Copies were sent to the White House, The President and the Vice President, Fauci’s alma mater Cornell University and the media.

Definitely worth reading the entire article!

http://pvsheridan.com/sheridan2fauci-1-21july2020.pdf

Original Article: https://wwwnc.cdc.gov/eid/article/26/5/19-0994_article

26, Number 5—May 2020

Policy Review

Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures

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Jingyi Xiao1, Eunice Y. C. Shiu1, Huizhi Gao, Jessica Y. Wong, Min W. Fong, Sukhyun Ryu, and Benjamin J. CowlingComments to Author 

Author affiliations: University of Hong Kong, Hong Kong, China

Cite This Article:

Xiao J, Shiu E, Gao H, et al. Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures. Emerging Infectious Diseases. 2020;26(5):967-975. doi:10.3201/eid2605.190994.

Abstract

There were 3 influenza pandemics in the 20th century, and there has been 1 so far in the 21st century. Local, national, and international health authorities regularly update their plans for mitigating the next influenza pandemic in light of the latest available evidence on the effectiveness of various control measures in reducing transmission. Here, we review the evidence base on the effectiveness of nonpharmaceutical personal protective measures and environmental hygiene measures in nonhealthcare settings and discuss their potential inclusion in pandemic plans. Although mechanistic studies support the potential effect of hand hygiene or face masks, evidence from 14 randomized controlled trials of these measures did not support a substantial effect on transmission of laboratory-confirmed influenza. We similarly found limited evidence on the effectiveness of improved hygiene and environmental cleaning. We identified several major knowledge gaps requiring further research, most fundamentally an improved characterization of the modes of person-to-person transmission.

Influenza pandemics occur at irregular intervals when new strains of influenza A virus spread in humans (1). Influenza pandemics cause considerable health and social impact that exceeds that of typical seasonal (interpandemic) influenza epidemics. One of the characteristics of influenza pandemics is the high incidence of infections in all age groups because of the lack of population immunity. Although influenza vaccines are the cornerstone of seasonal influenza control, specific vaccines for a novel pandemic strain are not expected to be available for the first 5–6 months of the next pandemic. Antiviral drugs will be available in some locations to treat more severe infections but are unlikely to be available in the quantities that might be required to control transmission in the general community. Thus, efforts to control the next pandemic will rely largely on nonpharmaceutical interventions.

Most influenza virus infections cause mild and self-limiting disease; only a small fraction of case-patients require hospitalization. Therefore, influenza virus infections spread mainly in the community. Influenza virus is believed to be transmitted predominantly by respiratory droplets, but the size distribution of particles responsible for transmission remains unclear, and in particular, there is a lack of consensus on the role of fine particle aerosols in transmission (2,3). In healthcare settings, droplet precautions are recommended in addition to standard precautions for healthcare personnel when interacting with influenza patients and for all visitors during influenza seasons (4). Outside healthcare settings, hand hygiene is recommended in most national pandemic plans (5), and medical face masks were a common sight during the influenza pandemic in 2009. Hand hygiene has been proven to prevent many infectious diseases and might be considered a major component in influenza pandemic plans, whether or not it has proven effectiveness against influenza virus transmission, specifically because of its potential to reduce other infections and thereby reduce pressure on healthcare services.

In this article, we review the evidence base for personal protective measures and environmental hygiene measures, and specifically the evidence for the effectiveness of these measures in reducing transmission of laboratory-confirmed influenza in the community. We also discuss the implications of the evidence base for inclusion of these measures in pandemic plans.

Methods and Results

We conducted systematic reviews to evaluate the effectiveness of personal protective measures on influenza virus transmission, including hand hygiene, respiratory etiquette, and face masks, and a systematic review of surface and object cleaning as an environmental measure (Table 1). We searched 4 databases (Medline, PubMed, EMBASE, and CENTRAL) for literature in all languages. We aimed to identify randomized controlled trials (RCTs) of each measure for laboratory-confirmed influenza outcomes for each of the measures because RCTs provide the highest quality of evidence. For respiratory etiquette and surface and object cleaning, because of a lack of RCTs for laboratory-confirmed influenza, we also searched for RCTs reporting effects of these interventions on influenza-like illness (ILI) and respiratory illness outcomes and then for observational studies on laboratory-confirmed influenza, ILI, and respiratory illness outcomes. For each review, 2 authors (E.Y.C.S. and J.X.) screened titles and abstracts and reviewed full texts independently.

We performed meta-analysis for hand hygiene and face mask interventions and estimated the effect of these measures on laboratory-confirmed influenza prevention by risk ratios (RRs). We used a fixed-effects model to estimate the overall effect in a pooled analysis or subgroup analysis. No overall effect would be generated if there was considerable heterogeneity on the basis of I2 statistic >75% (6). We performed quality assessment of evidence on hand hygiene and face mask interventions by using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach (7). We provide additional details of the search strategies, selection of articles, summaries of the selected articles, and quality assessment (Appendix).

