Accurately Comparing COVID-19 to Influenza

AS THE US AWAKENS FROM the period of time in this disaster when those who hold power have done what they can do to identify their most profitable position – including the CDC, who want “their own” test – and politicians, who waste precious, irreplaceable time slamming each other for what they believe might be political gain over COVID-19 – the US has emerged to the point where we realize we are a frog in the pot, and it is filling at an exponential rate with boiling water.

Still, there have been a number of comparisons of COVID-19 to influenza, and I wanted to publish an analysis of rates comparing the rate of spread of COVID-19 in the US to the rate of spread of influenza. “Can’t do that” people think, because we don’t know the number of undetected cases.

Actually, we kind of do, and we therefore can provide reasonable estimates for the comparison.

A study published this week estimated the percentage of undetected cases in China over the course of their outbreak at 86%.

The data for the influenza outbreak includes Influenza A and B, and are from this site. They reflect the first 49 days from the onset of the outbreak. Testing for influenza is extensive, but not thorough, and many cases of flu of course do not make it to a clinic. So the comparison is “COVID-19 spread corrected for not testing” to “Influenza spread with testing”. It is, I think the best we can do right now.

The corrected count for COVID-19 is Cases by Day X / (1-0.86). I plot both the uncorrected COVID-19 and the corrected.

This is just the first 49 days, but we can see where this is going. When testing comes, there will be a second major shock. To ease the shock, here is the full curve to date for the estimated total number of cases. From this analysis, we can estimate the number of cases in the US on 3/21/2020 to be between 120,000 and 140,000. The last five days may be an overestimate because local testing (testing using kits developed locally) started in medical facilities about five days ago.

I’ve also published a measure that tells of us how we are doing in controlling this beast. My measure of Effective R0 will adjust every five days to whatever the net influences on reporting of the number of cases – and while testing will also cause it to seem to increase until testing rates level out, it does not require testing because testing mathematically cancels out if the rate of testing between Day X and Day X-5 is roughly similar.

Here is the updated EffectiveR0. We know local testing began about five days ago, as the medical community’s faith in the CDC’s test wanes to zero.

We need to continue working on getting R0 below 1 and keep it there. That means continued or increasing social distancing. The more we do sooner, the sooner we can get back to normalcy. I hope the message that therapeutics are absolutely essential kicks into practice. People are debating which types of therapeutics, ok, fine. My position is that people should be given the option to select any therapeutic that has a rational basis for helping to reduce, but does not increase the spread, and does not sensitize people to SARS-CoV-20 or 21 in the future.

Of course as in any medicine, informed consent is a must, and patients must be afforded a list of possible and likely known side effects – and a list of certain outcomes for which we don’t yet have data. Those who can participate in social distancing, keep it up. Those who must not socially distance due to their essential roles should be given choices of CPT, antivirals, or both.

A new era of medicine may be born from the ashes of the COVID-19 outbreak in which we can unleash the full power of advanced technologies, computer modeling, including quantum computing to identify therapeutics for patients to be able to be treated safely with effective means of shutting down viral replication. Or we just might discover some simple remedies in use by some doctors across the US to treat viral illnesses.

There will be no vaccine for this virus due to Pathogenic Priming (aka ‘Immune Enhancement’) (see: Moderna and US NIAID Poised to Endanger the World Population?). Citizens deserve to know they may be at worse outcome from an infection of potentially deadly coronaviruses following exposure to a spike protein-based vaccines.

We need a therapy/outcomes tracking database so we have large amounts of data by which we can assess effective interventions.


Li et al., Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2). Science March 2020.


  1. shows US daily data points beginning Feb 15th, so yours is earlier. Can you share where you get your data?

    Also “The corrected count for COVID-19 is Cases by Day X / (1-0.86)”, where “X” is the detected cases on any given day, right?

    So a spreadsheet that is always updated, showing real+undetected cases could be made using the above formula where X is the detected cases (reported to-date)? Right?

  2. What, in your estimation, is causing the decline in death rates for this virus in China (and elsewhere) after the initial huge spike? Does surviving this virus confer a level of future immunity? Does the passage of this virus from one person to the next attenuate it so that it becomes less deadly as it spreads? I’d love to hear the current science and thinking around these questions.

  3. Why no comparison with influenza A + B real + undetected? Seems this would make quite a large difference in the influenza curve. Can you provide this simulation curve or a further explanation of why it’s not relevant.

    1. Oh it is relevant. Unfortunately I could find no estimate of the % undetected influenza cases per season. If you find one please share the link. Thanks.

  4. Hello…
    I am listening to a panel on which Dr. Weiler is sitting as a presenter. I am trying to reach out to those who might have the capacity to look into the following. My partner is a physician in KY. She tells me that her colleagues are reporting that in EVERY case, when testing for influenza, the tests are coming back negative, something which she, also a PhD Molecular Biology, says is a statistical impossibility. It’s one thing for the CDC to tell us there is no flu, another to see the testing actually demonstrate that. Just food for thought that I hope, might open another avenue for those gifted with talents to peal back yet another layer of this fraud. Thanks so much for your time!

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