On 2020-05-05 19:12:27, user Nancy Lapid wrote:
This is not the first case of placental SARS-CoV-2 infection. An earlier case was reported in JAMA April 30. "This case of miscarriage during the second trimester of pregnancy in a woman with COVID-19 appears related to placental infection with SARS-CoV-2, supported by virological findings in the placenta." https://jamanetwork.com/jou...
On 2020-05-07 13:34:42, user Heather Lipkind wrote:
Hoping this sparks more research. We have localized it within the placenta to the syncytiotrophoblast. Much to learn about SARS-CoV-2.
On 2020-05-05 21:26:27, user AnneG wrote:
That is fantastic! A game changer that explains why kids have such low occurrence!
On 2020-05-07 10:51:23, user Concerned Citizen wrote:
How is this different or improve on a paper that came out earlier almost a month ago and was already published in a peer-reviewed journal (strangely also does not seem to have cited that paper): https://www.medrxiv.org/con...
On 2020-05-07 12:18:58, user Jean-Baptiste Hazo wrote:
Thank you! Have you been adjusting for smoking status?
On 2020-05-07 14:01:03, user Dr Gareth Davies (Gruff) wrote:
Please note: the current version on medRxiv is an intial draft. A newer draft is being submitted soon with some important improvements and clarifications so we request everyone to please hold off on critiquing until the final draft is preprint submission is approved so that we don't waste time responding to issues that have already been addressed since draft 1.0. Many thanks!
On 2020-05-09 21:31:00, user Gennadi Glinsky wrote:
In agreement with this study, recent genomics-guided tracing of the SARS-CoV-2 targets in human cells identified Vitamin D as one of the top 3 potential COVID-19 mitigation agents <br /> https://doi.org/10.26434/ch...
On 2020-05-13 10:37:19, user Keith baker wrote:
PCOS females in ageing would be a interesting sub group. The genetics of AR and ACE2 play a role in their conditions when excess testosterone, gives rise to risk factors DBII, obesity and specifically male like adipose patterns, on torso and heart.
On 2020-05-17 19:04:29, user Shreyans Pagariya wrote:
For more detailed predictions on when COVID-19 could end in each state of India using the same model described in the article, take a look at https://covid19quarantine.i...
On 2020-05-18 15:43:12, user Mandy Peffers wrote:
Data will be available on Array Express E-MTAB-9106 at a future date.
On 2020-04-03 21:10:45, user Marconi Neves wrote:
Good article. We need to know how to test the quality of masks and other personal protective equipament.
On 2020-06-25 22:40:27, user Greg Green wrote:
Mr. Cohen,
Great read. to be clear, what is your best estimate, in terms of percentage, of the number of false positives for current mass testing?
On 2020-06-26 22:11:48, user Hilda Bastian wrote:
It's excellent that this trial was done, but the preprint is overly positive: given it's not clear that anyone either working in, or exercising in the gym, was infected, it's not possible to know if the hygiene and social distancing measures worked.
There have been clusters of outbreaks related to gyms (for example in Japan and South Korea), and this needs to be discussed. Given that infected gym employees have been shown to have been the source of clusters, it's problematic that all employees weren't tested and considered more here.
This trial report is missing key methodological information, such as the method of randomization. At one point, the authors refer to the trial's protocol, but do not provide a reference for it. (That level of detail on methodological issues isn't included in the ClinicalTrials.gov entry for the trial.)
I think it's unfortunate that this was a non-inferiority trial, given the known risk of gym clusters. The bar was set too low for this trial. There was too much missing data on testing - nearly 20% of participants and nearly 10% of employees. The authors argue that disease is more critical than infection, but the risk of seeding clusters is a critical concern in gym re-opening.
On 2020-06-28 05:19:24, user David Perkins wrote:
This study is so flawed that it should be immediately withdrawn, and the study designers reeducated on how to run a study. The flaw is that it doesn't test for the following: "If workers or users at a gym have covid-19, can procedures be put in place at the gym to greatly reduce (or even eliminate) the spread of the disease to other workers or users at the gym?" (Said another way "Is is safe to go to a gym and work out?") To run such a study without the consent of the workers or users would be unethical (or most likely, illegal). Instead, a study was set up to see who knows what? Was it that the equipment or the building doesn't spread the disease? I am completely shocked that this study was carried out and that it had coverage in the NYTimes and other national publications. Because using people that are carriers of Covid-19 is unethical, a better experiment would be to use a non-lethal disease such as the common cold (or the flu) and try to determine which procedures at gyms minimizes its transmission.<br /> Again, this study did not determine if it was safe to use a gym. It showed nothing!
On 2020-06-28 02:19:40, user LB wrote:
I appreciate the difficult circumstances under which this study was conducted, but would like some clarification, because there are some discrepancies in the data. The text states that "All patients who needed supplemental oxygen therapy in the control group also required further ICU support." However, the table shows only 8 of the 16 requiring ICU support. This section, "Among 9 patients given DMB within the first week of onset of symptoms, only one patient required oxygen therapy. This patient was one of the two cases which deteriorated within 24 hours of DMB initiation." seems to indicate that two patients in the DMB group required ICU care, but only one is listed in the table.
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.
On 2020-06-29 15:58:18, user JS wrote:
This preprint has now been published as:<br /> Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome. Science Immunology 26 Jun 2020: Vol. 5, Issue 48, eabd2071. doi.org/10.1126/sciimmunol.abd2071
On 2020-04-11 01:07:55, user Moi wrote:
Some stats about the situation in Germany and Chile (JHU numbers used):<br /> Delay \Psi around 13 (DE) and 14 (CL), resp, with quite small SD.<br /> Death rate \theta around 0,05 for both countries, constant since several weeks, far lower than your 14%
These are of course only the visible cases, not quite your concern.
Anyway, the numbers are different for different countries. Why?
And not speaking about asians, who seem to have basically overcome it.
On 2020-07-02 17:21:31, user Felice Bruno wrote:
what is the dosing protocol for Ivermectin used in the study ?
On 2020-07-04 10:45:14, user MathaHi wrote:
Confusing Terminology: on page 12: "We believe that the analysis in our study shows conclusively that COVID-19 epidemics grow according to the Gompertz Function and not the Sigmoid Function". I think the authors intended to set off the Gompertz Functions against Logistic Functions that are used when assuming that the rate of infection remains proportional to the product of the already infected population and the amount of still susceptible individuals. Logistic Functions as well as Gompertz Functions are both considered as special cases of Sigmoid Functions. Same issue at page 21 and 22.
Furthermore, assuming that the rate of infection is proportional to the currently infectious population instead of the already infected population might partially explain why it is decreasing faster than with the logistic SI model, as infected individuals become Resistant. For those viral epidemiologists that require more explanation: heterogeneity in both individual and collective susceptibility does the rest.
On 2020-04-15 11:57:13, user ?????? ??????? wrote:
! conflicting studies : https://academic.oup.com/jt...
On 2020-04-12 04:43:17, user Bárbara Souto wrote:
It seems that the authors want to reinforce an "almost-effect" of chloroquine. They wrote that matched 25 pairs of patients from Changsa, the only place using chloroquine, to compare the 25 individuals who have taken chloroquine, as a kind of case-control nested study. They said they found a difference of 12% and none patient in chlorquine group got worse (with a almost significance. p = 0.074). Well, two groups of 25 with zero outcome in one of them and 12% difference means that only three people in the comparison group got worse. A very small number to consider. But what about the p-value? 0.074 is a very promising p-value, suggesting that the non-significance was just a type II error. We should believe that this p-value is a probability derived from a Fisher exact test. But not. The p-value of a Fisher test from these numbers is 0.234. The 0.074 p-value came from a chi-square calculation. The authors have forgotten that the chi-squared test must not be used when there is a zero in one of the cells. I hope that the reviewers realize this shameful mistake and ask for correction.<br /> Francisco Souto<br /> Brazil
On 2020-07-13 09:32:26, user OxImmuno Literature Initiative wrote:
On 2019-06-28 18:46:32, user hkahn wrote:
Congratulations on an ambitious study design. It would be great to have also a comparative cohort sampled from the general adult population, but that would be very costly. Perhaps you could attempt parallel analyses from the EPIC population cohorts in Germany.
ANTHROPOMETRY:<br /> I didn't find many details, but surely the standing waist circumference (WC by the WHO protocol) will be included. I urge BeLOVE to consider adding the supine sagittal abdominal diameter (SAD) to the phenotyping assessments. The SAD has been quickly, reliably measured by a portable sliding-beam caliper (http://www.cdc.gov/nchs/dat... "http://www.cdc.gov/nchs/data/nhanes/nhanes_13_14/2013_Anthropometry.pdf)"). Studies in Sweden, Finland, India, Taiwan, Brazil, USA have demonstrated that SAD can serve to estimate the amount of visceral (intra-abdominal) adipose tissue. The supine SAD usually performs better than WC to identify dysglycemia, dyslipidemia, transaminase elevations, and hypertension. Since your participants will be supine for portions of the CRU assessment, you could inexpensively add the caliper measurement at that time.
Your SAD values by the low-cost caliper could be compared with the more costly dimensions and VAT area (or volume) estimates extracted from your supine abdominal imaging.
Population-based normative values for adult SAD are now available from Finland (Health 2000 Study) and from NHANES (2011-2016) in the USA. They confirm that SAD increases with age and tends to be larger for men than women.
The indicator SAD/height ratio (SADHtR) yields values that are nearly identical for men and women; thus, SADHtR can be evaluated as a risk estimator for men and women (just as the BMI purports to serve for men and women equally). Population norms for SADHtR are available from Finland and the USA. From the initial 4 years of NHANES we have demonstrated that SADHtR is superior to WHtR (and much superior to BMI) for identifying adults with insulin resistance (HOMA-IR), hypertriglyceridemia, and increased values of Tg/HDLc or the TyG index (https://www.ncbi.nlm.nih.go... "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003239/)").
I hope these thoughts will contribute to the success of the BeLOVE Study.
On 2019-07-16 21:33:06, user David Ludwig wrote:
One correction and one clarification:
There are two errors (slight underestimates) in the upper bounds of the effect sizes in the abstract. The relevant sentence should read: “Estimated energy requirement was higher in the Low vs High group by models involving ITT (ranging from 181 [CI 8-353] to 246 [64-427] kcal/d; P<=0.04) and PP (ranging from 245 [43-446] to 323 [122-525] kcal/d; P<=0.02).” The data in Table 2 are correct.
The full database will be publicly posted upon final publication of the manuscript in a peer-review journal.
On 2019-07-19 16:09:15, user Guyguy wrote:
EVOLUTION OF THE EBOLA EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI
Thursday, July 18, 2019
The epidemiological situation of the Ebola Virus Disease dated 17 July 2019:
Since the beginning of the epidemic, the cumulative number of cases is 2,532, 2,438 confirmed and 94 probable. In total, there were 1,705 deaths (1,611 confirmed and 94 probable) and 718 people cured.<br /> 402 suspected cases under investigation;<br /> 10 new confirmed cases, including 4 in Beni, 2 in Butembo, 2 in Mandima, 1 in Vuhovi and 1 in Mutwanga;<br /> 7 new confirmed case deaths:<br /> 4 community deaths, 2 in Beni, 1 in Mandima and 1 in Vuhovi;<br /> 3 ETC deaths including 1 in Beni, 1 in Katwa and 1 in Mabalako;<br /> 1 person healed out of Ebola Treatment Center (ETC) Butembo.
NEWS
Cross-border collaboration<br /> Uganda's health authorities have launched investigations to find the contacts of a patient who died at the ETC in Beni on July 15, 2019, who had spent a day in Kasese district in Uganda a few days earlier. The patient is a Beni shopkeeper who went to the Mpondwe market in Kasese on Thursday, July 11 before returning to Beni on Friday, July 12. She was a regular at the Kasese market where she bought her goods, including fish.<br /> To enter Uganda, she did not go through a formal entry point where there was a health check, which did not allow health teams to detect her. However, after her admission to the ETC of Beni, she informed the medical teams of her trip to Kasese and the teams then alerted the Ugandan authorities. During her visit to the market, she would have vomited four times, increasing the risk of contamination of people who had been in direct contact with her. So, the Ugandan Ministry of Health and WHO launched the investigation in Kasese to identify all contacts and vaccinate them.
Point of entry surveillance<br /> From now on, the Port of Entry Monitoring Team will operate 24 hours a day at Goma International Airport. This surveillance began this Thursday, July 18, 2019.<br /> Port of Entry monitoring teams work night and day to find contacts from confirmed cases traveling in the area. It was the teams at the OPRP Health Checkpoint in the Nyragongo Health Zone who intercepted two bikers who had transported the deceased pastor and his mother. The two bikers were then directed to the vaccination teams to protect themselves against the disease. In general, when contacts from affected areas attempt to travel to Goma or Bunia and are intercepted at a checkpoint, they are usually returned to their original health zone to complete their 21-day follow-up period.
Minister of Health on mission in Eastern DRC<br /> The Minister of Health, Dr. Oly Ilunga Kalenga arrived in Goma this Thursday, July 18, 2019. He spent the day on the ground to meet the different teams responsible for protecting the city against the virus. He began his visit through the Great Northern Control Point, called the OPRP, located in the Nyragongo Health Zone where the pastor from Butembo passed. In the same health zone, he also visited the new Ebola treatment center (ETC) still under construction. This ETC, built by Médecins Sans Frontières (MSF), will have a capacity of 60 beds.<br /> Its mission will continue throughout North Kivu and Ituri to ensure the proper conduct of the response.
Press Conference in Goma: Minister of Health reassured people<br /> The coordination of the response held a press conference on Thursday in Goma following the WHO statement on the public health emergency of international concern.<br /> The Minister of Health reassured the population that the response teams and health staff in Goma City had been preparing for the arrival of sick people from areas affected by the epidemic. . Thus the person was very quickly identified and isolated, he said, adding that all the people who were in contact with this case were found and vaccinated. He took the opportunity to congratulate the health center nurse Afia Himbi who had quickly recognized this case and promised to meet him during his stay in Goma.<br /> He called on caregivers to remain vigilant and attentive. To the population, he recommended the respect of the measures of hygiene, the call of the green number if a relative is sick, the agreement to be vaccinated and to be followed during 21 days when one is identified like contact and the respect for safe and dignified burials.<br /> During this press conference, Dr. Oly Ilunga also referred to the statement of the international expert committee on the public health emergency. For the Minister of Health, the DRC welcomed this statement, noting that for the DRC, the epidemic is a public health emergency with a risk of regional spread since its declaration in August 2018. "It is in this spirit coordinating the response has worked with international partners, such as WHO, UNICEF and others, "he said.<br /> He also pointed out that this declaration is of greater importance for the neighboring countries of the DRC. He reassured his foreign counterparts of the intensification of surveillance in the DRC. He recalled that WHO has advised against closing borders and restricting international movements of the population. He hopes that this declaration will not have too much impact on the lives of the population.
THE RESPONSE TO THE OUTBREAK
165,907 Vaccinated persons<br /> The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 19 May 2018.
76 001 290<br /> Controlled people<br /> 80 entry points (PoE) and operational health checkpoints (PoC)
137 Contaminated health workers<br /> One health worker, vaccinated, is one of the new confirmed cases of Mandima.<br /> The cumulative number of confirmed / probable cases among health workers is 137 (5% of all confirmed / probable cases), including 41 deaths.
On 2019-07-21 06:26:16, user Guyguy wrote:
ENGLISH
OFFICIAL PRESS RELEASE RELATED TO THE EPIDEMIC OF EBOLA VIRUS DISEASE IN EASTERN DRC
The Democratic Republic of the Congo takes note of the statement by the World Health Organization (WHO) that the current epidemic is a public health emergency of international concern and endorses the recommendations of the WHO Director-General not to impose travel and trade restrictions and stigmatization of populations already in need of assistance.
The Democratic Republic of the Congo reiterates its strong commitment to continue the response to the Ebola virus epidemic and to strengthen cross-border control and control of major internal roads to ensure that no cases are omitted or escapes from the surveillance teams.
The response to the Ebola Virus Disease outbreak is now under the direct supervision of His Excellency the President of the Republic. To this end, it was decided to entrust the responsibility of the Technical Secretariat of the Multisectoral Committee to a team of experts under the direction of Professor Jean Jacques MUYEMBE TAMFUM.
This team of experts is responsible for coordinating all the activities for implementing the Ebola response strategy. The Technical Secretariat is in charge of putting in place all the innovative measures that are urgent and indispensable for the rapid control of the epidemic.
His Excellency the President of the Republic reassures the Congolese people and the neighboring countries that the measures currently taken in connection with the response to the Ebola Virus Disease in the DRC are likely to eradicate this epidemic.
Kinshasa, July 20th, 2019.
