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backandnow:

Bayesian back-calculation and nowcasting for line list data during the COVID-19 pandemic

simulation

  • cluster.R: Parallel processing for the simulation (complete line list data).
  • cluster_ss.R: Parallel processing for the simulation (delayed surveillance initiation and real time estimation).
  • rt.rds: Daily reproductive numbers used in the simulation.
  • The output folder: Raw simulation output files and processing code.

Source code

  • backnow.cpp: Bayesian back-calculation and nowcasting.

Final Result: clean output used in the paper

  • result.R: Code for generating all the figures and tables.
  • count.rds: Daily case count estimates for complete line list data.
  • count_ss.rds: Daily case count estimates for delayed surveillance initiation.
  • count_ss1.rds: Daily case count estimates for real time estimation.
  • rest.rds: Time-varying reproductive number estimates for complete line list data.
  • rest_ss.rds: Time-varying reproductive number estimates for delayed surveillance initiation.
  • rest_ss1.rds: Time-varying reproductive number estimates for real time estimation.
  • eva1.rds: Coverage rates and RMSE for complete line list data.
  • eva2.rds: Coverage rates and RMSE for delayed surveillance initiation.
  • eva3.rds: Coverage rates and RMSE for real time estimation.
  • geweke.rds: Geweke's diagnostics

Daily flow rates in Massachusetts

  • pop_flow_county_byday_dataframe.csv: Data containing average daily flow rates over all Massachusetts counties.