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Initial economic damage from the COVID-19 pandemic in the United States is more widespread across ages and geographies than initial mortality impacts.

ABSTRACT: The economic and mortality impacts of the COVID-19 pandemic have been widely discussed, but there is limited evidence on their relationship across demographic and geographic groups. We use publicly available monthly data from January 2011 through April 2020 on all-cause death counts from the Centers for Disease Control and Prevention and employment from the Current Population Survey to estimate excess all-cause mortality and employment displacement in April 2020 in the United States. We report results nationally and separately by state and by age group. Nationally, excess all-cause mortality was 2.4 per 10,000 individuals (about 30% higher than reported COVID deaths in April) and employment displacement was 9.9 per 100 individuals. Across age groups 25 y and older, excess mortality was negatively correlated with economic damage; excess mortality was largest among the oldest (individuals 85 y and over: 39.0 per 10,000), while employment displacement was largest among the youngest (individuals 25 to 44 y: 11.6 per 100 individuals). Across states, employment displacement was positively correlated with excess mortality (correlation = 0.29). However, mortality was highly concentrated geographically, with the top two states (New York and New Jersey) each experiencing over 10 excess deaths per 10,000 and accounting for about half of national excess mortality. By contrast, employment displacement was more geographically spread, with the states with the largest point estimates (Nevada and Michigan) each experiencing over 16 percentage points employment displacement but accounting for only 7% of the national displacement. These results suggest that policy responses may differentially affect generations and geographies.

SUBMITTER: Polyakova M

PROVIDER: S-EPMC7668078 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Initial economic damage from the COVID-19 pandemic in the United States is more widespread across ages and geographies than initial mortality impacts.

Polyakova Maria M Kocks Geoffrey G Udalova Victoria V Finkelstein Amy A

Proceedings of the National Academy of Sciences of the United States of America 20201020 45

The economic and mortality impacts of the COVID-19 pandemic have been widely discussed, but there is limited evidence on their relationship across demographic and geographic groups. We use publicly available monthly data from January 2011 through April 2020 on all-cause death counts from the Centers for Disease Control and Prevention and employment from the Current Population Survey to estimate excess all-cause mortality and employment displacement in April 2020 in the United States. We report r ...[more]

PMID: 33082229

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Project description:BackgroundExcess caloric intake is linked to weight gain, obesity, and related diseases, including type 2 diabetes mellitus and cardiovascular disease (CVD). Obesity incidence is rising, with nearly 3 in 4 US adults being overweight or obese. In 2018, the US federal government finalized the implementation of mandatory labeling of calorie content on all menu items across major chain restaurants nationally as a strategy to support informed consumer choice, reduce caloric intake, and potentially encourage restaurant reformulations. Yet, the potential health and economic impacts of this policy remain unclear.Methods and resultsWe used a validated microsimulation model (CVD-PREDICT) to estimate reductions in CVD events, diabetes mellitus cases, gains in quality-adjusted life years, costs, and cost-effectiveness of the menu calorie labeling intervention, based on consumer responses alone, and further accounting for potential industry reformulation. The model incorporated nationally representative demographic and dietary data from National Health and Nutrition Examination Surveys 2009 to 2016; policy effects on consumer diets and body mass index-disease effects from published meta-analyses; and policy effects on industry reformulation, policy costs (policy administration, industry compliance, and reformulation), and health-related costs (formal and informal healthcare costs, productivity costs) from established sources or reasonable assumptions. We modeled change in calories to change in weight using an established dynamic weight-change model, assuming 50% of expected calorie reductions would translate to long-term reductions. Findings were evaluated over 5 years and a lifetime from healthcare and societal perspectives, with uncertainty incorporated in both 1-way and probabilistic sensitivity analyses. Between 2018 and 2023, implementation of the restaurant menu calorie labeling law was estimated, based on consumer response alone, to prevent 14 698 new CVD cases (including 1575 CVD deaths) and 21 522 new type 2 diabetes mellitus cases, gaining 8749 quality-adjusted life years. Over a lifetime, corresponding values were 135 781 new CVD cases (including 27 646 CVD deaths), 99 736 type 2 diabetes mellitus cases, and 367 450 quality-adjusted life years. Assuming modest restaurant item reformulation, both health and economic benefits were estimated to be about 2-fold larger than based on consumer response alone. The consumer response alone was estimated to be cost-saving by 2023, with net lifetime savings of $10.42B from a healthcare perspective and $12.71B from a societal perspective. Findings were robust in a range of sensitivity analyses.ConclusionsOur national model suggests that the full implementation of the US calorie menu labeling law will generate significant health gains and healthcare and societal cost-savings. Industry responses to modestly reformulate menu items would provide even larger additional benefits.