Personal Protective Measures

Hand Hygiene

Thumbnail of Meta-analysis of risk ratios for the effect of hand hygiene with or without face mask use on laboratory-confirmed influenza from 10 randomized controlled trials with >11,000 participants. A) Hand hygiene alone; B) hand hygiene and face mask; C) hand hygiene with or without face mask. Pooled estimates were not made if there was high heterogeneity (I2 >75%). Squares indicate risk ratio for each of the included studies, horizontal lines indicate 95% CIs, dashed vertical lines ind

Figure 1. Meta-analysis of risk ratios for the effect of hand hygiene with or without face mask use on laboratory-confirmed influenza from 10 randomized controlled trials with >11,000 participants. A) Hand hygiene alone;…

We identified a recent systematic review by Wong et al. on RCTs designed to assess the efficacy of hand hygiene interventions against transmission of laboratory-confirmed influenza (8). We used this review as a starting point and then searched for additional literature published after 2013; we found 3 additional eligible articles published during the search period of January 1, 2013–August 13, 2018. In total, we identified 12 articles (9–20), of which 3 articles were from the updated search and 9 articles from Wong et al. (8). Two articles relied on the same underlying dataset (16,19); therefore, we counted these 2 articles as 1 study, which resulted in 11 RCTs. We further selected 10 studies with >10,000 participants for inclusion in the meta-analysis (Figure 1). We excluded 1 study from the meta-analysis because it provided estimates of infection risks only at the household level, not the individual level (20). We did not generate an overall pooled effect of hand hygiene only or of hand hygiene with or without face mask because of high heterogeneity in individual estimates (I2 87 and 82%, respectively). The effect of hand hygiene combined with face masks on laboratory-confirmed influenza was not statistically significant (RR 0.91, 95% CI 0.73–1.13; I2 = 35%, p = 0.39). Some studies reported being underpowered because of limited sample size, and low adherence to hand hygiene interventions was observed in some studies.

We further analyzed the effect of hand hygiene by setting because transmission routes might vary in different settings. We found 6 studies in household settings examining the effect of hand hygiene with or without face masks, but the overall pooled effect was not statistically significant (RR 1.05, 95% CI 0.86–1.27; I2 = 57%, p = 0.65) (Appendix Figure 4) (11–15,17). The findings of 2 studies in school settings were different (Appendix Figure 5). A study conducted in the United States (16) showed no major effect of hand hygiene, whereas a study in Egypt (18) reported that hand hygiene reduced the risk for influenza by >50%. A pooled analysis of 2 studies in university residential halls reported a marginally significant protective effect of a combination of hand hygiene plus face masks worn by all residents (RR 0.48, 95% CI 0.21–1.08; I2 = 0%, p = 0.08) (Appendix Figure 6) (9,10).

In support of hand hygiene as an effective measure, experimental studies have reported that influenza virus could survive on human hands for a short time and could transmit between hands and contaminated surfaces (2,21). Some field studies reported that influenza A(H1N1)pdm09 and influenza A(H3N2) virus RNA and viable influenza virus could be detected on the hands of persons with laboratory-confirmed influenza (22,23), supporting the potential of direct and indirect contact transmission to play a role in the spread of influenza. Other experimental studies also demonstrated that hand hygiene could reduce or remove infectious influenza virus from human hands (24,25). However, results from our meta-analysis on RCTs did not provide evidence to support a protective effect of hand hygiene against transmission of laboratory-confirmed influenza. One study did report a major effect, but in this trial of hand hygiene in schools in Egypt, running water had to be installed and soap and hand-drying material had to be introduced into the intervention schools as part of the project (18). Therefore, the impact of hand hygiene might also be a reflection of the introduction of soap and running water into primary schools in a lower-income setting. If one considers all of the evidence from RCTs together, it is useful to note that some studies might have underestimated the true effect of hand hygiene because of the complexity of implementing these intervention studies. For instance, the control group would not typically have zero knowledge or use of hand hygiene, and the intervention group might not adhere to optimal hand hygiene practices (11,13,15).

Hand hygiene is also effective in preventing other infectious diseases, including diarrheal diseases and some respiratory diseases (8,26). The need for hand hygiene in disease prevention is well recognized among most communities. Hand hygiene has been accepted as a personal protective measure in >50% of national preparedness plans for pandemic influenza (5). Hand hygiene practice is commonly performed with soap and water, alcohol-based hand rub, or other waterless hand disinfectants, all of which are easily accessible, available, affordable, and well accepted in most communities. However, resource limitations in some areas are a concern when clean running water or alcohol-based hand rub are not available. There are few adverse effects of hand hygiene except for skin irritation caused by some hand hygiene products (27). However, because of certain social or religious practices, alcohol-based hand sanitizers might not be permitted in some locations (28). Compliance with proper hand hygiene practice tends to be low because habitual behaviors are difficult to change (29). Therefore, hand hygiene promotion programs are needed to advocate and encourage proper and effective hand hygiene.

Respiratory Etiquette

Respiratory etiquette is defined as covering the nose and mouth with a tissue or a mask (but not a hand) when coughing or sneezing, followed by proper disposal of used tissues, and proper hand hygiene after contact with respiratory secretions (30). Other descriptions of this measure have included turning the head and covering the mouth when coughing and coughing or sneezing into a sleeve or elbow, rather than a hand. The rationale for not coughing into hands is to prevent subsequent contamination of other surfaces or objects (31). We conducted a search on November 6, 2018, and identified literature that was available in the databases during 1946–November 5, 2018. We did not identify any published research on the effectiveness of respiratory etiquette in reducing the risk for laboratory-confirmed influenza or ILI. One observational study reported a similar incidence rate of self-reported respiratory illness (defined by >1 symptoms: cough, congestion, sore throat, sneezing, or breathing problems) among US pilgrims with or without practicing respiratory etiquette during the Hajj (32). The authors did not specify the type of respiratory etiquette used by participants in the study. A laboratory-based study reported that common respiratory etiquette, including covering the mouth by hands, tissue, or sleeve/arm, was fairly ineffective in blocking the release and dispersion of droplets into the surrounding environment on the basis of measurement of emitted droplets with a laser diffraction system (31).

