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Superspreaders Cities Coming to a Theater Near You

In high school, everyone joked that they would never use their Algebra 2 again, but mathematicians appear to be planning a takeover of the world with all their models of doomsday COVID 19 predictions.  Mathematicians reported their model to predict which cities could become super-spreaders for diseases like COVID 19 in PLOS Computational Biology recently.  They claim their crystal ball can identify which cities are dangerous and perilous.  At best it will make for 2nd rate science fiction thriller about the end of normal life on earth.

Yes, I am unimpressed given the series of COVID 19 crystal ball projections made by the experts and their so called “models”.  I have touched on this before, but basically, a model can be manipulated in a million ways to get whatever result you want.  Besides, that, either a bad model or bad data fed into that model gives the same worthless results.

Don’t get me wrong, I was one of the odd ones who actually enjoyed math in high school until calculus problems wore me out.  I am just saying that we are not very good at predicting the future even with so called science and its mathematical models.

All I ask in our search for COVID answers is that we don’t use more unproven models to fundamentally reshape society.  We are still spiraling out of control with that most recent COVID 19 insanity.  For 2021 and beyond, let’s learn from our mistakes and take these models with a grain of salt.

 

Original Article:

Brandon Lieberthal, Allison M. Gardner. Connectivity, reproduction number, and mobility interact to determine communities’ epidemiological superspreader potential in a metapopulation network. PLOS Computational Biology, 2021; 17 (3): e1008674 DOI: 10.1371/journal.pcbi.1008674

 

Thanks to Science Daily:

PLOS. “New statistical model predicts which cities could become ‘superspreaders’: Model efficiently combines connectivity between cities with cities’ varying suitability for spread.” ScienceDaily. ScienceDaily, 18 March 2021. <www.sciencedaily.com/releases/2021/03/210318142518.htm>.

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