and/or denials in approvals for UN to retrieve, count and move UN humanitarian aid from Kerem Shalom to other parts of the Gaza Strip, which mean that we are unable to fully verify all trucks which have transited the land crossings. We will resume presentation of comprehensive data once the situation at the crossing allows.” Similarly, the acknowledgement of “considerable uncertainty about population denominators” does not logically lead to the conclusion that this would “…have only marginally affected our estimates”.

      Policy Implications

      The conclusion of the article makes politicized recommendations that are disconnected from the findings. The authors’ recommendation to “reinstate UNRWA’s role as an independent and experienced on-the-field monitor” is unsupported, and the summary dismissal and evaluation of COGAT data as “not of sufficient quality to guide decision-making”, reflects bias rather than a balanced analysis. Considerations relating to the role that international actors can and should play is determined by far more complex factors that are the partial shipping data analyzed here.

      The claim that Israel, “as the de facto occupying power”, did not ensure sufficient food availability to Gaza (while acknowledging the relatively short period of deficiency), vastly oversimplifies the complex dynamics of the conflict and the multifaceted factors affecting food availability. This claim appears intended to promote the use of the study as “evidence” supporting “forensic efforts” (in the courts) to prove allegations that “Israel deliberately has starved Gaza’s population”, presenting as fact a disputed interpretation of Israeli combat operations in Gaza as constituting occupation, and hence its obligations under international law, while ignoring weighty arguments to the contrary. This view also ignores corresponding obligations of Hamas as the governing power in Gaza, and the role of international humanitarian actors. The legal questions on this point are far beyond the scope of this review, but there is no basis in the data provided to make this claim – it is simply presented as an unsubstantiated assertion. In order to evaluate the morality, legitimacy or legality of the Israeli military strategy in response to the Hamas attacks and terror infrastructure, including its impact on food availability, it is necessary to examine and understand the strategy challenges in conditions of military asymmetry, the large-scale use of human shields to protect Hamas forces, and urban warfare as exist in Gaza. The authors of this article appear to be unaware of this central dimension in the issues they are claiming to address. Given the slanted narrative, the selective and biased use of data and their interpretation, and the far-reaching and unsupported conclusions, it is difficult to escape the impression that this study is aimed at providing a prosecution with ostensibly credible academic findings, rather than advancing open-ended research in support of humanitarian efforts.

      Timely and reliable data are crucial to address the critical needs of the war-affected civilian population of Gaza. There is no doubt that data “on the civilian impacts of the war in Gaza”, and “situational awareness on food security in Gaza” are “important to inform appropriate humanitarian response”. It is also undoubtedly true that “humanitarian actors should review whether there is adequate coordination and technical expertise in place to ensure that what food is allowed into Gaza is both calorically efficient and diverse enough to maintain the best-possible diet, especially for population groups most vulnerable to malnutrition”. How a retrospective simulation of the food supply informs “situational awareness” is less obvious. Slanted, simplistic and politicized framing of the findings that ignore complexity, place the onus on Israel alone, and overlook the role of Hamas, the agency of Palestinian civil society, and the responsibility and obligations of the international community, do not advance scholarly discourse, nor will it strengthen the cooperation that is urgently needed to strengthen humanitarian efforts to benefit the civilians of Gaza.

    1. On 2021-11-23 01:10:34, user Charles Warden wrote:

      Hi,

      Thank you very much for posting this preprint.

      I have a couple questions:

      1) Is it possible to add a bar for predictions made with clinical data alone (without genomic data) in Figure 3?

      2) Is it possible to give some sense of the number of samples / SNPs affected by each of the criteria in Supplemental Figure S9?

      Thanks again!

      Sincerely,<br /> Charles

    1. On 2021-05-01 23:02:46, user Nick Day wrote:

      The logistic fit for the B.1.1.7 lineage looks good. It is interesting to see that it works for such a range of (spatial, sampling, etc.) scales. It may also be of interest to see the logistic curve fits (for two individual mutations across all lineages) during 2020 for the initial spread phase of P681H and the saturation phase of D614G. The data for this is presented at https://www.biorxiv.org/con... - see also the comment there.

    1. On 2020-05-27 12:07:53, user disqus_BjRKMZenfK wrote:

      How many samples were excluded as their ct value was > 35, which could indicate low viral load, but not able to be sequenced? Also, the timing of sample collection before, during, or after the peak of the infection could influence these results.

    1. On 2020-04-15 19:07:06, user Gregory Armstong wrote:

      Thanks for contributing this. It's a very important topic. There are few well controlled studies of risk factors for COVID-19.

      My one comment--and I didn't read the entire manuscript: I'd strongly recommend removing vital signs and laboratory findings from the regression. Those are manifestations of severe disease, not risk factors for it. They're some of the main considerations in deciding whether to hospitalize and whether to admit to the ICU. They should correlate strongly with both, and including them in the model will severely dilute the impact of true risk factors and could completely hide them. They shouldn't be considered independent variables.

