Optimal Targeted Lockdowns in a Multi-Group SIR Model

We study targeted lockdowns in a multi-group SIR model where infection, hospitalization and fatality rates vary between groups—in particular between the “young”, “the middle-aged” and the “old”. Our model enables a tractable quantitative analysis of optimal policy. For baseline parameter values for the COVID-19 pandemic applied to the US, we find that optimal policies differentially targeting risk

[yasudayasu]

(巷間言われる、経済学は代表的個人というあり得ないものを考えているという批判と違って)属性の違いが結論を左右するようなときにはこういうヘテロなモデルを考えたがりがちだよね。御せない場合を除いて。

[bhikkhu]

“For baseline parameter values for the COVID-19 pandemic applied to the US, we find that optimal policies differentially targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter lockdown policies on the oldest group.”