Covid19-Sources

This cross-sectional study examines the differences in excess death rates between Republican and Democratic voters in Florida and Ohio after the COVID-19 vaccine became available for all adults.

Huaier Effects on Functional Compensation with Destructive Ribosomal RNA Structure after Anti-SARS-CoV-2 mRNA Vaccination. PubMed, SCI, Scopus, ESCI, PMC indexed

Among workers 35 to 44 years old, a stunning 34% more died than expected last quarter, with above-average rates in other age groups, too. But why?

Objective: To characterise Long COVID in a highly vaccinated population infected by Omicron. Design: Follow-up survey of persons testing positive for SARS-CoV-2 in Western Australia, 16 July-3 August 2022. Setting: Community Participants: 22,744 persons with COVID-19 who had agreed to participate in research at the time of diagnosis were texted a survey link 90 days later; non-responders were telephoned. Post stratification weights were applied to responses from 11,697 (51.4%) participants, 94.0% of whom had received = 3 vaccine doses. Main outcome measures: Prevalence of Long COVID - defined as reporting new or ongoing COVID-19 illness-related symptoms or health issues 90 days post diagnosis; associated health care utilisation, reductions in work/study and risk factors were assessed using log-binomial regression. Results: 18.2% (n=2,130) of respondents met case definition for Long COVID. Female sex, being 50-69 years of age, pre-existing health issues, residing in a rural or remote area, and receiving fewer vaccine doses were significant independent predictors of Long COVID (p 0.05). Persons with Long COVID reported a median of 6 symptoms, most commonly fatigue (70.6%) and difficulty concentrating (59.6%); 38.2% consulted a GP and 1.6% reported hospitalisation in the month prior to the survey due to ongoing symptoms. Of 1,778 respondents with Long COVID who were working/studying before their COVID-19 diagnosis, 17.9% reported reducing/discontinuing work/study. Conclusion: 90 days post Omicron infection, almost 1 in 5 respondents reported Long COVID symptoms; 1 in 15 of all persons with COVID-19 sought healthcare for associated health concerns =2 months after the acute illness. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by the Western Australia Department of Health ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Human Research Ethics committee of Western Australia Department of Health gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript.

Viral respiratory tract infections are a leading cause of morbidity and mortality worldwide. Unfortunately, the transmission routes and shedding kinetics of respiratory viruses remain poorly understood. Air sampling techniques to quantify infectious viruses in the air are indispensable to improve in …