    1. On 2024-12-03 21:03:36, user xPeer wrote:

      Courtesy review from xPeerd.com

      This manuscript introduces DeepEnsembleEncodeNet (DEEN), an innovative polygenic risk score (PRS) model integrating autoencoders and fully connected neural networks (FCNNs) to address limitations of existing PRS methods. By disentangling dimensionality reduction and predictive modeling, DEEN enables the capture of both linear and non-linear SNP effects, improving prediction accuracy and risk stratification for binary (e.g., hypertension, type 2 diabetes) and continuous traits (e.g., BMI, cholesterol). Evaluation using UK Biobank and All of Us datasets highlights superior performance over established methods. While conceptually and methodologically compelling, areas such as interpretability, generalizability across diverse populations, and computational efficiency warrant further refinement.

      Major Revisions<br /> 1. Interpretability and Practicality<br /> Black-Box Concerns: The complexity of the DEEN model limits its interpretability compared to simpler PRS methods like Lasso or PRSice. While the manuscript acknowledges this limitation, incorporating efforts to visualize model predictions (e.g., feature importance maps or SNP clustering analysis) would enhance its usability (Section: Discussion, p.16).<br /> Clinical Translation: The manuscript emphasizes the potential of DEEN for clinical utility but lacks discussion on the challenges of implementing deep learning models in healthcare. Addressing regulatory barriers and clinician engagement would add value (Section: Discussion, p.17).<br /> 2. Population Generalizability<br /> Demographic Bias: Both datasets used (UK Biobank, All of Us) consist predominantly of European-ancestry individuals. This limits the model's applicability to global populations. Expanding the discussion on efforts to improve DEEN’s cross-ancestry generalizability is essential (Section: Results, p.11).<br /> Validation Across Diverse Cohorts: While DEEN is validated on two datasets, additional external validations across non-European populations would strengthen claims of generalizability and reliability.<br /> 3. Comparative Analyses<br /> Missing Baseline Methods: Although DEEN is compared with multiple PRS methods, inclusion of additional machine learning benchmarks (e.g., gradient boosting models, convolutional neural networks for SNP effects) would better contextualize DEEN’s advantages (Section: Results, p.8).<br /> Risk Stratification Assessment: The risk stratification results are promising but need more rigorous evaluation metrics beyond odds ratios, such as net reclassification improvement (NRI) or integrated discrimination improvement (IDI).<br /> 4. Computational Efficiency<br /> Resource Requirements: DEEN’s reliance on high-performance computing resources (e.g., GPU usage) is noted but not sufficiently quantified. Providing benchmarks of computational costs and runtime against alternative methods is crucial for practical implementation (Section: Methods, p.19).<br /> Optimization: While grid search was used for hyperparameter tuning, exploring automated optimization frameworks (e.g., Bayesian optimization) could reduce computational overhead.<br /> 5. Data Filtering and Variant Selection<br /> Potential Bias from Variant Filtering: The preselection of SNPs based on p-values may exclude rare variants or those with small effects. A sensitivity analysis on SNP filtering thresholds would clarify the robustness of DEEN’s predictive power (Section: Methods, p.20).<br /> Minor Revisions<br /> 1. Typos and Formatting<br /> Figure Legends: Some figures (e.g., Figure 5) lack clear explanations of axes and statistical methods.<br /> Grammar: Line 124: Replace "similarly drive CRC progression" with "similarly drive progression."<br /> 2. AI Content Analysis<br /> Estimated AI-Generated Content: ~20-25%.<br /> Implications: Repetitive phrasing in methodological descriptions and literature summaries suggests potential AI assistance. While the technical content appears valid, manual rephrasing can enhance originality and scientific depth.<br /> 3. Statistical Reporting<br /> Insufficient Confidence Intervals: Odds ratio enrichment results lack 95% confidence intervals in several places, undermining statistical rigor (Section: Results, p.9).<br /> Inconsistent Metric Definitions: Terms like “improved R²” and “higher AUC” are used loosely. Precise numerical values and effect size comparisons would improve clarity.<br /> 4. Terminology Consistency<br /> Key terms like "dimensionality reduction" and "risk stratification" should be consistently defined and applied across sections to avoid ambiguity.<br /> Recommendations<br /> Enhance Model Interpretability:

      Integrate explainability tools (e.g., SHAP values, visualization of autoencoder layers) to clarify how SNPs influence predictions.<br /> Discuss the potential for hybrid models balancing interpretability and performance.<br /> Address Demographic Bias:

      Validate DEEN using datasets from underrepresented populations (e.g., African, Asian ancestries).<br /> Incorporate transfer learning techniques to enhance generalizability.<br /> Benchmarking and Evaluation:

      Compare DEEN against additional advanced machine learning models for PRS.<br /> Introduce advanced evaluation metrics like NRI and IDI to strengthen claims.<br /> Refine Computational Analysis:

      Provide detailed resource utilization benchmarks.<br /> Explore alternative hyperparameter optimization methods to improve training efficiency.<br /> Expand Data Analysis:

      Perform a sensitivity analysis on variant filtering thresholds.<br /> Investigate the inclusion of rare variants to improve model robustness.