Project description:Background Produce prescription programs, providing free or discounted produce and nutrition education to patients with diet-related conditions within health care systems, have been shown to improve dietary quality and cardiometabolic risk factors. The potential impact of implementing produce prescription programs for patients with diabetes on long-term health gains, costs, and cost-effectiveness in the United States has not been established. Methods and Results We used a validated state-transition microsimulation model (Diabetes, Obesity, Cardiovascular Disease Microsimulation model), populated with national data of eligible individuals from the National Health and Nutrition Examination Survey 2013 to 2018, further incorporating estimated intervention effects and diet-disease effects from meta-analyses, and policy- and health-related costs from published literature. The model estimated that over a lifetime (mean=25 years), implementing produce prescriptions in 6.5 million US adults with both diabetes and food insecurity (lifetime treatment) would prevent 292 000 (95% uncertainty interval, 143 000-440 000) cardiovascular disease events, generate 260 000 (110000-411 000) quality-adjusted life-years, cost $44.3 billion in implementation costs, and save $39.6 billion ($20.5-58.6 billion) in health care costs and $4.8 billion ($1.84-$7.70 billion) in productivity costs. The program was highly cost effective from a health care perspective (incremental cost-effectiveness ratio: $18 100/quality-adjusted life-years) and cost saving from a societal perspective (net savings: $-0.05 billion). The intervention remained cost effective at shorter time horizons of 5 and 10 years. Results were similar in population subgroups by age, race or ethnicity, education, and baseline insurance status. Conclusions Our model suggests that implementing produce prescriptions among US adults with diabetes and food insecurity would generate substantial health gains and be highly cost effective.

Project description:IntroductionSanfilippo syndrome is a rare disease and fatal genetic disorder with no FDA-approved treatment in the United States (US), and no comprehensive assessment of economic disease burden is available.ObjectivesTo develop a model to estimate the economic burden associated with Sanfilippo syndrome in the US using direct costs, indirect costs and valued intangibles (disability-adjusted life years, or DALYs) from 2023 onward.Design and settingA multistage comorbidity model was generated based on Sanfilippo syndrome symptoms, and disability weights from the 2010 Global Burden of Disease Study. Attributable increase in caregiver mental health burden were estimated using data from the CDC National Comorbidity Survey and retrospective studies on caregiver burden. Direct costs were approximated from the 2019 EveryLife Foundation survey, and indirect costs were estimated from Federal income data. Monetary valuations were adjusted to USD 2023 and given a 3% discount rate from 2023 onward.Main outcome measuresIncidence of Sanfilippo syndrome was calculated for each year, and year-over-year DALYs due to patient years lived with disability (YLDs) and years life lost (YLLs) were calculated by comparing to the health-adjusted life expectancy (HALE) in the US. Direct and indirect costs were calculated for each simulated patient from onset of symptoms to death.ResultsFrom 2023-2043, overall economic burden in the US attributable to Sanfilippo syndrome was estimated to be $2.04 billion USD present value (2023) with current standard of care. The burden to individual families exceeded $8 million present value from time of birth per child born with Sanfilippo syndrome.ConclusionSanfilippo syndrome is a rare lysosomal storage disease, however the severe burden associated with the disease for individual families demonstrates a considerable cumulative impact. Our model represents the first disease burden value estimate associated with Sanfilippo syndrome, and underscores the substantial morbidity and mortality burden of Sanfilippo syndrome.

Dataset Information

Initial economic damage from the COVID-19 pandemic in the United States is more widespread across ages and geographies than initial mortality impacts.

Publications

Initial economic damage from the COVID-19 pandemic in the United States is more widespread across ages and geographies than initial mortality impacts.

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