Coronavirus Aid, Relief, And Economic Security Research Articles

Echoes from the past: How America's major moments shaped mental health policies through a young adult lens.

This commentary examines key mental health policies across four transformative historical periods in America: the aftermath of World War II (1939-1946), the Civil Rights Movement (1954-1968), the Great Recession (2007-2009), and the COVID-19 pandemic (2020-2023). The post-WWII era established today's foundational mental health system, emphasizing military personnel, as reflected in the National Mental Health Act of 1946. During the Civil Rights Movement, the focus shifted toward community equality, leading to the Community Mental Health Act of 1963. The economic challenges of the Great Recession, especially affecting young adults, prompted a deep dive into the Affordable Care Act. The social isolation and economic suffering from the COVID-19 pandemic led to the Coronavirus Aid, Relief, and Economic Security (CARES) Act. The article highlights the need for a more inclusive policy development approach, one that recognizes and integrates the unique perspectives of young adults in shaping mental health policies and discourse. It concludes with recommendations to guide future policy evolution for enhanced mental health and societal well-being. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Distribution of CARES Act Provider Relief Funding to Psychiatric Care Organizations.

More than $100 billion in Coronavirus Aid, Relief, and Economic Security (CARES) Act funding was intended to support financially stressed health care providers during the COVID-19 pandemic. The distribution of the CARES Act's Provider Relief Fund among psychiatrists is poorly understood. Analyzing funding received by 2,593 psychiatric care organizations (PCOs), the authors found that funding was more equally distributed across care organizations of different sizes in psychiatry versus other specialties. Substantially less relief funding was received by PCOs per provider relative to other specialties. This disparity in relief funding is surprising given that specific earmarks of the CARES Act were intended to improve U.S. mental health care capacity, meriting further attention.

The Impact of the CARES Stimulus Payments on COVID-19 Transmission and Mortality

Abstract In this paper, we study the impact of the Coronavirus Aid, Relief, and Economic Security (CARES) Act economic impact payments to individuals on the spread of COVID-19 and subsequent mortality. There is a large economic literature linking income shocks and mortality. Using an event study approach and controlling for time-varying stay-at-home directives, we find no statistically significant change in confirmed case rates and no meaningful change to death rates from COVID-19. Our research suggests that distributing the individual stimulus payments at the same time to everyone had no effect on the spread of COVID-19.

The Keynesian Stimulus Model: Stimulating Economic Activities with Direct Transfers

Governments use direct transfers as a fiscal measure to stimulate economic activities during shocks. As COVID-19 continues to ravage economies globally, governments worldwide have responded with fiscal and monetary policies to manage the pandemic’s economic impact. In addition, the U.S. government has intervened with direct transfers to provide liquidity to prevent a prolonged shock. However, opinions are divided on the efficacy of the Keynesian stimulus policy. This study used a mixed-method research design to analyze the classical Keynesian model and compares it with the monetarist model to provide insight into the stimulus policy outcomes of the Coronavirus Aid Relief and Economic Security (CARES) Act of 2020 and subsequent policies used to manage the COVID-19 shock. Time-series data from the Bureau of Economic Analysis (BEA), Bureau of Labor Statistics (BLS), and the Federal Reserve Bank (the Fed) of the percentage changes in GDP, disposable personal income (DPI), and personal consumption expenditure (PCE), as well as unemployment rates (UR), interest rates (INT), and inflation rates (IFL), were collected and analyzed. The study used multiple regression (MR) to empirically examine the variables' relationships to ascertain both models’ short-term efficacy. The results suggest that DPI, PCE, and UR significantly predicted the percentage change in GDP in the Keynesian model, whereas, UR, INT, and IFL did not substantially predict the change in GDP in the monetarist model.

Implications of Student Loan COVID-19 Pandemic Relief Measures for Families with Children

The initial years of the COVID-19 pandemic and the resulting economic fallout likely posed particular financial strain on U.S. households with children, who faced income disruptions from widespread jobs and hours cuts in addition to new childcare and instruction demands. One common expense for many such households is their student loan payment. The Coronavirus Aid, Relief, and Economic Security (CARES) Act included provisions to curb the impacts of these payments, which have been extended several times. These measures were not targeted and thus applied independent of need. This chapter analyzes two nationally representative datasets and finds: 1) families with children were more likely to benefit from pandemic student loan relief than those without children, but this relief was concentrated among higher-income and White families and 2) there were larger improvements in overall credit health and an increased use of other credit among families with student loan debt that was eligible for relief relative to those with student loan debt that was not.