    1. On 2022-02-06 16:42:31, user scalp axos wrote:

      It shows a negative vaccine efficiency, you can't dismiss the same criteria used to evaluate vaccine efficiency (which is the number of positives) when it's negative but use it to prove the vaccine prevent infection when it's positive:

      "Vaccine effectiveness (VE) was estimated in a time-to-event analysis of Danish residents >=12 years comparing the rate of infections in unvaccinated and vaccinated individuals with a two-dose BNT162b2 or mRNA-1273 vaccination series."

      Long story short, it means exactly that: people who were vaccinated were more likely to be infected vs people who weren't. If it doesn't, then the study is pointless because it is literally how VE is assessed (infection rate in vaccinated vs infection rate in unvaccinated), besides, your "logic" can be used the other way around: having more infected people amongst the unvaccinated wouldn't mean that unvaccinated are more likely to be infected, it would just mean that "more people who were not vaccinated tested positive"...

    1. On 2021-04-09 15:15:15, user Martin Bleichner wrote:

      We read this preprint in our journal club and have collected some comments I would like to share. <br /> Overall, we liked the approach and the straightforward message of the paper. <br /> Comments regarding the paradigm<br /> • Do you control somehow for word length? In the given example, “swift” is shorter than “swrfeq”. <br /> • Are word combinations repeated? I.e., do participants see ‘swift horse’ as well as ‘swrfeg horse’? In that case, participants may remember that they saw a similar item before. Hence, memory could play a role<br /> Controls and Patients<br /> • The ACE-R scores overlap between the two groups (range controls 83 – 100, range MCIR (64-99). Isn’t it then surprising that the results in figure 8 show such a good separation?<br /> Signal Analysis<br /> • The ERP subtraction was only done for the cap. Based on those results, it was concluded that it does not make a difference, and hence this approach was not used for the cEEGrid data. Since the segmentation of the ERP components depends on the data quality that differs between the two devices, this transfer might not be valid.<br /> • It is stated that the lexical retrieval effect is absent in the MCI-group, but in figure 3, the alpha rebound, for example, seems to be present in both groups to some degree. Furthermore, in figure 4, the main difference between the conditions (bottom TRF) is between 600 and 800 msec), i.e., exactly before the alpha rebound kicks in (around 800 msec figure 3). <br /> Comparison Cap cEEGrid<br /> For Figures 7 and 8, individual electrodes were used. It would be interesting to know how variable that was across subjects and how often the different electrodes were chosen. Furthermore, given that the results of the individualized electrodes and standard electrodes are comparable, it would be interesting to see the spectra of all channels. <br /> • The electrodes used for referencing and re-referencing are not completely clear to us. Unfortunately, different people use different names for the electrodes A layout-plot of the cEEGrids with indications of gnd, ref, etc. would be helpful.

      Figures<br /> • The figures are difficult to compare to each other (different units [% signal change for the cap, but t-values for the cEEGrid] in same-colored color bar, different time axis, etc.) E.g., in figure 6 Top TRF x-axis is from 0 to 1.4, Bottom TRFs from 0 to 1. Figures are differently scaled along the x-axis.<br /> • Please indicate in the figures the important time points (word off-set, onset, etc.)<br /> • Explain the ROC-curve in detail. What data goes in exactly? Should be added to the method section.

      On page 20 the is a space missing between “The” and “current”.

    1. On 2021-09-30 02:46:32, user Fiona Weir wrote:

      70% of people in Dane County are vaccinated [6-your source]. If representative, you would expect a similar profile in your study; however only 38% of your cohort is vaccinated. This raises crucial questions about selection/inclusion... Was self-reporting reliable? Were cases excluded when vaccination status was not self-reported? Were unvaccinated people much more likely to test? Were vaccinated people likely to test only if they were actually ill, and therefore likely to have a higher virus load in any case? These issues plus the low cohort size may make your findings unreliable.

    2. On 2021-08-21 22:44:12, user Ands Hofs wrote:

      Can we please introduce more calibrated PCR that measures the mucosa DNA count and gives out<br /> Viral Load = viral units / mucosa DNA units?<br /> Only then the force and technique of swabbing is not changing the resulting viral load wildly.

      Even RTLAMP.org is able to do this, open science test, might be liked by some in the comments here, done in a parallel test, and Boston Children's Hospital did a very good job showing children sometimes have 10x higher calibrated viral loads, which has to be treated early with determination in nasopharynx and mouth, like with xylitol + Grape Seed Extract nasal spray, puff and breathe in a bit to protect vocal chords, upper trachea, whole nasopharynx. Vulnerables: add azelastine as pre-spray dito. Report on CARVIN (11.8.2021) shows excellent efficacy.

      If you want "life" reproduction rate, you have to train a dog, see scent dog identification of samples .. covid. Work of TiHo, small animals university Hannover. Built a training device they call scent learning box, like a game for the dog. In one week it is on 95% congruency of PCR, but better: 4 days before infectiousness, and quasi live. It doesn't over-diagnose and does diagnose viral replication. <br /> There is a group that built a speech interface for a dog. This would enable to train the dog on many illnesses, differentiate flu from covid, and even predict severe case, as it can smell susceptibility to autoantibodies (or in another picture: prevalence of MCAS, see Prof. Afrin on Covid. Having deep implications on therapy and prevention. The tricky part is to diagnose MCAS with its 200 mostly congruent symptoms to Post-Covid. So obviously related except scarred tissue of course.)