Background Type 2 diabetes (T2DM) incidence is increased after diagnosis of COVID-19. The impact of vaccination on this increase, for how long it persists, and the effect of COVID-19 on other types of diabetes remain unclear. Methods With NHS England approval, we studied diabetes incidence following COVID-19 diagnosis in pre-vaccination (N=15,211,471, January 2020-December 2021), vaccinated (N =11,822,640), and unvaccinated (N=2,851,183) cohorts (June-December 2021), using linked electronic health records. We estimated adjusted hazard ratios (aHRs) comparing diabetes incidence post-COVID-19 diagnosis with incidence before or without diagnosis up to 102 weeks post-diagnosis. Results were stratified by COVID-19 severity (hospitalised/non-hospitalised) and diabetes type. Findings In the pre-vaccination cohort, aHRS for T2DM incidence after COVID-19 (compared to before or without diagnosis) declined from 3.01 (95% CI: 2.76,3.28) in weeks 1-4 to 1.24 (1.12,1.38) in weeks 53-102. aHRS were higher in unvaccinated than vaccinated people (4.86 (3.69,6.41)) versus 1.42 (1.24,1.62) in weeks 1-4) and for hospitalised COVID-19 (pre-vaccination cohort 21.1 (18.8,23.7) in weeks 1-4 declining to 2.04 (1.65,2.51) in weeks 52-102), than non-hospitalised COVID-19 (1.45 (1.27,1.64) in weeks 1-4, 1.10 (0.98,1.23) in weeks 52-102). T2DM persisted for 4 months after COVID-19 for ∼73% of those diagnosed. Patterns were similar for Type 1 diabetes, though excess incidence did not persist beyond a year post-COVID-19. Interpretation Elevated T2DM incidence after COVID-19 is greater, and persists longer, in hospitalised than non-hospitalised people. It is markedly less apparent post-vaccination. Testing for T2DM after severe COVID-19 and promotion of vaccination are important tools in addressing this public health problem. Evidence before this study We searched PubMed for population-based observational studies published between December 1st 2019 and July 12th 2023 examining associations between SARS-CoV-2 infection or COVID-19 diagnosis (search string: SARS-CoV-2 or COVID* or coronavirus*) and subsequent incident diabetes (search term: diabetes). Of nineteen relevant studies; eight had a composite outcome of diabetes types, six stratified by diabetes type and five pertained to type-1-diabetes (T1DM) only. We did not identify any studies relating to gestational or other types of diabetes. Eleven studies were from the US, three from the UK, two from Germany, one from Canada, one from Denmark and one from South Korea. Most studies described cumulative relative risks (for infection versus no infection) one to two years post-SARS-CoV-2 infection of 1.2 to 2.6, though four studies found no associations with T1DM after the post-acute period. All studies lacked the power to compare diabetes relative risk by type, severity, and vaccination status in population subgroups. One study examined relative risks by vaccination status, but this used a composite outcome of diabetes and hyperlipidaemia and was conducted in a predominantly white male population. Two studies of T1DM found no evidence of elevated risk beyond 30 days after COVID-19 diagnosis, whilst two reported elevated risks at six months. Two studies of type 2 diabetes (T2DM) examined relative risks by time period post-infection: one study of US insurance claims reported a persistent association six months post-infection, whereas a large UK population-based study reported no associations after 12 weeks. However, the latter study used only primary care data, therefore COVID-19 cases were likely to have been under-ascertained. No large studies have investigated the persistence of diabetes diagnosed following COVID-19; key to elucidating the role of stress/steroid-induced hyperglycaemia. Added value of this study This study, which is the largest to address the question to date, analysed linked primary and secondary care health records with SARS-CoV-2 testing and COVID-19 vaccination data for 15 million people living in England. This enabled us to compare the elevation in diabetes incidence after COVID-19 diagnosis by diabetes type, COVID-19 severity and vaccination status, overall and in population subgroups. Importantly, excess diabetes incidence by time period since infection could also be quantified. Since healthcare in the UK is universal and free-at-the-point-of-delivery, almost the entire population is registered with primary care. Therefore the findings are likely to be generalisable. We found that, before availability of COVID-19 vaccination, a COVID-19 diagnosis (vs. no diagnosis) was associated with increased T2DM incidence which remained elevated by approximately 30% beyond one year after diagnosis. Though still present (with around 30% excess incidence at eight weeks), these associations were substantially attenuated in unvaccinated compared with vaccinated people. Excess incidence was greater in people hospitalised with COVID-19 than those who were not hospitalised after diagnosis. T1DM incidence was elevated up to, but not beyond, a year post COVID-19. Around 73% of people diagnosed with incident T2DM after COVID-19 still had evidence of diabetes four months after infection. Implications of all the available evidence There is a 30-50% elevated T2DM incidence post-COVID-19, but we report the novel finding that there is elevated incidence beyond one-year post-diagnosis. Elevated T1DM incidence did not appear to persist beyond a year, which may explain why previous studies disagree. For the first time in a general-population dataset, we demonstrate that COVID-19 vaccination reduces, but does not entirely ameliorate, excess diabetes incidence after COVID-19. This supports a policy of universal vaccination and suggests that other public health activities, such as enhanced diabetes screening after severe COVID-19, may be warranted, particularly in unvaccinated people. ### Competing Interest Statement NC is compensated by AstraZeneca for membership of Data Monitoring and Safety Committees for clinical trials. The other authors report no conflicts. ### Clinical Protocols ### Funding Statement This study was funded by the COVID-19 Longitudinal Health and Wellbeing National Core Study, funded by the UKRI Medical Research Council (MC\_PC\_20059); the COVID-19 Data and Connectivity National Core Study, funded by the UKRI Medical Research Council; and by the CONVALESCENCE long COVID study, funded by the UK National Institute for Health and Care Research (COVID-LT-009). This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Health Research Authority [REC reference 22/PR/0095] and the University of Bristol's Faculty of Health Sciences Ethics Committee [reference 117269] gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data were linked, stored, and analysed securely within the OpenSAFELY platform (https://opensafely.org/). Detailed pseudonymised patient data are potentially reidentifiable and therefore not shared. Details of access to OpenSAFELY secure data analytics platform is described on the OPENSAFELY (website https://opensafely.org/).

