Healthcare facility capacity optimization during COVID-19 pandemic using epidemiological models and mathematical modeling

This research proposes a mathematical model to assign COVID-19 patients to healthcare facilities. The study aims to minimize unmet demand and the number of infected people, while accounting for capacity constraints of the healthcare facilities. The number of infected COVID-19 patients is estimated using epidemiological models (i.e., Susceptible-Infectious-Recovered model). The study focuses on 67 counties in Florida, where the number of infected people and healthcare capacity vary between counties. The model takes into account the movement of patients between counties, as patients may need to move to a different county for treatment. The movement of infected individuals between counties further spreads the COVID-19 virus, and this effect is also incorporated into the SIR model.