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2020

First-principles machine learning modelling of COVID-19

Magri, Luca, Doan, Nguyen Anh Khoa

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The coronavirus disease 2019 (COVID-19) has changed the world since the World Health Organization declared its outbreak on 30th January 2020, recognizing the outbreak as a pandemic on 11th March 2020.

As often said by politicians and scientific advisors, the objective is "to flatten the curve", or "push the peak down", or similar wording, of the virus spreading.
Central to the official advice are mathematical models and data, which provide estimates on the evolution of the number of infected, recovered and deaths.
The accuracy of the models is improved day by day by inferring the contact, recovery, and death rates from data (confirmed cases).

First-principles machine learning modelling of COVID-19 · Around

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Contributions to the mathematical theory of epidemics—I
W. Kermack and A. McKendrick · 1991
Earlier work this paper cites.
The mathematics of infectious deseases
Herbert W Hethcote · 2000
Earlier work this paper cites.
Numerical Recipes
Original
Will Tribbey · 2004
Earlier work this paper cites.

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Mathematical models of infectious disease transmission
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https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf
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https://administracion.gob.es/pag_Home/atencionCiudadana/Estado-de-alarma-crisis-sanitaria.html#.Xn3xj0dKjIU
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https://www.bbc.co.uk/news/uk-52014472
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https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology
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Then

https://www.gazzettaufficiale.it/eli/id/2020/03/09/20A01558/sg
2020
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Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
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