Source: Office of the President of the Democratic Republic of the Congo
********************************<br /> FRENCH
COMMUNIQUE OFFICIEL EN RAPPORT AVEC L'EPIDEMIE DE LA MALADIE A VIRUS EBOLA A L'EST DE LA RDC
La République Démocratique du Congo prend acte de la déclaration de l'Organisation Mondiale de la Santé (OMS) faisant de l'épidémie actuelle une urgence de santé publique de portée internationale et fait siennes les recommandations du Directeur Général de l'OMS de ne pas imposer des restrictions des voyages et de commerce ainsi que la stigmatisation des populations se trouvant déjà dans le besoin d'une assistance.
La République Démocratique du Congo réitère son ferme engagement à poursuivre la riposte à l'épidémie de la Maladie à virus Ebola et à renforcer le contrôle transfrontalier et celui des principales routes internes afin de veiller à ce qu'aucun cas ne soit omis ou n'échappe aux équipes de surveillance.
La conduite de la riposte à l'épidémie de la Maladie à virus Ebola se fait désormais sous la supervision directe de Son Excellence Monsieur le Président de la République. A cet effet, il est décidé de confier la responsabilité du Secrétariat Technique du Comité Multisectoriel à une équipe d'experts, sous la direction du Professeur Jean Jacques MUYEMBE TAMFUM.
Cette équipe d'experts a pour mission d'assurer la coordination de l'ensemble des activités de mise en oeuvre de la stratégie de riposte à la Maladie à virus Ebola. Le Secrétariat Technique est chargé de mettre en place toutes les mesures innovantes urgentes et indispensables au contrôle rapide de l'épidémie.
Son Excellence Monsieur le Président de la République rassure les populations congolaises et les pays voisins que les mesures actuellement prises en rapport avec la riposte à la Maladie à virus Ebola en RDC sont de nature à éradiquer cette épidémie.
Fait à Kinshasa, le 20 juillet 2019.
Source: Cabinet du Président de la République Démocratique du Congo
On 2019-09-30 05:24:02, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 25 SEPTEMBER 2019
The epidemiological situation of the Ebola Virus Disease dated September 25, 2019
Thursday, September 26, 2019
Since the beginning of the epidemic, the cumulative number of cases is 3,178, of which 3,066 confirmed and 112 probable. In total, there were 2,126 deaths (2014 confirmed and 112 probable) and 981 people healed.
• 483 suspected cases under investigation; <br /> • 3 new confirmed cases, including: <br /> • No cases in North Kivu; <br /> • 3 in Ituri, including 2 in Mandima and 1 in Mambasa; <br /> • 4 new confirmed deaths, including; <br /> • 1 community death in Ituri in Mandima; <br /> • 3 deaths of confirmed cases in North Kivu, including 2 in Katwa and 1 in Beni; <br /> • 1 person cured out of CTE in North Kivu in Butembo; <br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 160 (5% of all confirmed / probable cases), including 41 deaths. <br /> NEWS <br /> Six people from Mambasa cured of Ebola Virus Disease out of Komanda CTE in Ituri * <br /> • The Ebola Treatment Center (ETC) in Komanda, Ituri province, unloaded on Thursday, September 26, 2019, six people cured of Ebola Virus Disease, all from Mambasa; <br /> • For the director of the Komanda CTE, Claude Banga Lonema, this treatment center receives patients from the Nyakunde and Komanda health zones, as well as from Mambasa well before the construction of its CTE, which has become functional for almost a week; <br /> • For the director of the CTE of Komanda, Dr. Claude Banga Lonema, all these cures are the work of a whole team, including medical and paramedical staff, psychosocial teams, nutritionists and hygienists and guards, to whom he is grateful for all their efforts in this day-to-day treatment center, as well as dedication and their apostolate; <br /> • The coordinator ai of the Subcommittee on Response and Chief Medical Officer of the Komanda Health Zone, Dr. Faustin Singo Ngozo, said on this occasion that the success and success of Ebola Virus Disease is an asset for everyone in the response. This success must be shared, because if surveillance does not work, there will always be notification of deaths. The presence of cures at the Komanda CTE shows that epidemiological surveillance has been successful in detecting cases in a timely manner and has enabled the care physicians to have sufficient time to treat these patients. To this end, he recommended mutual support among all the teams in the response to push him out of the way to harm the epidemic, which he said has lasted too long, to continue working with the same momentum. He also asked the six healings to help the response in sensitizing everyone in his respective environment. Military healing, he said, is a resource that can educate his colleagues to end this epidemic; <br /> • Among the Mambasa healers who were discharged from the Komanda Treatment Center were an 8-year-old girl, a man in uniform, including the Armed Forces of the Democratic Republic of the Congo, and the village chief of Makoko II, a village in strong resistance. The latter two promised to raise awareness about Ebola Virus Disease in their respective communities; <br /> • This triumphal exit from the six healings of Mambasa, an area still showing resistance against EVD, was made in the presence of the few partners, namely the delegates of WHO and UNICEF: <br /> • Beginning with the prayer, this ceremony also ended with prayer and a family photo between the cures and the teams of the response in this ETC; <br /> • Immediately after, their exits from the CTE of Komanda, the cured were accompanied by the teams of the response to Mambasa, their respective health zone, where a festive atmosphere awaited them; <br /> • The Komanda CTE is located in the Mangiva Health Area, precisely in Makayanga village in the health zone of Komanda, 100 km from the Mambasa health zone.
As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:
VACCINATION <br /> • Expanded ring vaccination around 2 confirmed cases in the Mataba Health Area in Kalunguta, North Kivu. In addition, two other vaccination rings, in the same health zone, are waiting to be opened in Lisasa and Kabasha Health Zones; <br /> • Since the beginning of vaccination on August 8, 2018, 228,430 people have been vaccinated; <br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.
MONITORING AT ENTRY POINTS <br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 98,818,462; <br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.
LEXICON <br /> • A community death is any death that occurs outside a #Ebola Treatment Center. <br /> • A probable case is a death for which it was not possible to obtain biological samples for confirmation in the laboratory but where the investigations revealed an epidemiological link with a confirmed or probable case.
On 2019-10-02 02:06:42, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT 29 SEPTEMBER 2019<br /> The epidemiological situation of the Ebola Virus Disease dated September 29, 2019<br /> Monday, September 30, 2019
• Since the beginning of the epidemic, the cumulative number of cases is 3,191, of which 3,077 are confirmed and 114 are probable. In total, there were 2,133 deaths (2019 confirmed and 114 probable) and 991 people healed . <br /> • 346 suspected cases under investigation; <br /> • 3 new confirmed cases, including: <br /> • 1 in North Kivu in Kalunguta; <br /> • 2 in Ituri, including 1 in Mambasa and 1 in Mandima; <br /> • 4 new confirmed deaths in Ituri, including: <br /> • 1 community death in Ituri 1 in Mandima; <br /> • 3 confirmed deaths in CTEs in Ituri, including 2 in Mambasa and 1 Komanda; <br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 160 (5% of all confirmed / probable cases), including 41 deaths.
Synthesis of epidemiological data at week 39 (from 23 to 29/09/019)
• Number of probable new cases: 3 <br /> • Number of new confirmed cases: 20 <br /> • Number of new healings: 16 <br /> • Number of new deaths: 12 <br /> • Community: 4 <br /> • Confirmed deaths: 8
NEWS
Local providers of 17 silent and hard-to-reach health areas in Mambasa in Ituri sensitized on EVD
• One hundred and two local providers of 17 silent and hard-to-reach health areas in the Mambasa Ebola Virus Disease Response (EVD) sub-coordination were sensitized from 29 to 30 September 2019 in women's ward in Mambasa in Ituri province on this disease;
• This took place during a briefing day for the purpose of helping to stop the transmission of Ebola Virus Disease in this sub-coordination in order to prevent its spread to other health zones. , DRC provinces and neighboring countries;
• This day also had the objective of setting up a functional alert system in the community and in the health structures of the target health areas and a communication system allowing a rapid response in case of notification of a validated alert. , a new confirmed or probable case and accelerate ownership of the response by communities, their leaders and local health system actors;
• These local providers were trained on EVD basics, early definitions / detections of cases and actions to be taken, as well as escalation of alerts, risk communication and community engagement. They were also trained on dignified and safe burial (DHS), active case finding, community-level monitoring tools and reporting system, risk communication and community engagement;
• Awareness Day was opened by Mambasa Territory Administrator Mr. Idriss Koma Kukodila in the presence of the Deputy General Coordinator for Ebola Response to the Epidemic, Dr. Justus Nsio Mbeta, the Physician the coordination of the Mambasa Health Zone, representing the Mambasa sub-coordinator of the response and the field coordinators of WHO and UNICEF;
• The sub-coordination of the Mambasa response includes 3 health zones, including Mambasa, Lolwa and Mandima, and 28 health areas, including 6 hot spots reporting cases within 14 days. These include Binase, Lolwa, Mambasa, Salama, Mandima and Some;
• The 17 health areas are: Banana, Tabala, Bandishende, Makoko II, Epulu, Salate, Molokai, Bukulani, Akokora, Pede, Bakaiko Kenya, Nduye, Bongupanda, Malembi, Bahaka, Lolwa and Some. These are health areas that do not report EVD alerts and are areas of difficult access and insecurity.
VACCINATION
• Since vaccination began on August 8, 2018, 230,489 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 100,607,920;
• 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:
On 2019-10-10 12:58:07, user GuyguyKabundi Tshima wrote:
EPIDEMIOLOGICAL SITUATION
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT OCTOBER 07, 2019<br /> Tuesday, October 08, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,206, of which 3,092 are confirmed and 114 are probable. In total, there were 2,143 deaths (2029 confirmed and 114 probable) and 1006 people healed.<br /> 443 suspected cases under investigation;<br /> 1 new case confirmed at CTE in Ituri in Mandima;<br /> 1 new confirmed death in North Kivu in Mabalako;<br /> 10 people were cured from the CTE, including 7 in Ituri in Komanda and 3 in North Kivu, including Beni, 1 in Katwa and 1 in Mabalako;<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.
No more confirmed cases of EVD at Butembo CTE<br /> - The Butembo Ebola Treatment Center (CTE) in North Kivu no longer has a confirmed case of Ebola Virus Disease;<br /> - The last two confirmed cases supported in this CTE have been released since Sunday, October 07, 2019 and have been reintegrated this Tuesday, October 08, 2019 in their respective communities by the teams of the response to the Virus Disease #Ebola of the psychosocial care. These cases are respectively health zones of Biena and Kayna;<br /> - Miss Ornella Bwira Zawadi, psychosocial supervisor at Butembo CTC, explains the psychosocial care at the Treatment Center. The Butembo CTE uses 17 psychologists subdivided into four blocks of tasks. These are triage supervisors, suspected cases, confirmed cases and accompanying village;<br /> - In the triage center, the psychologist ensures the awareness of newly admitted CTE cases. These new cases are normally 72 hours in the ETC and are taken on the 1st and the last day;<br /> - From the first day, the psychologist announces the result to the patients, its clinical evolution and its state. The patient who is positive is moved from the suspect's room to the confirmed block, while the patient who is negative until the third day remains in the suspected cases;<br /> - When the person is confirmed Ebola case, the psychologist is responsible for announcing his result, to make him aware of its evolution and life at the CTE. He asks him questions about his career in order to facilitate the follow-up of contacts;<br /> - It also monitors the confirmed case daily and ensures the relay between the patient and his family;<br /> - The accompanying person allows the good collaboration between the other CTE provider teams with the patient. It transmits various information of the patient, as well as its evolution to the other teams of the CTE;<br /> - Thereafter, intervenes the reintegration of suspected or confirmed cases cured and removed from the CTE. The psychiatrist accompanies him in his community. He educates his community and his family, explaining that the person who has been cured of Ebola is not dangerous and can not infect anyone else with the Ebola Virus Disease;<br /> - This Tuesday, October 08, 2019, Butembo CTE also released non Ebola people who were admitted to CTE as suspected cases.
VACCINATION
MONITORING AT ENTRY POINTS
As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:
On 2019-10-16 12:34:53, user GuyguyKabundi Tshima wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS OF OCTOBER 10, 2019<br /> Friday, October 11, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,210, of which 3,096 confirmed and 114 probable. In total, there were 2,146 deaths (2032 confirmed and 114 probable) and 1028 people healed.<br /> 422 suspected cases under investigation;<br /> 2 new case confirmed at CTE in Ituri in Mandima;<br /> 2 new confirmed deaths, including 1 in North Kivu in Mabalako and 1 in Ituri in Mandima;<br /> 1 person healed out of CTE in Ituri in Mambasa;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.
NEWS
President Félix-Antoine Tshisekedi Tshilombo submits to sanitary control for the prevention of #Ebola Virus Disease at Beni Airport<br /> - The Head of State, Coordinator of the Multisectoral Committee for the Ebola Virus Epidemic Response (CMRE), President Félix-Antoine Tshisekedi Tshilombo and his delegation were welcomed on Thursday, October 10, 2019 by the monitoring team at the entry points / sanitary control at Mavivi Airport in Beni, North Kivu Province. President Tshisekedi and his team have gone through all stages of health control at this point of entry to prevent Ebola Virus Disease;<br /> - The Ebola Virus Epidemic Response Coordination Team and a few members of the CMRE Technical Secretariat have been staying in Mambasa, Ituri province since Wednesday. It is in this part of the Democratic Republic of Congo that the last confirmed cases of #Ebola Virus Disease are concentrated;<br /> - This team, made up of the different experts in Ebola Virus Disease, has moved closer to Mambasa to coordinate closely the activities of the response;<br /> - Since they have been there, several activities have taken place, among which the release of 5 cured people from the ETC and a big meeting with all the partners of the response present in this sub-coordination. This meeting stems from the orientations to end the epidemic in this part of the DRC.
VACCINATION
MONITORING AT ENTRY POINTS
As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:
On 2019-11-13 01:31:13, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 11, 2019
Tuesday, November 12, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,287, of which 3,169 confirmed and 118 probable. In total, there were 2,193 deaths (2075 confirmed and 118 probable) and 1067 people cured.<br /> • 545 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths of confirmed cases have been recorded;<br /> • No cured person has emerged from ETCs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;
NEWS
Organization of a press conference in Goma on the introduction of the second Ebola vaccine in the Democratic Republic of Congo
• The coordination of the epidemic response to Ebola Virus Disease organized this Tuesday, November 12, 2019, jointly with the International Non-governmental Organization Médecins Sans Frontières of France (MSF / France), a press conference on introduction of the second Ebola vaccine, Johnson & Johnson, at the Karibu Hotel in Goma, capital of North Kivu Province;<br /> • During this press conference, the coordinator of the response, Prof. Steve Ahuka Mundeke, announced that vaccination with this second vaccine will start on Thursday, November 14, 2019 in two health areas of Karisimbi in Goma, including Majengo and Kahembe. The beginning of the vaccination will thus precede the official launch of the introduction of this vaccine which will intervene in the days to come;<br /> • This vaccine will be administered intramuscularly in two doses with an interval of 56 days. It targets adults and children over twelve months old. It has a strong immune response and its dose has the advantage of increasing this response by making it more sustainable in order to protect populations against a possible Ebola outbreak, according to a member of the consortium that took care of the study of this vaccine, Dr Hugo Kavunga, project manager INRB, member of the consortium;<br /> • Everyone is eligible for this vaccine, including children over the age of one, even pregnant and lactating women. In addition, for women of childbearing age, they will be offered a pregnancy test. Those who do not want it, will always be vaccinated. Pregnant women will be followed, said Vaccine Project Coordinator at MSF / France, Dr Véronique Urbaniak;<br /> • The choice of vaccination site was made after several studies and it is in order to protect the population against possible epidemics that Majengo and Kahembe were selected;<br /> • The vaccine is called Ad26.Zebov / MVA-BN-Filo. It is of Belgian-American origin and is named Johnson and Johnson. It has already been used in Sierra Leone in West Africa, Uganda and soon Rwanda. This second vaccine complements the first in-use vaccine in belt strategy and has already saved more than 3,000 people to date;<br /> • In addition to the speakers, two other members of the consortium took part in the press conference, including the London Shool Project Investigator Dr. Dan Baush and the Epicenter's Immunization Coordinator Marie Burton.
VACCINATION
• Preparation of the launch of the 2nd Ebola vaccine, J & J in Kahembe and Majengo Health Areas in Karisimbi, Goma, North Kivu;<br /> • 37 participants, including 4 high-risk contacts, 6 contacts, 7 CPs and 20 front-line staff, were vaccinated from the confirmed case of 09 November 2019 in the Bingo Health Area in Mabalako, North Kivu;<br /> • Since vaccination began on August 8, 2018, 250,622 people have been vaccinated;<br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.
MONITORING AT ENTRY POINTS
• Disruption of activities at PoC VIRENDI (SC BUTEMBO) following clashes between FARDC soldiers and incivists not otherwise identified.<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 116,184,525 ;<br /> • To date, a total of 111 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.
As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:
On 2019-11-08 19:03:54, user Rachel Couban wrote:
looking forward to reviewing the definition :)
On 2020-02-03 16:29:21, user Sarah wrote:
Hi, I'm not sure why you use the study 3 (Read et al.2020) estimate at 3.8. Their estimate is 3.11 (95%CI, 2.39-4.13). Is it an error?
