A key issue in the current coronavirus COVID-19 pandemic is how it compares to “seasonal flu,” “flu,” “influenza” or “pneumonia and influenza,” terms that are often used interchangeably but have different definitions or implied definitions in different contexts.
For example, the widely quoted infection fatality rate for the “flu” of 0.1 percent (one in a thousand) is based on models from the CDC that assume deaths from the influenza viruses are grossly underreported. Regardless of the models, in common English usage a large fraction of the public interprets “flu” as synonymous with “common cold.” The effective infection fatality rate of the common usage “flu”/”common cold” (averaged over all diseases and people) is far below 0.1 percent.
An overlapping key issue is whether false positives from the coronavirus RT-PCR test or diagnoses without the test (e.g. lung x-rays or examination of a patient by a doctor) has attributed a substantial number of conventional pneumonia deaths and heart attacks to the COVID-19 coronavirus.
Remarkably, the United States Centers for Disease Control (CDC) appears to use two different counts (or model outputs?) of annual deaths from “influenza and pneumonia” or “pneumonia and influenza” that differ by over a factor of three.
The “Deaths: Final Data for 2017” report (Page Six, Table B) lists “influenza and pneumonia” as the eighth leading cause of death with 55,672 deaths in 2017.
In contrast, the Weekly Pneumonia and Influenza (P&I) Mortality Surveillance lists over 180,000 deaths from “pneumonia and influenza” (mostly pneumonia) in 2017 in the data files on the site apparently used to generate the FluView plot displayed. The weekly surveillance number provides a much larger pool of potential false positives than the more widely quoted number of about 50,000 “flu” deaths per year.
Influenza: a study in contemporary medical politics by Peter Doshi
Peter Doshi has published many articles on the CDC’s “flu” death numbers, the CDC’s long history of seemingly contradictory claims about influenza and pneumonia, and related topics. Some of these are available online. His Ph.D. dissertation Influenza: a study in contemporary medical politics from MIT goes into much more detail and is available at: https://dspace.mit.edu/handle/1721.1/69811 (Click Download on the left side)
If MIT does not work (MIT download is faster), an archival copy is available at: http://www.mathematical-software.com/778073688-MIT.pdf
This is a well written but long (312 pages) dissertation. All of it is relevant to the current pandemic crisis, but it is a lot to digest. The most important and most relevant to the current pandemic section is Chapter 4: False Assumptions: a Shaky Foundation for Consensus (Pages 151-212, including tables and figures).
Key topics discussed in detail in this chapter include:
The CDC uses models to assign many deaths to influenza (the influenza viruses) even though doctors rarely diagnose influenza, rarely list influenza as a cause of death on death certificates, and most laboratory tests of samples from patients with respiratory illnesses (often called Influenza Like Illnesses or ILI) do not confirm the presence of the influenza viruses and often identify other viruses such as rhinovirus, adenovirus, various coronaviruses, etc. as present instead. These models may even assign deaths listed on death certificates as heart attacks to the total.
The models differ from researcher and publication to researcher and publication, have changed dramatically over the years, notably a jump from 20,000 estimated “flu” deaths in 2002 to a widely quoted estimate of 36,000 in 2003.
The evidence that flu vaccines work is weak and contradictory.
Conclusion
There is a remarkable lack of key measurements in the current coronavirus COVID-19 pandemic. These include the actual mortality rate (aka infection fatality rate) broken down by age, sex, race, pre-existing medical conditions, ambient temperature, sunlight levels, pollution levels, and other risk factors. The false positive and false negative rates of the tests for the disease, both the tests for an active infection such as the RT-PCR tests and tests for past infection such as the antibody tests. The methods and rates of transmission for the disease. Aerosol transmission probably occurs at least at a low level and is virtually unstoppable.
The confusing language and numbers on pneumonia and influenza on the CDC web site and in various official reports and documents seem to be primarily for marketing the flu vaccines rather than enabling informed decisions by patients and doctors or supporting external scientific research into the influenza viruses or other diseases.
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About Me
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).