A virus that spread to 168 countries with a speed that is unmatched by any disease outside of historical plagues is a virus that must be examined closely.
We expect a 90%+ Clinical Attack Rate (CAR) over two years, if the trend demonstrated with serological data from 1918 survivors holds true. More than 97% carried antibodies to the 1918 Influenza.
Though a 2% Clinical Fatality Rate (CFR) may appear slight and unconcerning, be mindful of the practical mathematics. That 2% equates 1 death of every 55 people in your community, in your company and in your family if the CAR holds at 90%. As the case exponentiation occurs from school openings, colder weather and human-fit Genetic Acquisitions, the general risk factors of today will give way to a “sheer randomness” of attack, as one colleague astutely commented. If life-long debility holds as a statistically significant feature of this type of IDRRV Influenza, many of the survivors will bear neurological artifacts of this avoidable disease for the rest of their lives.
Three-Time Loser in 1918
Although most have obviously survived the FirstWave and most will obviously survive the SecondWave, no guarantees are available to any individual human with this Influenza serotype. An expert on Influenza History recalled for me recently the documented "three-time loser" from the 1918 Spanish Influenza. That individual in 1918 was struck during all three waves and recovered in the first two. His antibody product from two illnesses certainly did not protect him from the third wave that killed him. This evidence of the “three-time loser” and many other cases with back-to-back illnesses during the 1918 plague suggests that Adaptive Immunity did not play the most significant role in survival. A robust, but properly regulated Innate Immune response appears to be the proper solution to an IDRRV assault.
Children and Young Adults
As you have seen in media reports, children and young adults represent a statistically large portion of the confirmed cases and the confirmed deaths at a rate not seen since 1918. After four years of focused research on these types of viral strains in these particular hosts, we continue to speculate that an endogenous growth factor, yet unidentified may be involved (termed as GFλ ). Though research abounds on single molecule signalers, little is actually known about the complex systems of cell-to-cell signaling and even less about the interdependence of intra-cellular signals. GFλ could perhaps be an interactive system of hormones, cytokines or chemokines.
Growth Factor Lambda will be found to either be present in higher levels or normally only present within children, young adults and pregnant women. GFλ will be found to affect metabolism at the sub-cellular, organelle level. This factor may even be an anti-factor, a re-tasker, that moves resources away from “base/normal” function and onto high growth activities. That higher or “different” metabolism driven by GFλ may enable an Interferon-Deranging, Rapid Replicating Virus (IDRRV) like PF11 a significant advantage in speed of reproduction, multi-tropism and / or variation in genetic expression and genetic acquisition. We would like to see additional labs moving quickly toward these types of investigations. The implications are astounding. Because the signaling molecules have diverse individual roles and more diverse combination effects with complex feedback cycles, discrete measurement and experiment design allow only for a limited understanding at this stage of research capability. As we have seen in practice these past 90 days, the medical industry cannot safely and successfully regulate these types of complex systems using single-point, synthetic interventions. Most of the confirmed deaths on file occurred during or after advanced medical treatment.
Pregnancy poses a very certain risk for the mother and the child. In South America, one country has reported that 10% of all deaths to date related to pregnancy.
Though most individuals will eventually be infected, certain positions are in a higher risk. Healthcare workers (doctors, nurses, pediatric specialists, respiratory therapists and administrators) and educators (elementary and secondary school teachers, university professors, headmasters and administrators) are dying from this virus as they serve in their respective roles. Most of our military academies, more than one reported USN battle group, soldiers across Iraq and USArmy bases have been affected with quarantines from this virus. We expect that the global trend will be similar with confirmed cases starting in mid-June at Sandhurst, the Royal Military Academy of the UK. Law Enforcement and First Responders have been significantly impacted with reports of deaths from contact in their daily duties and some departments reporting 40% absenteeism. Christian missions and summer camps have been infected widely. Any position, including school and university-based employment, that requires congregation regularly with alternate mixing of individuals creates a higher Influenza virus raw exposure count, thus a higher risk of developing fulminant infection.
We endeavoured to make an “apples to apples” comparison here of Seasonal Influenza death rates to PF11. Obstacles occurred. The primary block is the continued espousal by the CDC of the number “36,000”, a mythical mathematical model output that generalises annual US deaths related to Influenza-Like-Illness (ILI) AND secondary Pneumonia (bacterial, viral or fungal). The figure of “36,000” was created, in a calculation, but nonetheless, created. Facts are not created, nor are they spoken into being by repetition. However, repetition may be used to manage perception toward or away from a fact, even to revise the public perception to a position that is 180 degrees polar from the fact.
Knowledge is discovered, not built by consensus or a popular vote of opinions, not pulled by the wind of political philosophy and certainly not established by the payment of the highest bidder. Data that is surfaced, investigated, repeated and proven may be promoted to the unimpeachable fact category. Although political policy has no effect on creating fact, the reigning political voice does hold a primary strength in creating perception. Much of the recent public health messaging on PF11 appears to be based not on facts, but reliant upon consensus “science” or some other group of non-correlative and causality-free hypotheses. Are we having our perceptions managed?