Respiratory etiquette is often listed as a preventive measure for respiratory infections. However, there is a lack of scientific evidence to support this measure. Whether respiratory etiquette is an effective nonpharmaceutical intervention in preventing influenza virus transmission remains questionable, and worthy of further research.

Face Masks

Thumbnail of Meta-analysis of risk ratios for the effect of face mask use with or without enhanced hand hygiene on laboratory-confirmed influenza from 10 randomized controlled trials with >6,500 participants. A) Face mask use alone; B) face mask and hand hygiene; C) face mask with or without hand hygiene. Pooled estimates were not made if there was high heterogeneity (I2 >75%). Squares indicate risk ratio for each of the included studies, horizontal lines indicate 95% CIs, dashed vertical 

Figure 2. Meta-analysis of risk ratios for the effect of face mask use with or without enhanced hand hygiene on laboratory-confirmed influenza from 10 randomized controlled trials with >6,500 participants. A) Face mask…

In our systematic review, we identified 10 RCTs that reported estimates of the effectiveness of face masks in reducing laboratory-confirmed influenza virus infections in the community from literature published during 1946–July 27, 2018. In pooled analysis, we found no significant reduction in influenza transmission with the use of face masks (RR 0.78, 95% CI 0.51–1.20; I2 = 30%, p = 0.25) (Figure 2). One study evaluated the use of masks among pilgrims from Australia during the Hajj pilgrimage and reported no major difference in the risk for laboratory-confirmed influenza virus infection in the control or mask group (33). Two studies in university settings assessed the effectiveness of face masks for primary protection by monitoring the incidence of laboratory-confirmed influenza among student hall residents for 5 months (9,10). The overall reduction in ILI or laboratory-confirmed influenza cases in the face mask group was not significant in either studies (9,10). Study designs in the 7 household studies were slightly different: 1 study provided face masks and P2 respirators for household contacts only (34), another study evaluated face mask use as a source control for infected persons only (35), and the remaining studies provided masks for the infected persons as well as their close contacts (11–13,15,17). None of the household studies reported a significant reduction in secondary laboratory-confirmed influenza virus infections in the face mask group (11–13,15,17,34,35). Most studies were underpowered because of limited sample size, and some studies also reported suboptimal adherence in the face mask group.

Disposable medical masks (also known as surgical masks) are loose-fitting devices that were designed to be worn by medical personnel to protect accidental contamination of patient wounds, and to protect the wearer against splashes or sprays of bodily fluids (36). There is limited evidence for their effectiveness in preventing influenza virus transmission either when worn by the infected person for source control or when worn by uninfected persons to reduce exposure. Our systematic review found no significant effect of face masks on transmission of laboratory-confirmed influenza.

We did not consider the use of respirators in the community. Respirators are tight-fitting masks that can protect the wearer from fine particles (37) and should provide better protection against influenza virus exposures when properly worn because of higher filtration efficiency. However, respirators, such as N95 and P2 masks, work best when they are fit-tested, and these masks will be in limited supply during the next pandemic. These specialist devices should be reserved for use in healthcare settings or in special subpopulations such as immunocompromised persons in the community, first responders, and those performing other critical community functions, as supplies permit.

In lower-income settings, it is more likely that reusable cloth masks will be used rather than disposable medical masks because of cost and availability (38). There are still few uncertainties in the practice of face mask use, such as who should wear the mask and how long it should be used for. In theory, transmission should be reduced the most if both infected members and other contacts wear masks, but compliance in uninfected close contacts could be a problem (12,34). Proper use of face masks is essential because improper use might increase the risk for transmission (39). Thus, education on the proper use and disposal of used face masks, including hand hygiene, is also needed.

Environmental Measures

Surface and Object Cleaning

For the search period from 1946 through October 14, 2018, we identified 2 RCTs and 1 observational study about surface and object cleaning measures for inclusion in our systematic review (40–42). One RCT conducted in day care nurseries found that biweekly cleaning and disinfection of toys and linen reduced the detection of multiple viruses, including adenovirus, rhinovirus, and respiratory syncytial virus in the environment, but this intervention was not significant in reducing detection of influenza virus, and it had no major protective effect on acute respiratory illness (41). Another RCT found that hand hygiene with hand sanitizer together with surface disinfection reduced absenteeism related to gastrointestinal illness in elementary schools, but there was no major reduction in absenteeism related to respiratory illness (42). A cross-sectional study found that passive contact with bleach was associated with a major increase in self-reported influenza (40).

Given that influenza virus can survive on some surfaces for prolonged periods (43), and that cleaning or disinfection procedures can effectively reduce or inactivate influenza virus from surfaces and objects in experimental studies (44), there is a theoretical basis to believe that environmental cleaning could reduce influenza transmission. As an illustration of this proposal, a modeling study estimated that cleaning of extensively touched surfaces could reduce influenza A infection by 2% (45). However, most studies of influenza virus in the environment are based on detection of virus RNA by PCR, and few studies reported detection of viable virus.

Although we found no evidence that surface and object cleaning could reduce influenza transmission, this measure does have an established impact on prevention of other infectious diseases (42). It should be feasible to implement this measure in most settings, subject to the availability of water and cleaning products. Although irritation caused by cleaning products is limited, safety remains a concern because some cleaning products can be toxic or cause allergies (40).

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Discussion

In this review, we did not find evidence to support a protective effect of personal protective measures or environmental measures in reducing influenza transmission. Although these measures have mechanistic support based on our knowledge of how influenza is transmitted from person to person, randomized trials of hand hygiene and face masks have not demonstrated protection against laboratory-confirmed influenza, with 1 exception (18). We identified only 2 RCTs on environmental cleaning and no RCTs on cough etiquette.

