Insights from Optimal Pandemic Shielding in a Multi-Group SEIR Framework

TL;DR

This paper uses a multi-group SEIR model calibrated for Germany to analyze and compare the effectiveness of various COVID-19 policy measures, highlighting the benefits of targeted shielding and combined strategies.

Contribution

It extends the multi-group SEIR model to include diverse policy measures and social interactions, providing new insights into optimal shielding strategies during a pandemic.

Findings

Targeted shielding by age group improves efficiency.

Combining multiple policies reduces mortality and economic impact.

Physical distancing can lessen the need for strict shielding.

Abstract

The COVID-19 pandemic constitutes one of the largest threats in recent decades to the health and economic welfare of populations globally. In this paper, we analyze different types of policy measures designed to fight the spread of the virus and minimize economic losses. Our analysis builds on a multi-group SEIR model, which extends the multi-group SIR model introduced by Acemoglu et al.~(2020). We adjust the underlying social interaction patterns and consider an extended set of policy measures. The model is calibrated for Germany. Despite the trade-off between COVID-19 prevention and economic activity that is inherent to shielding policies, our results show that efficiency gains can be achieved by targeting such policies towards different age groups. Alternative policies such as physical distancing can be employed to reduce the degree of targeting and the intensity and duration of shielding. Our results show that a comprehensive approach that combines multiple policy measures simultaneously can effectively mitigate population mortality and economic harm.