Die WHO hat bestätigt, dass eine Welle von Corona-Infektionen um den Erdball geht. Sie warnt vor einer existenziellen Bedrohung durch die Evolution der Viren, falls die öffentliche Gesundheitsinfrastruktur nicht in der Lage sein wird, diese neuesten Varianten unter Kontrolle zu halten.

The SARS-CoV-2 Omicron variant of concern (VOC) has multiple mutations in the spike (S) protein, which mediates viral infection and immunity. We analysed a sub lineage of Omicron, designated omicron XBB (XBB), that showed structural and functional changes in the S protein in response to the African selection pressures. We used molecular modelling to compare the S protein structures of the original Omicron and XBB found that XBB had a reduced receptor-binding domain (RBD) due to the loss of some β-sheets, which may increase its affinity to the human angiotensin-converting enzyme 2 (hACE2) receptor. We also used Fast Unconstrained Bayesian AppRoximation (FUBAR) and Recombination Detection Program 4 (RDP 4) to perform selection and recombination analysis respectively of the S protein sequences of Omicron and XBB and detected signals of positive selection and recombination in the N terminal domain (NTD) of the S1 subunit, which contains antibody-binding epitopes, and the RBD, which is involved in viral entry. Our results reveal the structural and functional adaptation of the Omicron XBB variant in Africa and its potential implications for viral pathogenesis and immunity. ### Competing Interest Statement The authors have declared no competing interest.

NIH-funded research links alterations to inflammatory protein, underscores vaccine importance.

In this Personal View, we discuss current knowledge on SARS-CoV-2 RNA or antigen persistence in children infected with SARS-CoV-2. Based on the evidence that the virus can persist in adults, we have done a literature review and analysed studies that looked for SARS-CoV-2 RNA or antigens in children undergoing autopsy, biopsy, or surgery for either death from COVID-19 or multisystem inflammatory syndrome, or assessments for long COVID-19 or other conditions. Our analysis suggests that in children, independent from disease severity, SARS-CoV-2 can spread systemically and persist for weeks to months.

In the published article, there was an error in the Funding statement. The funding statement was missing a second source. The published version is as follow: the authors received funding from the Agency for Science, Technology and Research (A*STAR) Career Development Award (C21112056). The correct Funding statement appears below.FUNDINGThe authors received funding from the Agency for Science, Technology and Research (A*STAR) Career Development Award (C21112056) and Singapore National Medical Research Council (OFYIRG19may- 0007). The authors apologize for this error and state that this does not change the scientific conclusions

The risk of developing venous thromboembolisms is elevated among cancer patients with COVID-19 taking anticancer drugs, new data show.

The laboratory accident hypothesis of COVID-19’s origins is a bust, but the popular consensus is unwilling to accept it.

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Das Robert-Koch-Institut will herausgefunden haben, dass Corona-Massnahmen wie Lockdowns und Maskenpflicht die Pandemie erfolgreich eindämmten. Die Datenwissenschafter Oliver Beige und Daniel Haake erklären im Gespräch ihre Zweifel an den Ergebnissen der Studie.