On 2020-02-10 07:08:01, user ScientistCN wrote:
Only 1099 patients were analyzed, how can we get the significant figure to 0.01%?
On 2020-02-15 21:55:51, user Nate wrote:
It does need to be pointed out that this is Pre-Print at this point in time. It still needs to go through peer-review, etc., to be published.
That said, if this research is borne out/validated then this is pretty problematic news. The Chinese Government gave an R0 value of 2.6-2.9 or something like that, and also has publicly said the mortality rate is similar to the 2006 SARS outbreak (which had a lower R0 of something like 1.9 or something (possibly lower) ultimately. Assuming these figures are more accurate, If the Chinese Government is either not finding or hiding the number of cases but not the number of deaths, it actually may be good news, as the mortality rate would be considerably lower. However if they are wrong about or lying about both figures and it is both more contagious and more deadly, this could be a pretty serious epidemic/pandemic. If they, for instance are underestimating or underreporting the mortality rate by about .5 deaths per 1000 (I believe that’s the metric I’ve seen), the mortality rate would be roughly that of the 1918 Spanish Flu. Now, we are far better at treating symptoms now and preventing person to person spread of disease as we were in 1918, as well as developing vaccines. We have a lot of developed treatments that could be effective in minimizing symptoms or fighting the disease as well, even short of a currently viable cure/particularly effective treatment.<br /> However, that R0 value, if anywhere close to on target is pretty alarming. Even if the actual value is halfway between China’s figures and this study’s figures, and even if it were merely as deadly as SARS was.
Still, this isn’t an official figure yet. This isn’t even published, we don’t know how much other research will validate this number or contest it. So don’t panic based on a pre-print article. This probably has more value being available for other researchers, whom seeing other people’s figures, or methodology could benefit in their own research or methodology, and public heath officials who need to try to assess what a worst case scenario may look like. If these figures are accurate, they would be alarming. Even somebody who can read statistics and the language correctly in shouldn’t simply take something like this as fact, until it gets through peer review, other experts evaluate it once it’s published, and other figures start to align with their findings. I engaged in speculation, as it is really concerning should these figures be correct, and an interesting conversation to engage in. However, I am not credentialed in epidemiology, public health, or medicine. You should listen to experts and public health officials, over then speculation of somebody like myself. I am discussing the implications of this if true, not rendering an expert opinion.
On 2020-02-29 22:14:11, user Meat house man wrote:
Thank you for this in this dynamic situation..let me know which journal it gets published in.<br /> I agree with your conclusion re R0..
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.
On 2020-03-05 21:03:21, user Arturo Tozzi cns wrote:
CROSS-REACTIVITY BETWEEN COVID-19 AND CHILDHOOD VACCINES?
One speculation for the lower SARS clinical severity in children is that cross-protective antibodies were elicited in children as a response to one of their childhood vaccines.<br /> A 2007 paper (on mice immunised with various vaccines) states that children's vaccines do not induce cross reactivity against SARS-CoV
https://www.ncbi.nlm.nih.go...
However, the above-mentioned paper is affected by several bias.
Therefore, would it be feasible to look for cross-correlations between the RNA and proteic sequences of the NCOV 2019 and the immunogenic epitopes of the vaccines administeded to chinese children? If a correlation does exist, it could be possible to vaccinate the whole sensitive population.
Arturo Tozzi<br /> Center for Nonlinear Science, Department of Physics, University of North Texas, Denton, Texas, USA<br /> tozziarturo@libero.it<br /> Arturo.Tozzi@unt.edu
Gennaro D'Amato<br /> Division of Respiratory and Allergic Diseases, Department of Chest Diseases, High Specialty A. Cardarelli Hospital, Napoli, Italy<br /> Medical School of Specialization in Respiratory Diseases, University on Naples Federico II.<br /> gdamatomail@gmail.com
On 2020-03-09 02:23:08, user Angel Paternina-Caicedo wrote:
Great to see more data on the COVID-19 epidemic. The following comment does not deal with study methods. Despite the study appears methodologically sound, the Supplementary Material is not complete at this point, and this is needed for a full assessment.
This comment focus on the broad interpretation on the results of this study. The results of this study does not support the conclusion that the disease has been contained in Wuhan.
The study does not show evidence of no circulation in Wuhan after containment measures.
According to the results of this study, these isolation and quarantine measures have been effective to curve down and delay the peak attack-rate. Despite this, so far, there is no evidence that the final peak attack-rate will be lower after these measures, meaning, the final tally of infected population may not differ with or without these containment measures. The epidemic is only a few months old, and COVID-19 is still circulating in Wuhan and elsewhere in the world.
Also, the economic costs of shutting down the entire city are not quantified yet. And this experience is unlikely to be able to replicate in most of the world.
The conclusion that COVID-19 is contained after these strong measures in Wuhan, based on results of this study, are misleading. Notwithstanding, the delay to achieve the peak attack rate may give some time for the development and testing of a vaccine.
On 2020-03-12 20:49:50, user personfromreddit wrote:
Thank you for the well-designed and informative experiments and paper. The implications are critically important to managing COVID-19 patients and preventing further outbreak. However, in seeking publication for this paper I strongly recommend that the authors bolster their discussion -- specifically on the topic of in vitro vs. in vivo aerosolization. I am not a virologist, but I understand that just because SARA-CoV-2 can be aerosilized in similar systems that you used in your paper, that it may not mean there is clinical aerosolization and viral spread. While you touch on this in the paper and state that it is "plausible" that aerosol may contribute to spread, I think there needs to be more nuance to this discussion as to how likely this may be. To my understanding there are notable cases where in vitro systems such as the one in this study have found steady viral aerosols, but clinical aerosolization was not significant enough to present a means of viral spread (i.e. ebola).
I think discussing the topic of aerosolization in more detail are especially important for this paper during this time period -- one where many non-virologists and laypeople are reading high-brow virology literature. A more careful and detailed discussion of the implications of these findings will help prevent undue interpretations of these results.
On 2020-03-13 18:45:34, user naturebroad wrote:
What about Formica, laminates, butcher block, stone (soapstone, granite, marble, etc.), quartzite, solid surface kitchen countertops (acrylic resin, polyester resin or a combination of the two that is combined with filler,etc.),
On 2020-03-14 16:18:13, user Donna Lovitt Wells wrote:
In the dental profession aerosols are created pretty much every time a dental hygienist treats a patient or dentist uses a high speed drill. Would these professions be at high risk even if they use all appropriate PPE given that the aerosols stay in the air?
On 2020-03-20 05:00:15, user Leo Sandip Baniya wrote:
What is the optimum temperature for COVID virus to survive ?
On 2020-03-20 14:58:48, user David C. Norris, MD wrote:
https://twitter.com/davidcn...
On 2020-03-21 16:42:23, user Nick wrote:
I attempted to reproduce Tables 2 and 3 (R code included at the end of the post), and obtained these results:<br /> `Table 2, Day 3: reported p=0.005, calculated p=0.0136<br /> Table 2, Day 4: reported p=0.04, calculated p=0.0780<br /> Table 2, Day 5: reported p=0.006, calculated p=0.0148<br /> Table 2, Day 6: reported p=0.001, calculated p=0.0019
Table 3, Day 3: reported p=0.002, calculated p=0.0019<br /> Table 3, Day 4: reported p=0.05, calculated p=0.0429<br /> Table 3, Day 5: reported p=0.002, calculated p=0.0025<br /> Table 3, Day 6: reported p<0.001, calculated p=0.0005`
That is, Table 3 was more or less reproduced, but Table 2 wasn't; most of my p values are around twice the ones in the preprint.
Of the 8 tests, 5 produced warnings because chisq.test() doesn't like cell values of 0 or 1. Using fisher.test() from the "stats" package got rid of the warnings and caused some of the Table 2 p values to move towards the ones in the preprint, but only one (Day 6) got close. It isn't clear to me why one would use Fisher's Exact Test here --- my understanding is that it is not sufficient to invoke per-cell numbers of less than 6, as many authors seem to do, but I don't have a reference to hand for that.
Code:<br /> `t2.d3 <- chisq.test(matrix(c(10, 10, 1, 15), ncol=2))<br /> cat("Table 2, Day 3: reported p=0.005, calculated p=", sprintf("%.4f", t2.d3$p.value), "\n", sep="")
t2.d4 <- chisq.test(matrix(c(12, 8, 4, 12), ncol=2))<br /> cat("Table 2, Day 4: reported p=0.04, calculated p=", sprintf("%.4f", t2.d4$p.value), "\n", sep="")
t2.d5 <- chisq.test(matrix(c(13, 7, 3, 13), ncol=2))<br /> cat("Table 2, Day 5: reported p=0.006, calculated p=", sprintf("%.4f", t2.d5$p.value), "\n", sep="")
t2.d6 <- chisq.test(matrix(c(14, 6, 2, 14), ncol=2))<br /> cat("Table 2, Day 6: reported p=0.001, calculated p=", sprintf("%.4f", t2.d6$p.value), "\n", sep="")
t3.d3 <- chisq.test(matrix(c(1, 15, 5, 9, 5, 1), ncol=3))<br /> cat("Table 3, Day 3: reported p=0.002, calculated p=", sprintf("%.4f", t3.d3$p.value), "\n", sep="")
t3.d4 <- chisq.test(matrix(c(4, 12, 7, 7, 5, 1), ncol=3))<br /> cat("Table 3, Day 4: reported p=0.05, calculated p=", sprintf("%.4f", t3.d4$p.value), "\n", sep="")
t3.d5 <- chisq.test(matrix(c(3, 13, 7, 7, 6, 0), ncol=3))<br /> cat("Table 3, Day 5: reported p=0.002, calculated p=", sprintf("%.4f", t3.d5$p.value), "\n", sep="")
t3.d6 <- chisq.test(matrix(c(2, 14, 8, 6, 6, 0), ncol=3))<br /> cat("Table 3, Day 6: reported p<0.001, calculated p=", sprintf("%.4f", t3.d6$p.value), "\n", sep="")`
On 2020-03-21 18:05:24, user Joanna Haas wrote:
1) There were 26 patients treated with hydroxychloroquine. Of these 6 are excluded because they did not continue the full 10 day course of treatment; 3 were transferred to ICU, one died, one discontinued due to adverse reaction (nausea) and one left hospital early.
Thus among the 26 patients started on with hydroxychloroquine, 15% (4/26) went to ICU or died vs. 0/15 of the controls, a difference that may be due to chance. However the baseline characteristics of the 6 patients who deteriorated rapidly are not presented in Supplementary Table 1. The analysis of outcomes of the treated group are based on the remaining 20 treated patients.
Among the 36 patients presented in S Table I the treated group is significantly older and more have lower respiratory tract disease at baseline (30% vs 12.5%).
What is the impact of treatment on clinical course? Among the 20 patients who received hydroxychloroquine, six were given azithromycin "to prevent clinical infection". Since 5 of 6 had negative swabs at day 3, it is possible that clinical and viral status diverge.
While it is to be hoped that hydroxychoroquine with or without azythromycin will be of use in treating patients infected with SARS CoV2, the data presented in this manuscript, which is focused on viral shedding, are limited. Clinical outcome and safety data are needed. An intention to treat analysis needs to be included for the clinical outcomes.
On 2020-03-21 20:58:27, user Sinai Immunol Review Project wrote:
This study was a single-arm, open label clinical trial with 600 mg hydroxychloroquine (HCQ) in the treatment arm (n = 20). Patients who refused participation or patients from another center not treated with HCQ were included as negative controls (n = 16). Among the patients in the treatment arm, 6 received concomitant azithromycin to prevent superimposed bacterial infection. The primary endpoint was respiratory viral loads on day 6 post enrollment, measured by nasopharyngeal swab followed by real-time reverse transcription-PCR.
HCQ alone was able to significantly reduce viral loads by day 6 (n = 8/14, 57.1% complete clearance, p < 0.001); azithromycin appears to be synergistic with HCQ, as 6/6 patients receiving combined treatment had complete viral clearance (p < 0.001).
Chloroquine is thought to inhibit viral infection, including SARS-Cov-2, by increasing pH within endosomes and lysosomes, altering the biochemical conditions required for viral fusion1,2. However, chloroquine also has immuno-modulatory effects that I think may play a role. Chloroquine has been shown to increase CTLA-4 expression at the cell surface by decreasing its degradation in the endo-lysosome pathway; AP-1 traffics the cytoplasmic tail of CTLA-4 to lysosomes, but in conditions of increased pH, the protein machinery required for degradation is less functional3. As such, more CTLA-4 remains in endosomes and is trafficked back to the cell surface. It is possible that this may also contribute to patient recovery via reduction of cytokine storm, in addition to the direct anti-viral effects of HCQ.
Despite what is outlined above, this study has a number of limitations that must be considered. First, there were originally n = 26 patients in the treatment arm, with 6 lost to follow up for the following reasons: 3 transferred to ICU, 1 discharge, 1 self-discontinued treatment d/t side effects, and 1 patient expired. Total length of clinical follow up was 14 days, but the data beyond day 6 post-inclusion are not shown.
Strikingly, in supplementary table 1, results of the real-time RT-PCR are listed for the control and treatment arms from D0 – D6. However, the data are not reported in a standard way, with a mix of broadly positive or negative result delineation with Ct (cycle threshold) values, the standard output of real time PCR. It is impossible to compare what is defined as a positive value between the patients in the control and treatment arms without a standardized threshold for a positive test. Further, the starting viral loads reported at D0 in the groups receiving HCQ or HCQ + azithromycin were significantly different (ct of 25.3 vs 26.8 respectively), which could explain in part the differences observed in the response to treatment between 2 groups. Finally, patients in the control arm from outside the primary medical center in this study (Marseille) did not actually have samples tested by PCR daily. Instead, positive test results from every other day were extrapolated to mean positive results on the day before and after testing as well (Table 2, footnote a).
Taken together, the results of this study suggest that HCQ represents a promising treatment avenue for COVID-19 patients. However, the limited size of the trial, and the way in which the results were reported does not allow for other medical centers to extrapolate a positive or negative result in the treatment of their own patients with HCQ +/- azithromycin. Further larger randomized clinical trials will be required to ascertain the efficacy of HCQ +/- azithromycin in the treatment of COVID-19.
References
On 2020-03-22 10:37:56, user Nathan wrote:
Here's a re-analysis based on mixed-effects logistic regressions, including time and age as covariates: https://nfaivre.netlify.com...
On 2020-03-24 15:03:38, user Sinai Immunol Review Project wrote:
Title: Clinical Features of Patients Infected with the 2019 Novel Coronavirus (COVID-19) in Shanghai, China
Summary: This single-center cohort study analyzes the clinical and laboratory features of 198 patients with confirmed COVID-19 infection in Shanghai, China and correlated these parameters with clinical disease severity, including subsequent intensive care unit (ICU) admission. 19 cases (9.5%) required ICU admission after developing respiratory failure or organ dysfunction. Age, male sex, underlying cardiovascular disease, and high symptom severity (high fever, dyspnea) were all significantly correlated with ICU admission. Additionally, ICU admission was more common in patients who presented with lymphopenia and elevated neutrophil counts, among other laboratory abnormalities. Flow cytometric analysis revealed that patients admitted to the ICU had significantly reduced circulating CD3+ T cell, CD4+ T cell, CD8+ T cell, and CD45+ leukocyte populations compared to the cohort of patients not requiring ICU admission.
Limitations: The limitations of this study include the relatively small sample size and lack of longitudinal testing. The authors also did not assess whether respiratory comorbidity – such as asthma or chronic obstructive lung disease – in addition to immunosuppression affected ICU admission likelihood.
Relevance: COVID-19 has already sickened thousands across the globe, though the severity of these infections is markedly diverse, ranging from mild symptoms to respiratory failure requiring maximal intervention. Understanding what clinical, laboratory, and immunologic factors predict the clinical course of COVID-19 infection permits frontline providers to distribute limited medical resources more effectively.
Review by Andrew Charap as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine at Mount Sinai.
On 2020-03-24 16:03:36, user Sinai Immunol Review Project wrote:
In a cohort of 222 patients, anti-SARS-CoV-2 IgM and IgG levels were analyzed during acute and convalescent phases (up to day 35) and correlated to the diseases’ severity. The same was done with neutrophil-to-lymphocyte ratio. High IgG levels and high neutrophil-to-lymphocyte ratio in convalescence were both independently associated to the severity of the disease. The simultaneous occurrence of both of these laboratory findings correlated even stronger to the diseases’ severity.<br /> Severe cases with high neutrophil-to-lymphocyte ratios had clearly higher levels of IL-6. The authors propose that a robust IgG response leads to immune-mediated tissue damage, thus explaining the worse outcome in patients with overexuberant antibody response.
