2021/09/13 by Gianluca Bianchin, Bianchin, Gianluca, Emiliano Dall’Anese +10
Mathematics · Psychology · #Advanced Causal Inference Techniques #COVID-19 and Mental Health #COVID-19 epidemiological studies #FOS: Electrical engineering #FOS: Mathematics #Mental Health Research Topics #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2109.06025
openalex publication_date 2021/09/13 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Since the early months of 2020, non-pharmaceutical interventions (NPIs) --\nimplemented at varying levels of severity and based on widely-divergent\nperspectives of risk tolerance -- have been the primary means to control\nSARS-CoV-2 transmission. We seek to identify how risk tolerance and vaccination\nrates impact the rate at which a population can return to pre-pandemic contact\nbehavior. To this end, we develop a novel feedback control method for\ndata-driven decision-making to identify optimal levels of NPIs across\ngeographical regions in order to guarantee that hospitalizations will not\nexceed a given risk tolerance. Results are shown for the state of Colorado, and\nthey suggest that: coordination in decision-making across regions is essential\nto maintain the daily number of hospitalizations below the desired limits;\nincreasing risk tolerance can decrease the number of days required to\ndiscontinue NPIs, at the cost of an increased number of deaths; and if\nvaccination uptake is less than 70 %, at most levels of risk tolerance, return\nto pre-pandemic contact behaviors before the early months of 2022 may newly\njeopardize the healthcare system.\n