University of Cambridge > > Isaac Newton Institute Seminar Series > Epidemics and population structure: One step forward, and two steps back

Epidemics and population structure: One step forward, and two steps back

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If you have a question about this talk, please contact Mustapha Amrani.

Infectious Disease Dynamics

In general, the incorporation of population structure into epidemic models creates problems of dimensionality for prediction (the `forward problem’). Even for the `simple epidemic’ / SI model, complete individual heterogeneity of n individuals leads to a dynamical system whose size grows like 2^n.

There are, however, two `inverse problems’ where this curse becomes a blessing: for statistical inference, flat directions in parameter space can become identifiable once more stratification of data is available; and the presence of population structure allows a far wider range of control and mitigation strategies to be compared than are possible in a homogeneous system.

This talk will consider: (i) the generation of predictions from heterogeneous epidemic models without excessive dimensionality; (ii) the use of multiple stratified data sources to resolve statistical questions about the otherwise unidentifiable but epidemiologically important quantities; (iii) informing public health policy on the basis of these considerations. Real-world examples will come from the 2009 H1N1 influenza pandemic.

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

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