A main criticism is that the criteria for stratifying patients in severe vs. non-severe are not described. The only reference related to this is the difference between the percentage of patients who needed mechanical ventilation, which was greater in patients with both high IgG levels and high neutrophil-to-lymphocyte ratio. No patient with both low IgG levels and low neutrophil-to-lymphocyte ratio was treated with mechanical ventilation.<br /> The proposed correlation of severity with IL-2 and IL-10 levels is not very strong.<br /> Furthermore, although mostly ignored in the paper’s discussion, one of the most interesting findings is that an early increase in anti-SARS-CoV-2 IgM levels also seems to correlate with severe disease. However, as only median values are shown for antibody kinetics curves, the extent of variation in acute phase cannot be assessed.
Anti-SARS-CoV-2 IgG levels and with neutrophil-to-lymphocyte ratio predict severity of COVID-19 independently of each other. An additive predictive value of both variables is noticeable. Importantly, an early-on increase in anti-SARS-CoV-2 IgM levels also seem to predict outcome.
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.
On 2020-03-24 19:51:57, user Aaron wrote:
From the Discussion: "Other studies have showed that high expression of ACE2 in the patients with hypertension, diabetes, and cardiovascular diseases might facilitate SARS-CoV-2 to enter the targeted cells in the respiratory system, and prolong the time of viral clearance [11, 31]."<br /> The references cited here do not show what the authors claim. Reference 11 is only a hypothesis that increased ACE2 expression in ACE inhibitor patients could lead to increased infection rates and increased case severity. These findings of ACE2 expression upregulation following ACE inhibition have only been demonstrated in rats and mice (the renin-angiotensin system is reviewed extensively in reference 31). Even if this phenomenon was shown to be identical in humans, there is no evidence showing that this upregulation leads to increased infection and/or increased case severity.
The authors go on to point out that age and incidence of hypertension, diabetes, etc. are difficult to untangle. This is a great point to make and it would be interesting if the authors can show that their cohort includes a significant population of younger patients with these comorbidities rather than the expected coincidence of older age and hypertension and/or diabetes. However, even if this is shown to be the case, an indication for hypertension or diabetes (type I or II) is not synonymous with ACE inhibitor use. Therefore, the authors should be mindful of any claims that equate hypertension or diabetes to ACE inhibitor use.
On 2020-03-26 03:45:03, user JohnMo wrote:
The inclusion of ACE inhibitors / ARB's as a covariate would also be helpful to distinguish outcomes of DM/HTN on these drugs vs. alternative drugs.
On 2020-03-26 00:03:02, user Your college professor wrote:
Some people suggest that the fact that COVID-19 binds to ACE2 receptors means there's a fertility risk involved, but we've had ACE2 binding corona viruses like HCoV-NL63 circulating for centuries and as far as I am aware nobody has ever observed any such harm from them.
We also have an autopsy of SARS fatalities, where no viral material was discovered in testicular tissues.
There's an argument to be made that the authors used an improper control group, as their control group apparently excludes men with fertility problems. The authors write:
The control group came from the population who previously received reproductive function evaluation and were classified as having normal fertility
In other words, rather than a normal distribution of the population, they're inevitably excluding a portion of subfertile men from their control group. One of the main symptoms commonly seen in subfertile men is the elevated LH levels they observed in COVID19 patients.
However, there is another problem that is more relevant than the above shortcomings. Luteinizing hormone is secreted in pulses, in a diurnal pattern. In contrast, FSH, which has no clean diurnal pattern, is not statistically significantly different between their control group and their COVID19 survivors.
What this diurnal LH pattern means is that you want to make sure that your control group is tested at the same time of day as your experimental group (ie COVID19 survivors). This explains for example why comparing different studies done on male fertility will lead to widely varying average levels of LH in different groups of subjects. The control group being measured at a different time of the day compared to the experimental group would also explain the prolactin differences seen in this particular study.
Unfortunately, the authors of this study don't mention when the control group had their values measured and when the survivors had their values measured. As a consequence, you can't consider this a proper control group, which means their results provide no evidence for their suggestion that COVID19 might cause fertility damage. Similarly, the 75th percentile they report for LH is not abnormally high, which would have been indicative of potential fertility problems.
Based on these problems, I don't see how this study would survive peer review.
On 2020-03-27 13:15:49, user Joshua Gagne wrote:
Is there an obvious explanation for why the decrease in PM2.5 would be so much larger for the other cities (18.9 ug/m3) than for Wuhan (1.4 ug/m3)? It's the opposite of my (perhaps naive) expectation.
On 2020-03-30 23:21:41, user Brian Coyle wrote:
They use Wallinga & Kretzchmar's age-based transmission matrix to model CoV2 transmission among age groups. The Wallinga estimates are based on influenza, and show "school-aged children and young adults will experience the highest incidence of infection and will contribute most to further spread of infections". This is not a useful model for CoV2, where children are not driving spread. This paper's estimates show isolating children has the biggest impact, which is almost surely not accurate.
On 2021-05-21 04:28:38, user Irem Karaman wrote:
Published version of this manuscript: https://www.tandfonline.com...
On 2021-05-25 16:46:56, user Ghatotpach Pilandi wrote:
Beltrane is not "moderate." They first had "moderate" in the title, then changed it to "Severe." The introduction still uses "moderate" but the inclusion criteria in the main text is "severe hypoxemic respiratory failure" plus more indicators of severity. Did tje meta study authors read the study?
On 2021-05-25 17:36:04, user debernardis wrote:
As Juan Chamie first pointed out (https://twitter.com/AOlavar... "https://twitter.com/AOlavarria/status/1397202822672879621?s=19)") you inverted the results of Niaee 2020. This invalidates your conclusions re mortality. It's better to retract, probably.
On 2021-05-25 18:52:14, user Stephen J. Collings wrote:
Looks like an error in the extraction of data from Niaee 2020 has led to an incorrect mortality conclusion. Please correct as a matter of urgency.
On 2021-05-26 02:24:19, user ????? ????? wrote:
Hi, I'm Dr.Niaee and I was surprised that even basic data from our RCT is completely mispresented and is WRONG. We had 60 indivisuals in control groups and 120 in intervention groups and even this simple thing is mispresrntated.
On 2021-05-27 13:57:01, user unscientific science wrote:
This is the new version of the article:
On 2021-05-25 20:39:22, user Luiz Henrique Oliveira wrote:
Nice paper, but you guys didn´t determine the % of efficience is for... is for light cases? moderate or serious cases? 28% for people above 80 years, that means that 72% of positive cases died when in serious cases? there´s a lot of miss informations that need to answer and in brazil a lot of midia is announcing this article as " the vaccine does not work"
On 2021-05-27 06:18:59, user Mike Stevens wrote:
Well, it’s not whether there is a mandate in place, is it?<br /> It’s whether the mandate is adhered to.<br /> And when people actually comply, and wear the masks, Covid spread declines.<br /> https://journals.plos.org/p...
Funny how a disease spread primarily through droplet spread can be halted by methods that stop droplet spread, isn’t it?<br /> Who would have thought it?
On 2021-05-27 17:47:20, user Right Warrior wrote:
This hasn't been subject to peer review yet. Why are we supposed to take this at face value?
On 2021-06-01 12:34:57, user The_European1000 wrote:
This is not good information, and the research is not well done.
They used a two-tailed t test with Holm Sidak correction, as if that is suffient to compensate for the complex interplay of factors that produce the same result (infection/non infection). Hell, they even made a simple linear regression to add insult to injury.
Essentially, to explain it more simply, using those tests rests on the assumption that there are 2 categories that correlate to other to categories perfectly- mask/not mask and infected/not infected.
This is not the case. Masks wearers that social distance will have lesses infection rates than mask wearers who do not. Ventialtion of enclosed areas is also an issue.
These "researchers" did not account for the confounding variables that affect infection rates- everything from other measures to testing rate differences among states.
Overall, there are many flaws with this research. Not good.
On 2021-06-21 17:58:22, user Greg wrote:
I will pose a very simple question. If masks worked, why wasn't the pandemic stopped in its tracks? Instead, it has played out like all outbreaks do. Masks didn't work in 1918 during the Spanish Flu pandemic, and they don't work now. Surgical masks or cloth masks were never meant to stop viruses. Why do you think workers in highly-secure biolabs wear airtight suits? Why go through all that trouble if they could just pop on a surgical mask?
The fact is, masks are simply for show. They make people feel safe and secure, but it's all theater. That's why you see people continuing to wear them even after the mandates have been lifted. They make them feel safe. It's always been about feelings, when it should've been about science.
On 2021-09-01 16:46:01, user WGardner wrote:
I would like to know more about how you controlled for fidelity of mask usage? This should consider whether or not people consistently wore masks, and wore them correctly. Having a mask mandate is a poor marker for whether or not masks work as it does not equate to people actually wearing masks.
On 2021-06-03 13:46:26, user Nicolas Banholzer wrote:
This work has been refined and is now published in PLOS ONE: https://journals.plos.org/p...
On 2021-06-05 13:55:27, user Tim Winton wrote:
Would it be possible to see the code for this?
On 2021-06-06 13:42:01, user Maryam Pahlavan wrote:
Hej, How I canrequest for dataset?
On 2021-06-10 04:54:34, user ejmah wrote:
On 2021-06-10 17:55:41, user Steve Johnson wrote:
It is possible that fully vaccinated participants fared better because testing for infection was done 5 weeks or more after dose 1. Are there results for partially vaccinated participants tested 5 weeks after dose 1, but free from infection in prior tests?
On 2021-06-10 17:59:48, user Aliya Amirova wrote:
Peer-reviewed and published article: https://openheart.bmj.com/c...
On 2021-06-10 20:23:12, user John Jay wrote:
Sorry if this was already mentioned, but is there a discussion of how the demographics (ie age, co-morbidities, status before care, etc.) varied between the group given 3,000mg HCQ + 1,000mg AZM and all other patients in the study?
On 2021-06-14 17:19:23, user Sherry Grace wrote:
Paper now in print! https://globalheartjournal....
On 2021-06-18 16:19:49, user Jim D wrote:
Hi, I have CLL, asymptomatic and very low count. I had the Pfizer vaccine, both doses. My arm was sore for 3 weeks after the first shot even tho I moved it around alot. On the third day after my second shot, it seemed that my shingles was reactivated, big pain, couldn't sleep. My PCP sent me to emergency for CT scan. Other than spike in white cell count, nothing showed from the scan. I shared the info about this study with PCP and Hemotology oncologist to try to get a quantitative antibody test. I have not heard back, other than those tests are extremely difficult to get. Also then with further reading, I learned that even with a quantitative test, I would not learn much since there is no standard for determining what number is safe.<br /> My question is: has there been any new info since this study was posted. Thanks. J
On 2022-01-07 04:29:43, user Cameron Cooper wrote:
Is this the study Rand Paul is quoting?
On 2021-06-22 03:53:16, user Bob Horvath wrote:
Thank you for this paper - parents of PANS patients are grateful to see this kind of genetics work being done on PANS. May I ask:
1) What was the total number of variants meeting the criteria described (at lines 141-144 of the document for the European samples, and lines 154-158 for the U.S samples)?
2) Presumably, the list of candidate genes (described at lines 161-162) were all the genes that encompassed the variant lists in 1) above, with the possible exception of MTHC2 and BID that are mentioned as additions. What was the total number of candidate genes considered, before the list was narrowed to the 11 listed?
On 2021-07-17 14:18:34, user killshot wrote:
Make sure there is some effort to randomize according to vitamin D status! Otherwise the data is quite flawed and meaningless.
On 2021-03-13 17:08:08, user truthful melody wrote:
Honest question seeking a good faith answer:
Does anyone know why the CDC is not reporting the variant cases that were widely reported in the media from the paper?
The headline on multiple outlets was, “Houston has all the variants”.
However, these are the current numbers from the CDC:
Texas (March 11, 2021)<br /> B.1.17 Variant: 140<br /> P.1. Variant: 0<br /> B.1.351 Variant: 1<br /> Source: US COVID-19 Cases Caused by Variants | CDC
The CDC is still reporting zero P1 cases in Texas and only one B.1.351.
Since Houston is a city in Texas, and I see from the comments section here that the cases are included in GISAID, what is the discrepancy here?
On 2021-03-17 10:27:00, user Olaf Storbeck wrote:
I took the Vitamin D data from that paper but pulled the Covid-19 data myself due to severe data errors I found in the figures (very similar to the other commentors). I also corrected the Turkey Vitamin D data to that from a much better meta analysis ((Alpdemir, Medine & Alpdemir, Mehmet. (2019). Vitamin D deficiency status in Turkey: A meta-analysis. International Journal of Medical Laboratory. 10.14744/ijmb.2019.04127).<br /> The analysis in this preprint it fully dominated (beside the data errors) from the Czech data point, which is clearly an outlier and unfortuneatly not even shown in Figure 1.
When correcting the failures I got a significant correlation of Vitamin D deficiency to Covid-19 cases and deaths with p values on 0.0005 to 0.02 range.
On 2021-03-18 12:54:03, user H.C. So wrote:
This is an online calculator (intended for educational and research purposes only) based on the prediction model in this paper <br /> http://labsocuhk.ddns.net:8889/covid19/
Hon-Cheong SO
On 2021-03-20 04:41:11, user Wael wrote:
This work is immense. I appreciate the fact that the research devised 29 objective points to measure the level of Hesitancy, way to go. The methodology is really robust. I know that because I already have two publications using reliability models. In addition, the figures are clear.
On 2021-03-22 14:43:29, user tuulaojavuo wrote:
This article is erroneous. E.g. the Larson 2010 data is wrong. The results and all the major conlusions are thus erroneous.
(The Larson 2010 data has categories "symptoms" and "no symptoms" switched, that error alone changes all the results & conclusions of the study)
This article should be retracted immediately
On 2021-04-04 11:06:22, user kingmanninen wrote:
Re: Version 8; please see SUPPLEMENTARY FILE 4.
On 2021-04-07 12:36:01, user Atomsk's Sanakan wrote:
The paper is published here:
"SARS-CoV-2 antibody prevalence in England following the first peak of the pandemic"<br /> https://www.nature.com/arti...
On 2021-04-09 19:32:45, user Dr. Nandkumar Kamat wrote:
In Indian state of Goa, with more than 3597 active cases ( cumulative 61239 cases, 845 deaths) as on April 9, Four Covid19 positive RT PCR samples taken just one day apart , in March 2021 from two males and females in same district produced four variants B.1.1.7; B.1.1.36, B.1 L452R, E484Q and B.1.1.464. The patients had no travel history. How samples taken one day apart can produce four different variants? . In four Positive samples?. What such high variant prevalence indicates? How to manage such a situation?. Any ideas? . The sequencing efforts are very slow.
On 2021-04-15 03:32:28, user Mark Czeisler wrote:
Note from the authors:
This paper was published in BMC Public Health on 15 March 2021 following peer review. Below is a link to the article, along with the PubMed citation.
https://bmcpublichealth.bio...
Czeisler MÉ, Howard ME, Robbins R, Barger LK, Facer-Childs ER, Rajaratnam SMW, Czeisler CA. Early public adherence with and support for stay-at-home COVID-19 mitigation strategies despite adverse life impact: a transnational cross-sectional survey study in the United States and Australia. BMC Public Health. 2021 Mar 15;21(1):503. doi: 10.1186/s12889-021-10410-x. PMID: 33722226; PMCID: PMC7957462.
On 2021-04-15 09:52:40, user Brendan Ruban wrote:
It's enough to make your mind spin. Credit to the authors for their excellent endeavours. We want a free thinking, critical, scientifically literate public that we can present the evidence to, and then they'll make great decisions. But we'll never have that. Even my friends who received degree level scientific education fail to assess evidence thoroughly. Quantifying how well the message will be followed is surely beyond scientific analysis being so multifaceted. The messenger, the environment, the message, the personal affect on the follower... So many factors. I am a huge fan of scientific evidence, but there are so many things in life in which we'll never gain enough lucidity from the classical scientific approach. We need another tool that is rational and thoughtful and will be respected. And perhaps we need to look into sociology and political thought to guide us. Scientific analysis and simplistic messaging cannot fill that gap in the highly nuanced, diverse world we now live in. My two cents.
On 2021-04-18 07:24:24, user Nicole wrote:
Had covid in early January 2020. Felt like death for over a week, the sickest I'd ever felt. Starting beginning of 2021 I've had "covid toe" (itchy red/painful blisters on two of my toes) and have had very dry inside of my nose for over a month that has resulted in several nose bleeds, raw scabby areas inside my nose and bloody, dry boogers 24/7.<br /> I wish more of this was shared and studied -- this affects people for a loooooong time.
On 2021-04-19 16:28:26, user Motti Gerlic wrote:
Happy to share our Final ver after peer review for this preprint which was published in Cell Report Medicine:<br /> BNT162b2 Vaccination Effectively Prevents the Rapid Rise of SARS-CoV-2 Variant B.1.1.7 in high risk populations in Israel https://t.co/Nazw3Og3uq<br /> https://www.cell.com/cell-r...
