“It is natural to think that wearing a mask, no matter new or old, should always be better than nothing. Our results show that this belief is only true for particles larger than 5 micrometers, but not for fine particles smaller than 2.5 micrometers,” said author Jinxiang Xi.
The researchers found that wearing a mask with low (less than 30%) filtration efficiency can be worse than without.
The number of covid-19 infections likely to have been acquired in hospital are rising again for the first time in three weeks and their proportion of all cases has reached record levels for the second wave, HSJ can reveal.
Young children account for only a small percentage of COVID-19 infections — a trend that has puzzled scientists. Now, a growing body of evidence suggests why: kids’ immune systems seem better equipped to eliminate SARS-CoV-2 than are adults’.
“Children are very much adapted to respond — and very well equipped to respond — to new viruses,” says Donna Farber, an immunologist at Columbia University in New York City. Even when they are infected with SARS-CoV-2, children are most likely to experience mild or asymptomatic illness.
Another clue that children’s response to the virus differs from that of adults is that some children develop COVID-19 symptoms and antibodies specific to SARS-CoV-2 but never test positive for the virus on a standard RT-PCR test. In one study, three children under ten from the same family developed SARS-CoV-2 antibodies — and two of them even experienced mild symptoms — but none tested positive on RT-PCR, despite being tested 11 times over 28 days while in close contact with their parents, who had tested positive.
Little is known about the interests of the doctors, scientists, and academics on whose advice the UK government relies to manage the pandemic. Attempts to discover more are frequently thwarted, finds Paul D Thacker.
We identified severe acute respiratory syndrome coronavirus 2 RNA in an oropharyngeal swab specimen collected from a child with suspected measles in early December 2019, ≈3 months before the first identified coronavirus disease case in Italy. This finding expands our knowledge on timing and mapping of novel coronavirus transmission pathways.
Suppose that you are worried that you might have a rare disease. You decide to get tested, and suppose that the testing methods for this disease are correct 99 percent of the time (in other words, if you have the disease, it shows that you do with 99 percent probability, and if you don’t have the disease, it shows that you do not with 99 percent probability). Suppose this disease is actually quite rare, occurring randomly in the general population in only one of every 10,000 people.
If your test results come back positive, what are your chances that you actually have the disease?
Do you think it is approximately: (a) .99, (b) .90, (c) .10, or (d) .01?
Surprisingly, the answer is (d), less than 1 percent chance that you have the disease!
This fact may be deduced using something called Bayes’ theorem…
“We fully support the swine flu vaccination programme … The vaccine has been thoroughly tested,” they declared in a joint statement.
Except, it hadn’t. Anticipating a severe influenza pandemic, governments around the world had made various logistical and legal arrangements to shorten the time between recognition of a pandemic virus and the production of a vaccine and administration of that vaccine in the population. In Europe, one element of those plans was an agreement to grant licences to pandemic vaccines based on data from pre-pandemic “mock-up” vaccines produced using a different virus (H5N1 influenza). Another element, adopted by countries such as Canada, the US, UK, France, and Germany, was to provide vaccine manufacturers indemnity from liability for wrongdoing, thereby reducing the risk of a lawsuit stemming from vaccine related injury.
Randomised control trial study showing safety and efficacy of COVID-19 vaccine has clear conflicts of interest.
WHO has received user feedback on an elevated risk for false SARS-CoV-2 results when testing specimens using RT-PCR reagents on open systems.
As with any diagnostic procedure, the positive and negative predictive values for the product in a given testing population are important to note. As the positivity rate for SARS-CoV-2 decreases, the positive predictive value also decreases. This means that the probability that a person who has a positive result (SARS-CoV-2 detected) is truly infected with SARS-CoV-2 decreases as positivity rate decreases, irrespective of the assay specificity. Therefore, healthcare providers are encouraged to take into consideration testing results along with clinical signs and symptoms, confirmed status of any contacts, etc.
While the truth about Tamiflu emerged only after years of exhaustive work by the Cochrane review group and investigative journalists, the machinations behind remdesivir’s rapid climb were evident at an early stage. On 29 April, the same day as a trial was published showing no significant effect of remdesivir among patients in hospital, remdesivir’s manufacturer rushed out interim findings of a more favourable trial by press release and with full White House honours. The much vaunted but minimal benefits shown in severely ill people were used to justify FDA approvals and worldwide purchase. Now a much larger trial has found little or no benefit in hospital patients, and a BMJ Rapid Recommendation, produced in collaboration with the World Health Organization and Magic App, has come down against use of remdesivir in patients with covid-19 of any severity.
…Science by press release, on the basis of interim or ad hoc analyses, and without access to the data, also afflicts our knowledge about the covid-19 candidate vaccines. Patients and the public deserve better than this. So do health professionals. Pandemic or no pandemic, decisions must be based on scrutiny of the full data from trials that are independent of drug and vaccine manufacturers.
At a panel discussion about the Great Reset hosted by the World Economic Forum in mid-November, former Secretary of State John Kerry – Biden’s would-be special presidential envoy for climate – firmly declared that the Biden administration will support the Great Reset and that the Great Reset “will happen with greater speed and with greater intensity than a lot of people might imagine.”