Hand hygiene is a widely used intervention and has been shown to effectively reduce the transmission of gastrointestinal infections and respiratory infections (26). However, in our systematic review, updating the findings of Wong et al. (8), we did not find evidence of a major effect of hand hygiene on laboratory-confirmed influenza virus transmission (Figure 1). Nevertheless, hand hygiene might be included in influenza pandemic plans as part of general hygiene and infection prevention.

We did not find evidence that surgical-type face masks are effective in reducing laboratory-confirmed influenza transmission, either when worn by infected persons (source control) or by persons in the general community to reduce their susceptibility (Figure 2). However, as with hand hygiene, face masks might be able to reduce the transmission of other infections and therefore have value in an influenza pandemic when healthcare resources are stretched.

It is essential to note that the mechanisms of person-to-person transmission in the community have not been fully determined. Controversy remains over the role of transmission through fine-particle aerosols (3,46). Transmission by indirect contact requires transfer of viable virus from respiratory mucosa onto hands and other surfaces, survival on those surfaces, and successful inoculation into the respiratory mucosa of another person. All of these components of the transmission route have not been studied extensively. The impact of environmental factors, such as temperature and humidity, on influenza transmission is also uncertain (47). These uncertainties over basic transmission modes and mechanisms hinder the optimization of control measures.

In this review, we focused on 3 personal protective measures and 1 environmental measure. Other potential environmental measures include humidification in dry environments (48), increasing ventilation (49), and use of upper-room UV light (50), but there is limited evidence to support these measures. Further investigations on the effectiveness of respiratory etiquette and surface cleaning through conducting RCTs would be helpful to provide evidence with higher quality; evaluation of the effectiveness of these measures targeting specific population groups, such as immunocompromised persons, would also be beneficial (Table 2). Future cost-effectiveness evaluations could provide more support for the potential use of these measures. Further research on transmission modes and alternative interventions to reduce influenza transmission would be valuable in improving pandemic preparedness. Finally, although our review focused on nonpharmaceutical measures to be taken during influenza pandemics, the findings could also apply to severe seasonal influenza epidemics. Evidence from RCTs of hand hygiene or face masks did not support a substantial effect on transmission of laboratory-confirmed influenza, and limited evidence was available on other environmental measures.

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Ms. Xiao is a postgraduate student at the School of Public Health, University of Hong Kong, Hong Kong, China. Her primary research interests are influenza epidemiology and the dynamics of person-to-person transmission.

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Acknowledgments

This study was conducted in preparation for the development of guidelines by the World Health Organization on the use of nonpharmaceutical interventions for pandemic influenza in nonmedical settings.

This study was supported by the World Health Organization. J.X. and M.W.F. were supported by the Collaborative Research Fund from the University Grants Committee of Hong Kong (project no. C7025-16G).

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Shiu  EYC, Leung  NHL, Cowling  BJ. Controversy around airborne versus droplet transmission of respiratory viruses: implication for infection prevention. Curr Opin Infect Dis. 2019;32:372–9. DOIExternal LinkPubMedExternal Link

Marr  LC, Tang  JW, Van Mullekom  J, Lakdawala  SS. Mechanistic insights into the effect of humidity on airborne influenza virus survival, transmission and incidence. J R Soc Interface. 2019;16:20180298. DOIExternal LinkPubMedExternal Link

Reiman  JM, Das  B, Sindberg  GM, Urban  MD, Hammerlund  MEM, Lee  HB, et al. Humidity as a non-pharmaceutical intervention for influenza A. PLoS One. 2018;13:e0204337. DOIExternal LinkPubMedExternal Link

Gao  X, Wei  J, Cowling  BJ, Li  Y. Potential impact of a ventilation intervention for influenza in the context of a dense indoor contact network in Hong Kong. Sci Total Environ. 2016;569-570:373–81. DOIExternal LinkPubMedExternal Link

McDevitt  JJ, Rudnick  SN, Radonovich  LJ. Aerosol susceptibility of influenza virus to UV-C light. Appl Environ Microbiol. 2012;78:1666–9. DOIExternal LinkPubMedExternal Link

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Figures

Figure 1. Meta-analysis of risk ratios for the effect of hand hygiene with or without face mask use on laboratory-confirmed influenza from 10 randomized controlled trials with >11,000 participants. A) Hand…

Figure 2. Meta-analysis of risk ratios for the effect of face mask use with or without enhanced hand hygiene on laboratory-confirmed influenza from 10 randomized controlled trials with >6,500 participants. A)…

Tables

Table 1. Summary of literature searches for systematic review on personal and environmental nonpharmaceutical interventions for pandemic influenza

Table 2. Knowledge gaps for personal protective and environmental nonpharmaceutical interventions for pandemic influenza

Pamela A. Popper, President

Wellness Forum Health

From the very beginning of the COVID-19 debacle, there has been a major difference between factual information concerning this virus and the stories that have been told to the public by government and public health officials.

The Fictional Tale Begins

The fiasco started with a model developed by Neil Ferguson of the Imperial College of London which predicted that tens of millions of people would die due to COVID-19 infection. COVID-19 was compared to the Spanish flu, which killed approximately 50 million people in 1918. Ferguson’s report stated that the only way to prevent massive deaths would be for the entire population of the planet to be locked down and for people to remain separated for 18 months until a vaccine was available. Total isolation would be needed because the isolation of just vulnerable populations like the elderly would only reduce deaths by half.[1]

“Renowned experts” like Mr. Fauci and Deborah Birx apparently did not check Ferguson’s background. He had demonstrated on numerous occasions that he was unable to accurately predict anything. In 2002, he predicted that 150,000 people would die from Mad Cow Disease, but only 2704 died. His estimation was 55 times higher than the real number. A few years later he predicted that 65,000 people would die of swine flu, and only 457 people died – his estimation was 142 times higher than the real number.[2] And his prediction of deaths from bird flu was 200,000,000 and only 455 people died – a prediction 439,560 times higher than the real number.[3]

As of June 25, total deaths worldwide from COVID-19 had reached 494,179 – not tens of millions – and even this number is questionable. This time Ferguson was off not by thousands or hundreds of thousands – but by millions. And the average age at death was 80, with almost all who died having multiple co-morbidities. The virus has had little effect on young and healthy people.