On 2021-04-23 07:42:37, user The Crane Report wrote:
"The authors have declared no competing interests"<br /> Sinetra Gupta received almost £90,000 from the Georg and Emily von Opel Foundation to fund research “into the prevalence of COVID-19 in the population” in the first week of April 2020.<br /> https://www.opendemocracy.n...
On 2021-04-25 13:30:44, user Robert Saunders wrote:
Clery and colleagues state that “evidenced based treatments are available” for chronic fatigue syndrome. These are listed as Cognitive Behavioural Therapy-for-fatigue (CBT-f), Activity Management (AM) and Graded Exercise Therapy (GET).
In 2017 the US Centers for Disease Control and Prevention concluded that there are no effective treatments for CFS, after it re-examined the scientific evidence and removed CBT and GET as recommended treatments [1].
Similarly, the 2020 draft NICE guideline for ME/CFS specifically warns against the prescription of CBT and GET as treatments due to the evidence that they are ineffective and potentially harmful [2]. 89% of outcomes in studies of non-pharmacological interventions for ME/CFS have been graded as “very low quality” with a high or very high risk of bias by NICE’s independent experts. And no outcomes in any studies of CBT or GET are graded as better than “low quality” [3].
Clery and colleagues cite Nijhof et al (FITNET) [4] for their claim that “at least 15% of children with CFS/ME [sic] remain symptomatic after one year of treatment”. It should be noted that Nijhof et al used the 1994 CDC Fukada diagnostic criteria [5], which is less specific than other criteria as it does not require post-exertion malaise (PEM) as a symptom.
Evidence suggests that most people with fatigue and other persistent symptoms following viral infection will recover within 2 years with no treatment, but a minority with ME/CFS will not recover [6,7]. There is no reliable evidence to suggest that long term outcomes are any better for those who have been prescribed CBT or GET and there is good evidence to suggest that these interventions are harmful [8].
There is undoubtedly a need for children and adults with post-viral fatigue syndromes and ME/CFS to be given appropriate advice and support to manage and cope with the effects of their illnesses. However, acknowledgement of the very low quality of past studies and the evidence that CBT and GET are neither safe nor effective treatments for ME/CFS should be considered a prerequisite for any research pertaining to the provision of such services.
References:
On 2021-05-04 02:06:41, user Uri Kartoun wrote:
Ref 9 actually does rely on combining structured and unstructured data elements. The paper is one of the earliest to identify NAFLD patients using EMRs - indeed it is limited, but I wouldn't write "fail to provide the full clinical picture of NAFLD" because it is not true.
On 2021-05-05 01:00:46, user Andre Boca Ribas Freitas wrote:
Unfortunately, the drop of proportion of elderly people among total of deaths is due in large part to the increase in deaths among young people!<br /> This is due to the characteristics of variant P.1, which leads to more serious cases among young people.
On 2021-05-06 12:22:51, user Steeve Asselin wrote:
The old adage I feel applies here: It is not because we can do it that we should do it...Has thoughts ever been given to the potential of such innovative process to be misused by Life Insurance Companies to increase or worse, deny life insurance to a person because that innovation "estimated" (because it is an estimation NOT a calculation) that the probability of this person to die is above 50% in the coming years...
On 2021-05-10 02:20:37, user Jogen ( G12 Student) wrote:
Good day, may I request for the questionnaire because we're currently conducting the same study and it would be a big help for us, thankyou in advance.
On 2021-05-12 06:41:10, user Mary b wrote:
may I request for the questionnaire? We are currently conducting our data gathering for the barriers in online learning that is related to your studies. Thank you in advance
On 2021-05-10 15:04:07, user Zsofi Igloi wrote:
article has been published in Emerg Infect Dis. 2021;27(5):1323-1329. https://doi.org/10.3201/eid...
On 2021-09-16 10:11:35, user kdrl nakle wrote:
The paper claims significant increase of virulence yet many epidemiologists in the US would claim that is not the case with any of the variants. Which is true?
On 2021-08-20 12:21:27, user Jodi Schneider wrote:
Additional breakthrough infection data (from states that are collecting more info than the CDC is expecting) could be useful for comparison and contextualization in discussion. https://www.kff.org/policy-...
On 2021-08-21 14:43:23, user Paul-Olivier Dehaye wrote:
This paper has now been published (and presumably peer-reviewed).
New title: Adherence and Association of Digital Proximity Tracing App Notifications With Earlier Time to Quarantine: Results From the Zurich SARS-CoV-2 Cohort Study
https://www.ssph-journal.or...
It still includes in the introduction, despite showing the opposite:
These findings provide evidence that DPT may reach exposed contacts faster than MCT, with earlier quarantine and potential interruption of SARS-CoV-2 transmission chains.
On 2021-08-23 10:32:30, user ingokeck wrote:
Dear authors, I have a problem following your comparison between vaccinated cases and non-vaccinated cases. I understand how you select the vaccinated cases with your flowchart (thank you for providing one, this really helps to understand!), but I don't understand how you create the non-vaccinated controls. If you simply add up all non-vaccinated cases, you will get a huge bias towards non-vaccinated cases, as the vaccination campaign was still ongoing during your analysis period. So you will need to account for the differences in exposure, i.e. for a vaccinated case in week 10 which got infected in week 8 you need to look at the dose2 percentage even 2 weeks earlier, i.e. week 6 to normalize the exposure risk between vaccinated and non-vaccinated persons. It would be interesting to see the result. If you can share the anonymized raw data, I may be able to help.
On 2021-08-25 12:07:48, user Prof. W Meier-Augenstein, FRSC wrote:
What other than the difference in antibody titer post-vaccination and post-infection is the take-home message of this study? Surely, the decline in antibody titer per se months after vaccination or primary infection is not a surprising finding but could be expected? Antibodies have a finite life-span given by their Ig specific half-life (for example 21 days for IgGs). In the absence of a subsequent challenge (e.g. by a secondary infection) antibodies formed in response to the challenge posed by vaccination or primary infection will have all but cleared from serum after 6+ months. Furthermore, the difference in antibody titer between mRNA vaccinated and SARS-CoV-2 infected could not have come as a big surprise either considering mRNA vaccination results in expression of spike-protein “only” which means in contrast to a viral infection host cells are actually not infected and do not reproduce copious amounts of the virus which will take longer to fight and clear from the body than the spike protein. For the same reason, macrophages (phagocytes) are unlikely to be involved in the mRNA vaccinated group to the same degree as they are in the group infected by the virus. The natural decline of IG antibodies produced in response to the mRNA vaccine does not offer an exclusive explanation for breakthrough infection. Instead, breakthrough infection occurring 146+ days post vaccination are most likely the result of a “perfect storm”, an unfortunate coincidence of the higher virulence of the Delta variant of <<7 days incubation time, the associated higher viral load produced, and the fact the production of neutralising antibodies by B-memory cells takes up to 4-5 days to reach its peak.
On 2021-08-26 03:53:13, user IMO wrote:
Interesting study. Funny how little discussion there is from the media or the public health machine about immunity conferred by infection. No mention from on high about extending "passport" privileges to those who have been infected and then chosen not to get vaccinated. What's up with that?
On 2021-08-26 14:57:06, user JK wrote:
Is anyone really surprised by this?
On 2021-08-28 11:49:17, user Doug Truitt wrote:
So if one lives in Kentucky previous infection is less protective than vaccination - https://www.cdc.gov/mmwr/vo... - and if one lives in Israel previous infection is more protective than vaccination (this study). I'd be interested in discussion as to why these two studies are at odds with one another.
On 2021-08-29 05:35:10, user some_guy wrote:
Is there any variable control?
The first question that pops into my mind is: are we comparing the same populations?
People who were first vaccinated are disproportionately old people with weaker immune systems, more likely to be infected anyways. I wonder how much does this impact the results.
On 2021-08-30 07:37:30, user 4qmmt wrote:
This paper has one major flaw that is not discussed: We know for certain who was vaccinated and of those, 199 had symptoms. Though 8 of the matched recovered had symptoms, they were assumed to have been infected because of a + PCR test in the past, which as we all know produces tons of false positives (Israel's Ct is 35-40). In fact, the paper's own data shows that of the 238 PCR+ in the vaccinated cohort, only199 were actually positive, i.e., symptomatic = ill, and in the recovered cohort, of 19 PCR+, only 8 were symptomatic, suggesting at least 60% false positives. Thus, while the number of vaccinated is certain, the true number of previously infected is at most 8, but could in fact be 0, as the Cleveland Clinic study found.
In fact, last weeks' MoH data in Israel shows that 73% of PCR + tests are on people with no symptoms, i.e., not infected. So this paper is actually saying that the risk of infection for vaccinated vs. recovered is between 27X to Infinite X.
On 2021-09-01 03:04:45, user bgoo2 wrote:
To all the people commenting on this article who have no idea how to critically evaluate study methodology.... let's just skip over the lack of control variables and omission of addressing the Santa's naughty list of biases.
Let's just get right to the bones of it... while you are searching for your "natural immunity" as opposed to vaccination (how did that go with Polio, by the way? And Tetanus? And Rubella? And Hepatitis? ... hint: those vaccines came out before the Twitter era) ... where the FAHQK do you intend to keep the millions of symptomatic infected people who require hospitalization while they recover?
How did that work out in 2020? How is that working out now? Every whack job shouting about natural immunity doesn't seem to acknowledge that to get there... you have to sacrifice a whole lot of people who would've otherwise been protected by a vaccine.
Alabama USA has less than 5 million people. 38% of the population is double vaccinated as of August 31. Nearly 2500 people are in hospital with mild to severe Covid symptoms.
Ontario Canada has 15 million people. Triple the population. 67% double vaccinated. Less than 350 hospitalized.
We can repeat these comparisons across the globe. The results of this years' vaccination program is completely undeniable.
The results in an under-vaccinated population is undeniable.
Thankfully, each day, the percentage of unvaccinated grows smaller and smaller.
And it is very quickly isolating who the remaining lunatics are in your community. (hint: they're ironically usually the ones who clearly have trouble saying NO to refined carbohydrates)
Literally, that's the end of the story.
On 2021-09-04 14:10:39, user criticalscientist wrote:
It is likely that emergence of the Delta variant, which has 10 mutations in the spike protein, is due to leakiness of the mRNA vaccines based on the single spike antigen. I more worry about the Mu variant that appears to be completely resistant to monoclonal antibodies. Time to develop new vaccines using multiple viral proteins or develop an "attenuated" virus mimicking natural immunity.
On 2021-09-09 04:36:47, user Salvatore Chirumbolo wrote:
Dear Colleagues, my congratulations for this valuable and excellent paper. With a Colleague of mine, Sergio Pandolfi (Rome) we too addressed the topic of natural immunized subjects against SARS-CoV2 (see Pandolfi S, Chirumbolo S. On reaching herd immunity during COVID-19 <br /> pandemic and further issues. J Med Virol. 2021 Sep 7. doi: <br /> 10.1002/jmv.27322. Epub ahead of print.) but we highlighted also the controversial issue of the immunization route, i.e. mucosal versus intramuscular, I mean sIgA-B cell mediated respect to a DC-mediated immunity towards the IgGs production, with obviously different B-cell memory. Do you think that this is one of the major differences between immunized vs vaccinated people? And if serum anti-RBD IgGs are the only clue for evaluating immunized people, why a "certain" discriminating attitude exists towards natural immunized subjects respect to vaccinated ones?
Many thanks in advance<br /> Regards<br /> SC
On 2021-09-09 13:13:01, user Wolfgang Birkfellner wrote:
sorry, the comment referred to another paper ... my bad ...
On 2021-09-10 07:18:00, user Jim Ayers wrote:
I hate to ask a dumb question but did the study include people with long haul covid and people who died? Quoting the study '46,035 persons in each of the groups.' The fraction of a percent who died or the few percent who have long covid who may feel too sick to participate in a study could invert the study if not accounted for since they have been weeded out of the cohort and need to be adjusted for. This study could be 100 percent wrong if the up to 20% who have long haul covid aren't participating.
On 2021-08-26 10:17:10, user Ollie wrote:
This might be an interesting approach. However, something is worrying me:<br /> 1/ The first equation in this paper "r*dr/dt = ..." is not derived, just presented as a citation from a book consisting of 304 pages. A book that is not readily accessible lest one borrows or buys it. The reader thus cannot understand the validity of this equation. The number of open and close brackets is not equal, which implies that the citation is incorrect. Further, it is a pity that parameter e_s(T_a) in the equation is explained in a slightly sloppy manner by omitting the subscript a for T in the text.<br /> 2/ The second equation is stated by the authors, rather than derived from hypotheses. A derivation seems relevant here, as the intuition of the reader (at least mine) tells him or her that the relationship between evaporated volume and surface area reduction of spherical drops is only linear for evaporation that causes very little radius decrease, or in other words: only for evaporation (dV) where dR<<r, where="" dv="the" evaporated="" volume,="" r="the" initial="" radius="" of="" a="" droplet,="" and="" dr="" the="" change="" of="" r.="" if="" this="" intuition="" is="" correct,="" it="" should="" be="" evaluated="" why="" the="" indicator="" air="" drying="" capacity="" is="" indeed="" relevant,="" as="" it="" is="" likely="" that="" in="" a="" given="" timeframe="" for="" some="" drops="" who="" evaporate="" only="" slightly="" dr<<r="" indeed,="" but="" for="" other="" droplets="" dr="R" (complete="" evaporation).="">
On 2021-08-26 16:24:55, user Felix Poppelaars wrote:
This preprint has now been published in the peer-reviewed journal Scientific Reports:<br /> https://pubmed.ncbi.nlm.nih...
On 2021-08-26 18:46:13, user vicweast wrote:
If a vaccinated person contracts covid-19 (breakthrough infection) and their symptoms do not include symptoms like coughing/sneezing... are they as contagious as a person who has coughing/sneezing symptoms? This is what I am not reading anywhere, and yet it seems to be exactly the point.
On 2021-09-05 11:40:00, user OverSpun wrote:
The term "infected" appears to translate in this article to the presence of virus (detectable SARS-Cov2 at Ct<25) rather than the presence of the disease (i.e clinical manisfestions of COVID-19). Chronic carriers of other pathogens such as Staphylococcus are sometimes referred to as "not infected".
Beyond the cellular pathophysiology of bacteria vs virus, this is more than linguistic trivia because it challeges the assumption that SAR-Cov-2 asymptomatic carriers are in a transient subclinical state rather than chronic carriers. If such chronic carriers exist, are they more likely to have been vaccinated or obtained their partial immunity from a live virus infection, i.e. an acute case of COVID-19?
The following quote from this article highlights the importance of determining if mRNA vaccines have the potential to create chronic carriers: <br /> "Notably, 68% of individuals infected despite vaccination tested positive with Ct <25, including at least 8 who were asymptomatic at the time of testing."
Clinical management and public health policy require confirmation that all asymptomatic carriers are eventually clear of SARS-Cov-2 and any causative relationship between the vaccine and such carrier state is well undestood.
On 2021-08-29 16:06:28, user Paul Wolf wrote:
I wonder if the infectiousness of the delta variant could be a blessing in disguise, if it dominates over other, potentially more dangerous variants.
On 2021-08-29 19:50:51, user Yvonne wrote:
Based on Pfizer (6 month) study, the vulnerable started getting vaccinated on a great scale in February (USA) if you add 6 months that would put that vaccinated population at August, therefore the question would be asked, once the 6 month time frame of those vaccinated within a specific period, be deemed “unvaccinated” come August? With increasing spike cases/hospitalization in August (USA) and the term “unvaccinated” being used, who are within the description of “unvaccinated”, those never getting a vaccine? Or would the term include those who were vaccinated and now have passed the 6 months? I think August would be more of a complete study, if the term “unvaccinated” group is clearly defined. That would require maintaining that data, tracking the expiration of the 6 months when those vaccinated are spiking in cases. While this is helpful, the public should be shown how the spikes are increasing in August for full transparency and even comparison.
The next spike of population vaccinated in April 2021 (USA) will hit the 6 month cycle in October. Therefore December will show if the spikes in November are from that vaccinated group.
On 2021-08-31 15:57:16, user leoniehaimson wrote:
Did you project what weekly testing of 100% of students would achieve in terms of infection reduction?
On 2021-09-01 20:00:22, user Peter Hanse wrote:
This should be checked against "Experimental investigation of indoor aerosol dispersion and accumulation in the context of COVID-19: Effects of masks and ventilation" Physics of Fluids 33, 073315 (2021)
On 2021-09-07 15:50:49, user Zach wrote:
Im confused if it doesn't reduce death significantly statistically and increases serious adverse events by double. Why is this being pushed as effective or safe? This data proves both to be wrong. If your chance of death is unchanged and your hospitalization rate is nearly doubled it literally makes no sense to take this. What am I missing?
On 2021-09-09 11:59:48, user Mohammad Ali wrote:
Please find the published version here: https://link.springer.com/a...
