• Corpus ID: 249605724

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… 

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

TLDR
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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