Participation in the CARES Act Provider Relief Fund policy by dentists in South Carolina's safety net.

The Coronavirus Aid, Relief, and Economic Security (CARES) Act appropriated $100billion to the Provider Relief Fund, allowing for direct payments to health care providers due to COVID-19. Few studies have evaluated participation in the Provider Relief Fund (PRF), and none have specifically looked at dental providers in the safety net. We conducted a retrospective, secondary data analysis using a quasi-experimental cohort design of South Carolina dentists who received PRF payments, comparing those who did and did not participate in the safety net. Safety net practice was operationalized as those participating in Medicaid, and whether they provided care in dental health professional shortage areas, or rural communities. Of the 628 dental providers in South Carolina who received PRF payments, 34% were identified as Medicaid providers while 66% did not participate in Medicaid; we found no statistical difference between payments to Medicaid versus non-Medicaid dental providers. Of PRF payments to dental providers participating in South Carolina's Medicaid program, we found no difference between payments to rural and urban providers but did find that practices offering services in dental care shortage areas received less than providers practicing in counties not designated as a shortage area. The PRF achieved its goal of distributing financial support to providers affected by the COVID-19 pandemic. But without policy imperatives linked to need-based allocations or incentives for PRF recipients to serve safety net populations, we may later learn this was a missed opportunity for PRF.

Public sentiment and opinion regarding the CARES Act.

The Coronavirus Aid, Relief, and Economic Security(CARES) Act was the largest stimulus package in US history. In this paper, I look into whether public sentiment improved in response to the CARES Act, and analyze public opinion regarding the CARES Act, implementing a Latent Dirichlet Allocation (LDA) model. The sentiment analysis results indicate a significant improvement of public sentiment following the announcement of the CARES Act, which fades away after a week but improves again as the date to receive the first stimulus check approaches. The topic modeling results highlight support toward certain programs and some criticism of the CARES Act.

Disparities in Telemedicine Literacy and Access in the United States.

Because of the expansion of telehealth services through the 2020 Coronavirus Aid, Relief, and Economic Security (CARES) Act, the potential of telemedicine in plastic surgery has gained visibility. This study aims to identify populations who may have limited access to telemedicine. The authors created a telemedicine literacy index (TLI) using a multivariate regression model and data from the US Census and Pew Research Institute survey. A multivariate regression model was created using backwards elimination, with TLI as the dependent variable and demographics as independent variables. The resulting regression coefficients were applied to data from the 2018 US Census at the county level to create a county-specific technological literacy index (cTLI). Significance was set at P < 0.05. On multivariable analysis, the following factors were found to be significantly associated with telemedicine literacy: age, sex, race, employment status, income level, marital status, educational attainment, and urban or rural classification. Counties in the lowest tertile had significantly lower median annual income levels ($43,613 versus $60,418; P < 0.001) and lower proportion of the population with at least a bachelor's degree (16.7% versus 26%; P < 0.001). Rural areas were approximately three times more likely to be in the lowest cTLI compared with urban areas ( P < 0.001). Additional associations with low cTLI were Black race ( P = 0.045), widowed marital status ( P < 0.001), less than high school education ( P = 0.005), and presence of a disability ( P = 0.01). These results highlight disadvantaged groups at risk of being underserved with telehealth. Using these findings, key stakeholders may be able to target these communities for interventions to increase telemedicine literacy and access.

Open for Economic Activities during the COVID-19 Pandemic: Factors Related to State Reopening Policies in a Federal Policy Vacuum

What factors influence state governors to issue an executive order to reopen economic activities more or less quickly when removing the COVID-19 pandemic restrictions? Without comprehensive federal guidelines, state governors were faced with an administrative dilemma in devising mitigation policies that promoted safe public health measures while encouraging more business activity. Following the federal directive to reopen in April 2020, governors in all 50 states signed executive orders, but some waited longer than others. We argue that variation in the timing of the enactment of initial executive orders is influenced by political factors, financial resources factors, interstate factors, and problem severity of the public health incidence. Using an event history analysis, our Cox proportional hazard regression model suggests that states with unified Republican governments, more state funding obtained from the Coronavirus Aid, Relief, and Economic Security (CARES) Act, and participation in regional collaboration resumed activities earlier compared to states with more neighbors that issued reopening executive orders and states with more per capita income. Results indicate that, in crisis situations, unified political partisanship, the receipt of federal funding, and coordination with other states facilitate rapid policy adoption.