Am 20.07.2023 veröffentlichte das Robert-Koch-Institut einen Projektabschlussbericht zum StopptCOVID-Projekt, in dem die Effektivität der Corona-Maßnahmen in Deutschland untersucht werden soll. Diese Studie hat den Anspruch, die Wirksamkeit einer großen Menge einzelner pharmazeutischer (Impfung) und nicht-pharmazeutischer Interventionen (z.B. Schulschließungen, Kontaktbeschränkungen) auf das Infektionsgeschehen zu überprüfen. Hierbei wird ein übliches statistisches Analyseverfahren – ein sog. Regressionsmodell – verwendet, mit dem der zeitliche Verlauf der Corona-Wellen – gemessen anhand des bekannten „R-Wertes“ – zu erklären versucht wird. Die Modellanalyse liefert Ergebnisse, die dahingehend interpretiert werden, dass nahezu jede getroffene Maßnahme den gewünschten Effekt – also eine Minderung des Infektionsgeschehens bzw. eine Senkung des R-Wertes – hatte. Darüber hinaus wird in der Studie festgestellt, dass bei vielen Maßnahmen die gewünschte Wirkung bereits vor ihrem Inkrafttreten eingetreten ist, was mit freiwilligen Verhaltensänderungen – genauer: einer Antizipation der Maßnahmen durch die Bevölkerung – erklärt wird. Weiterhin wird ausdrücklich darauf hingewiesen, dass Maßnahmen nur im Verbund mit anderen Maßnahmen ihre volle Wirkung entfalten. Da es sich bei der RKI-Untersuchung um eine quantitative Modellierungsstudie handelt, die den Anspruch erhebt, kausale Einflüsse von Maßnahmen auf das Infektionsgeschehen nachzuweisen, ist es notwendig, das zu Grunde gelegte methodische Konzept sowie die aus den Modellergebnissen getroffenen Schlussfolgerungen einer kritischen Prüfung zu unterziehen, wie es beispielsweise in Begutachtungsprozessen bei wissenschaftlichen Fachzeitschriften unternommen wird. Hierbei zeigt sich, dass die RKI-Studie dem wissenschaftlichen Anspruch, derartige Aussagen zu treffen, nicht genügt. Erstens wird bereits ein Studienkonzept gewählt, mit dem es gar nicht möglich ist, kausale Einflüsse von Interventionen zu überprüfen; hierfür wäre ein anderer Modelltyp aus dem Bereich der sog. Kausalinferenz von Nöten. Vereinfacht ausgedrückt kann der gewählte Modellansatz nur überprüfen, ob das Infektionsgeschehen nach Einsetzen einer Maßnahme geringer war als davor oder danach; es kann damit nicht überprüft werden, ob das Infektionsgeschehen auch aufgrund dieser Maßnahme gedrosselt wurde. Doch auch schon im ersten Punkt wird der genannte Nachweis nicht erbracht, da die gewünschte Wirkung zum Teil bereits zeitlich vor dem Einsetzen der Maßnahmen erfolgte. Zweitens gibt es in der Modellanalyse eine Reihe weiterer Probleme, die, unabhängig vor der Wahl des Modelltyps, eine Ableitung belastbarer Aussagen erschweren. Hierzu gehört unter anderem, dass für das Modell Annahmen zur höheren Übertragbarkeit der späteren Virusvarianten getroffen werden, die einfach in das Modell „gesetzt“ werden und die gleichzeitig die Modellergebnisse stark beeinflussen. Die Wirkung von Corona-Maßnahmen wird im vorliegenden Modell nicht ergebnisoffen geprüft, sondern zum Teil bereits durch das Modelldesign vorausgesetzt. Weiterhin werden auch einige Gütekriterien für derartige Modellanalysen, wie sie in der Fachliteratur aus den Bereichen Statistik/Ökonometrie behandelt werden, verletzt bzw. ihre Behandlung wird nicht dokumentiert. Hinzu kommen Probleme in der Berechnung des R-Wertes und Verzerrungen in dessen Datengrundlage. Drittens sind auch wesentliche Schlussfolgerungen der Studie nicht durch deren eigene Modellergebnisse gesichert. Dass die Bevölkerung Maßnahmen „freiwillig vorweggenommen“ habe, ist lediglich eine Behauptung, die sich nicht ausreichend belegen lässt und für die sich sogar Gegenbeispiele finden lassen. Einige Ergebnisse sind widersprüchlich - zum Beispiel ein kontraproduktiver Effekt von Masken in bestimmten Altersgruppen -, ohne dass diese paradoxen Ergebnisse inhaltlich erklärt werden. Auch die Aussage, wonach Maßnahmen erst „im Verbund“ eine ernsthafte Wirkung haben, ist in dieser Pauschalität bereits logisch nicht nachvollziehbar und wird durch die RKI-Studie auch nicht belegt. Wir empfehlen daher eine Neubearbeitung der Studie auf der Grundlage des bestehenden Datensatzes (Re-Analyse) durch eine unabhängige Instanz. Vor diesem Hintergrund empfehlen wir weiterhin die Veröffentlichung des zugrunde gelegten Datensatzes sowie des Quellcodes der Auswertung.

