Recent years have witnessed the development of data
driven models of contagion processes rooted in the combination
of large scale data mining techniques, computational approaches and mathematical modeling. Although these models are increasingly used to support public-health decisions
they are often under debate by only considering their value
as forecasting tools. Here I will discuss, by using specific
modeling examples, how computational models can be used
in real time to provide situational awareness, intervention
planning and projections, and the identification of factors
that fundamentally influence the course of contagion processes.
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IFISC Colloquia
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