CARES and crime

PurposeThe US signed the Coronavirus Aid, Relief, and Economic Security (CARES) Act in March 2020 to alleviate the harsh economic effects of the pandemic and related shutdowns. A substantial part of the bill expanded and increased unemployment insurance payments, where a growing area of research estimates strong anti-poverty effects. The authors examine the effect of these policies on crime.Design/methodology/approachThe authors use new event study and difference-in-differences techniques to estimate the effect of increasing unemployment insurance payments on property crime and violent crime. Then, the authors estimate the effect of expanded unemployment qualification programs on crime. The authors use a rich set of controls including unemployment, contemporaneous policies and mobile device tracking data to estimate the degree to which people stayed at home.FindingsThey find that increasing unemployment insurance payments decreased crime by 20%, driven by a 24% decrease in property crime. The authors also find suggestive evidence that expanding unemployment qualifications decreases crime.Practical implicationsThe authors find a new and substantial benefit of expanded unemployment insurance beyond their antipoverty effects.Originality/valueTo the authors' knowledge, this is the first study that directly examines the impact of the CARES Act on crime.

Inflation: The problems for aquaculture

Inflation: The problems for aquaculture

Airline market exit after a shock event: Insights from the COVID-19 pandemic

During the COVID-19 pandemic, passenger demand for air transportation declined drastically. In the Unites States (U.S.), the Coronavirus Aid, Relief, and Economic Security (CARES) Act provided financial assistance. In return, commercial passenger airlines were given minimum service obligations, which allowed airlines to remove markets (flights between origin and destination airport pairs) from their networks as long as they continued operating in all cities that they serviced pre-pandemic. A binary logit methodology is used to model airline-market level decisions to continue operating in a market or to exit it. Two time periods are modeled: during normal operating conditions (before the pandemic) and after a major shock event (after the beginning of the pandemic). Results show that after the pandemic, 8.4 times more airline markets are exited as compared to before. Interestingly, the probability of exit is found to vary widely across markets, airports, and airlines. Some market characteristics have a high probability of exit both before and after the pandemic, including low passenger revenue per available seat mile, low flight frequencies, and flights to/from multi-airport cities. In contrast, other market characteristics impact airlines’ market exit decisions in only one time period rather than both. For example, during normal operating conditions, airport size does not impact market exit. However, after the pandemic, the probability of exit is 1.8 to 2.2 times higher for the larger hub airports as compared to the smallest airports (non-hubs), a result that is explained within the context of the CARES Act minimum service obligations.

Make the Invisible Underbanked Visible: Who Are the Underbanked?

When the COVID-19 pandemic caused businesses to close and triggered high unemployment in 2020, millions of unbanked U.S. households, those without a bank account, had to wait for weeks and months for their stimulus checks to arrive. The delayed delivery of stimulus checks issued by the Coronavirus Aid, Relief, and Economic Security (CARES) Act sheds light on the critical role that safe, affordable financial services and products play in people’s ability to cope with financial shocks. Dialogues over banking practices have been framed with a banked-unbanked dichotomous framework that masks more nuanced understandings of households’ financial realities, including the underbanked, who use a bank account and alternative financial services simultaneously. Using data from the 2015 National Financial Capability Study, this study identifies and compares predictors of being underbanked and unbanked, respectively. We found that the underbanked group is a sizable, distinctively different group. Income volatility and welfare benefit receipt are both associated with being underbanked rather than unbanked. Our findings call for expanding the current, limited framework to gain more complete, nuanced understandings of banking practices.

Utilization Gaps During the COVID-19 Pandemic: Racial and Ethnic Disparities in Telemedicine Uptake in Federally Qualified Health Center Clinics.