      Even better: build an electronic nose as sensitive as a dog's nose on some marker molecules for covid and a tensor flow neural network in a mobile phone to read it out. The do progress with mice conk cell detecting proteins they use as film on a chip based electronic nose.

    1. On 2021-03-02 21:59:38, user cybericius wrote:

      For a year already I have dry nose and every morning dry flat parts with dry blood come out when blowing. Never had this before, and very hard to breath through nose before blowing it out. The mucus during the day feels more stickier than ever before.<br /> Inside the tip of the nose I feel a sensitive area. Sometimes I smell iron (blood?). Humidifier doesn't help, I keep the air on 55%. Would be great to know how to find a way back to have normal nose state again.

    1. On 2020-04-03 02:08:32, user Shawn wrote:

      There seems to be no discussion in this paper of the fact that the exponential spread could be accounted for by close in-person contact. One could reason that a virus can spread quickly in a susceptible population regardless of weather if there is a short distance between an infected and susceptible individual. A viral particle won't need to spend much time in the environment in this particular scenario and likely can avoid any negative impacts due to ambient temperature/humidity.

      The authors should have refrained from making such a definitive conclusion about SARS-CoV-2 in any respect.

    1. On 2022-01-13 14:39:26, user Peter wrote:

      I thought this was a fascinating article. I tweeted.

      I thought that the conclusion went further than the evidence.

      You state that "…have<br /> been training dogs to detect Sars-CoV-2 virus in human sweat, by detecting volatile organic<br /> compounds (VOCs) in infected patients [1]. The VOCs exact nature is still under identification<br /> [2]."

      In other words, you do not suggest that the dogs detect the virus per se; just that whatever they smell allows them to distinguish people with Covid-19 from people without the infection.

      This study shows that they can detect the same smell in at least some people with Long Covid.

      But you then conclude that "This study suggests the persistence of a viral infection in some Long COVID patients".

      Given that there is nothing to suggest that the dogs can smell the virus, per se, the fact that they can detect the same smell in people with Long Covid certainly does not suggest the persistence of a viral infection.

      There may be many hypotheses - probably better hypotheses - to explain the finding; but the conclusion is clearly unwarranted.

      I do not know if you saw the tweet https://twitter.com/Evidenc... from @EvidenceMatters in reply to my tweets. It reads: "Beyond the information that none of the LC people had been admitted to ICU, it would have been helpful to know how many had been hospitalised and some info. about their vaccine history/plausible variant for infection etc.<br /> I was unclear on how many sniff sessions there had been."

      I note that the paper has not yet been peer reviewed. Perhaps you will address some of these points before it is published.

    2. On 2022-01-13 08:19:03, user PierreLouis wrote:

      Nice study. I disagree with your conclusion, though. We can’t deduce from the data that dogs sensed persistance of viral infection. They may sense the smell associated with the so-called long Covid syndrome. Which may not related to viral persistance but to post-infection metabolic chronic disturbance. Interesting controls would be patients with non infection-related depression and patients with chronic fatigue after another infection (cured bacterial sepsis for example). Anyway, a very original and provocative study!

    1. On 2020-05-22 18:36:01, user Frank Taeger wrote:

      Why would you basically choose the LOWEST of all possivle IFRs from every single study. Even the Gangelt study. The authors of the study itself have already done most of the corrections for you. If you actually did the corrections for external validation of specificity, the Gangelt study for example ranks MUCH higher, almost double the value you have counted there. Not even the authors use such a low estimate of IFR. And later on, another person in that area died, so that is not even correct anymore.

    1. On 2019-07-16 13:28:54, user Guyguy wrote:

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

      ITURI.

      NEWS:

      High-Level Meeting on Ebola in Geneva

      On Monday, July 15, 2019, the Minister of Health, Dr. Oly Ilunga Kalenga, participated in the high-level meeting in Geneva to mobilize the international community to end the Ebola epidemic in the Democratic Republic of the Congo. His statement is available: Ladies and gentlemen.

