PyRenew

2024

epidemiology
bayesian
A flexible tool for simulation and statistical inference of epidemiological models, emphasizing hierarchical multi-signal renewal models.

ActivePackage2024version0.1.0stars29

  1. Bayer, D.
  2. Morris, D. H.
  3. Vega Yon, G. G.University of UtahiD
  4. Martin, T.
  5. Bidari, S.

Link•Repository

A Package for Bayesian Renewal Modeling with JAX and NumPyro

About

A flexible tool for simulation and statistical inference of epidemiological models, emphasizing hierarchical multi-signal renewal models. Built on top of the ‘numpyro’ Python library, ‘PyRenew’ provides core components for model building. A renewal model estimates new infections from recent past infections using a generation interval, from which it infers the time-varying reproduction number R(t). PyRenew’s strength lies in multi-signal integration for pooling information across diverse observed data streams, such as hospital admissions, wastewater concentrations, and emergency department visits, each with distinct observation delays, noise characteristics, and spatial resolutions.

Cite

@Manual{pyrenew,
  title = {PyRenew: A Package for Bayesian Renewal Modeling with JAX and NumPyro},
  author = {{Bayer}, {Damon} and {Morris}, {Dylan H} and {Vega Yon}, {George G.} and {Martin}, {Trevor} and {Bidari}, {Subekshya}},
  year = {2024},
  url = {https://github.com/CDCgov/PyRenew},
  note = {Python package version 0.1.0},
}

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