Estimates of the value of life lost from COVID-19 in Ohio.

The economic burden of mortality due to the novel coronavirus (COVID-19) extends beyond the lives lost. Data from the Ohio Department of Public Health and Social Security Administration was used to estimate the years of potential life lost, 72,274 and economic value of those lost lives, US$17.39 billion. These estimates may be used to assess the risk-trade off of COVID-19 mitigation strategies in Ohio.

Economic burden of lives lost due to COVID-19 in New York State.

Aim: To examine the economic impact of lives lost due to the COVID-19 pandemic across New York State. Materials & methods: Death counts by age range and period life expectancy were extracted from the NYS Department of Health, NYC Department of Health and Mental Hygiene, and Social Security Administration website. Years of potential life lost and value of statistical life (VSL) were calculated. Results: The average years of potential life lost per person was 12.72 and 15.13, and the VSL was US$119.62 and 90.45 billion, in NYS and NYC, respectively. VSL was greatest in Queens and Brooklyn, followed by the Bronx, Manhattan and Staten Island. Conclusion: New York City, specifically Queens and Brooklyn, bore the greatest economic burden of lives lost across the state.

COMPENSATING DIFFERENTIALS FOR OCCUPATIONAL HEALTH AND SAFETY RISKS: IMPLICATIONS OF RECENT EVIDENCE

The most enduring measure of how individuals make personal decisions affecting their health and safety is the compensating wage differential for job safety risk revealed in the labor market via hedonic equilibrium outcomes. The decisions in turn reveal the value of a statistical life (VSL), the value of a statistical injury (VSI), and the value of a statistical life year (VSLY), which have both mortality and morbidity aspects that we describe and apply here. All such tradeoff rates play important roles in policy decisions concerning improving individual welfare. Specifically, we explicate the recent empirical research on VSL and its related concepts and link the empirical results to the ongoing examinations of many government policies intended to improve individuals' health and longevity. We pay special attention to recent issues such as the COVID pandemic and newly emerging foci on distributional consequences concerning which demographic groups may benefit most from certain regulations. © 2023 by Emerald Publishing Limited.

The benefits and costs of U.S. employer COVID-19 vaccine mandates.

In 2021, the Biden Administration issued mandates requiring COVID-19 vaccinations for U.S. federal employees and contractors and for some healthcare and private sector workers. These mandates have been challenged in court; some have been halted or delayed. However, their costs and benefits have not been rigorously appraised. This study helps fill that gap. We estimate the direct costs and health-related benefits that would have accrued if these vaccination requirements had been implemented as intended. Compared with the January 2022 vaccination rates, we find that the mandates could have led to 15 million additional vaccinated individuals, increasing the overall proportion of the fully vaccinated U.S. population from 64% to 68%. The associated net benefits depend on the subsequent evolution of the pandemic-information unavailable ex ante to analysts or policymakers. In scenarios involving the emergence of a novel, more transmissible variant, against which vaccination and previous infection offer moderate protection, the estimated net benefits are potentially large. They reach almost $20,000 per additional vaccinated individual, with more than 20,000 total deaths averted over the 6-month period assessed. In scenarios involving a fading pandemic, existing vaccination-acquired or infection-acquired immunity provides sufficient protection, and the mandates' benefits are unlikely to exceed their costs. Thus, mandates may be most useful when the consequences of inaction are catastrophic. However, we do not compare the effects of mandates with alternative policies for increasing vaccination rates or for promoting other protective measures, which may receive stronger public support and be less likely to be overturned by litigation.

Revisiting the value of a statistical life: an international approach during COVID-19

Although the employment of the value of a statistical life (VSL) is a cornerstone of USA governmental risk analysis, many argue that the VSL is flawed when evaluating proposed regulations. The VSL is only an estimate of the willingness to accept wage versus risk, which may be inaccurate for policies that mitigate large risks in pandemics, such as COVID-19. The VSL is revisited using a different approach and utilized in measuring the total value of loss from deaths caused by COVID-19 for 48 selected countries. The modified theory of the demand for health by Gary Becker is utilized to measure the VSL resulting from consumer optimization of utility, subject to constraints and investments in health made to change their survivorship at different ages. Estimates show that the VSL for an average American is around $7.2 million compared to the world VSL of about $1.3 million. Switzerland has the highest VSL of approximately $9.4 million. The total value of loss from deaths caused by COVID-19 is around 6.1% of the USA GDP, compared to the global loss of 1.2% of the world's GDP, while Belgium has the highest value of loss with 9.7% of its GDP. The best possible data and procedures are necessary to make robust and reliable public health decisions while responding to the COVID-19 pandemic. The VSL measure introduced here can be applied to a specific individual, group, or population. It is comprehensive, straightforward, generalizable, and provides a consistent measure with the most popular methods. More importantly, it provides an added value to the existing methods that enable us to break down the VSL into two main components, one that accounts for working time. The other accounts for leisure time and different diminishing consumption and discount rates.

