The concern that SARS-CoV-2 could be spread by people without symptoms originally came from a single case report. It was alleged that an asymptomatic woman from China had spread the virus to 16 other contacts in Germany. Later reports showed that, at the time of contact, this woman was taking medication for flu-like symptoms, invalidating the evidence provided for the theory of asymptomatic transmission. As with other common respiratory viruses, SARS-CoV-2 spreads by being exhaled, coughed or sneezed into the air. The largest droplets fall quickly and settle on the ground whilst the most lightweight particles, known as aerosols, may remain suspended in the air for days. Once the virus is present in the environment, it spreads by finding its way into the respiratory tract of new hosts in a large enough quantity (known as the ‘viral load’ or ‘infectious dose’) to infect them. The theory of fomite transmission (touching contaminated surfaces and then touching the face) is not supported by scientific evidence.
…In asymptomatic individuals, the viral load is typically very low and the infectious period is also short in duration. They may still exhale virus particles, which another person may encounter. However, the overall likelihood of transmitting the disease to others is negligible. Thus asymptomatic cases are not the major drivers of epidemics. As Dr Anthony Fauci of the US National Institute of Allergy and Infectious Diseases stated in March 2020: ‘In all the history of respiratory-borne viruses of any type, asymptomatic transmission has never been the driver of outbreaks. The driver of outbreaks is always a symptomatic person.’
- No evidence that masks reduce viral transmission in real-world settings
- Wearing masks is likely to do harm
- Masks increase compliance with the ongoing public health tyranny
- Masks are dehumanising
- Masks perpetuate the elevated levels of fear
The recently-launched Smile Free campaign – of which I’m a part – is campaigning for the removal of mask mandates in the UK, and believes that, in a democratic society, the evidential bar to justify mandating a behaviour should be set very high. The research in support of masks offering protection against SARS-CoV-2 infection falls a long way short of this threshold, and the negative consequences of wearing them are considerable. The decision whether to wear a face covering should be a personal one, not one imposed by Government diktat. All mask mandates must be lifted on June 21 and this most insidious of all the Covid-19 restrictions must never return.
The process of learning about and developing an investigational medicine is divided into four phases. At first, very few people receive the medicine being studied. The number of people participating in clinical studies grows along with our understanding of the investigational medicine, and the research continues as long as the potential benefits outweigh the risks.
The case for the prosecution of Johnson is likely to be heard in a parliamentary inquiry (with Dominic Cummings as the star witness) which should bring scrutiny of the Imperial College cliff-edge hypothesis. This suggests that Covid cases surged every day until lockdown, so Prime Ministerial dither cost thousands of lives. Only when he eventually agreed to lock down on March 23, says Imperial, did cases collapse. This theory is one of the most influential ever deployed in government – and now looks as if it could be bunkum.
We don’t have to guess anymore, given how much Covid data exists. The ONS, Zoe/King’s College, the React-2 study run by a different team at Imperial: none support Neil Ferguson’s cliff-edge theory. All show Covid cases falling before lockdowns. So what forced the virus into retreat, if not stay-at-home orders? We can look at another form of contagion: news, spread digitally. People saw how things were getting dangerous and stayed home of their own accord. This is more than theory. Mobile phone data offers rich detail of this worldwide trend.
Many countries introduced the requirement to wear masks in public spaces for containing SARS-CoV-2 making it commonplace in 2020. Up until now, there has been no comprehensive investigation as to the adverse health effects masks can cause. The aim was to find, test, evaluate and compile scientifically proven related side effects of wearing masks. For a quantitative evaluation, 44 mostly experimental studies were referenced, and for a substantive evaluation, 65 publications were found. The literature revealed relevant adverse effects of masks in numerous disciplines. In this paper, we refer to the psychological and physical deterioration as well as multiple symptoms described because of their consistent, recurrent and uniform presentation from different disciplines as a Mask-Induced Exhaustion Syndrome (MIES). We objectified evaluation evidenced changes in respiratory physiology of mask wearers with significant correlation of O2 drop and fatigue (p < 0.05), a clustered co-occurrence of respiratory impairment and O2 drop (67%), N95 mask and CO2 rise (82%), N95 mask and O2 drop (72%), N95 mask and headache (60%), respiratory impairment and temperature rise (88%), but also temperature rise and moisture (100%) under the masks. Extended mask-wearing by the general population could lead to relevant effects and consequences in many medical fields.