Enter Fauci: Liar in Chief

Mr. Fauci reported in an article in the New England Medical Journal published in March 2020 that “…the case fatality rate may be considerably less than 1%. This suggests that the overall clinical consequences of Covid-19 may ultimately be more akin to those of a severe seasonal influenza (which has a case fatality rate of approximately 0.1%)…”[4]

Yet just days later on March 11 2020 Fauci said that the COVID-19 mortality rate was “ten times worse” than seasonal flu.[5] He told a Congressional hearing on March 11 that “The flu has a mortality rate of 0.1 percent. This has a mortality rate of 10 times that. That’s the reason I want to emphasize we have to stay ahead of the game in preventing this.”[6]  Both of Fauci’s statements cannot be true – COVID-19 can’t be similar to normal seasonal flu AND have a death rate 10 times higher than seasonal flu.

Predictions of Death Rate by Others

“Globally, about 3.4% of reported COVID-19 (the disease spread by the virus) cases have died,” said WHO Director-General Tedros Adhanom Ghebreyesus at a briefing. “By comparison, seasonal flu generally kills far fewer than 1% of those infected.”[7]

But President Trump disagreed, stating that he had consulted with experts who said that many people who are exposed to flu are either asymptomatic or have such mild symptoms that they do not seek medical care. These people are not part of the data set when determining death rates. Thus, he said the actual mortality rate “is way under 1%.”[8]

The winner; Trump. According to Caitlin Rivers, epidemiologist at the Johns Hopkins Center for Public Health, the current best estimate for fatality rates are 0.5% to 1.0%.[9]

Ginning up the numbers in order to gin up the fear is a good way to get people to agree to vaccines for COVID-19. But even vaccine advocate Paul Offit refused to engage in the deception. He stated publicly that the WHO’s prediction of a 3.4% fatality rate was too high, and that the real number would likely be lower than 1.0%. “We’re more the victim of fear than the virus,” he said and also that he thought the world was witnessing a “wild overreaction” to the disease.”[10]

Speaking of Overreactions…

China is one of the most authoritarian regimes in the world, so no one was surprised when the government locked down its citizens. But the lockdowns by other governments in what used to be free countries is still shocking to many people. The consequences have been devastating – 40 million jobs lost, businesses permanently closed, suicides, overdoses, increased poverty, and food insecurity. Data clearly shows that the lockdowns had little effect, and yet the draconian measures continue.

An analysis of data prepared by the University of Oxford’s Blavatnik School of Government concerning Europe’s restrictions showed that lockdowns made little difference.[11] And JP Morgan issued a report in May showing that most countries showed decreasing rates of infection after restrictions were lifted – these included Denmark and Germany.[12]

The Norwegian Health Authority has published a report which showed that the virus never spread as fast as was anticipated, and the infection rate was already decreasing when the lockdown was ordered in Norway.[13] According to Camilla Stoltenberg, director of Norway’s public health agency, “Our assessment now, and I find that there is a broad consensus in relation to the reopening, was that one could probably achieve the same effect – and avoid part of the unfortunate repercussions – by not closing. But, instead, staying open with precautions to stop the spread.” She went on to say that it is important to be honest about the effect of lockdowns in the event that infection rates rise again.[14]

Many people find this information confusing in view of articles claiming that the lockdowns prevented hundreds of millions of infections and saved millions of lives. A recent article in The Washington Post made just such a claim.[15] But the article cited a study that was submitted on March 22, shortly after the lockdowns began.[16] I cannot fathom how a research group could report that the lockdowns saved millions of lives in advance of when the data on how many lives were saved could possibly have been made available.

But What About New Cases?

There are several issues concerning “new cases.” The first is that tens of millions of people are now being tested, and most are asymptomatic. Regardless of health status at the time of the test, all positives are being reported as “cases.” In other words, people who are healthy and have no symptoms are now “cases.”

Second, the tests are incredibly inaccurate. Tests for COVID-19 were approved by the FDA under emergency use authorization, which means that they were only required to perform well in test tubes and no real world demonstration of clinical viability was required, according to David Pride MD, associate director of microbiology at the University of California San Diego.[17]

Several issues were never addressed. One is the risk of cross-reactivity with other viruses. Another is that the presence of coronavirus is likely to remain for several months after the infectious period has passed, which means the tests are useless for determining who should be quarantined. Yet another is the risk of cross contamination, particularly when testing large numbers of people in crowded settings. Even the tiniest amount of cross contamination can lead to a false positive result, which means people who are have never been exposed to COVID19 could be subjected to unwarranted quarantines.

The tests are produced by several vendors, and each has established its own and as-yet-unmeasured accuracy. The variations are myriad, according to Dr. Pride. He says that some tests can detect as few as 100 copies of a viral gene while others require 400 copies for detection.[18] Additionally, most will show positive results for as long as 6 months, while the actual time the person is contagious is only a few days.

Some experts, like Dr. Steven Woloshin of Dartmouth College, are suggesting that perhaps the FDA should actually investigate the tests further to determine which ones, if any, are accurate. What a concept!