Valuing COVID-19 Morbidity Risk Reductions.

Many economic analyses, including those that address the COVID-19 pandemic, focus on the value of averting deaths and do not include the value of averting nonfatal illnesses. Yet incorporating the value of averting nonfatal cases may change conclusions about the desirability of the policy. While per case values may be small, the number of nonfatal cases is often large, far outstripping the number of fatal cases. The value of averting nonfatal cases is also increasingly important in evaluating COVID-19 policy options as vaccine- and infection-related immunity and treatments reduce the case-fatality rate. Unfortunately, little valuation research is available that explicitly addresses COVID-19 morbidity. We describe and implement an approach for approximating the value of averting nonfatal illnesses or injuries and apply it to COVID-19 in the United States. We estimate gains from averting COVID-19 morbidity of about 0.01 quality-adjusted life year (QALY) per mild case averted, 0.02 QALY per severe case, and 3.15 QALYs per critical case. These gains translate into monetary values of about $5,300 per mild case, $11,000 per severe case, and $1.8 million per critical case. While these estimates are imprecise, they suggest the magnitude of the effects.

Economic evaluation for mass vaccination against COVID-19.

BACKGROUND: Vaccine is supposed to be the most effective means to prevent COVID-19 as it may not only save lives but also reduce productivity loss due to resuming pre-pandemic activities. Providing the results of economic evaluation for mass vaccination is of paramount importance for all stakeholders worldwide. METHODS: We developed a Markov decision tree for the economic evaluation of mass vaccination against COVID-19. The effectiveness of reducing outcomes after the administration of three COVID-19 vaccines (BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and AZD1222 (Oxford-AstraZeneca)) were modelled with empirical parameters obtained from literatures. The direct cost of vaccine and COVID-19 related medical cost, the indirect cost of productivity loss due to vaccine jabs and hospitalization, and the productivity loss were accumulated given different vaccination scenarios. We reported the incremental cost-utility ratio and benefit/cost (B/C) ratio of three vaccines compared to no vaccination with a probabilistic approach. RESULTS: Moderna and Pfizer vaccines won the greatest effectiveness among the three vaccines under consideration. After taking both direct and indirect costs into account, all of the three vaccines dominated no vaccination strategy. The results of B/C ratio show that one dollar invested in vaccine would have USD $13, USD $23, and USD $28 in return for Moderna, Pfizer, and AstraZeneca, respectively when health and education loss are considered. The corresponding figures taking value of the statistical life into account were USD $176, USD $300, and USD $443. CONCLUSION: Mass vaccination against COVID-19 with three current available vaccines is cost-saving for gaining more lives and less cost incurred.

Welfare economics of managing an epidemic: an exposition.

This paper reviews recent findings on the normative analysis of private and governmental countermeasures against infectious diseases, focusing on COVID-19. Based on a model that relates the economic activity to infectious disease epidemics, policies that maximize social welfare are considered. Lockdowns in many countries are measures that restrict economic activity over a wide area, and the economic damage they cause is extremely large. Existing studies on the net benefit of lockdown implemented in 2020 have reached mixed conclusions as to whether it is warranted or not. Although the estimates of costs and effects are relatively stable, the setting of the value of a statistical life for converting effects into benefits has a wide range and is also likely to overestimate benefits. Therefore, a careful procedure for setting is particularly crucial to obtain a reliable evaluation of countermeasures. Compared to uniform restriction of activities, taking measures to restrict activities by selecting targets may improve efficiency. Attributes that can be used to select targets include those that can be identified at little or no cost, such as age and industry, and those that can only be identified at a cost, such as close contact with infectious individuals and the presence of pathogens. In comparison to lockdown, these measures may reduce human suffering and economic suffering. No trade-off exists between uniform activity restrictions and selective activity restrictions.