The risk of being exposed to Covid-19 indoors is as great at 60 feet as it is at 6 feet — even when wearing a mask, according to a new study by Massachusetts Institute of Technology researchers who challenge social distancing guidelines adopted across the world.
MIT professors Martin Z. Bazant, who teaches chemical engineering and applied mathematics, and John W.M. Bush, who teaches applied mathematics, developed a method of calculating exposure risk to Covid-19 in an indoor setting that factors in a variety of issues that could affect transmission, including the amount of time spent inside, air filtration and circulation, immunization, variant strains, mask use, and even respiratory activity such as breathing, eating, speaking or singing.
Relative risk reduction and absolute risk reduction measures in the evaluation of clinical trial data are poorly understood by health professionals and the public. The absence of reported absolute risk reduction in COVID-19 vaccine clinical trials can lead to outcome reporting bias that affects the interpretation of vaccine efficacy. The present article uses clinical epidemiologic tools to critically appraise reports of efficacy in Pfzier/BioNTech and Moderna COVID-19 mRNA vaccine clinical trials. Based on data reported by the manufacturer for Pfzier/BioNTech vaccine BNT162b2, this critical appraisal shows: relative risk reduction, 95.1%; 95% CI, 90.0% to 97.6%; p = 0.016; absolute risk reduction, 0.7%; 95% CI, 0.59% to 0.83%; p < 0.000. For the Moderna vaccine mRNA-1273, the appraisal shows: relative risk reduction, 94.1%; 95% CI, 89.1% to 96.8%; p = 0.004; absolute risk reduction, 1.1%; 95% CI, 0.97% to 1.32%; p < 0.000. Unreported absolute risk reduction measures of 0.7% and 1.1% for the Pfzier/BioNTech and Moderna vaccines, respectively, are very much lower than the reported relative risk reduction measures. Reporting absolute risk reduction measures is essential to prevent outcome reporting bias in evaluation of COVID-19 vaccine efficacy.
A critical appraisal of phase III clinical trial data for the Pfizer/BioNTech vaccine BNT162b2 and Moderna vaccine mRNA-1273 shows that absolute risk reduction measures are very much lower than the reported relative risk reduction measures. Yet, the manufacturers failed to report absolute risk reduction measures in publicly released documents. As well, the U.S FDA Advisory Committee (VRBPAC) did not follow FDA published guidelines for communicating risks and benefits to the public, and the committee failed to report absolute risk reduction measures in authorizing the BNT162b2 and mRNA-1273 vaccines for emergency use. Such examples of outcome reporting bias mislead and distort the public’s interpretation of COVID-19 mRNA vaccine efficacy and violate the ethical and legal obligations of informed consent.
A study evaluating COVID-19 responses around the world found that mandatory lockdown orders early in the pandemic may not provide significantly more benefits to slowing the spread of the disease than other voluntary measures, such as social distancing or travel reduction.
Ivor Cummins aka the Fat Emperor – gives James the lowdown on why you can’t trust anything our governments tell us about Covid-19. If you want the facts on Coronavirus – how deadly is it? do lockdowns and masks work? how does it compare with previous pandemics? – you’ve come to the right place
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Background and Aims
The most restrictive non‐pharmaceutical interventions (NPIs) for controlling the spread of COVID‐19 are mandatory stay‐at‐home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).
We first estimate COVID‐19 case growth in relation to any NPI implementation in subnational regions of 10 countries: England, France, Germany, Iran, Italy, Netherlands, Spain, South Korea, Sweden, and the US. Using first‐difference models with fixed effects, we isolate the effects of mrNPIs by subtracting the combined effects of lrNPIs and epidemic dynamics from all NPIs. We use case growth in Sweden and South Korea, two countries that did not implement mandatory stay‐at‐home and business closures, as comparison countries for the other 8 countries (16 total comparisons).
Implementing any NPIs was associated with significant reductions in case growth in 9 out of 10 study countries, including South Korea and Sweden that implemented only lrNPIs (Spain had a non‐significant effect). After subtracting the epidemic and lrNPI effects, we find no clear, significant beneficial effect of mrNPIs on case growth in any country. In France, e.g., the effect of mrNPIs was +7% (95CI ‐5%‐19%) when compared with Sweden, and +13% (‐12%‐38%) when compared with South Korea (positive means pro‐contagion). The 95% confidence intervals excluded 30% declines in all 16 comparisons and 15% declines in 11/16 comparisons.
While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less restrictive interventions.
The scientific literature and publishing scientists have been rapidly and massively infected by COVID-19 creating opportunities and challenges. There is evidence for hyper-prolific productivity.