# Approximating optimal SMC proposal distributions in individual-based epidemic models

@inproceedings{Rimella2022ApproximatingOS, title={Approximating optimal SMC proposal distributions in individual-based epidemic models}, author={Lorenzo Rimella and Christopher P Jewell and Paul Fearnhead}, year={2022} }

Many epidemic models are naturally defined as individual-based models: where we track the state of each individual within a susceptible population. Inference for individual-based models is challenging due to the high-dimensional state-space of such models, which increases exponentially with population size. We consider sequential Monte Carlo algorithms for inference for individual-based epidemic models where we make direct observations of the state of a sample of individuals. Standard…

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### Inference on Extended-Spectrum Beta-Lactamase Escherichia coli and Klebsiella pneumoniae data through SMC$^2$

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An individual-based model for the epidemic, with the state of the model determining which individuals are colonised by the bacteria, is introduced and an eﬃcient SMC 2 algorithm is developed to estimate parameters and compare models for the transmission rate.

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