There are currently 110 different screening tests in use, and the FDA says it has asked the makers of tests to perform follow-up studies, and that it is tracking “problems” with the tests. But what we know now is that the makers of these tests cannot report how often the tests falsely clear or wrongly diagnose patients. The only requirement for approval was 60 test tube samples which, according to Dr. Robert Kaplan of Stanford University, have little resemblance to real-world situations. He says, “You’re testing people in parking lots, the patients themselves are extremely anxious and unable to follow instructions.”

The FDA issued a warning to doctors in May concerning Abbott Lab’s rapid ID Now test, stating that it was inaccurate between one third and 50% of the time. Accuracy issues with this test have been identified by researchers are Stanford, Cleveland Clinic, and Loyola University.[19]  Abbott denies this but has not submitted any data. I suppose we are just supposed to take their word for it.

If the error rate is actually as high as 50%, there could be millions of people who have erroneously tested positive, thus inflating the number of “cases.”

And then there is even more deception. According to an article in the Arizona Republic on Weds June 10, experts report that, “Arizona’s COVID-19 spread is ‘alarming’ and action is needed.” Yahoo News reported a spike in cases in all southwestern states.[20]

The reality? More cases are being diagnosed because more people are showing up for healthcare services which were delayed while the fake pandemic was at its height. In most cases, facilities are requiring that these people get tested as a requirement for care. Thousands of asymptomatic people are testing positive (we’ll ignore the fact that the tests are inaccurate for a moment). These asymptomatic people are reported as cases. According to health officials, in early June the increase in hospitalizations was due to people who were finally able to have “elective surgeries” starting May 1. According to Arizona Health Director Dr. Cara Christ, most beds were in use by non-COVID patients.”[21] In fact, there was only one new admission for COVID on June 8.[22]

So how does the media report that hospitalizations of COVID patients are up? By reporting everyone who is in the hospital who tests positive as a “case.” Having your knee replaced and tested positive for COVID? Counted as hospitalization for COVID. Having a stent replaced and tested positive for COVID? You are classified as a hospitalization for COVID. See how it works? You can create a whole new pandemic and reason for wearing masks, and being panicked and social distancing and keeping schools closed just by misrepresenting the data. And it is being done every day.

Is COVID-19 Worse Than Seasonal Flu?

According to the Centers for Disease Control (CDC)’s website, about 9% of the world’s population is affected by flu annually with up to one billion infections, 3-5 million severe cases, and 300,000-500,000 deaths per year.[23] [24] It is estimated that 20% of Americans are affected, with 25-50 million documented cases, 225,000 hospitalizations and tens of thousands of deaths annually.[25] [26] [27] [28] [29]  Historically, the elderly account for 90% of influenza deaths.[30]  These data are for “normal” years.

One season that was considered abnormal was 2009-2010, during which the swine flu (H1N1) was circulating. CDC data shows that there were 60.8 million cases, 274,304 hospitalizations, and 12,469 deaths from swine flu in the U.S.[31]  It is estimated that as many as 575,400 people died of H1N1 worldwide during a one-year period.[32]

Let’s contrast these numbers with COVID-19 data. As of June 28 there were 10,081,545 cases of COVID-19 and 501,298 deaths reported worldwide.[33] Keep in mind that the tests are inaccurate – with a margin of error that could be as high as 50%.

And we know that the number of deaths has been inflated since doctors were instructed to forge death certificates. Dr. Deborah Birx , who serves on the White House task force announced during a press briefing on Tuesday April 7 that the deaths of all patients who died with coronavirus, even if the cause of death was not due to COVID-19, should list COVID-19 as cause of death on the death certificate.[34]

Dr. Scott Jensen, a Minnesota Family practice doctor and state Senator, reported receiving a 7-page document from CDC instructing him to do this. As for the motivation? “Fear is a great way to control people,” he told a television station.[35]

Several states, including Colorado and Washington State, have started adjusting their death rates downward after legislators and activity groups exposed the fact that deaths from other causes, including gunshots, were being reported as COVID deaths.[36] [37]

The Bottom Line

Accurate data are still not being reported to the public by government and health officials. In fact, it seems that there is a deliberate and ongoing attempt to mislead the public with inaccurate and inflated data. I cannot think of any legitimate reason for actions such as these that cause fear, panic, financial distress, closure and failure of businesses, unemployment, irreparable harm to children, and death. Only despots who have no respect for human life could engage in such deception. And despots are in control of us right now.

[1] Ferguson NM, Laydon D, Nedjati-Gilani G et al. “Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand.” Imperial College COVID-19 Response Team March 16 2020

[2] National CJD Research and Surveillance Unit. “Disease in the UK (By Calendar Year.” University of Edinburgh May 4 2020

[3] Sturcke J. “Bird flu pandemic could kill 150,000.” The Guardian Sept 30 2005

[4] Fauci AS, Lane HC, Redfield RR. “Covid-19 – Navigating the Uncharted.” NEJM 2020 Mar;382:1268-1269

[5] Bailey R. “COVID-19 Mortality Rate ‘Ten Times Worse’ Than Seasonal Flu, Says Dr. Anthony Fauci.” Mar 11 2020 https://reason.com/2020/03/11/covid-19-mortality-rate-ten-times-worse-than-seasonal-flu-says-dr-anthony-fauci/

[6] https://thehill.com/changing-america/well-being/prevention-cures/487086-coronavirus-10-times-more-lethal-than-seasonal

[7] WHO Director reports that globally, about 3.4% of reported COVID-19 cases have died, more than flu.” Healthcare News Mar 4 2020

