Evaluating COVID-19 vaccine allocation policies using Bayesian m-top exploration

@article{Cimpean2023EvaluatingCV,
  title={Evaluating COVID-19 vaccine allocation policies using Bayesian m-top exploration},
  author={Alexandra Cimpean and Timothy Verstraeten and Lander Willem and Niel Hens and Ann Now'e and Pieter J. K. Libin},
  journal={ArXiv},
  year={2023},
  volume={abs/2301.12822}
}
Individual-based epidemiological models support the study of fine-grained preventive measures, such as tailored vaccine allocation policies, in silico. As individual-based models are computationally intensive, it is pivotal to identify optimal strategies within a reasonable computational budget. Moreover, due to the high societal impact associated with the implementation of preventive strategies, uncertainty regarding decisions should be communicated to policy makers, which is naturally… 
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