COVID-19: Health and Economic Impacts of Societal Intervention Policies in the U.S.

Boloori, Alireza; Saghafian, Soroush

doi:10.2139/ssrn.3681610

Cited by 4 publications

(5 citation statements)

References 34 publications

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“…However, there is limited work linking outbreak dynamics to decision‐support models. With a few notable exceptions (Boloori & Saghafian, 2020; Eryarsoy et al., 2022), the relevant literature mostly focuses on analyzing pandemic spread.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A few recent works examine the economic impact of intervention policies for COVID‐19. For instance, Boloori and Saghafian (2020) provide an analytical decision‐making framework based on a compartmental disease‐spread model to study the economic burdens of pandemic containment policies in the United States. They suggest that while severe societal intervention policies may not be cost effective, the policies imposed by the US government over a 4‐month period increased quality‐adjusted life years per capita.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With a few notable exceptions (Boloori & Saghafian, 2020;Eryarsoy et al, 2022), the relevant literature mostly focuses on analyzing pandemic spread. Recently, a number of studies have been published exploring different types of containment measures to control the spread of a pandemic.…”

Section: Literature Reviewmentioning

confidence: 99%

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Managing disease containment measures during a pandemic

Shahmanzari

Tanrısever

Eryarsoy

et al. 2023

Production and Operations Management

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Throughout the current COVID-19 pandemic, governments have implemented a variety of containment measures, ranging from hoping for herd immunity (which is essentially no containment) to mandating complete lockdown. On the one hand, containment measures reduce lives lost by limiting the disease spread and controlling the load on the healthcare system. On the other hand, such measures slow down economic activity, leading to lost jobs, economic stall, and societal disturbances, such as protests, civil disobedience, and increases in domestic violence. Hence, determining the right set of containment measures is a key social, economic, and political decision for policymakers. In this paper, we provide a model for dynamically managing the level of disease containment measures over the course of a pandemic. We determine the timing and level of containment measures to minimize the impact of a pandemic on economic activity and lives lost, subject to healthcare capacity and stochastic disease evolution dynamics. On the basis of practical evidence, we examine two common classes of containment policies-dynamic and static-and we find that dynamic policies are particularly valuable when the rate of disease spread is low, recovery takes longer, and the healthcare capacity is limited. Our work reveals a fundamental relationship between the structure of Pareto-efficient containment measures (in terms of lives lost and economic activity) and key disease and economic parameters such as disease infection rate, recovery rate, and healthcare capacity. We also analyze the impact of virus mutation and vaccination on containment decisions.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Managing disease containment measures during a pandemic

Shahmanzari

Tanrısever

Eryarsoy

et al. 2023

Production and Operations Management

View full text Add to dashboard Cite

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“…Our proposed optimization algorithm differs in several ways from existing approaches to assessing interventions via SEIR epidemiological models. A number of papers simulate a small number of candidate interventions, e.g., full lockdown versus school-only lockdown (Kucharski et al 2020, Prem et al 2020, Di Domenico et al 2020, El Housni et al 2020, Favero et al 2020, Boloori and Saghafian 2020, restrict the candidates to a simple parametric class for which exhaustive search is computationally feasible (e.g., trigger policies based on hospital admissions as in Duque et al 2020 or confirmed cases as Ahn et al 2021), or use global optimization methods such as simulated annealing (Dutta et al 2021). When considering a more complex policy space like in our targeting model, such approaches can lead to significantly sub-optimal results and misleading conclusions.…”

Section: Optimization Of Interventionsmentioning

confidence: 99%

Quantifying and Realizing the Benefits of Targeting for Pandemic Response

Camelo¹,

Iancu

et al. 2021

Preprint

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To respond to pandemics such as COVID-19, policy makers have relied on interventions that target specific population groups or activities. Such targeting is potentially contentious, so rigorously quantifying its benefits and downsides is critical for designing effective and equitable pandemic control policies. We propose a flexible modeling framework and a set of associated algorithms that compute optimally targeted, time-dependent interventions that coordinate across two dimensions of heterogeneity: population group characteristics and the specific activities that individuals engage in during the normal course of a day. We showcase a complete implementation in a case study focused on the Île-de-France region of France, based on commonly available hospitalization, community mobility, social contacts and economic data. We find that optimized dual-targeted policies have a simple and explainable structure, imposing less confinement on group-activity pairs that generate a relatively high economic value prorated by activity-specific social contacts. When compared to confinements based on uniform or less granular targeting, dual-targeted policies generate substantial complementarities that lead to Pareto improvements, reducing the number of deaths and the economic losses overall and reducing the time in confinement foreach population group. Since dual-targeted policies could lead to increased discrepancies in the confinements faced by distinct groups, we also quantify the impact of requirements that explicitly limit such disparities, and find that satisfactory intermediate trade-offs may be achievable through limited targeting.

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“…The COVID‐19 pandemic accentuated resource scarcity (even in our wealthiest societies) and emphasized such trade‐offs (Chen et al., 2020; Donaldson & Mitton, 2020). This has been palpable at all levels of decision‐making, including at the broadest level of a trade‐off between health versus the economy (Boloori & Saghafian, 2020).…”

Section: Introductionmentioning

confidence: 99%

Preparing for future pandemics: A multi‐national comparison of health and economic trade‐offs

et al. 2023

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Government investment in preparing for pandemics has never been more relevant.The COVID-19 pandemic has stimulated debate regarding the trade-offs societies are prepared to make between health and economic activity. What is not known is:(1) how much the public in different countries are prepared to pay in forgone GDP to avoid mortality from future pandemics; and (2) which health and economic policies the public in different countries want their government to invest in to prepare for and respond to the next pandemic. Using a future-focused, multi-national discrete choice experiment, we quantify these trade-offs and find that the tax-paying public is prepared to pay $3.92 million USD (Canada), $4.39 million USD (UK), $5.57 million USD (US) and $7.19 million USD (Australia) in forgone GDP per death avoided in the next pandemic. We find the health policies that taxpayers want to invest in before the next pandemic and the economic policies they want activated once the next pandemic hits are relatively consistent across the countries, with some exceptions. Such results can inform economic policy responses and government investment in health policies to reduce the adverse impacts of the next pandemic.

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COVID-19: Health and Economic Impacts of Societal Intervention Policies in the U.S.

Cited by 4 publications

References 34 publications

Managing disease containment measures during a pandemic

Managing disease containment measures during a pandemic

Quantifying and Realizing the Benefits of Targeting for Pandemic Response

Preparing for future pandemics: A multi‐national comparison of health and economic trade‐offs

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