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And why answering it holds the key to treating and preventing this condition and others like it

As COVID cases rise once again, we are unprepared for the "mass disabling" event caused by long COVID

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European Archives of Psychiatry and Clinical Neuroscience - A significant proportion of patients after SARS-CoV-2 infection suffer from long-lasting symptoms. Although many different symptoms are...

COVID-19 pathology is associated with concerted inhibition of mitochondrial gene expression in mammalian hosts.

This cohort study uses data from commercially available smart thermometers to estimate the role of children in household transmission of SARS-CoV-2 from the beginning of the pandemic until October 2022.

A study published yesterday in JAMA Network Open suggests that 70.4% of nearly 850,000 US household COVID-19 transmissions originated with a child. A team led by Boston Children's Hospital researchers gave smartphone-connected thermometers to 848,591 households with 1,391,095 members, who took 23,153,925 temperature readings from October 2019 to October 2022. Fevers were a proxy for infection. Of all readings, 57.7% were from adults. Most households (62.3%) reported temperatures from only one person, while 37.7% included multiple participants taking 51.6% of all readings. Most children were 8 years or younger (58.0%), and more females than males participated in each age group.

Bivalent COVID-19 mRNA vaccines expressing both the ancestral D614G and Omicron BA.5 spike proteins were introduced in August 2022 with the goal of broadening immunity to emerging SARS-CoV-2 Omicron subvariants. Subsequent studies on bivalent boosters found neutralizing antibody responses similar to boosters with the original monovalent vaccine, likely the result of immunological imprinting. Guidelines allow for administration of a second bivalent booster in high-risk groups, but it remains unknown whether this would broaden antibody responses. To address this question, we assessed longitudinal serum SARS-CoV-2-neutralizing titers in 18 elderly immunocompetent individuals (mean age 69) following a fourth monovalent booster and two BA.5 bivalent booster vaccines using pseudovirus neutralization assays against D614G, Omicron BA.5, and Omicron XBB.1.5. There was a small but significant increase in peak neutralizing antibody responses against Omicron BA.5 and XBB.1.5 following the first bivalent booster, but no significant increase in peak titers following the second bivalent booster. Omicron-specific neutralizing titers remained low after both doses of the BA.5 bivalent booster. Our results suggest that a second dose of the BA.5 bivalent booster is not sufficient to broaden antibody responses and to overcome immunological imprinting. A monovalent vaccine targeting only the spike of the recently dominant SARS-CoV-2 may mitigate the back boosting associated with the original antigenic sin. ### Competing Interest Statement D.D.H. co-founded TaiMed Biologics and RenBio, serves as a consultant for WuXi Biologics and Brii Biosciences, and is a board director at Vicarious Surgical. Aubree Gordon served as a member of the scientific advisory board for Janssen Pharmaceuticals. The remaining authors have declared no conflicts of interest

COVID-19 has taken a toll on the nation's heart health but how profound is only starting to emerge. Heart attack deaths spiked early in the pandemic, erasing years of progress in battling cardiovascular disease.

The SARS-CoV-2 virus hijacks our cellular power plants known as mitochondria. A new study hypothesizes that could potentially explain long Covid.