Disease-economy trade-offs under alternative epidemic control strategies

Abstract

Public policy and academic debates regarding pandemic control strategies note disease-economy trade-offs, often prioritizing one outcome over the other. Using a calibrated, coupled epi-economic model of individual behavior embedded within the broader economy during a novel epidemic, we show that targeted isolation strategies can avert up to 91% of economic losses relative to voluntary isolation strategies. Unlike widely-used blanket lockdowns, economic savings of targeted isolation do not impose additional disease burdens, avoiding disease-economy trade-offs. Targeted isolation achieves this by addressing the fundamental coordination failure between infectious and susceptible individuals that drives the recession. Importantly, we show testing and compliance frictions can erode some of the gains from targeted isolation, but improving test quality unlocks the majority of the benefits of targeted isolation.

Proactive vs. reactive country responses to the COVID-19 pandemic shock

“…This does not imply however that proactive strategies are in principle always preferable to reactive ones, and does not rule out the possibility that a well implemented reactive strategy could deliver equally good results in some circumstances. For instance, it has been recently shown that target isolation policies, where infectious individuals are rewarded to isolate themselves, can be used to couple economic and epidemic models for more effective control strategies [63]. Beyond direct economic effects, a longitudinal analysis of data from 15 countries has recently shown that elimination strategies are more effective in reducing transmission and deaths, while minimizing potential mental health effects [64] which play an important role for individuals and society [65].…”

How to control the spatiotemporal spread of Omicron in the region with low vaccination rates

“…Although our previous study on province-level onset risk prediction in South Africa revealed the trend of early spread of Omicron and ways to effectively control its early spread at the province level (8), it could not to meet the current needs of precise epidemic control and economic recovery (9)(10)(11). Being at the third year of the COVID-19 pandemic, ensuring normal social and economic activities to a greater extent is one of the most critical factors to be considered in epidemic control, especially for low-income areas with limited vaccination rates (12)(13)(14)(15).…”

A simple planning problem for COVID-19 lockdown: a dynamic programming approach

“…Following the COVID-19 outbreak a large number of papers have been written combining elements of both epidemiology and economics. One important motivation for these papers is that the pandemic faced policymakers with the challenge of keeping the virus diffusion under control while avoiding to suffocate economic activity (see, e.g., Acemoglu et al 2021;Alvarez et al 2021;Ash et al 2022;Atkeson 2020;Eichenbaum et al 2021;Farboodi et al 2021;Fabbri et al 2023;Favero 2020;Federico and Ferrari 2021;Federico et al 2022;Goenka and Liu 2020;Gollier 2020). From a mathematical perspective, this motivation leads to the formulation of suitable dynamic optimization problems, that can be tackled with different techniques.…”