Guiding Covid policy: cost-benefit analysis and beyond

Cost-benefit analysis (CBA) is inappropriate as an aid to Covid policy-making because the plural, incommensurable values at stake are not all amenable to monetary measurement. CBA for Covid policy is also undermined by pervasive uncertainty and ignorance, and has some troubling distributional implications. However, non-consequentialist alternatives to CBA tend towards implausibly absolutist prohibitions on risk imposition. Arguments for setting aside consequentialism for special circumstances (the precautionary principle, or a medical rule of rescue) are also problematic when applied to Covid policy. A broad consequentialist approach to policy guidance is defended, one which does not demand commensuration on a common monetary scale. Despite the absence of commensuration, policy guidance is still possible.

Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses

We discuss and review literature on the macroeconomic effects of epidemics and pan-demics since the late twentieth century. First, we cover the role of health in driv -ing economic growth and well-being and discuss standard frameworks for assessing the economic burden of infectious diseases. Second, we sketch a general theoretical framework to evaluate the trade-offs policy makers must consider when addressing infectious diseases and their macroeconomic repercussions. In so doing, we emphasize the dependence of economic consequences on (i) disease characteristics;(ii) inequal-ities among individuals in terms of susceptibility, preferences, and income;and (iii) cross-country heterogeneities in terms of their institutional and macroeconomic environments. Third, we study pharmaceutical and nonpharmaceutical policies aimed at mitigating and preventing infectious diseases and their macroeconomic repercus-sions. Fourth, we discuss the health toll and economic impacts of five infectious dis-eases: HIV/AIDS, malaria, tuberculosis, influenza, and COVID-19. Although major epidemics and pandemics can take an enormous human toll and impose a staggering economic burden, early and targeted health and economic policy interventions can often mitigate both to a substantial degree. (JEL E20, H50, I12, I14, I15, I18, J17)

Economic burden of lives lost due to COVID-19 in California State.

Aim: To examine the economic impact of lives lost due to the coronavirus pandemic across California and Los Angeles (LA) County. Patients & methods: Years of potential life lost (YPLL) and the value of statistical life (VSL) were calculated using mortality data from the California Department of Public Health, the LA County Department of Public Health and the Social Security Administration websites. Results: In California and LA County, the average YPLL per person were 14.3 and 14.7 and the VSLs were approximately US$219.9 billion and $82.7 billion, respectively. YPLL and VSL were greatest for Latinos aged 50-64. Conclusion: The economic burden of lives lost due to the coronavirus across California and LA County is substantial. Latinos aged 50-64 were most affected.

Macro-level efficiency of health expenditure: Estimates for 15 major economies.

The coronavirus disease 2019 (COVID-19) pandemic highlights the importance of strong and resilient health systems. Yet how much a society should spend on healthcare is difficult to determine because additional health expenditures imply lower expenditures on other types of consumption. Furthermore, the welfare-maximizing ("efficient") aggregate amount and composition of health expenditures depend on efficiency concepts at three levels that often get blurred in the debate. While the understanding of efficiency is good at the micro- and meso-levels-that is, relating to minimal spending for a given bundle of treatments and to the optimal mix of different treatments, respectively-this understanding rarely links to the efficiency of aggregate health expenditure at the macroeconomic level. While micro- and meso-efficiency are necessary for macro-efficiency, they are not sufficient. We propose a novel framework of a macro-efficiency score to assess welfare-maximizing aggregate health expenditure. This allows us to assess the extent to which selected major economies underspend or overspend on health relative to their gross domestic products per capita. We find that all economies under consideration underspend on healthcare with the exception of the United States. Underspending is particularly severe in China, India, and the Russian Federation. Our study emphasizes that the major and urgent issue in many countries is underspending on health at the macroeconomic level, rather than containing costs at the microeconomic level.

The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach.

OBJECTIVES: To assess the economic burden of COVID-19 that would arise absent behavioral or policy responses under the herd immunity approach in the United States and compare it to the total burden that also accounts for estimates of the value of lives lost. METHODS: We use the trajectories of age-specific human and physical capital in the production process to calculate output changes based on a human capital-augmented production function. We also calculate the total burden that results when including the value of lives lost as calculated from mortality rates of COVID-19 and estimates for the value of a statistical life in the United States based on studies assessing individual's willingness to pay to avoid risks. RESULTS: Our results indicate that the GDP loss associated with unmitigated COVID-19 would amount to a cumulative US$1.4 trillion by 2030 assuming that 60 percent of the population is infected over three years. This is equivalent to around 7.7 percent of GDP in 2019 (in constant 2010 US$) or an average tax on yearly output of 0.6 percent. After applying the value of a statistical life to account for the value of lives lost, our analyses show that the total burden can mount to between US$17 and 94 trillion over the next decade, which is equivalent to an annual tax burden between 8 and 43 percent. CONCLUSION: Our results show that the United States would incur a sizeable burden if it adopted a non-interventionist herd immunity approach. FUNDING: Research reported in this paper was supported by the Alexander von Humboldt Foundation, the Bill & Melinda Gates Foundation (Project INV-006261), and the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG) and the National Natural Science Foundation of China (NSFC). Preparation of this article was also supported by the Value of Vaccination Research Network (VoVRN) through a grant from the Bill & Melinda Gates Foundation (Grant OPP1158136). The content is solely the responsibility of the authors.

