Python code for "Tracking R of COVID-19: A New Real-Time Estimation Using the Kalman Filter". Authors: Francisco Arroyo, Francisco Bullano, Simas Kucinskas, and Carlos Rondón-Moreno.
Suggested citation: Arroyo-Marioli F, Bullano F, Kucinskas S, Rondón-Moreno C (2021) Tracking R of COVID-19: A new real-time estimation using the Kalman filter. PLoS ONE 16(1): e0244474. https://doi.org/10.1371/journal.pone.0244474
We update the database daily (if possible). New estimates are available around 8:00 AM ET. Instructions for the database are available in the README file included in the folder "Estimates-Database". The stable link to the dataset is: https://github.com/crondonm/TrackingR/tree/main/Estimates-Database
See README file for detailed instructions.
The original data are collected by the John Hopkins CSSE team and are publicly available online (https://github.com/CSSEGISandData/COVID-19).
- 26/3/2021: We have updated the estimation procedure to (i) use more informative priors; and (ii) allow for intra-week seasonality. With these changes, we get estimates of R that are more consistent with the growth rate of infections seen in each country.
You can write an email to simas [dot] kucinskas [at] hu [dash] berlin [dot] de – all comments and suggestions are most welcome.