Alliance for Pandemic Preparedness
July 6, 2020
Modeling, State Estimation, and Optimal Control for the US COVID-19 Outbreak
Category: Article Summary
Topic: Modeling and Prediction
- Tsay et al. reported a novel, optimization-based decision-making framework for managing the COVID-19 outbreak in the US. This includes modeling the dynamics of affected populations, estimating the model parameters and hidden states from data, and an optimal control strategy for sequencing social distancing and testing events such that the number of infections is minimized.
- Results show that social distancing and quarantining are most effective when implemented early, with quarantining of confirmed infected subjects having a much higher impact. The “on-off” policies alternating between strict social distancing and relaxing such restrictions can be effective at “flattening” the curve while likely minimizing social and economic cost.
Tsay et al. (July 1, 2020). Modeling, State Estimation, and Optimal Control for the US COVID-19 Outbreak. Scientific Reports. https://doi.org/10.1038/s41598-020-67459-8