On 2020-04-22 20:36:24, user Konstantin Momot wrote:
The crucial issue here is sample selection. The participants essentially self-selected, but that is a potential source of huge bias. As a hypothetical scenario, if the people who chose to participate were predominantly people who’d had a cold and were curious to find out if it was COVID, then the cohort would a priori be hugely overweight with people who had a higher-than-average likelihood of COVID exposure. That would not be a good sample of the general population in that it would not represent the true percentage of CoV-exposed and CoV-naive people in the population as a whole. That would mean that the 2-4% figure is completely meaningless. Given how crucial this number is to any epidemiological modelling, I think it's important to remember that this is just one study with no guarantee of flawless methodology, and avoid making far-fetched conclusions based on limited evidence.
On 2020-04-23 17:56:51, user Fiona Mulvey wrote:
Does anyone know if Stanford have made any statement on this? It seems to have been uploaded the day after their weekly townhall discussions on COVID-19, and I'm hoping there'll be another one today where they'll address this, here: https://med.stanford.edu/co...
On 2020-04-23 18:41:00, user Young-In Kim wrote:
It’s not going to get peer reviewed well just like the studies on hydrochloroquine. That’s not a sample to apply to the whole population when we have data from all over the world. It’s picking and choosing data. I might well take my sample from worst hit parts of NYC n Italy to prove a point.
On 2020-04-23 18:52:50, user Deplorable Kev wrote:
So they tested for IgG antibodies in the population and found a high number of persons already had been exposed and likely immune. Interesting, but that depends on if their assay cross reacts with US Coronavirus and if so, then this is not correct. If their test is specific for COVID-19 antibodies then he is correct. PS: I believe it was here much earlier and we saw cases as early as mid November. Most of this early antibody testing has not been evaluated for cross reactivity yet.
On 2020-05-16 23:36:43, user PANAGIOTIS AMPATZIS wrote:
There is a hit piece from Buzz Feed news (I know lol) that says the Jet Blue founder (and anti lockdown proponent) gave 5000$ to the study to influence it. They make a huge deal out of it, so please release the full amount of the funding as an answer to show them that 5000 dollars is a small amount to make the study unreliable.
Keep up the good work
On 2020-04-20 20:43:45, user Kenneth Melendez wrote:
So what these people are saying is that if you did the study LAST year, that you would get .5% false positives, about 10K people if you tested all of Santa Clara. You should declare them to be asymptomatic cases, and say that there are 9.5 times the number of asymptomatic cases as confirmed cases in Santa Clara. Time to call the media.
And if you want to believe their results, then you surely want to believe the that the false positive rate (1-specificity) was accurately determined by 2 false positives out of 371 tests of old (assured non-infected) samples.
On 2020-04-20 22:26:21, user Andy wrote:
Preliminary results of USC-LA County are out. Unfortunately, that study also suffers from self-selection bias. We need to know how many people were contacted initially; should we count those who declined to participate as presumed negatives?
In the Santa Clara study, people were contacted initially through Facebook. We need to know how many people saw the ad, and should we also count those who declined to participate as presumed negatives? (Surely the authors know how many people saw the Facebook ad.)
Edit to add: Wait a minute, I just saw comment by Anon who participated with a link but without Facebook. So the study is even more flawed.
On 2020-04-20 23:15:57, user Yaud Xatrixer wrote:
What is the maker of the testing kit? What was the specificity of it?
On 2020-04-21 20:29:57, user rerutled wrote:
The Santa Clara results calibrated the test using known gold-standard "negative for covid19" blood. They had 401 "pre-covid19" samples; of those, 2 resulted in "positives". Thus, the test produces a "false positive" rate of 2 out of 401.
They gave the test to 3330 people, and 50 of those tests returned positive. How many of them can be produced by the observed "false positives"?
On average, for a sample of size 3300, one expects approximately 3330*(2/401) = 16.6 false positive results. Is that statistically significantly different from the 50 detected? It depends on what the uncertainty in that "16.6" is. Playing fast and dirty, take the Gaussian uncertainty in that false positive rate to be fractionally, 1/sqrt(2) = 0.70. So the false positive rate is 16.6+/-11.7. Which means, the 50 detected is only (50-16.6)/11.7 = 2.9 sigma above the false positive rate.
Nobody in science should claim a detection which is only 2.9 sigma different from the false positive number. This result is not significantly different from NO DETECTION of positive anti-bodies.
It's even worse than that, though, because I used the Gaussian uncertainty; and as you know - since you have taken an undergraduate class in statistics and understand the binomial, poisson, and Gaussian distributions - the Gaussian approximation isn't accurate for this situation, and one should use the Poisson distribution, or better yet the binomial distribution; but, again, because of that undergraduate class, you remember that both the Poisson and binomial distributions have a broad wingy excess in the higher direction above the mode; which means, the significance of even the detection of ANY positive covid19 antibodies in the Santa Clara County results is even LESS significant than 2.9 sigma.
The authors of this result should answer this criticism, stating what they believe to the the probability of detecting 50 positive results among 3330 tested, given their measured false positive rate.
On 2020-04-22 16:02:39, user Texas Longhorns wrote:
The research paper does not indicate how many of those that participated had already been tested for Covid and what those test results were.
If they over sampled people that had already tested positive and recovered of course you will get a higher rate of positive antibodies. That would not be indicative of the general population.
There is also the problem of false positives because the test can trigger for the common cold that is also a coronavirus.
I don't think this research passes muster as any reliable indication of antibodies in the general population and should absolutely not be used as a basis to reopen businesses and large public gatherings.
Having antibodies to one strain of the virus may not give you any immunity to the more than 8 strains of Covid we know are out there.
Even if the test results are accurate at 2% that is nothing and you need at least 60% solid immunity to consider any large population to have herd immunity protection.
On 2020-04-17 22:20:15, user Teddy Weverka wrote:
To take this test, people had to violate the ORDER OF THE HEALTH OFFICER OF THE COUNTY OF SANTA CLARA DIRECTING ALL INDIVIDUALS LIVING IN THE COUNTY TO CONTINUE SHELTERING AT THEIR PLACE OF RESIDENCE EXCEPT FOR ESSENTIAL NEEDS. What do you bet that people willing to violate that order have a higher prevalence of covid-19 antibodies? The paper ought to mention this source of bias.
On 2020-04-18 14:47:42, user Chris S wrote:
Were participants asked if they had been tested? If so, could the rate of actual COVID-19 testing among participants relative to the general population (at the time of survey) be used to assess ascertainment bias?
On 2020-04-19 03:40:52, user disqus_B1vk25qxNZ wrote:
Possibly other coronaviruses that the population has been exposed to confer cross immunity to SARS-CoV-2. If so, the benign virus could be a vaccine analogous to cowpox and smallpox.
On 2020-04-22 22:06:16, user Marie Benz wrote:
Table 2 discrepancies which favored the non-treatment group, lack of randomization, lack of information on when treatment was begun as well as lack of number of doses completed make this paper unable to be interpreted since it is being heralded by news media as demonstrating that such treatment has now been proven ineffective. Clearly the jury is still out but the authors owe it to the country and the scientific community to point out in the media that this is not enough to conclude that HC or HC + AZ is ineffective or dangerous and that present therapies should not be altered one way or the other based on this report.
On 2020-04-23 21:23:57, user Benjamin Goldhagen wrote:
There were dozens of comments here this morning. Where can they be found?
On 2020-04-24 01:46:41, user Mike wrote:
Note: the original version has been previously discussed at length. medrxiv is redirecting that paper to v2 (this paper), making those comments are no longer available. This is a link to those comments: https://disqus.com/home/dis...
Below is my original comment with updates for this version of the paper
This was certainly an interesting paper. They’ve done a lot of work and the findings are notable. IMHO it warrants as much attention as the original pro-HCQ study via Dr. Raoult (~3/15). While it is entertaining, I will add that it is not conclusive, nor without fault. A double-blind study is still required.
It is important to note that this is version 2 of a previously released paper and it is much the same, with no major differences in the conclusions reached compared to v1. Therefore, my previous comment still holds true. Below I’ve included them followed by a new list of observations.
Observations/Questions (updated)
1. "hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease” (p.12)<br /> 2. “as expected, increased mortality was observed in patients treated with hydroxychloroquine, both with and without azithromycin” (p.12) — I assume it’s expected because the patients given drugs were in a more severe state (and more likely die regardless of treatment)<br /> 3. "we cannot rule out the possibility of selection bias or residual confounding” (p.13)<br /> 4. demographic: 100% male, 66% black, median age ~70 (59 youngest); (Table 2, p.17)<br /> 5. uses PSM, which despite a common practice, could be considered controversial (https://gking.harvard.edu/f... "https://gking.harvard.edu/files/gking/files/psnot.pdf)")<br /> 6. Unless I missed it, I didn't see any specifics about how the treatments were administered.<br /> - How long before death were patients treated?<br /> - What was the quantity/frequency/duration of the treatments?<br /> - Were the treatments consistent between hospitals?<br /> 7. The rate of ventilation was less in HC+AZ (half of the HC and no-HC rates). Why was that? What does that suggest?<br /> 8. Although they were statistically insignificant, what was the result of the 17 women not included in the study?<br /> 9. Why does the paper seem to address political points? It seems like the Abstract is editorialized, which I'm not used to. The result seems to address topical issues of the times, having awareness of other similar studies being conducted, rather than a standalone independent study of its own. I interpret this as potential for some analysis/deciphering bias. I don't mind in the Discussion sentence as it's normal, I'm just not as accustomed to seeing it in the Abstract.
New List of Observations
1. There seems to be some bias in the number of healthy people with no-HC treatment, but left in the study. Those people are going to be unlikely to die to begin with. This is not a comparison of apples to apples.??
To clarify:<br /> ?- Dramatic difference in percentage of people people that had fever temperatures (38.1-39.0ºC / 100.58-102.2ºF); HC:11.3%, HC+AZ:11.5%, no-HC:7.6%. There’s ~4% difference between treated and untreated fever temps (more likely to die) in favor of untreated cohort. ?<br /> - Compare that with the percentage of people that had normal temperatures (35-37ºC/95-98.6ºF);HC:56.7%, HC+AZ:52.2%, no-HC:61.4%. There’s a 5-9% difference between treated and untreated normal temps (likely to not die) in favor of untreated cohort.
??So in this study, there was a larger proportion of people that did not have fevers, suggesting the data may be padded. In absolute numbers it's approx. a 40 person swing, which is a fairly large percentage in such a small study/survey. Similar observations are for systolic blood pressure and breaths per minute. There appears to be more healthy people? again.
2. Creatinine is created when muscles breakdown creatine. It’s a waste product removed by the kidneys. Levels are elevated when the kidneys begin to fail. Notice, there’s a much larger presence in the HC-groups, which suggests there was a larger percentage of these patients experiencing kidney failure.?
3. There are an awful lot of missing data in solely the no-HC group for statistically significant criteria. For instance Erythrocytes (red blood cells that transport oxygen), there 11.4% (!) missing in no-HC patients, yet that category has a P-value of 0.001 (<0.05 is statistically significant).??
Hermatocrit is the same way (missing 11.4% for no-HC). It’s also related to red blood cells, it is the ratio of red blood cells to the blood volume. Same missing amount for Leukocytes (white blood cells) test. And also Lymphocytes —white blood cells in lymphatic system, which transports fatty acids from the digestive system and white blood cells from the lymph nodes into the bones— not only has a lot of missing data, but the disproportional low count (<800 per mm^3) may warrant further investigation.
4. Even looking at the statistically significant Cerebrovascular disease, there are a much larger percentage of HC-only patients per its cohort.?
5. Table 4 describes a greater percentage of people using HC+AZ being discharged (recovering) w/o ventilation; 5% more than no-HC patients. Keep in mind that 30% of the no-HC patients were given AZ.
On 2020-04-28 00:30:59, user Mark Reeder wrote:
I am advocating that the authors, in the interest of public health, fill in the blanks of the following statement:<br /> "It was found that ___ of the 7 patients reclassified from the 'No HC' to the HC group (after ventilation began) died. Likewise, ___ of the 12 patients reclassified form the 'No HC group' into the 'HC+AZ' group died."<br /> Based on a comparison of Tables 4 and 3, the first blank must be either 6 or 7 whereas the second blank must be between 7 and 12, inclusive.
If the groups are compared based on whether they were given the drug(s) PRIOR to ventilation or prior to discharge, the HC+AZ is better by either a 20% margin over the 'No HC' group or by a FACTOR of 6. <br /> To wit, let's assume that all 12 of reclassified as HC+AZ died. That would mean that only 2 in the original HC+AZ group died. Since we have no idea when the HC+AZ drug was administered to those who died without ventilation, a fair comparison would show that HC+AZ, one might justifiably count only the 2/90 (2.2%) in that group (excluding deaths w/o vent.) as having had HC+AZ early enough in treatment. It would also mean that 3+(6 or 7) + 12 out of 162 (13.6%, also excluding deaths prior to ventilation) eventually died. <br /> This would be a huge difference with HC+AZ coming out as a terrific alternative (factor of 6 better) if given early enough. By the same logic (pre-vent treatment only, excluding non-vent deaths), the worst case for HC+AZ would still mean a 20% IMPROVEMENT over the control group! <br /> But we cannot know unless the authors (or others) are ethical and transparent enough complete the sentence above. Even if they disagree with the foregoing analysis, what is the downside in providing those numbers?<br /> I understand the difficulty of dealing with imperfect data. But for that very reason, good science demands that all information be placed on the table.
On 2020-04-22 00:53:03, user Mike Cee wrote:
This paper is flawed and should be withdrawn immediately.<br /> 1) This paper is flawed due to the limitation discussed on page 12 about the likelihood that the HCQ group, "However, hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease, as assessed by baseline ventilatory status and metabolic and hematologic parameters."<br /> Doctors working the front lines have already noted that patients at SYMPTOMS ONSET + 14 days should not be prescribed HCQ<br /> 2) The important grouping by number of days since SYMPTOM ONSET was left out of this study. Previous studies, while anecdotal, suggest that patients should be prescribed HCQ early because it is believed to prevent the virus from infecting the type 2 lung cell through the ACE2 receptor and thus stops the progression of the disease.<br /> 3) This study did not document the dosage given to the patients. That would have been a helpful inclusion so we could understand if the patients who died were actually poisoned by excessive the treatment.<br /> 4) HCQ prescribed in patients in the first week after SYMPTOMS ONSET to include a zinc supplement which anecdotal evidence suggests a dual function of the combination: The HCQ provides an avenue for the zinc to enter the Type 2 lung cell where it interferes with the virus replication process.
On 2020-04-22 03:32:32, user Cheri Trigg wrote:
According to MedCram Zinc is what actually helps. Chloroquine is how the zinc gets into the cells. MedCram is a medical journal on Youtube. Update #32 and 34 go into depth on this. It is tragic to use a medication meant as a delivery system and not use it to deliver. Not sure to laugh or bawl. I hope the word gets out to use zinc before the zithromyacin at least.
On 2020-04-23 08:03:58, user excivilservant wrote:
I'm amazed nobody has commented on this, given the mass of media coverage about tracing and testing. Isn't a fairly obvious point that the model on social interaction is based on a pre-virus, no restrictions world. That's not the world we will be in for the coming months at least. Many/most/all hospitality businesses will be closed and these are the places where one would imagine a substantial number of social interactions occur, especially ones that widen the social circle beyond family and close friends. The survey data underlying the model will have the details. Even leaving aside formal restrictions, a lot of people will be acting in a much more conservative way about going out and about. Numbers travelling by train, tube and bus are likely to be greatly reduced. Again, the model could be adjusted, or a sensitivity test done. So the efficacy of tracing should be much greater than the article implies - or, put another way, the effort required to trace people should be a lot less, as there will be a (much) lower average number of contacts. No doubt the authors are actually on to this, but I thought I should point it out anyway.
On 2020-04-25 13:53:09, user Rosemary TATE wrote:
Since this is an observational study, and you answered yes to "(I have) uploaded the relevant EQUATOR Network research reporting checklist(s), could you please explain why you have not uploaded the STROBE guidelines? So many people are doing the same and I'm wondering why. I'm trying to think of ways of improving the process of sorting the wheat from the chaff in this explosion of preprints. While this looks like wheat, it would be really helpful if you could<br /> 1. State the type of study in the title (some journals require this and it is very helpful)<br /> 2. Upload the checklist.<br /> Many thanks.
On 2020-06-10 21:34:06, user DFreddy wrote:
Table 1 is missing? Also in additional material, an empty file
On 2020-04-26 15:17:51, user peopletrees wrote:
Can you post the r script that you wrote in order to process and analyze this data? I'm particularly interested in the rstanarm model specification.
On 2020-04-27 03:28:31, user Sam Leumas wrote:
How was the data even collected? Veracity of this information?How can you tell if the contracted virus is from within house, transport area,outdoors,malls etc? Common sense tells stagnation of air is a probability but still,seems like there is a major flaw in the data collection process.
On 2020-04-10 16:34:41, user Brian wrote:
this looks at "3 or more case outbreaks" if outdoor spread is happening it's probably on a smaller scale, as people are out less.