Do the Benefits of COVID-19 Policies Exceed the Costs? Exploring Uncertainties in the Age-VSL Relationship.

Numerous analyses of the benefits and costs of COVID-19 policies have been completed quickly as the crisis has unfolded. The results often largely depend on the approach used to value mortality risk reductions, typically expressed as the value per statistical life (VSL). Many analyses rely on a population-average VSL estimate; some adjust VSL for life expectancy at the age of death. We explore the implications of theory and empirical studies, which suggest that the relationship between age and VSL is uncertain. We compare the effects of three approaches: (1) an invariant population-average VSL; (2) a constant value per statistical life-year (VSLY); and (3) a VSL that follows an inverse-U pattern, peaking in middle age. We find that when applied to the U.S. age distribution of COVID-19 deaths, these approaches result in average VSL estimates of $10.63 million, $4.47 million, and $8.31 million. We explore the extent to which applying these estimates alters the conclusions of frequently cited analyses of social distancing, finding that they significantly affect the findings. However, these analyses do not address other characteristics of COVID-19 deaths that may increase or decrease the VSL estimates. Examples include the health status and income level of those affected, the size of the risk change, and the extent to which the risk is dreaded, uncertain, involuntarily incurred, and outside of one's control. The effects of these characteristics and their correlation with age are uncertain; it is unclear whether they amplify or diminish the effects of age on VSL.

Economic lessons for COVID-19 pandemic policies.

The COVID-19 pandemic poses novel health issues. However, the benefits and costs of the pandemic and policies to address it have a familiar economic structure. Chief among the health-related benefits are the monetized values of the U.S. mortality costs of $3.9 trillion in 2020. The combined U.S. mortality and morbidity costs are $5.5-5.9 trillion. Global mortality costs in 2020 total $10.1 trillion. The skewed age distribution of COVID-19 illnesses has stimulated increased advocacy of downward adjustments in the value of a statistical life (VSL) for older people. This article examines the role of age for policy analysis generally and for the rationing of scarce medical treatments, such as ventilators. Mortality risk reduction benefits should be based on the reduced probability of death multiplied by the pertinent VSL. Effective communication of risks to foster precautions hinges on the credibility of the information source, which public officials have jeopardized. Efficient control of risks imposes limits on personal freedoms to foster health improvements.

Valuing mortality risk in the time of COVID-19.

In evaluating the appropriate response to the COVID-19 pandemic, a key parameter is the rate of substitution between wealth and mortality risk, conventionally summarized as the value per statistical life (VSL). For the United States, VSL is estimated as approximately $10 million, which implies the value of preventing 100,000 COVID-19 deaths is $1 trillion. Is this value too large? There are reasons to think so. First, VSL is a marginal rate of substitution and the potential risk reductions are non-marginal. The standard VSL model implies the rate of substitution of wealth for risk reduction is smaller when the risk reduction is larger, but a closed-form solution calibrated to estimates of the income elasticity of VSL shows the rate of decline is modest until the value of a non-marginal risk reduction accounts for a substantial share of income; average individuals are predicted to be willing to spend more than half their income to reduce one-year mortality risk by 1 in 100. Second, mortality risk is concentrated among the elderly, for whom VSL may be smaller and who would benefit from a persistent risk reduction for a shorter period because of their shorter life expectancy. Third, the pandemic and responses to it have caused substantial losses in income that should decrease VSL. In contrast, VSL is plausibly larger for risks (like COVID-19) that are dreaded, uncertain, catastrophic, and ambiguous. These arguments are evaluated and key issues for improving estimates are highlighted.

The forgotten numbers: A closer look at COVID-19 non-fatal valuations.