[8] Ibid

[9] Hamilton J. “Antibody Tests Point To Lower Death Rate For The Coronavirus Than First Thought.” May 28 2020

[10] Rider R. “Trump and the Coronavirus Death Rate.” Factcheck Posts March 5 2020

[11] Petherick A, Kira B, Angrist N, Hale T, Phillips T, Webster S. “Variation in government responses to COVID-19.” Blavatnik School Working Paper May 28 2020

[12] Stickings T. “Lockdowns failed to alter the course of pandemic and are now destroying millions of livelihoods worldwide, JP Morgan study claims.” Daily Mail May 22 2020

[13] https://www.fhi.no/contentassets/c9e459cd7cc24991810a0d28d7803bd0/vedlegg/notat-om-risiko-og-respons-2020-05-05.pdf

[14] Nelson F. “Norway health chief: lockdown was not needed to tame Covid.” The Spectator May 27 2020

[15] Olsen H. “No the lockdowns weren’t an overreaction.” Washington Post Jun 9 2020

[16] Hsiang S, Allen D, Annan-Phan S et al. “The effect of large-scale anti-contagion policies on the COVID-19 pandemic.” Nature 2020 Jun https://doi.org/10.1038/s41586-020-2404-8

[17] Pride D. “Hundreds of different coronavirus tests are being used – which is best?” The Conversation April 4 2020

[18] IBID

[19] Perrone M. “Accuracy of many virus tests unknown.” Associated Press Jun 15 2020

[20] Horowitz D. “Horowitz: The new panic lie: Increased coronavirus hospitalizations and cases in the southwest. The media thinks we don’t understand arithmetic.” The Blaze June 12 2020

[21] “AZDHS: COVID-19 hospitalizations up, but most beds in use by other patients.” KTAR News Jun 6 2020

[22] Horowitz D. “Horowitz: The new panic lie: Increased coronavirus hospitalizations and cases in the southwest. The media thinks we don’t understand arithmetic.” The Blaze June 12 2020

[23] Lambert LC, Fauci AS. “Influenza vaccines for the future.” NEJM 2010 Nov;363(21):2036-2044

[24] Centers for Disease Control and Prevention. “Estimates of deaths associated with seasonal influenza – United States, 1976-2007.” MMWR Morb Mortal Wkly Rep 2010 Aug;59(33):1057-1062

[25] Lambert LC, Fauci AS. “Influenza vaccines for the future.” NEJM 2010 Nov;363(21):2036-2044

[26] Centers for Disease Control and Prevention. “Estimates of deaths associated with seasonal influenza – United States, 1976-2007.” MMWR Morb Mortal Wkly Rep 2010 Aug;59(33):1057-1062

[27] Simonsen L, Clarke MJ, Williamson GD, Stroup DF, Arden NH, Schonberger LB. “The impact of influenza epidemics on mortality: introducing a severity index.” Am J Public Health 1997 Dec;87(12):1944-1950

[28] Simonsen L, Fukuda K, Schonberger LB, Cox NJ. “The impact of influenza epidemics on hospitalizations.” J Infect Dis 2000 Mar;181(3):831-837

[29] Thompson WW, Shay DK, Weintraub W et al. “Influenza-associated hospitalizations in the United States.” JAMA 2004 Sep;292(11):1333-1340

[30] Molinari NA, Ortega-Sanchez IR, Messonnier ML et al. “The annual impact of seasonal influenza in the US: measuring disease burden and costs.” Vaccine 2007 Jun;25(27):5086-5096

[31] https://www.cdc.gov/flu/pandemic-resources/2009-h1n1-pandemic.html

[32] IBID

[33] https://www.worldometers.info/coronavirus/?utm_campaign=homeAdUOA?Si

[34] https://www.foxnews.com/politics/birx-says-government-is-classifying-all-deaths-of-patients-with-coronavirus-as-covid-19-deaths-regardless-of-cause

[35] https://www.youtube.com/watch?v=Pfa4b7T0ZHY

[36] https://www.freedomfoundation.com/washington/wa-dept-of-health-to-stop-counting-deaths-improperly-attributed-to-covid-19/

[37] Blitzer R. “Colorado Gov Polis pushes back against CDC’s coronavirus death counts.”  Fox News https://www.foxnews.com/politics/colorado-gov-pushes-back-against-cdcs-coronavirus-death-counts

Download A Review of the Response to COVID-19

Pamela A. Popper, President

Wellness Forum Health

Fortunately, the public no longer has to listen to daily briefings by Fauci and Birx, two of the most incompetent doctors in the U.S. In my opinion, both should lose their jobs and Fauci should lose his medical license (Birx no longer holds a medical license) because they used bad information provided by unreliable sources to make policy recommendations that resulted in death and devastation throughout the U.S. Many people might refer to this as malpractice.

Suicides and overdose deaths increased exponentially as people became despondent over factors like isolation, economic ruin, and food insecurity. Child and spousal abuse increased. Murders increased. Nursing home patients died as a result of neglect when family members no longer could visit and supervise their care. People died who could not access medical treatment while hospitals and other facilities were closed and all resources were set aside for the COVID patients who never showed up.

