Why It's Good for COVID-19 Models to Be Wrong

Why It’s Good for COVID-19 Models to Be Wrong –

As we react to the predictions that epidemiological models make, changing the ways we act and go about our lives, those estimates can appear totally off. But if a model’s predictions end up being wrong, that might mean it’s done exactly the job it was supposed to.

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Sources:
https://www.nytimes.com/2020/03/17/world/europe/coronavirus-imperial-college-johnson.html
https://www.ft.com/content/67e6a4ee-3d05-43bc-ba03-e239799fa6ab
https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregisteredweeklyinenglandandwalesprovisional/latest
http://www-sop.inria.fr/members/Ian.Jermyn/philosophy/writings/Boxonmaths.pdf
https://www.nature.com/articles/d41586-020-01003-6
https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
https://covid19.healthdata.org/united-states-of-america
https://wwwnc.cdc.gov/eid/article/26/7/20-0282_article