BackgroundThe Coronavirus Aid, Relief, and Economic Security (CARES) Act led to the rapid implementation of telemedicine across healthcare office settings. This innovation has the potential to improve healthcare use and ensure continuity of care. However, this delivery model could have an unintended consequence of worsening racial/ethnic disparities in healthcare utilization if adoption varies across sub-populations.ObjectiveTo examine associations between telemedicine use and race/ethnicity between 3/1/2020 and 11/30/2020, and the influence of other individual- and geographical-level factors on this relationship.DesignCohort studyParticipantsEMR data from 55 clinics in a FQHC networkMain MeasuresThe dependent variable was visit type (in-person vs. telemedicine). Predictors of interest were patient race and ethnicity. To account for repeated visits within each patient nested within clinic, a three-level, mixed-effects, multivariable, logistic regression model was used. Subgroup analyses examined correlates of telemedicine use in African American and Hispanic cohorts, separately.Key ResultsThe analytic sample included 233,302 visits for 67,733 unique patients. African Americans (OR = 0.65, 95% CI: 0.61, 0.69), Asians (OR = 0.58, 95% CI: 0.52, 0.65), and American Indians / Alaska Natives and other Pacific Islanders (OR = 0.82, 95% CI: 0.70, 0.98) were significantly less likely to use telemedicine compared to Whites. Hispanics were also less likely to have a telemedicine visit (OR = 0.49, 95% CI: 0.47, 0.51) compared to non-Hispanics. Nonacute visits were more likely to be conducted via telemedicine. Distance to clinic exhibited a dose-response relationship such that patients who lived farthest from the clinics were most likely to have telemedicine visits. In the subgroup analyses to examine predictors of telemedicine use, the dose-response relationship between distance from clinic and telemedicine use persisted, with increasing distance associated with increasing likelihood of telemedicine use, in both African American and Hispanic cohorts. Nonacute visits were associated with telemedicine use in the Hispanic cohort, but not in the Black / African American cohort.ConclusionRacial/ethnic disparities in telemedicine use persisted among this cohort. However, telemedicine improved utilization for African Americans and Hispanics living farther away from the clinic.

Hyperpigmentation: Looking beyond hydroquinone

Hyperpigmentation is the most common complaint in the age group 40-45years, seeking consultation for skin disorders. Hydroquinone is a commonly used depigmenting agent in clinical practice for treating hyperpigmentation. Prolonged use of hydroquinone has been associated with cancer risk and exogenous ochronosis. The CARES (The Coronavirus Aid, Relief, and Economic Security Act) Act of 2020has instituted significant changes to hydroquinone containing OTC (over the counter) products, and consequently, many hydroquinone-based OTC products had to be withdrawn from the market. Henceforth, products containing hydroquinone would need US Food and Drug Administration approval via new drug application pathways for commercialization. Alternative treatment options to hydroquinone in clinical practice are reviewed in this paper with regard to their safety and efficacy vis a vis hydroquinone. Also, new potential treatment options such as thiamidol, Polypodium leucotomos, and glutathione are discussed. The review shows that these alternative depigmenting agents can be rationally combined to achieve desired treatment goals in the management of hyperpigmentation.

Going Virtual When The Doors Close: Addressing Geriatric Workforce Training Needs During A Pandemic

The focus of our Geriatric Workforce Enhancement Program (GWEP) is to enhance long-term services and support (LTSS) and primary care healthcare workforce capacity through interprofessional education (IPE) and to increase patient, family, and caregiver engagement. When it became evident that LTSS settings, schools, and communities were going to be adversely impacted by the COVID-19 pandemic for the unforeseeable future, our GWEP quickly pivoted to address new challenges and initiate technology to continue our programs. In this symposium, we describe four programs implemented or revised during the COVID-19 pandemic. We utilized CARES (Coronavirus Aid, Relief and Economic Security) funding to develop a 3-part Project ECHO on utilizing telehealth in LTSS settings. We pivoted quarterly Fireside Chats – community-based educational programs held at partnering LTSS settings for older adults and caregivers – to bi-weekly and now monthly webinars addressing topics relevant to COVID-19 and combatting social isolation. Because students could no longer attend an in-person IPE course introducing them to long-term care, we revised the course to be online with a partnering nursing home participating in an interactive mock care conference. Finally, a 2-semester undergraduate Honors College project-based course introducing students to successful aging utilized virtual activities to expose students to the challenges of hospice care during a pandemic. With these adaptations, as well as activities that advocated for, and supported, LTSS settings and older adults, our GWEP program was able to continue to provide education and support to the setting and individuals most impacted by COVID-19.