On 2020-04-28 13:51:34, user alasdair hay wrote:
I am not convinced this paper provides any evidence on the safety of HFNC in respiratory infections. My understanding is the study shows similar number of respiratory particles were measured in all conditions from breathing air to any 02 device or coughing.
I would be more reassured if the articlce demonstrated an increased number of respiratory aerosol particles with some airway devices or proccedures but not HFNC. In fact there is no control demonstrating the SMPS aerosol measurement probe detects respiratory droplets. The only particles the probe appeared to detect were produced by a candle. If the probe is picking up a background number of particles in the air and those produced by a candle it is not picking up anything of medical interest
On 2020-05-01 09:48:59, user Kasper Kepp wrote:
This paper on the state-of-the-art Danish blood-donor data finds a IFR = 0.08% for people between 0-69 years of age. The study is very important because the sampling bias from case fatality ratios (the iceberg effect of knowing almost all deaths but only the most symptomatic cases, i.e. missing the dark number) is largely removed.
By interpolation, the Danish population now has approximately 1.6% infection, corresponding to 100,000 people out of 6 million. The dark number stands at 12-fold the known cases (7-18).
Some minor sampling biases remain (people who are blood donors need to be healthy and may be socioeconomically skewed) but considering the wide blood donor representativeness in Denmark, I think all Danish researchers will agree that sampling bias must be small.
The IFR is also fully in line with the most representative data we have from Iceland (14% of population tested, 48000 tests), where the sampling bias is essentially eliminated, which stands at approximately 0.56% (10 deaths / 1799 cases as of May 1) and includes all the high-risk individuals >70 years. https://www.worldometers.in...
Compared to the Santa Clara study, which caried potential major sampling bias, this issue seems to be now largely removed. Consensus in Denmark is now emerging that the overall whole-population crude mortality of covid-19 is of the order of 0.25-0.6%, in excellent agreement with the Iceland data.
These two countries have not have their health care systems strained, making them the relevant data also for this reason for pinpointing the "real" mortality of covid-19 absent overmortality by capacity exhaustion as seen in some other countries.
Obviously, the fact that the IFR is 0.08% for the 0-69 year old has enormous implications for political decision making in Scandinavia, as it evidences that most of the population can build immunity at much reduced mortality than previously assumed.
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).
On 2020-05-03 19:00:29, user John Goodrich wrote:
So the WP has now written about the data from this Yale group. Where’s the report of the study, with the actual data?
On 2020-05-04 00:02:15, user Kyriakos wrote:
On 2020-04-06 17:15:59, user Matheus Macedo-Lima wrote:
It seems to me some of the countries used in this analysis are still under-testing (Brazil, USA etc). Would a more suitable dependent variable be deaths/confirmed COVID cases?
On 2020-04-17 21:15:41, user Carlos Alejandro wrote:
Panama has the highest mortality per capita in the whole of Latin America and vaccinates with BCG.
On 2025-08-21 08:10:06, user Taukim Xu wrote:
Comments from the authors-01:
Since the preprint was made available, we have been honored to receive numerous publication invitations from various journals. We would like to express our sincere gratitude for your interest and recognition of our work.<br /> However, we feel it is important to clarify that this manuscript is currently under consideration at another journal. Therefore, we are unable to submit it to your publication at this time.
Dr. Taukim Xu
On 2025-10-18 04:34:17, user CDSL JHSPH wrote:
Hello!
Thank you for sharing this preprint. I found it very interesting, and I believe this is an excellent contribution to improving statistical approaches in antibiotic trial designs. I believe that the comparisons between MCP-Mod and Fractional Polynomials (FP) models provided a very strong case for adopting model-based frameworks to more accurately identify duration-response relationships and estimate the Minimum Effective Duration (MED). I also believe that the demonstration of these methods outperforming traditional pairwise comparisons, particularly in smaller sample sizes, helps highlight the potential to make trials more efficient without compromising reliability and ultimately the patient.
I also appreciate how you clearly discussed the limitations of traditional methods and how there is a need to move towards more model-driven designs. The emphasis on the simulation as a proof-of-concept framework was well-structured and persuasive. I think it would be very interesting to see how these approaches would perform under real clinical data. This is where patient adherence, comorbidities, and variable response rates could truly test the robustness of these models.
I think that in future works, expanding on various factors like dose-spacing, variability in treatment adherence, or non-monotonic response patterns that affect model performance could help further strengthen the clinical applicability of your framework. Overall, I found that this paper sets a solid foundation for refining antibiotic trial methodologies, and also bridges the gap between statistical modeling and real-world trial optimization.
On 2025-11-17 18:55:33, user David Stapells wrote:
Interesting.
Small comment:<br /> Rather than head size explaining larger amplitudes in females, Don and colleagues suggest cochlear travelling wave differences:
Don, M., Ponton, C.W., Eggermont, J.J., Masuda, A. (1994). Auditory brainstem response (ABR) peak amplitude variability reflects individual differences in cochlear response times. J Acoust Soc Am, 96, 3476–3491.<br /> Don, M., Ponton, C.W., Eggermont, J.J., Masuda, A. (1993). Gender differences in cochlear response time: An explanation for gender amplitude differences in the unmasked auditory brain-stem response. J. Acoust. Soc. Am., 94, 2135–2148.
On 2025-11-30 14:34:14, user Jeff Lubell wrote:
This article has now been published in a peer-reviewed journal. Please use that version. Thank you. Here is the citation: Torok RA, Lubell J, Rudy RM, Eccles J, Quadt L. Variant connective tissue as a risk factor for long COVID: a case-control study of data from a retrospective online survey of adults in the USA and UK. BMJ Public Health. 2025 Sep 17;3(2):e002949. doi: 10.1136/bmjph-2025-002949. PMID: 41001233; PMCID: PMC12458677.
On 2020-04-20 18:14:27, user Wladimir J. Alonso wrote:
Not being temperature-dependent does not imply that it might not be seasonal. For instance, in equatorial regions seasonality of influenza is driven by the rainy and dry seasons, not temperature (see references below).
Tamerius J, Nelson M, Zhou S, Viboud C, Miller M, Alonso WJ. Global Influenza Seasonality: Reconciling Patterns Across Temperate and Tropical Regions. Environ Health Perspect. 2010
Alonso WJ, Viboud C, Simonsen L, Hirano EW, Daufenbach LZ, Miller MA. Seasonality of influenza in Brazil: a traveling wave from the Amazon to the subtropics. Am J Epidemiol. 2007;165(12):1434–42.
Alonso WJ, Yu C, Viboud C, Richard SA, Schuck-Paim C, Simonsen L, et al. A global map of hemispheric influenza vaccine recommendations based on local patterns of viral circulation. Sci Rep. 2015;5:17214.
On 2020-04-01 18:46:10, user Miklos Kertesz wrote:
Does this modeling shed any light on the approximate number of those who have been infected, and are now presumably immune?<br /> Your curves fall off quite fast. Is this realistic?
On 2020-04-04 21:18:14, user Lucy Branum wrote:
Does this data reflect the lack of PPE for healthcare providers, and other essential workers? I appreciate that is a difficult factor to quantify, but if your healthcare providers are becoming infected and therefore spreading the virus to others, and becoming ill themselves, I would have to assume that would have a massive impact on the trajectory of the curve.
On 2020-04-05 15:41:10, user Art Mills wrote:
This was supposed to be updated yesterday and had a notification it was to be, then after the daily press conference, suddenly was not updated and the notification it was to be updated was removed. Why?
The ICU and Vent numbers in the model to support the 93K deaths by Aug. 4 are off by a factor of 10 (meaning they have modeled far too high). The update yesterday should have brought those lines down. Why would we not update to reflect a line closer to the actual numbers?
On 2020-04-06 07:06:24, user Tom T Walker wrote:
Many of the State projections radically changed when updated 4/5. For example Colorado's peak date went from 4/17 to 4/4, hence an ICU deficit of 762 to a surplus of 421. Other states had similar swings in the opposite direction. Wondering if there might have been some data entry issue. Is Colorado really suddenly 1-day past it's peak date?
On 2020-04-07 07:38:54, user dreich wrote:
Every place in the US is significantly under-testing.<br /> This means that the infection rate is underestimated.<br /> And because there aren't enough tests almost no post mortem tests on performed for any deaths.<br /> This has the "advantage" of under-counting the number of fatalities which makes the organized incompetence (intentional or otherwise) seem less bad. The bigger the number the worse it looks for the guilty politicians.
On 2020-04-10 13:51:26, user steve rubin wrote:
Does anyone know peak hospitalization during the 2017-2018 flu season? From the cdc summary there were 808,000 total hospitalizations with 61,000 deaths and I remember the flu season was pretty long. I wonder how the curves for new cases, deaths, hospitalizations and icu use looked. I remember stories that the hospitals were crowded but I don't remember stories about people dying because there weren't beds or ventilators.
I know that it's unpopular to compare coronavirus to the flu. Underestimating a threat is dangerous and could (and maybe did) lead to delay in ramping up testing and beds and ventilators and other necessary medical resources.
When people were predicting 2,000,000 deaths in the US and then 200,000 deaths I could understand the fears. But now they're predicting 60,000 deaths and it may end up half of that, so I think it's reasonable to make the comparisons.
Comparing situations to past situations is usually our best way to understand how to react. In terms of how contagious and how lethal this epidemic/pandemic is, it now seems that it and the flu are similarly contagious and that covid is much less lethal. The big difference is that we have a pretty big number of people with significant immunity to the flu while it's likely there was little immunity in our population to covid-19. If we end up with 200,000,000 people becoming infected but with only 60,000 deaths, then covid was a fifth as lethal as the flu for 2017-2018 with 3 in 10,000 infections dying vs 14 in 10,000 infections dying from the flu.
However the comparison to the flu can lead to some counter-arguments. For example, the cdc uses a multiplier of ~80 for estimated current flu infections vs confirmed flu infections. Applying that to covid-19 means that we have ~500,000 confirmed cases so we would have had 40,000,000 total infections leaving another 160,000,000 to go assuming 60% of the population for herd immunity. Projecting deaths would mean 17,000 + 68,000 for a total of 85,000. We'll soon know what that multiplier is for covid-19 because there are a number of antibody surveys going on in the US and internationally. You can bet that the same thing will happen for the flu next year and we'll have a more accurate estimate of infections and lethality for the flu rather than the current guesstimates.
A big question is how social distancing will have affected the final number of infections and deaths. It seems so logical that social distancing will curb infections and deaths, but many suggest that it may end up only prolonging the length of the pandemic while not making a significant difference in total final infections and total final deaths. The antibody tests may give us the answer to that as well.
On 2020-04-17 17:15:59, user Susan N Dallas wrote:
Did we give up on the projections? Where is the last 5-6 days of data?
On 2020-04-22 08:47:13, user Katri Jalava wrote:
This is a really interesting study from the environmental epidemiology perspective. However, the authors fail to present some of the key findings they surely have. The clinical presentation of their cases is "not interesting", as they are anyway, typical Covid-19 cases, that could be shortened. You could also try to get some of your food control experts as authors, they might be able to give you good clues about the potential spread modes with employees and hygienic situation in the supermarket. Also if one of the epidemiologists from China-CDC would help you to clear the epidemiological messages, that would be useful. Your current conclusions are "not really interesting".
If possible, it would be very important to know how many customers were screened, at which time points? Also the time line for the employees when they were at work and when did their symptoms begin, ie. how long they were working while infectious? What type of supermarket this was, how much selling, customer profile? Also the description of the supermarket employees job duties, were they at the cashier, providing meat or other over-the-counter food etc.? How many children were exposed either as case household contacts or in the supermarket?
You should try to follow up the asymptomatics. How many of them went on to develop symptoms, even mild? If not, please state the follow up and initial examination date. Comparison of clinical symptoms between groups A and B is not really interesting (you could just state in your text that the groups did not differ, data not shown), but comparison of symptomatic vs. truly asymptomatic might be. However, there is plenty of studies on that and unless you detect something extraordinary, that is of interest. Were your cases really 48 year old, plus minus 2 years, ie. 46-50 year old. All of them? What were the isolation (cases) and quarantine (close contacts, yet not symptoms) measures, please describe and how this succeeded. Did you consider (or would you do a next study) to do serological survey among all cases, their close contacts and supermarket customers to see if they had SARS-CoV-2 antibodies?
Thanks for submitting this, this is a really nice and interesting study. Looking forward for the final paper.
On 2020-04-07 16:22:04, user Kevin Niall wrote:
"All received standard treatment (oxygen therapy, antiviral agents, antibacterial agents, and immunoglobulin, with or without corticosteroids)"
This could play a huge part in the difference considering teh very small sample size and the difference of 8 patients.
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.
On 2020-04-13 18:44:19, user Ty Martin wrote:
Why CQ and not HQ which has been shown to be safer?
On 2020-04-07 19:20:32, user Andrei Drabovich wrote:
There was no experimental proof presented that these variants impact ACE2 structure or function in any way.<br /> It is also not possible that ~3% genotype frequency for women and 1.5% for men (1.5% allele frequency for p.Asn720Asp) will result in additional >6% lethality. Were would additional 3-4.5% come from?
On 2020-04-08 00:15:34, user Sinai Immunol Review Project wrote:
Clinical features and the maternal and neonatal outcomes of pregnant women with coronavirus disease 2019
Keywords
Pregnancy, SARS-CoV2, neonatal and maternal Covid-19 outcome
Key findings
33 pregnant woman and 28 newborns were included in this retrospective multi-center study, conducted at 5 hospitals in Wuhan and Hubei province, China, between January 1 and February 20, 2020. All women were diagnosed with Covid-19 by qPCR or viral gene sequencing based on the Chinese New Corona Pneumonia Prevention and Control Program, 6th edition, and were further subdivided into four groups based on clinical severity: (1) mild, presence of mild clinical symptoms without radiological abnormalities; (2) moderate, fever or upper respiratory symptoms as well as radiological signs of pneumonia; (3) severe, at least one of the following: shortness of breath/respiratory rate >30/min, resting oxygen saturation SaO2<93%, Horowitz index paO2/FiO2 < 300 mmHg (indicating moderate pulmonary damage); and (4) severe-acute, acute respiratory distress with need for mechanical ventilation; systemic shock; multi-organ failure and transfer to ICU. Maternal admission to ICU, mechanical ventilation or death were defined as primary outcomes; secondary study outcomes comprised clinical Covid-19 severity in both mothers and newborns, including development of ARDS, neonatal ICU admission as well as mortality.
Maternal characteristics and outcome: 3 out of 33 women were in their second trimester of pregnancy (17, 20 and 26 weeks), and 15/33 (45.5%) had a previous history of underlying chronic health disorders including cardiovascular, cerebrovascular or nervous system disease. Common Covid-19 symptoms at presentation were fever (63.6%), dry cough (39.4%), fatigue (21.2%), and shortness of breath (21.2%). Less common symptoms included diarrhea, post-partum fever, muscle ache, sore throat and chest pain. 4 (12.1%) pregnant women had no apparent symptoms. The majority of cases were classified as mild (39.4%) or moderate (57.6%); however, one woman developed severe Covid-19. 40.6% of women were diagnosed with bilateral pneumonia, 43.8% presented with unilateral pneumonia, and 15.6% showed radiological ground-glass opacity. 87.9% of women required oxygen administration, and one (3%) woman had to be put on non-invasive mechanical ventilation (primary outcome). 81.5% of women had a C-section and only 5% had vaginal deliveries. Obstetrical complications were seen in 22.2% of women, including three cases of preterm rupture of membranes, two cases of hypertensive disorders of pregnancy, and one case of spontaneous preterm labor. Five pregnancies were ongoing at the end of the observation point of this study; one woman decided to have her pregnancy terminated. Neonatal outcome: Out of 28 newborns included in this study, 35.7% were born preterm at <37 weeks of gestation with Apgar scores ranging from 8-10/10 at 1 min and from 9-10/10 after 5 min, indicating normal heart and respiratory rates. 17.9% of newborns were of low birth weight (not specified) and 14.3% showed signs of fetal distress (also not specified). According to the authors of this study, none of the newborns presented with clinical Covid-19 symptoms. However, one newborn, delivered at 34 weeks of gestation, was diagnosed with (apparently Covid-19 unrelated?) ARDS and transferred to NICU (secondary outcome). Of 26 newborns tested for SARS-CoV2, only one was found positive and showed radiological signs of pneumonia, but no clinical symptoms of Covid-19. It remains unclear whether this was the same case as the newborn diagnosed with ARDS. The affected newborn did not require any treatment and was discharged at 16 days post birth. In summary, the primary outcome “mechanical ventilation” in pregnant women was rare (3%), no other primary outcomes were reached. Most Covid-19 cases in pregnant women were described as mild to moderate. Only one of 28 (3.57%) newborns was diagnosed with ARDS (secondary outcome).
