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

Guanlin Li,Shashwat Shivam,Michael E Hochberg,Yorai Wardi,Joshua S Weitz

doi:10.1016/j.isci.2021.102710

Abstract

SummaryLockdowns and stay-at-home orders have partially mitigated the spread of Covid-19. However, en masse 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.

Highlights

As of 7 March 2021, more than 116,166,652 cases of coronavirus disease 2019 (COVID-19) have been reported worldwide with more than 2,582,528 deaths globally (World Health Organization, 2021)
SUMMARY Lockdowns and stay-at-home orders have partially mitigated the spread of Covid19
En masse mitigation has come with substantial socioeconomic costs

Summary

Introduction

As of 7 March 2021, more than 116,166,652 cases of coronavirus disease 2019 (COVID-19) have been reported worldwide with more than 2,582,528 deaths globally (World Health Organization, 2021). Initial strategies can be broadly grouped into mitigation and suppression, where the former attempts to preserve essential health care services and contain morbidity and mortality, whereas the latter imposes more severe, emergency restrictions to prevent health care system collapse and provide conditions for easing-off toward less intense mitigation strategies (Walker et al, 2020). Both mitigation and suppression approaches carry considerable social and economic costs, meaning that policymakers and the public at large only adopt them for short time periods (OECDa, 2020). A problem is that control measures have often been applied irrespective of an individual’s disease status (and/or likely infection risk severity) and are driven, in part, by the absence of information-driven alternatives

Results

Discussion

Conclusion