Novel Methods for Reproduction Number Estimation, Back-Calculation, and Forecasting

A collection of functions related to novel methods for estimating R(t), created by the lab of Professor Laura White. Currently implemented methods include two-step Bayesian back-calculation and now-casting for line-list data with missing reporting delays, adapted in 'STAN' from Li (2021) , and calculation of time-varying reproduction number assuming a flux between various adjacent states, adapted into 'STAN' from Zhou (2021) .

WhiteLabRt

A collection of functions related to novel methods for estimating reproduction number, R(t), created by the lab of Professor Laura White at Boston University School of Public Health.

Currently implemented methods

• Temporal R(t) estimation: Two-step Bayesian back and nowcasting for linelist data with missing reporting delays, adapted in STAN from Li and White

  • Remaining todos:

    [] Implement the right-truncated NB distribution function in the likelihood and rng forms, see here for starters

• Spatial R(t) estimation: Calculating time-varying reproduction number, R(t), assuming a flux of infectors between various adjacent states. This was adapted in STAN from Zhou and White

  • Remaining todos:

    [] Continuing working on non-centered parameterization, AR1 process, and partial pooling [] Use tidy bayes for QC

Future plans

• Unified spatial-temporal R(t) estimation Combining the two methods above.
• Genetic-based R(t) Using genetic data to inform R(t) calculation