      Since August 1, 2018, the Democratic Republic of the Congo is facing the Ebola epidemic<br /> the most complex of its history and the history of public health.<br /> As you followed yesterday, July 14, a positive case from Butembo was declared in the city of Goma. This morning, the positive case, quickly identified and isolated, was<br /> repatriated to Butembo. Vaccination has been launched for all contacts. Since the beginning of this epidemic, we prepared with the WHO for the possibility of positive cases in Goma.<br /> The situation is therefore under control and is being managed, as we did a few weeks with the positive case reported in Uganda. By the way, as a reminder, Goma is not the first provincial capital to report a positive case. This was the case in Bunia there<br /> a few weeks and in Mbandaka during the ninth epidemic of Ebola Virus Disease<br /> occurring in the province of Ecuador from May 7 to July 24, 2018.<br /> The risk factors of the current epidemic remain:<br /> - The density of the population;<br /> - the high mobility of the population;<br /> - The geographical area concerned covering 23 health zones spread over 2 provinces;<br /> - Part of the response is deployed in areas of military operation where armed groups and community militias;<br /> - The instrumentalisation of the epidemic by certain political actors during the period<br /> election.<br /> The tenth Ebola outbreak is not a humanitarian crisis. It's a health crisis public service, which intervenes in an environment characterized by development and shortcomings of the health system. This crisis requires a technical public health response to break the chain of<br /> transmission of the virus by relying on the actors of the health system and its partners<br /> traditional.<br /> Several pillars are thus implemented to break the chain of transmission, whose<br /> vaccination. The Ministry of Health has invited the last 28 and 29 June in Kinshasa, the<br /> producers of the four most advanced vaccines to fight Ebola, as well as the experts<br /> national and international for a meeting of scientific exchanges on vaccination in<br /> part of the ongoing epidemic. It emerged from these exchanges that the vaccine produced by the Merck, currently used in this outbreak, is the only one that has demonstrated its<br /> efficacy for reactive vaccination in the case of the current response. The good news<br /> is that there are enough doses available of this vaccine. To avoid confusion and<br /> amalgams in the difficult context of this epidemic, the Ministry of Health decided that no other vaccine trial would be implemented in the DRC until the tenth epidemic<br /> will be in progress.<br /> To date, thanks to the commitment of all, sufficient funds have been mobilized for<br /> previous response plans. On behalf of the Congolese Government, I express my gratitude to all donors.<br /> In developing the third strategic response plan (SRP3), covering the period of from February to July 2019, a special effort was made to put in place information for monitoring activities and expenditures to increase accountability operational than the financial accountability of all actors.<br /> The process of developing the fourth strategic response plan (SRP4), which will cover the<br /> period from July to December 2019, ended this Friday, July 12, 2019 in Goma. The<br /> The process was participatory and inclusive, and took into account lessons learned on an ongoing basis.<br /> The methodology for budgeting - bottom up - is part of the unit costs and<br /> the volume of the different activities to be implemented in each zone of<br /> health; these were then aggregated by sub-coordination.<br /> The Government is grateful for the contribution of our various partners as well as<br /> donors. However, this support must be in the respect of the Government, and in<br /> partnership with institutions and not in parallel. Only the anchoring of the riposte in the<br /> health system and the strengthening of the actors of the Ministry of Health will<br /> to ensure the sustainability of all achievements of the response. All sectoral support plans for the response must be developed in the same spirit, in consultation with the ministries<br /> sector. Public health actors want to make SRP4 a "final push". To get there, we demand from all actors of discipline and accountability. In each pillar, in each sub-coordination, the Ministry of Health and the co-leaders accredit implementation agencies on the basis of five criteria to ensure accountability:<br /> - Have a demonstrated operational capacity with regard to the number and<br /> the expertise of human resources (not agencies in "learning curve", recruiting<br /> on Linkedin for North Kivu);<br /> - Rationalize geographical deployment and ensure an effective presence on the<br /> field (not just attending meetings);<br /> - Commit to implementing the activities according to the validated protocols for the response;<br /> - Make a commitment to transmit the data to the General Coordination of the response, in<br /> respecting the reporting tools that allow the monitoring of the indicators of<br /> performance and produce dashboards;<br /> - Commit to adopting the scales and the Manual of Procedures for the Management of<br /> human resources developed by the Ministry of Health and the World Bank, which<br /> that no other vaccine trial would be implemented in the DRC until the tenth epidemic<br /> will be in progress.<br /> To date, thanks to the commitment of all, sufficient funds have been mobilized for<br /> previous response plans. On behalf of the Congolese Government, I express my gratitude to all donors.<br /> In developing the third strategic response plan (SRP3), covering the period of<br /> from February to July 2019, a special effort was made to put in place information for monitoring activities and expenditures to increase accountability operational than the financial accountability of all actors.<br /> The process of developing the fourth strategic response plan (SRP4), which will cover the<br /> period from July to December 2019, ended this Friday, July 12, 2019 in Goma. The process was participatory and inclusive, and took into account lessons learned on an ongoing basis.<br /> The methodology for budgeting - bottom up - is part of the unit costs and the volume of the different activities to be implemented in each zone of health; these were then aggregated by sub-coordination. The Government is grateful for the contribution of our various partners as well as donors. However, this support must be in the respect of the Government, and in<br /> partnership with institutions and not in parallel. Only the anchoring of the riposte in the<br /> health system and the strengthening of the actors of the Ministry of Health will<br /> to ensure the sustainability of all achievements of the response. All sectoral support plans for the response must be developed in the same spirit, in consultation with the ministry<br /> sector. Public health actors want to make SRP4 a "final push". To get there, we<br /> demand from all actors of discipline and accountability.<br /> In each pillar, in each sub-coordination, the Ministry of Health and the co-leaders<br /> accredit implementation agencies on the basis of five criteria to ensure<br /> accountability:<br /> - Have a demonstrated operational capacity with regard to the number and<br /> the expertise of human resources (not agencies in "learning curve", recruiting<br /> on Linkedin for North Kivu);<br /> - Rationalize geographical deployment and ensure an effective presence on the<br /> field (not just attending meetings);<br /> - Commit to implementing the activities according to the validated protocols for the response;<br /> - Make a commitment to transmit the data to the General Coordination of the response, in<br /> respecting the reporting tools that allow the monitoring of the indicators of<br /> performance and produce dashboards;<br /> - Commit to adopting the scales and the Manual of Procedures for the Management of<br /> prepared by the Ministry of Health and the World Bank, whom I wish to thank in particular for its unfailing support for the Government since the beginning of this epidemic.<br /> Only discipline and accountability will allow us to put an end to this epidemic, which has<br /> that too long.<br /> Now is the time to think about the post-Ebola era and start developing with others<br /> sectors, ambitious development plans that alone will be able to resolve fundamental problems of the population.<br /> Thank you.<br /> Source: Ministry of Health press team on the state of the response to the Ebola epidemic in the Democratic Republic of Congo