The debacle starts with a model developed by Neil Ferguson of the Imperial College of London which predicted that tens of millions of people would die due to COVID-19 infection. COVID-19 was compared to the Spanish flu, which killed approximately 50 million people in 1918. Ferguson’s report stated that the only way to prevent massive deaths would be for the entire population of the planet to be locked down and for people to remain separated for 18 months until a vaccine was available. Total isolation would be needed because the isolation of just vulnerable populations like the elderly would only reduce deaths by half.[1]

Ferguson’s report was deemed so convincing that the World Health Organization, which had previously stated that lockdowns were not effective for containing infectious diseases, recommended that the world follow China’s example, which included mandatory lockdowns and contact tracing.[2]

It seems that nobody, including Fauci and Birx, checked out Ferguson’s background. In 2002, he predicted that 150,000 people would die from Mad Cow Disease, but only 2704 died. His estimation was 55 times higher than the real number. A few years later he predicted that 65,000 people would die of swine flu, and only 457 people died – his estimation was 142 times higher than the real number.[3] And his prediction of deaths from bird flu was 200,000,000 and only 455 people died – a prediction 439,560 times higher than the real number.[4]

As of June 8, total deaths worldwide had reached 410,000 – not tens of millions – and even this number is questionable. This time Ferguson was off not by thousands or hundreds of thousands – but by millions. And the average age at death was 80, with almost all who died having multiple co-morbidities. This hardly justifies destroying the lives of hundreds of millions of people by locking them down.

It seems that people who claim to be as smart as Fauci and Birx might think to check out the track record of the person who recommended such extreme measures prior to taking action. I’m regularly told by my critics that I’m not nearly as smart as Fauci, yet we do this type of checking in our office as standard procedure. One might also assume that the World Health Organization would check out Ferguson’s track record prior to making decisions that would affect over seven billion people. Apparently not. Yet there are those who still listen to and revere these doctors and the WHO. Amazing!

A group of researchers at Stanford Prevention Research Center published an article on June 11 expressing significant concerns about both the models, some of which were not accompanied by any disclosure concerning methodology, and the actions taken in response. What resulted was a misallocation of hospital resources, and unjustified delayed healthcare for non-COVID patients. The researchers also point out the negative impact on mental health, increased unemployment, the loss of health insurance, prospect of starvation, and the potential spread of other infectious diseases as just some of the negative consequences of the grossly incompetent actions of Fauci and Birx and their brainwashed followers.

Here are some examples of the disparities cited between predictions and reality in individual states:

New York

Prediction: up to 140,000 hospital beds and 40,000 intensive care units with ventilators would be required

Reality: 18,569 hospitalizations and 4908 intensive care units required. (Predictions almost 87% off on both)

Tennessee

Prediction: 15,500 hospital beds, 2500 ICU beds and 2000 ventilators would be needed to keep people alive

Reality: 1232 hospital beds, 245 ICU beds and 208 ventilators required 92% and 90% off respectively), projected loss of $3.5 billion in revenue by Tennessee hospitals by June 30 as a result of cessation of non-COVID patient care.

California

Projection: up to 1.2 million beds would be required.

Reality: COVID patients occupy less than 5% of California hospital beds, and less than 20% of ICU beds

Georgia

Massachusetts General Hospital projected over 23,000 deaths in Georgia within a month of opening the economy and the actual number was only 896 (almost 96% off).

The Stanford Group listed reasons for this debacle which included lack of expertise; groupthink and the bandwagon effect; and selective reporting (otherwise known as lying). In other words, top health officials in the U.S. and in many states were incompetent and willing to blindly follow what others said without question, and then lied about it.

The researchers also note that this is not a new problem and expressed surprise that forecasting is still used given its “dubious track record.” One of the reasons, they say, is that there are no serious consequences for people who make these bad decisions. To this point, as of the writing of this article, Fauci and Birx have not been criminally indicted for the death and destruction they have caused, and have not even been fired from their jobs.

The Stanford group goes on to write that even if a calamity the size of which the models predicted were to occur, policies like lockdowns have little impact on the death rate and generally do more harm than good, and add that exaggerated forecasts “…may cause more harm than the virus itself.”[5]

It’s somewhat amazing that in view of his colossal failure, Fauci now has the nerve to say that the problem is not him or his incompetence. It’s Americans. Instead of an apology, he takes us all to task in a recent podcast, stating that “…for reasons that are…inconceivable and not understandable – they just don’t believe science and they don’t believe authority.” He goes on to say that “science is truth,” which is true, but Fauci has not used science – he used information provided by a known charlatan who had been grossly mistaken before. Not able to help himself, he likens those of us who listened to him lie every day on national television and determined that he was a fraud to “anti-vaxxers” who do not want to be vaccinated even though, according to Fauci, the science clearly supports their safety. He never backs down, never admits he’s wrong.[6]

We must do everything possible to make sure that Fauci, Birx, state health directors, and elected officials will at some point stand trial for their crimes against humanity. And we must take back our freedoms and liberties and our government so that this can never happen again.

[1] Ferguson NM, Laydon D, Nedjati-Gilani G et al. “Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand.” Imperial College COVID-19 Response Team March 16 2020

[2] World Health Organization, Non-Pharmaceutical Public Health Measures for Mitigating the Risk and Impact of Epidemic and Pandemic Influenza, October 2019; World Health Organization, “Considerations for Quarantine of Individuals in the Context of Containment for Coronavirus Disease (COVID-19),” March 19, 2020.

[3] National CJD Research and Surveillance Unit. “Disease in the UK (By Calendar Year.” University of Edinburgh May 4 2020

[4] Sturcke J. “Bird flu pandemic could kill 150,000.” The Guardian Sept 30 2005

[5] Ioannidis JPA, Cripps S, Tanner MA. “Forecasting for COVID-19 has failed.” International Institute of Forecasters June 11 2020 https://forecasters.org/blog/2020/06/14/forecasting-for-covid-19-has-failed/

[6] Caplan J. “Anthony Fauci: Americans ‘Don’t Believe Science and They Don’t Believe Authority” Breitbart News Jun 18 2020

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