Disease-dependent interaction policies to support health and economic outcomes during the COVID-19 epidemic

作者：Guanlin Li, Shashwat Shivam, Michael Hochberg, Y. Wardi, Joshua S. Weitz · 发表于：iScience · 年份：2021 · DOI：10.1016/j.isci.2021.102710 · 被引用次数：75 · 研究领域：COVID-19 epidemiological studies、SARS-CoV-2 and COVID-19 Research、COVID-19 Pandemic Impacts

mitigation has come with substantial socioeconomic costs. In this paper, we demonstrate how individualized policies based on disease status can reduce transmission risk while minimizing impacts on economic outcomes. We design feedback control policies informed by optimal control solutions to modulate interaction rates of individuals based on the epidemic state. We identify personalized interaction rates such that recovered/immune individuals elevate their interactions and susceptible individuals remain at home before returning to pre-lockdown levels. As we show, feedback control policies can yield similar population-wide infection rates to total shutdown but with significantly lower economic costs and with greater robustness to uncertainty compared to optimal control policies. Our analysis shows that test-driven improvements in isolation efficiency of infectious individuals can inform disease-dependent interaction policies that mitigate transmission while enhancing the return of individuals to pre-pandemic economic activity.