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New data is emerging this week that suggests original computer projections related to COVID-19 are seriously flawed.

I alluded to this problem in a few previous articles, Accuracy of COVID-19 Testing, You're More Likely to Die From This Pandemic Disease Than COVID-19, and Staying Calm & Taking Action in the Face of COVID-19, and now we're starting to see real data come forth.

Recent large-scale independent studies, one from the University of Southern California (USC) and the other from Stanford University, each produced similar data indicating the new coronavirus (CoV-2), otherwise known as COVID-19, has already infected a larger portion of the population.

These new findings are significant as they suggest COVID-19 is far more common and much less lethal than the computer modeling government officials and mainstream media have been using to promote social distancing and shelter-in-place orders.

COVID-19 Antibody Testing in California Indicates COVID-19 Similar to Seasonal Flu

This implies that the overall fatality rate is much lower than the official media tallies suggest. In contrast with the current publicized fatality rate of about 2%-4.5% that was modeled with mathematical speculation, this new data suggests that between 0.1%- 0.2% percent of people infected by the virus will die, making COVID-19 no more deadly than the common seasonal flu.

The COVID-19 antibody tests in Los Angeles and Santa Clara Counties in California sought to discover how many people in these areas may have already been infected by checking to see how many of them have already developed antibodies for the virus. Antibodies, also known as immunoglobulins (Ig), are large proteins produced and used by the immune system to neutralize microorganisms such as pathogenic bacteria and viruses.

Based on representative samples, the Santa Clara County study suggests the true number of COVID-19 infections could be between 50 to 85 times higher than the number of reported ones. And in Los Angeles County, there might be 28 to 55 times more people infected than the official count.

This implies that the overall fatality rate is much lower than the official media tallies suggest. In contrast with the current publicized fatality rate of about 2%-4.5% that was modeled with mathematical speculation, this data suggests that between 0.1%- 0.2% percent of people infected by the virus will die, making COVID-19 no more infectious or deadly than the common seasonal flu.

About the Author

authorRene M. Rodriguez is a Doctor of Oriental Medicine and board licensed acupuncturist with 20 years experience in alternative natural medicine. He's in private practice in Los Angeles, CA, speciliazing in digestive disorders, skin conditions, infections, environmental illness, and mind-body health and wellness. For more information, please click here.


REFERENCES

  1. Atlas, S. (2020). The data is in — stop the panic and end the total isolation. The Hill. Retrieved from https://thehill.com/opinion/healthcare/494034-the-data-are-in-stop-the-panic-and-end-the-total-isolation .
  2. Bendavid, E., et. al. (2020). COVID-19 Antibody Seroprevalence in Santa Clara County, California. medRxiv. Retrieved from https://www.medrxiv.org/content/early/2020/04/17/2020.04.14.20062463.full.pdf .
  3. Finley, A. (2020). The Bearer of Good Coronavirus News: Stanford scientist John Ioannidis finds himself under attack for questioning the prevailing wisdom about lockdowns. Wall Street Journal. Retrieved from https://www.wsj.org/articles/the-bearer-of-good-coronavirus-news-11587746176 .
  4. Ioannidis, J.P.A. (2020). A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data. STAT. Retrieved from https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/ .
  5. Ioannidis, J.P.A. (2020). Coronavirus disease 2019: The harms of exaggerated information and non‐evidence‐based measures. Eur J Clin Invest, 50: e13222. doi:10.1111/eci.13222 . Retrieved from https://onlinelibrary.wiley.com/doi/full/10.1111/eci.13222 .
  6. Ioannidis, J.P.A., et. al. (2020). Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters. medRxiv. doi:10.1111/eci.13222 . Retrieved from https://www.medrxiv.org/content/10.1101/2020.04.05.20054361v1 .
  7. University of Southern California. (2020, April 20). Preliminary results of USC-LA County COVID-19 study released. USC.edu. https://pressroom.usc.edu/preliminary-results-of-usc-la-county-covid-19-study-released/

 

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