- Two-thirds of the private sector capacity that was block-purchased by NHS England was left unused over the summer
- Unprecedented block contracts in place for almost all the private hospital capacity, thought to be worth around £400m per month
- Comes as waiting times for elective care and diagnostic tests have steeply increased
- Capacity to carry out chemotherapy treatment was among that not fully used
- Insiders blame confusion and communication over contracts, and some argue the contracts were not needed
Most people will escape “severe” side effects, defined as those that prevent daily activity. Fewer than 2% of recipients of the Pfizer and Moderna vaccines developed severe fevers of 39°C to 40°C. But if the companies win regulatory approvals, they’re aiming to supply vaccine to 35 million people worldwide by the end of December. If 2% experienced severe fever, that would be 700,000 people.
Other transient side effects would likely affect even more people. The independent board that conducted the interim analysis of Moderna’s huge trial found that severe side effects included fatigue in 9.7% of participants, muscle pain in 8.9%, joint pain in 5.2%, and headache in 4.5%. In the Pfizer/BioNTech vaccine trial, the numbers were lower: Severe side effects included fatigue (3.8%) and headache (2%).
But that’s a higher rate of severe reactions than people may be accustomed to. “This is higher reactogenicity than is ordinarily seen with most flu vaccines, even the high-dose ones,” says Arnold Monto, an epidemiologist at the University of Michigan School of Public Health.
COVID-19 is caused by the coronavirus SARS-CoV-2, which jumped into the human population in late 2019 from a currently uncharacterised animal reservoir. Due to this recent association with humans, SARS-CoV-2 may not yet be fully adapted to its human host. This has led to speculations that SARS-CoV-2 may be evolving towards higher transmissibility. The most plausible mutations under putative natural selection are those which have emerged repeatedly and independently (homoplasies). Here, we formally test whether any homoplasies observed in SARS-CoV-2 to date are significantly associated with increased viral transmission. To do so, we develop a phylogenetic index to quantify the relative number of descendants in sister clades with and without a specific allele. We apply this index to a curated set of recurrent mutations identified within a dataset of 46,723 SARS-CoV-2 genomes isolated from patients worldwide. We do not identify a single recurrent mutation in this set convincingly associated with increased viral transmission. Instead, recurrent mutations currently in circulation appear to be evolutionary neutral and primarily induced by the human immune system via RNA editing, rather than being signatures of adaptation. At this stage we find no evidence for significantly more transmissible lineages of SARS-CoV-2 due to recurrent mutations.
We do not identify a single recurrent mutation in this set convincingly associated with increased viral transmission. Instead, recurrent mutations currently in circulation appear to be evolutionary neutral and primarily induced by the human immune system via RNA editing, rather than being signatures of adaptation. At this stage we find no evidence for significantly more transmissible lineages of SARS-CoV-2 due to recurrent mutations.
Many countries across the globe utilized medical and non-medical facemasks as non-pharmaceutical intervention for reducing the transmission and infectivity of coronavirus disease-2019 (COVID-19). Although, scientific evidence supporting facemasks’ efficacy is lacking, adverse physiological, psychological and health effects are established. Is has been hypothesized that facemasks have compromised safety and efficacy profile and should be avoided from use. The current article comprehensively summarizes scientific evidences with respect to wearing facemasks in the COVID-19 era, providing prosper information for public health and decisions making.
Children represented 1.1% (1,408/129,704) of SARS-CoV-2 positive cases between 16 January 2020 and 3 May 2020. In total, 540 305 people were tested for SARS-COV-2 and 129,704 (24.0%) were positive. In children aged <16 years, 35,200 tests were performed and 1408 (4.0%) were positive for SARS-CoV-2, compared to 19.1%–34.9% adults. Childhood cases increased from mid-March and peaked on 11 April before declining. Among 2,961 individuals presenting with ARI in primary care, 351 were children and 10 (2.8%) were positive compared with 9.3%–45.5% in adults. Eight children died and four (case-fatality rate, 0.3%; 95% CI 0.07% to 0.7%) were due to COVID-19. We found no evidence of excess mortality in children.
Children accounted for a very small proportion of confirmed cases despite the large numbers of children tested. SARS-CoV-2 positivity was low even in children with ARI. Our findings provide further evidence against the role of children in infection and transmission of SARS-CoV-2.
Stringent COVID-19 control measures were imposed in Wuhan between January 23 and April 8, 2020. Estimates of the prevalence of infection following the release of restrictions could inform post-lockdown pandemic management. Here, we describe a city-wide SARS-CoV-2 nucleic acid screening programme between May 14 and June 1, 2020 in Wuhan. All city residents aged six years or older were eligible and 9,899,828 (92.9%) participated. No new symptomatic cases and 300 asymptomatic cases (detection rate 0.303/10,000, 95% CI 0.270–0.339/10,000) were identified. There were no positive tests amongst 1,174 close contacts of asymptomatic cases. 107 of 34,424 previously recovered COVID-19 patients tested positive again (re-positive rate 0.31%, 95% CI 0.423–0.574%). The prevalence of SARS-CoV-2 infection in Wuhan was therefore very low five to eight weeks after the end of lockdown.
The Imperial model had larger errors, about 5-fold higher than other models by six weeks. This appears to be largely driven by the aforementioned tendency to overestimate mortality. At twelve weeks, MAPE values were lowest for the IHME-MS-SEIR (23.7%) model, while the Imperial model had the most elevated MAPE (98.8%). Predictive performance between models was generally similar for median absolute errors (MAEs)