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Inference of epidemiological dynamics using sequence data: application to influenza

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Infectious Disease Dynamics

In the past decade, there has been a rapid increase in the availability of high-resolution viral sequence and epidemiological data, combined with developments in statistical and computational methods to simulate and infer the population dynamics of viral infections. Sequence-based approaches have provided key insights into the spatial and temporal dynamics of influenza A viruses in humans. In this talk, we will review and contrast findings from phylogenetic and epidemiologic studies of influenza population dynamics.

This talk is part of the Isaac Newton Institute Seminar Series series.

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