Seeking the actual Influenza-only data demonstrated no recent year on record with a figure resembling “36,000”. In fact, most years trended very closely to 2,000 deaths, with many nearer to 1,000. When public health officials combine the two similar symptomologies of Influenza and Pneumonia (though the causes are generally diametrically opposed), a portion of the labor involved in testing and surveillance is alleviated from the medical community. Their gain is your loss due to the lowered accuracy, compatibility and actionability of their published data.
CDC Pediatric Data: Children under Age 18
The science community has known the risk of a High-CFR Pandemic and yet has failed to surveil the signals. Additional observation of public health reports inspired a validation of reports regarding deaths in the “under 18” category. The historical numbers are markedly lower than we have been led to believe during this “mild” Influenza “social messaging” campaign. When public health officials draw a parallel between Seasonal Influenza and PF11, they mischaracterise their own data. The present number of deaths from PF11 in young people clearly represents a substantial multiplier over previous years, but does not appear in those ratios in the official account.
Table 1 may lead you to perceive that the threat from PF11 is insubstantial, because Table 1 is very misleading for many reasons. The most prominent question that comes to mind is that far more than 29 PF11 deaths have occurred in this group according to state health departments and media reports, but the current surveillance monitoring system may not be up to task for capturing results in response to this summer anomaly. We are left to comparing apples and oranges when lives are at stake. Let’s evaluate other comparisons for a moment.
These data points do not allow us to make an “apples to apples” comparison; however, we may certainly conclude one clear peak using only CDC data. “Deaths per Day” is substantially higher this season than recent previous years and is peaking again during PF11. Again, disclaimers apply. We are working with another’s data.
Consider that rapid testing for PF11 failed to properly classify 31% to 60% of the ill across America, so the derived PF11 average is substantially lower than the actual deaths. Factor the false negative rate of the tests and the actual Deaths per Day quickly distinguishes itself from our earlier .46 to a minimum of .60, maximum of .74 and average of .67 Deaths per Day.
Moving closer to a valid comparison with this moderate data norming, Table 3 with the PF11 average adjustment for false negative testing increases compatibility of the data. Unfortunately, averaging is all that can be accomplished due to the weak surveillance.
A fair evaluation would promote Table 4 for the simple reason that “Seasonal” Influenza is very different than an Influenza that occurs in summer heat; however, the data points are relatively sparse though the situation does directly compare. Few to no deaths in any preceding year and 42 data-normed deaths this summer demonstrate a marked difference.
The average daily death figure in the final column of Tables 2, 3 and 4 is certainly not a product of a statistical model, but a simple division, a measurement of facts across time. When a daily average increases, a careful investigation is always in order because a change that is occurring consistently will accumulate rapidly and may establish variant behaviour and impacts. The data gathered and reported by public health officials fails to parallel, to inform, the “social messaging” emanating from those very same public health officials on PF11? History will examine motivations for this disparity and judge those who have acted dishonorably. We will report the data.
Underlying Health Conditions
The “managed message” campaign has consistently downplayed the PF11 death count while emphasising that “underlying health conditions” are more of a concern than the actual viral pathogen. We personally are baffled by this direction of messaging. Why are we baffled? The facts speak for themselves.
On a very related note, but not mentioned in the media, Johns Hopkins, in a recent study, found that 60% of Americans suffer from a chronic or degenerative disease and more than 25% suffer from two or more. The Johns Hopkins list of disease factors aligns with the set of complications for PF11. The “underlying health conditions” public messaging that is intended to soften the death count takes on a new light when you realise that 60% of Americans fall into the “pre-existing health conditions” category and, as such, become candidates for the PF11 death roles.
Is weight an “underlying health condition”? Apparently an overweight individual is at higher risk for Acute Respiratory Distress Syndrome (ARDS) and ICU admittance with PF11. The Michigan department of health reported that 90% of the individuals in their Intensive Care Units were overweight.
Is poor immune function a factor? If so, then an additional 23.5 million Americans that are defined as having various levels of Auto Immune Syndrome may face a difficult co-factor situation. Vaccines are known to suppress the maturation of innate immune cells (Th1 response via dendritic cells) at a higher rate within damaged immune systems. Mount Sinai studies have confirmed that a strong innate response is the basis for successful viral clearance. These studies and others suggest that an individual with present immune dysfunction may be at additional risk of derangement by the introduction of vaccine-delivered, Th2-stimulating antigen.
Perhaps we should stop being assuaged by clever interpretations and start reviewing the actual data with our own eyes?
For additional background on the clinical and epidemiological observational facts concerning Pandemic Influenza H1N1, please refer to the Table of Contents for PF11 Trends & Issues, Mid-Term.