    1. On 2021-06-12 13:48:28, user Igor M. wrote:

      What was the rationale for using different metrics in figure 2? One talks about "% inhibition" and another about "optical density"- comparing apples and oranges? Secondly, I could not for the life of me find the justification for the seemingly arbitrary definition of "positive" and "negative" thresholds.

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

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

    1. On 2021-07-30 16:44:39, 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.

      For this paper, there's also a mistake in the flow diagram in figure 1 - it appears as if papers have been excluded on the grounds of "non Spain" when that should be "non Africa".

    1. On 2020-09-26 21:24:12, user Keith Robinson wrote:

      If one point could be made clear to me regarding Table 1, where a sensitivity of 84.7% and Positive Predictive Value of 89.7% are given: These are compared against the gold-standard qRT-PCR, right?

      How would these values change if we were to consider only individuals who carried a contagious level of the virus (viral load of 1 million/mL). As a contagiousness test, wouldn't the sensitivity and PPV get even better than they already are? Close to 99%?

    1. On 2020-08-19 17:04:00, user Pat Tokarz wrote:

      Thank you for this important information in such a timely fashion. It will be interesting to compare your experience with other institutions<br /> over time.

    1. On 2022-01-04 14:03:44, user 101nemesis wrote:

      Again, you're equating negative to something without any explanation solely to push a narrative. <br /> Vaccine effectiveness is not generally ONLY about chances of infection but also hospitalization and death. The study needs to clarify and explain more.

      And negative VE cannot imply increased chance of infection as that's not how basic science works - which is probably why this study didn't clarify it more (even though they should have).

    1. On 2022-01-28 20:33:24, user cindy wrote:

      How was the control group assessed/reassessed? It may be beneficial to make it clearer that the control group is being reassessed?

    1. On 2020-04-22 12:31:02, user rupesh chaturvedi wrote:

      Here is preprint.

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

      Fan Wu, Aojie Wang, Mei Liu, Qimin Wang, Jun Chen, Shuai Xia, Yun Ling, Yuling Zhang, Jingna Xun, Lu Lu, Shibo Jiang, Hongzhou Lu, Yumei Wen, Jinghe Huang

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

    1. On 2025-01-21 00:01:42, user Alan Olan wrote:

      The article "Discovery of Breast Cancer and Autism Causes. Method of combining multiple researches to find non-infectious disease causes” has been published in the Journal Of Nursing and Healthcare ( 2024, volume 9, issue 3 ) and available at the link below:<br /> https://www.opastpublishers.com/peer-review/discovery-of-breast-cancer-and-autism-causesbrrnmethod-of-combining-multiple-researches-to-determine-noninfectious-disea-7819.html

    1. On 2021-05-24 16:53:32, user Gustavo Bellini wrote:

      Congratulations on the work! It would be interesting to analyze the action of vitamin D in the MHC complex, MICA / MICB.

      • A subgroup of lupus patients with nephritis, innate T cell activation and low vitamin D is identified by the enhancement of circulating MHC class I-related chain A<br /> https://doi.org/10.1111/cei...

      "Indeed, immune cells significantly up-regulate vitamin D receptor (VDR) transcription upon activation and proliferation (reviewed in [28]). In turn, through the binding of VDR, vitamin D induces the expression of anti-proliferative/pro-apoptotic molecules, thereby evoking immune tolerance 29, 30. Interestingly, recent data showed that MICA stands as a VDR-sensitive molecule, through which vitamin D renders tumour cells susceptible to NK cytotoxicity 31. According to this view, in our patients the gene expression of MICA in T cells was not associated with the up-regulation of TLR or ISG, as could have been expected, but paralleled levels of vitamin D instead. All these observations suggest that vitamin D could help to restore homeostasis of the immune system during flares, and that its deprivation may jeopardize MICA-dependent cell growth control."

      In addition, the inverse relationship between circulating sMICA and vitamin D found in our cohort suggests that the vitamin could prevent MICA shedding. Alternatively, sMICA impairment of NK functions could promote the uncontrolled proliferation of immune cells which, in turn, would facilitate the depletion of vitamin D.