Potential limitations
Major limitations of this study are its small size and the rudimentary and at times inadequate description of patient specifics. For example, underlying health conditions that might be affecting Covid-19 outcome in pregnant women should have been clearly specified (other than being of be listed (not just <37 weeks). Given that maternal infection status seemed mostly unknown at the time of birth and, more importantly, that the majority of cases in this study were clinically asymptomatic or mild to moderate, it remains unclear whether the C-sections performed were a medical necessity or elective procedures. This is of importance and should have been discussed. With regard to neonatal outcome, it is also not apparent whether the newborn found to be infected with SARS-CoV2 and the case diagnosed with ARDS were the same individual. If this was the case, it would be incorrect to refer to all newborns as asymptomatic. Additionally, it seems somewhat unlikely that a newborn with a near-perfect Apgar score would present with ARDS immediately after birth. Likewise, any individual diagnosed with ARDS would certainly be expected to receive supportive treatment including (invasive) mechanical ventilation. While it is highly relevant that overall clinical outcome in pregnant women diagnosed with Covid-19 seems better than in SARS or MERS (as discussed by the authors), it nevertheless needs to be stressed that more than 37% of newborns in this study were delivered preterm and that the obstetric complication rate of 22% seems higher than non-Covid-19 average.
Overall relevance for the field
Observations in this study confirm some of the findings published in a case series by Yu N et al. (Lancet Infect Dis 2020; https://doi.org/10.1016/ S1473-3099(20)30176-6). However, due to the relatively small study size of 33 pregnant women and 28 newborns, this study lacks statistical power and final conclusions on Covid-19 outcomes in pregnant women and newborns cannot be drawn. Yet, the data collected here are important and should be incorporated into larger data sets for more insight. Understanding the clinical course and effects of Covid19 in both pregnant women and newborns is essential, and while there are some recent publications on vertical SARS-CoV2 transmission between mothers and newborns (Dong L et al, JAMA March 26, 2020, doi:10.1001/jama.2020.4621; Zeng H et al, JAMA March 26, 2020, doi:10.1001/jama.2020.4861) as well as on neonatal infection at birth (Zeng L et al, JAMA March 26, 2020, doi:10.1001/jamapediatrics.2020.0878), our knowledge of how these patient subsets are affected is still very limited.
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.
On 2020-04-09 07:07:30, user Daniel Corcos wrote:
This calculation is made by dividing the number of deaths by the number of days since the FIRST Covid death, and by comparing to the number of deaths per day by driving during the same period. This means that the death rate by day is diluted with the period of low mortality per day from Covid.
But the highest mortality per day is yet to come. And, already, social distancing has been implemented and has some effect.<br /> This means that there is no evidence to support the hypothesis that there is overreaction to the pandemic.
On 2020-04-17 14:53:53, user Petard Stamo wrote:
"Absolute risk" is a very good measure to quantify the probability of dying from cancer and heart attack but it doesn't capture the dynamics of an infectious disease. It doesn't capture transmissivity. I am sure other people will find other features of an infectious disease that are missed with the "absolute risk" analysis. It has very complex dynamics. Ample Testing and exact classification of death as pointed out by dr. Ioannidis is the only way to APPROXIMATE "infection fatality rate". <br /> His analysis of the diamond princess cruise ship is very interesting IMO.
On 2020-04-11 12:00:55, user Sherlock Holmes wrote:
From an article in The Hill: "France has recorded 100 health incidents and four fatalities linked to experimental drugs for those with the coronavirus since late March..
France has has some 13.500 deaths of coronavirus. Is someone doing the maths?
On 2020-04-14 10:26:28, user Franko Ku wrote:
New trials must include use of zinc sulfate in <br /> combination with HCQ as well as as in latest French study with over 1000 patients in early stages added to HCQ and azithromycin, using same regimen to prove the great reported results.
On 2020-04-11 21:57:12, user H van Woerden wrote:
I think that this is a really important paper as it starts to explore the cost effectiveness of different approaches.
I am concerned about the effect of the fall in average incomes over the next decade on life expectancy and analysis of that issue by this team would be helpful. Particularly the fall in income for lower socio-economic groups.
On 2020-04-12 10:21:12, user Lev Yampolsky wrote:
wait a minute - there is one more confounding co-variable that radically affects death per million for which no control has been done as far as I can tell - timing of epidemics onset in each county. Clearly everything started early in large cities which are both travel hubs and tend to have higher PM2.5 than some nice place in Montana. This analysis will only be possible after the outbreak is over everywhere.
On 2020-04-13 08:45:15, user Alberto Villena wrote:
Please, have a look to this preprint: Lianne Abrahams, 2020: Covid-19: acquired acute porphyria hypothesis. https://osf.io/4wkfy/<br /> "Macaques infected with SARS-CoV-2 also have<br /> decreased red blood cell numbers (Munster 2020) and susceptibility to<br /> SARS-CoV-2 appears to be determined by blood group; blood group A is most<br /> affected whereas blood group O seems to be protected (Yang 2020). This finding<br /> is concordant with previous studies showing that susceptibility to the 2003<br /> strain of SARS-CoV was determined by blood group (Guillon 2008)."
On 2020-04-13 17:55:08, user Izz Thatso wrote:
The country benefiting the most from its BCG vaccination program, South Africa, probably has too few deaths in the defined 30 day period for it to be of statistical significance.
Why do my comments need to be approved?
On 2020-04-14 00:10:20, user Sinai Immunol Review Project wrote:
Main findings<br /> This report is a retrospective analysis of clinical data collected from 47 patients with confirmed COVID-19 disease (median age 64.91 years; 26 males; 24 severe cases). Upon admission, patients were assessed with an APACHE II score (mortality risk) and SOFA score (organ system dysfunction). Among other clinical parameters, including lymphocyte count, CRP, and enzyme levels, serum lactate dehydrogenase (LDH) level was most positively correlated with APACHE II and SOFA. Additionally, strong positive correlations were found between LDH and observational assessment of severity of pneumonia and of underlying coronary disease. Notably, serum LDH was also positively correlated with other univariate parameters, including troponin and CRP. Meanwhile, LDH was negatively correlated with lymphocyte count across different subsets, including CD4+ and CD8+ T cells.
Limitations<br /> Several studies have previously identified serum LDH as a predictive biomarker for COVID-19 progression (see references). Therefore, it is important to note that while LDH correlates with disease severity, it does not suffice as a reason for severe disease, so whether it serves as a robust predictive factor is not thoroughly supported; an explanation is still needed between the release of LDH from infected cells and disease severity.
Significance<br /> The identification of serum LDH as a predictive biomarker does glean insight into possible links between its release into the circulation and immune response to SARS-CoV-2 pathogenesis. It is important to note that LDH release itself requires significant damage to and permeabilization of plasma membranes, leading to necrotic cell death. Therefore, this report, and others like it, should warrant investigation into the link between SARS-CoV-2 infection and potential necrosis or pyroptosis of infected host cells. It is important to note that previous studies concerning biomarkers for SARS-CoV-1 disease have also identified serum LDH as an important correlative factor with disease severity1. And subsequent investigations have studied the activation of inflammasome structures involved in pyroptosis in the presence of SARS-CoV2-3.
On 2020-04-14 07:12:46, user Ole 500 wrote:
So they dosed the subjects at x2 and x3 the normal dosage of 400 mg/day. If I'm reading this right, they overdosed the patients and rediscovered known overdose side effects?
On 2020-04-14 08:38:01, user Quyen Vu wrote:
I am not scientist or sort of , however, BCG vaccine has been already used in Vietnam in 70 or 80 years until now , now covid?-19 death rate in Vietnam today is zero (today April 14th) , yes 0? ?at current infected 265 and recovered 155 . BCG is total make sense to me .
On 2020-04-15 13:58:04, user Buck Rogers wrote:
I don't understand why there is nothing here about the fact that Hydroxychloroquine opens a Zync channel to the cell and prevents the virus from replicating. Hydroxychloroquine was given 200MG twice a day with Azithromycin 500MG once a day. And most important Zync sulfate 220MG once a day. If you don't test the correct protocol what is the value of the research?
On 2020-04-15 14:38:14, user Lawrence Mayer wrote:
I am very suspicious of articles that are data driven but do not allow us to see the data. Why aren't papers like this being submitted to peer-reviewed journals? They are guaranteeing two week turn around from submission to posted on line.
I suggest people interested in learning about what has been reviewed by at least one expert join our discussion group on clinical epidemiology and science. We are over 2000 clinicians and epidemiologists discussing the latest empirical results on Covid19
Lawrence S. Mayer, MD, MS, PhD<br /> Faculty Associate<br /> Harvard University<br /> Professor Emeritus of Public Health, Medicine and Biostatistics
On 2020-04-16 06:58:38, user Kratoklastes wrote:
It would have been useful to tabulate critical illness (and deaths) - both by age cohort - and to have given some indication of the statistical properties of the estimators (beyond p-values).
The OR of 66× for the 75+ age cohort in the hospitalisation regression seems outlandish; the raw OR is 4× (i.e., the raw ratio of (Admitted|PosTest) for over-75s compared to the same quantity for 19-44 year olds).
That looks (to me) like a collinearity issue in the regressor matrix - a really wide CI for one really-obviously-important variable is another clue. (Call me a Bayesian!).
If your regressors were boolean (i.e., presence/absence) for comorbidities, VIF is not an appropriate test for collinearity: VIF performs poorly for categorical variables. Why not simply test the determinant of X´X, or its condition number, or its smallest eigenvalue?It's not a large matrix by modern standards - so it can't be a computational constraint. R's mctest package does a good job too (omcdiag includes the Farrar-Glauber test)
I would suspect some rank deficiency caused by correlation between hypertension and variables that represent CVD-ish things; not necessarily pairwise - and this is the problem with booleans.
Weak collinearity can happen because of weighted sums of columns - 3 boolean columns can give a run of '2' values, that correspond 'enough' with the '1's in the hypertension column. Add in other correlates with hypertension (age, obesity and maleness) and it would be suspicious if there wasn't collinearity.
I don't think it would be viewed negatively if you dropped the 19 newborns (who are confounders in the 'hospitalisation' regression, since they are always hospitalised), so long as it was clearly disclosed: the presence of those 19 observations will also mess up the 'critical illness' regression as well (it would only require a handful of newborns to need critical care for things unrelated to COVID19, to bias up the OR for their age group, and their presence already biases up recovery rates).
Lastly: it would be relatively straightforward to furnish the R script and the parameters (and residuals) without furnishing the data - that way interested people could generate their own pseudo-data and run some Monte Carlo experiments to get an idea of the asymptotic properties of the estimates. (To do it properly it would be good to have a covariance matrix so that the pseudodata could be generated by an appropriate cupola).
.
It's a pity that (as far as I am aware) Disqus does not permit any type of maths markup.
On 2020-04-16 10:58:04, user Pete Quinn wrote:
Hello, I expect that your results are far too conservative, by one or two orders of magnitude. I expect it's far more likely that by the end of this first wave (say mid-May, plus or minus), the total reported fatalities will lie in a range between about 1700 to 3500, given current restrictions (which are more lax than in neighboring Norway and Finland, which I estimate to report between about 200-450 and 100-250 respectively), and the new daily cases and fatalities will be small numbers by that point (handful or less fatalities daily). I hope I'm right and you are wrong, not for the sake of being right, but because, well, fatalities...
On 2020-04-16 12:24:09, user Eric Zorrilla wrote:
Hi,
I tried to comment on the preprint, but I cant tell if my comment is going through. I noticed some sig/near-sig OR relations in your Suppl. Table 1 that I thought were potentially of interest to highlight in your paper in addition to those you highlighted?
NON-HOSPITALIZATION also associated with<br /> Oseltamivir (of interest to field imo?)
And sig or nearly sig with<br /> Atenolol<br /> Lisformin<br /> Metformin<br /> Rosuvastatin
The joint presence of these anti-metabolic syndrome drugs (hypertension, diabetes, dyslipidemia) seems of interest as may support the emerging hypothesis/view that UNTREATED obesity/metabolic syndrome disorders may be worse than TREATED obesity/metabolic syndrome disorders as COVID-19 comorbidities.
DECREASED VENTILATION was sig. associated with<br /> Cetirizine (Zyrtec)<br /> Diphenhydramine (Benadryl)<br /> Cholecalciferol (Vitamin D3)<br /> I’m not sure if the first two are an age confound or something interesting vis-à-vis immune reactivity/hypersensitivity, but may be of interest to deconvolute/deconfound?<br /> And the Vitamin D3 may be of interest given various other emerging preprints on it?
Nice work and best wishes,<br /> Eric
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)?
On 2020-04-19 12:20:06, user Donna Marie Seyfried wrote:
Would be good if he used spell check. I’ll wait with my comments ntil it’s peer reviewed .
On 2020-04-16 23:38:02, user Edwin wang wrote:
April 16, 2020
Just a short note, China has changed the quarantine period for imported travellers (14-day for a centralized quarantine plus another 14-day home quarantine).
just read the news here: http://news.creaders.net/ch...
It is in Chinese, the key sentence is '14?????????+14?????????'. you could enter it into Goole translator
On 2020-04-17 20:31:38, user Brian Byrd wrote:
The authors have made a major error in asserting that
In order to evaluate whether CCBs have therapeutic effect in COVID-19 patients, we<br /> 199 retrospectively analyzed the medical record of 487 adult COVID-19 patients with<br /> 200 hypertension...
The effect of a drug is not discernible in this retrospective observational design.
This major error is extended and compounded when the authors claim that have identified a mortality reduction effect:
For the primary outcome of mortality, a beneficial effect in reducing the case fatality<br /> 234 rate (CFR) was observed in patients receiving amlodipine besylate, with the CFR<br /> 235 being significantly decreased from 26.1% (12/46) in non-amlodipine besylate treated<br /> 236 group to 6.8% (3/44) in amlodipine besylate treated group (P = 0.022).
It is irresponsible of the authors to include these incorrect claims of public health significance in a manuscript that is likely to be widely read prior to peer review. It is not clear how the authors can fix any damage that may already have been done, but they should most certainly immediately remove these unsupported and inappropriate claims.
On 2020-04-20 00:46:27, user deutsch wrote:
A conclusion with only two days oh HCQ and such a smal sample is dishonest!<br /> The probability of missing real differences between the treatments is very high with such a small sample. For example with real death rate 2% vs 4% the probability of false conclusion is 90%....
On 2020-04-21 08:34:15, user Maria wrote:
Don't you think that lung capacity differences are instead the key to explain the lower incidence and severity of the disease in women and children? Thank you.
On 2020-11-20 10:16:10, user Saar Wilf wrote:
Thank you for this publication. Given that we already have two successful vitamin D RCTs and dozens of retrospective studies, I believe the null hypothesis is that vitamin D is effective in reducing COVID-19 severity. Therefore the failure of this study is not enough to accept a new hypothesis.
Digging in to the details, the main problem is that the study was extremely underpowered. For example, the probability that it would have found a reduction of 50% in mortality with p<0.05 is only 25%. ICU admission and mechanical ventilation were a bit better with 61%, and 44%, and they indeed showed some effect (despite 1 treatment arm patient admitted to ICU before receiving treatment), although still not significant (as expected).
Sample size was calculated assuming vitamin D would reduce hospital stay from a mean of 7 to 3.5 days. That is extremely unlikely, especially given that bolus vitamin D takes a day or two to be mostly converted to 25(OH)D (and I assume more for 1,25(OH)d. anyone knows how long?).<br /> In essence, the study had a low probability of achieving any of its endpoints..
Patients were recruited 10 days after symptoms, and 90% were already on oxygen. It is possible that improving innate immunity is not very relevant at that point. Whatever effect it may have had, was further reduced due to 62% of patients receiving steroids.
While the study does not show vitamin D is not effective, it does suggest that at a late stage, alongside steroids, it is not *immensely* effective, i.e. does not reduce odds of severe outcomes by 5x or more. Our analysis at Rootclaim suggests that a 5x reduction is a reasonable outcome when vitamin D is administered correctly.
Thanks again.
On 2020-11-21 02:14:12, user kdrl nakle wrote:
Less than 5% acquired in schools. Except that you have no idea about asymptomatic transmissions because you do not test for that. And that is 50% or more among children. So when a parent gets infected you simply ascribe that to "community acquired." And we should really believe your tracing, right?
On 2020-11-21 09:00:00, user Ton Soons wrote:
the study didn’t address rhe intrinsic benefits of population-wide testing and it default assumes sensitivity and specifity will be a challenge. Suppose population-wide testing would be executed by using a pooled PCR-based testing strategy. Suppose the population-wide testing based on pooled PCR testing was addressed to a more realistic scenario by using it as a kind of front testing of HCW or at Nursing homes. More realistic scenario’s to study would als be:<br /> ->the added value of testing and monitoring of contacts during their quarantaine period (ttsi) in order to support backward contact tracing to find the super spreader. Keep in mind ‘mainly’ 20% is responsible for wide spreading!<br /> -> additional precaution taken to enter events, hospitals, restaurants, theaters, work envirionments.