Our research estimates COVID-19 non-fatal economic losses in the U.S. using detailed data on cumulative cases and hospitalizations from January 22, 2020 to July 27, 2020, from the Centers for Disease Control and Prevention (CDC). As of July 27, 2020, the cumulative confirmed number of cases was about 4.2 million with almost 300,000 of them entailing hospitalizations. Due to data collection limitations the confirmed totals reported by the CDC undercount the actual number of cases and hospitalizations in the U.S. Using standard assumptions provided by the CDC, we estimate that as of July 27, 2020, the actual number of cumulative COVID-19 cases in the U.S. is about 47 million with almost 1 million involving hospitalizations. Applying value per statistical life (VSL) and relative severity/injury estimates from the Department of Transportation (DOT), we estimate an overall non-fatal unadjusted valuation of $2.2 trillion for the U.S. with a weighted average value of about $46,000 per case. This is almost 40% higher than the total valuation of $1.6 trillion (using about $11 million VSL from the DOT) for all approximately 147,000 COVID-19 fatalities. We also show a variety of estimates that adjust the non-fatal valuations by the dreaded and uncertainty aspect of COVID-19, age, income, and a factor related to fatality categorization. The adjustments show current overall non-fatal valuations ranging from about $1.5 trillion to about $9.6 trillion. Finally, we use CDC forecast data to estimate non-fatal valuations through November 2020, and find that the overall cumulative valuation increases from about $2.2 trillion to about $5.7 trillion or to about 30% of GDP. Because of the larger numbers of cases involved our calculations imply that non-fatal infections are as economically serious in the aggregate as ultimately fatal infections.

Pricing the global health risks of the COVID-19 pandemic.

Policies to address the coronavirus disease 2019 (COVID-19) require a balancing of the health risk reductions and the costs of economic dislocations. Application of the value of a statistical life (VSL) to monetize COVID-19 deaths produces a U.S. mortality cost estimate of $1.4 trillion for deaths in the first half of 2020. This article presents worldwide COVID-19 costs for over 100 countries. The total global mortality cost through July 2, 2020 is $3.5 trillion. The United States accounts for 25% of the deaths, but 41% of the mortality cost. Adjustments for the shorter life expectancy and lower income of the victims substantially reduces the estimated monetized losses, but may raise fundamental equity concerns. Morbidity effects of COVID-19 affect many more patients than do the disease's mortality risks. Consideration of the morbidity effects increase the expected health losses associated with COVID-19 illnesses by 10% to 40%.

Temporary reduction in fine particulate matter due to 'anthropogenic emissions switch-off' during COVID-19 lockdown in Indian cities.

The COVID-19 pandemic elicited a global response to limit associated mortality, with social distancing and lockdowns being imposed. In India, human activities were restricted from late March 2020. This 'anthropogenic emissions switch-off' presented an opportunity to investigate impacts of COVID-19 mitigation measures on ambient air quality in five Indian cities (Chennai, Delhi, Hyderabad, Kolkata, and Mumbai), using in-situ measurements from 2015 to 2020. For each year, we isolated, analysed and compared fine particulate matter (PM2.5) concentration data from 25 March to 11 May, to elucidate the effects of the lockdown. Like other global cities, we observed substantial reductions in PM2.5 concentrations, from 19 to 43% (Chennai), 41-53% (Delhi), 26-54% (Hyderabad), 24-36% (Kolkata), and 10-39% (Mumbai). Generally, cities with larger traffic volumes showed greater reductions. Aerosol loading decreased by 29% (Chennai), 11% (Delhi), 4% (Kolkata), and 1% (Mumbai) against 2019 data. Health and related economic impact assessments indicated 630 prevented premature deaths during lockdown across all five cities, valued at 0.69 billion USD. Improvements in air quality may be considered a temporary lockdown benefit as revitalising the economy could reverse this trend. Regulatory bodies must closely monitor air quality levels, which currently offer a baseline for future mitigation plans.

Global mortality benefits of COVID-19 action.

The rapid spread of COVID-19 motivated countries worldwide to mitigate mortality through actions including social distancing, home quarantine, school closures, and case isolation. We estimate the global mortality benefits of these actions. We use county-level data on COVID-19 from January 2020, project the number of mortalities until September 2020, and calculate the global mortality benefits using the age- and country-specific value of a statistical life (VSL). Implementing all four types of actions above would save approximately 40.76 trillion USD globally, with social distancing accounting for 55% of the benefits. The monetary benefit would be the largest in the US, Japan and China. Our findings indicate that global actions during COVID-19 have substantial economic benefits and must be implemented in response to COVID-19.