Inference in epidemiological agent-based models using ensemble-based data assimilation

@article{Cocucci2022InferenceIE,
  title={Inference in epidemiological agent-based models using ensemble-based data assimilation},
  author={Tadeo J. Cocucci and Manuel Pulido and Juan Aparicio and Juan Ruiz and Mario Ignacio Simoy and Santiago Rosa},
  journal={PLoS ONE},
  year={2022},
  volume={17}
}
To represent the complex individual interactions in the dynamics of disease spread informed by data, the coupling of an epidemiological agent-based model with the ensemble Kalman filter is proposed. The statistical inference of the propagation of a disease by means of ensemble-based data assimilation systems has been studied in previous works. The models used are mostly compartmental models representing the mean field evolution through ordinary differential equations. These techniques allow to… 
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