Corpus ID: 237571674

Nonsmooth convex optimization to estimate the Covid-19 reproduction number space-time evolution with robustness against low quality data

@inproceedings{Pascal2021NonsmoothCO,
  title={Nonsmooth convex optimization to estimate the Covid-19 reproduction number space-time evolution with robustness against low quality data},
  author={Barbara Pascal and Patrice Abry and Nelly Pustelnik and St{\'e}phane G. Roux and R{\'e}mi Gribonval and Patrick Flandrin},
  year={2021}
}
Daily pandemic surveillance, often achieved through the estimation of the reproduction number, constitutes a critical challenge for national health authorities to design counter-measures. In an earlier work, we proposed to formulate the estimation of the reproduction number as an optimization problem, combining data-model fidelity and space-time regularity constraints, solved by nonsmooth convex proximal minimizations. Though promising, that first formulation significantly lacks robustness… Expand

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