This code is related to the paper (preprint):
Sandor Beregi, Sangeeta Bhatia, Anne Cori and Kris V. Parag, EpiControl: a data-driven tool for optimising epidemic interventions and automating scenario planning to support real-time response, MEDRXIV/2025/340271, Link
The related methodology is also used in:
Sandor Beregi, Kris V. Parag, Optimal algorithms for controlling infectious diseases in real time using noisy infection data, PLOS Computational Biology 21 (9), e1013426, Link
This code was intially adapted from the Epicont.jl Julia package.
| Example | Exp. Run time (on an average desktop) |
|---|---|
| Use EpiControl with compartmental models | < 1 min |
| Epidemic control based on deaths | < 1 min |
| Ebola example – using EpiEstim for R estimation | < 1 min |
| Bayesian hyperparameter optimisation | 30–40 mins |
| COVID-19 control with larger NPI space | 3–4 mins |
| Optimal control of ICU cases for COVID-19 | < 1 min |
| Threshold-based control of ICU cases for COVID-19 | < 1 min |
| COVID-19 vaccination and new variant | < 1 min |
Under construction.