      In summary, we propose a particular disease pheno-type characterized by the disruption of MICA-dependent cytotoxicity in patients with innate activation of T cells and possibly facilitated by low vitamin D levels."

      "Basically all cellular components of PBMCs belong to the innate and adaptive immune system. Therefore, it is not surprising that the immunologically most important region of the human genome, the HLA cluster, also highlights as a “hotspot” in the epigenome of PBMCs.<br /> However, it is remarkable that the HLA cluster is also a focused region of the vitamin D responsiveness of the epigenome. This observation provides a strong link to the impact of vitamin D on the control of theimmune system.<br /> In conclusion, in this proof-of-principle study we demonstrated that under in vivo conditions a rather minor rise in 25(OH)D3 serum levels results in significant changes at hundreds of sites within the epigenome of human leukocytes."

      The study below has shown evidence that the vitamin D endocrine system is dysregulated in sars-cov-2 infection.

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

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

    1. On 2021-07-15 21:52:38, user Brian Mowrey wrote:

      Results for the not-previously-infected group are barely presented/summarized. Without a calendar of absolute case counts, it is very difficult to get an idea of the real infection rate. I gave it a shot, using the relative plot in Figure 3. More at blog link.

      Not previously PCR-confirmed-infected infection rate: 2,154 / 49,652 = 4.3%<br /> -Completely Vaccinated infection rate: 15 / 28836 = 0.05%<br /> -Unvaccinated / Incompletely Vaccinated infection rate: 2,139 / 49,652 = 4.3%<br /> -Estimated Day 0 - 80 U/IV infection rate in 150-day units: (1620/49652)(15/8) = 6.1%<br /> -Estimated Day 80 - 150 U/IV infection rate in 150-day units: (529/21,332)(15/7) = 5.3%<br /> -Estimated Day 0 - 150 U/IV real infection rate (1620/49652) + (529/21,332) = 5.7%<br /> https://unglossed.substack....

    1. On 2021-08-07 18:55:51, user Ted Libson wrote:

      Here's an idea. COVID is been going around the world since November 2019. Coming up on two years ago.

      By now every medical person on the planet could have conducted their own double-blind, random ivermectin study . Twice.

      How come we're not reading through thousands of double-blind, random ivermectin studies right now?

    2. On 2021-08-12 10:05:30, user Ken Sprenger wrote:

      There are a number of concerns with the methodology and consistency in this study:<br /> 1. There is inconsistency in the description of the population of patients to be enrolled. The study registered on ClinicalTrials.gov (NCT 044297411) indicates that the study would include patients with mild to moderate COVID-19, whereas the title of the study published on medRxiv indicates that patients would have mild COVID-19. Then under Study Design in Methods in the publication, it indicates that the study would include mild to moderate COVID-19 patients. Then under Study Population in the publication it includes “asymptomatic cases”. In Table 1 All patients (N=89) and Symptomatic =72, therefore 17 (19%) of patients were asymptomatic. It would appear, therefore, that the definition of the study population had been substantially amended to include asymptomatic patients. There are a number of considerations:<br /> a. This was therefore no longer a study of ivermectin in patients with mild to moderate or even mild COVID-19, as stated in the publication and elsewhere.<br /> b. It would be important to know when the decision was made to enrol the asymptomatic patients and the reasons for this change.

      1. Under Intervention in the Methods section of the publication, the authors say “Unexpectedly some patients who were isolated in the hotels as verified positive patients were found to be borderline or negative upon our RT-PCR test” and were withdrawn from the study. Figure 1 indicates that 7 patients assigned to the ivermectin arm and 14 patients assigned to the placebo arm had Ct values >35 in the “two first tests”. <br /> a. This means that 18% of patients were withdrawn after the start of the study as they had all been enrolled and randomized. <br /> b. The Ct values given in Figure 1 are all >35, and so it is difficult to understand why the text in the publication says “borderline or negative”. What did borderline mean in regard to Ct values? <br /> c. The authors state under Intervention in Methods that “… all RT-PCR tests, including verification that patients were positive on day zero, were conducted by the same lab, at the Israel Central Virology Laboratory of the Ministry Of Health (located at Sheba Medical Centre).”<br /> d. Withdrawing 18% of patients who initially qualified for the study (Ct confirmed by Ministry of Health laboratory) because they had reduced viral shedding (even if negative or approaching negative) in subsequent RT-PCR tests when reduction of viral shedding is the endpoint of the study, is problematic. Generally once patients are enrolled in a study they should not be withdrawn by the investigator except for safety reasons, or if the participant withdraws consent. An intention to treat analysis including these patients should have been performed.

      2. There is a further change to the protocol which defines the time from symptom onset to start of medication. Initially start of study drug dosing appears to have been within 3 days of symptom onset, but then because of “delay in getting results in the community” of the RT-PCR this time was increased to 7 days from symptom onset. <br /> a. There is no indication of when this amendment was introduced, but it appears to be after the start of the study, in which case some patient’s day 6 (3 days from symptom onset + 3 days of study drug), will be different to others which will be 7 days from symptoms + 3 days of study drug. <br /> b. As it is possible that the viral load will be a little lower in patients on day 7 compared to day 3 after symptom onset, and the patients who started treatment on day 7 might reach Ct >30 at the end of 3 days of treatment sooner than patients who started treatment on day 3. <br /> c. Measuring the endpoint Ct (which will be changing with time, unrelated to study drug) at different intervals from baseline is potentially introducing a bias.

