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The saga of medical curves (3)
Curves for prediction


Curves for prediction


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What can epidemiological models contribute during a pandemic such as Covid-19? Can they justify measures that are difficult for the public by quantifying and explaining their direct effects on the spread of the disease?

Historically, differential equations emerged in response to geometrical questions and problems in physics, particularly the study of planetary motion, pendulums and, later, heat diffusion. Yet they have plenty of applications in biology too!

When faced with what seems to be the start of an epidemic, how can we predict how it will develop and spread geographically? Mathematical models attempt to answer these questions.

Driven by the desire for reliable demographic models, logistic functions emerged around 1840. They provide the best model for growth limited by external factors, extending Malthus's approach. Today they have unexpected applications, whether in marketing or household equipment.
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