# Robust Pandemic Control Synthesis with Formal Specifications: A Case Study on COVID-19 Pandemic

arXiv: https://arxiv.org/abs/2103.14262 · HTML: https://mlsanity.com/paper/2103.14262/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 39 references that are in the map.
- First posted on arXiv 26 Mar 2021.

## Builds on (most cited first, 10 of 10)

- [Transfer of Temporal Logic Formulas in Reinforcement Learning](https://mlsanity.com/paper/1909.04256/) (2019)
- [A SIDARTHE Model of COVID-19 Epidemic in Italy](https://mlsanity.com/paper/2003.09861/) (2020)
- [COVID-ABS: An Agent-Based Model of COVID-19 Epidemic to Simulate Health and Economic Effects of Social Distancing Interventions](https://mlsanity.com/paper/2006.10532/) (2020)
- [Modelling transmission and control of the COVID-19 pandemic in Australia](https://mlsanity.com/paper/2003.10218/) (2020)
- [Contact rate epidemic control of COVID-19: an equilibrium view](https://mlsanity.com/paper/2004.08221/) (2020)
- [An MILP Approach for Real-time Optimal Controller Synthesis with Metric Temporal Logic Specifications](https://mlsanity.com/paper/1603.02650/) (2016)
- [Control Strategies for COVID-19 Epidemic with Vaccination, Shield Immunity and Quarantine: A Metric Temporal Logic Approach](https://mlsanity.com/paper/2007.15114/) (2020)
- [Controller Synthesis for Multi-Agent Systems With Intermittent Communication: A Metric Temporal Logic Approach](https://mlsanity.com/paper/1909.09939/) (2019)
- [Differentially Private Controller Synthesis With Metric Temporal Logic Specifications](https://mlsanity.com/paper/1909.13294/) (2019)
- [The propagation of the economic impact through supply chains: The case of a mega-city lockdown against the spread of COVID-19](https://mlsanity.com/paper/2003.14002/) (2020)

## Built on by (most cited first, 1 of 1)

- [Uncertainty-Aware Signal Temporal Logic Inference](https://mlsanity.com/paper/2105.11545/) (2021)

## Abstract (arXiv)

Pandemics can bring a range of devastating consequences to public health and the world economy. Identifying the most effective control strategies has been the imperative task all around the world. Various public health control strategies have been proposed and tested against pandemic diseases (e.g., COVID-19). We study two specific pandemic control models: the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control; and the SEIR model with shield immunity control. We express the pandemic control requirement in metric temporal logic (MTL) formulas. We then develop an iterative approach for synthesizing the optimal control strategies with MTL specifications. We provide simulation results in two different scenarios for robust control of the COVID-19 pandemic: one for vaccination control, and another for shield immunity control, with the model parameters estimated from data in Lombardy, Italy. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications with robustness against initial state and parameter uncertainties.