      3. Medication is described differently in 3 places:<br /> a. Abstract in the publication: 0.2 mg/kg x 3 days.<br /> b. Randomisation section in Methods in the publication: in patients 40-69kg, 4 tablets (=12 mg daily) x 3 days and in patients >= 70 kg, 5 tablets (=15 mg daily) x 3 days.<br /> c. ClinicalTrials.com description: 3mg capsules, 15-20mg/day x 3 days.<br /> These three statements are all different doses and some are described as capsules, others as tablets. Consistency and the correct description of study medication is critical in a study which tests a drug against a placebo.

      4. Primary outcome. Under Outcomes in the publication it states “The primary endpoint was viral clearance following a diagnostic swab taken on the sixth day (third day after termination of treatment), in the intervention group compared to placebo.” A negative swab was defined as RT-PCR Ct >30. The authors point out that the standard for a negative swab in Israel is a Ct >40 and, although they don’t mention this, the manufacturer of the RT-PCR kit used in the study (Seegene Allplex CoV19) recommends a cut-off Ct >40 in their manual. Despite these exiting standards they made a decision to use a Ct >30 because for a Ct >40 “reaching this level may take a few weeks, and there is significant evidence that a non-infectious state is usually achieved at Ct level >30”. <br /> a. It seems inappropriate in a study such as this, to change a commonly accepted standard (Ct >40) in Israel to save a “few weeks” of time. <br /> b. The point at which the decision was made to use the Ct >30 as negative is not declared and one would be concerned if it was taken after the start of the study and particularly if it was after unblinding of the study!

      Conclusions:<br /> 1. There are numerous deviations from the ClinicalTrials.Gov description (amended version June 14, 2020) including: patient inclusion criteria, participant eligibility period post exposure (maximum 72 hours), study medication description, another 2 outcome measures which were not reported. Many deviations such as these raise concerns about the thoroughness with which the study was conducted and reported.<br /> 2. This was not a study of patients with mild to moderate COVID-19 as indicated in the publication title (or even with just mild COVID-19) as nearly 1 in 5 of randomized patients were asymptomatic. <br /> 3. A large number of patients (18%) were withdrawn from the study by the investigator as their RT-PCRs had Ct values >35) on day 2 and 4, after an initial positive. This is highly unusual and could have biased the study. An intention to treat analysis should have been performed. <br /> 4. The definition of a negative swab, which was really the endpoint, appears to have been made arbitrarily, as it did not align with Israel’s standards and the kit manufacturer’s manual, and there is no clarity as to when this decision was made. <br /> 5. A study amendment to the protocol which defined the time from symptom onset to start of study drug dosing was changed from 3 to 7 days. This could have biased the study.

      It might be true that Ivermectin does reduce viral shedding time in mild to moderate COVID-19. However this study is not rigorous enough, includes amendments which could have introduced bias, and has methodological issues. In my opinion it should not be accepted as good evidence that ivermectin reduces viral loads and could reduce isolation time in patients with COVID-19.

    1. On 2021-12-25 21:19:30, user Jori Lahdenperä wrote:

      Hello Jeff. I'm not knowledgeable but wish to be. Could you please tell me why a Negative VE would not be possible?

    1. On 2020-05-21 01:11:37, user Brian Richard Allen wrote:

      Be interesting to see how New Zealand:- whose authoritarian government has effectively prevented its subjects from acquiring herd immunity;- will fare when its borders are opened and tourists -- and the virus -- flow in.

    1. On 2021-08-22 19:34:47, user ingokeck wrote:

      There is another issue with the article. You do not describe the data collection for the control group. Has this been done with the same preprocessing, using the same PCR arrays, i.e. are the values that the RT-PCR generates comparable even though there is one year difference in the sampling? Did you use an internal control for human DNA so you know that the sample collection was the same every time to get normalized RNA loads independent of the sampling procedure?

      Even if the value generation is comparable, why do you think you can compare the Ct values from the D614G linage to the delta linage, given that it seems delta is more infectious than previous variants?

    1. On 2021-04-26 18:39:17, user William Alexander wrote:

      Question: in Figure 4B, a vaccination rate of 5000 per day is purported to reduce daily deaths and total cumulative infections over rates of 8000 and 12000. Why is your model predicting this non-intuitive result?

    1. On 2022-03-21 03:28:16, user Jameson wrote:

      The results section says it was NOT detectable after 12 days, the image seems to show it was not detected after 6 days, but the abstract says it WAS detected between 12-14 days. The image of this part of the data just has some ascii * characters indicating where the protein is absent but should have been observed. Could the authors clarify this?

    1. On 2021-01-15 14:45:01, user mary wrote:

      It is proven that links of interest have a massive influence on the results of such studies.<br /> Please take the prevailing legislation into account and list any link of interests of the persons involved in this study. Thank you.