Pre-pandemic to early-pandemic changes in risk of household food insecurity among Maryland families with children.

The objective was to examine risk and protective factors associated with pre- to early-pandemic changes in risk of household food insecurity (FI). We re-enrolled families from two statewide studies (2017-2020) in an observational cohort (May-August 2020). Caregivers reported on risk of household FI, demographics, pandemic-related hardships, and participation in safety net programs (e.g. CARES stimulus payment, school meals). Maryland, United States. Economically, geographically, and racially/ethnically diverse families with preschool to adolescent-age children. Eligibility included reported receipt or expected receipt of the CARES stimulus payment or a pandemic-related economic hardship (n=496). Prevalence of risk of FI was unchanged (pre-pandemic: 22%, early-pandemic: 25%, p=0.27). Risk of early-pandemic FI was elevated for non-Hispanic Black (aRR=2.1 [95% CI 1.1, 4.0]) and Other families (aRR=2.6 [1.3, 5.4]) and families earning ≤300% federal poverty level. Among pre-pandemic food secure families, decreased income, job loss, and reduced hours were associated with increased early-pandemic FI risk (aRR=2.1 [1.2, 3.6] to 2.5 [1.5, 4.1]); CARES stimulus payment (aRR=0.5 [0.3, 0.9]) and continued school meal participation (aRR=0.2 [0.1, 0.9]) were associated with decreased risk. Among families at risk of FI pre-pandemic, safety net program participation was not associated with early-pandemic FI risk. The CARES stimulus payment and continued school meal participation protected pre-pandemic food secure families from early-pandemic FI risk but did not protect families who were at risk of FI pre-pandemic. Mitigating pre-pandemic FI risk and providing stimulus payments and school meals may support children's health and reduce disparities in response to pandemics.

COVID‐19 Relief Laws Benefit Nonprofit Organizations

Legislation creating a $2.2 trillion economic stabilization package to combat the COVID‐19 pandemic became law on March 27, when President Trump signed the Coronavirus Aid, Relief, and Economic Security (CARES) Act (Pub. L. No. 116‐136). This was the third, and most massive, COVID‐19 emergency relief act passed by Congress in March. There are several features of the act of direct interest and import to nonprofit organizations.

Sustaining Tribal Fisheries: U.S. Economic Relief Policies during COVID-19

This article reviews the individual spend plans of U.S. states granted a funding allocation under Sec. 12005 of the Coronavirus Aid Relief and Economic Security (CARES) Act to identify consistency with legislative mandates to support Tribal commercial, subsistence, cultural, or ceremonial fisheries negatively impacted by the COVID-19 pandemic. Utilizing critical discourse analysis, this study identifies state discursive practices in supporting Tribal sovereignty in fisheries management for the advancement of Indigenous Ocean justice. State spending plans (n = 22) publicly available and submitted to the National Oceanic and Atmospheric Administration before July 2021 were reviewed. Few of the state spend plans listed impacts to Tribal fisheries due to the pandemic. Only two state plans included Tribal consultation and direct economic relief for commercial, subsistence, cultural, and/or ceremonial losses faced by neighboring Tribes and Tribal citizens. Overall, the protections within the CARES Act for Tribal fisheries were not integrated into state spend plans. The article identifies best practices for state fisheries relief policy content that is affirming of Tribal fishing rights and uses them to help address the ongoing pandemic crisis facing Tribal fisheries. These findings have relevance for future emergency relief programs that are inclusive of Tribal Nations. Honoring Tribal sovereignty and the federal trust responsibility must be the cornerstone of shared sustainable fisheries.

Association Between COVID-19 Relief Funds and Hospital Characteristics in the US

In response to financial stress created by the reduction in care during the COVID-19 pandemic, hospitals received financial assistance through the Coronavirus Aid, Relief, and Economic Security (CARES) Act program. To date, the allocation of CARES Act funding is not well understood. To examine the disbursement of the High-Impact Distribution CARES Act funds and the association between financial assistance and hospital-level financial resources prior to the COVID-19 pandemic. This cross-sectional analysis of US-based hospitals and health systems assesses the hospital characteristics associated with CARES Act funding with linear regression models using linked hospital and health system-level information on CARES Act funding with hospital characteristics from Hospital Cost Report data. Hospital and health system CARES Act financial assistance. Hospital and health system affiliation, status, and financial health prior to the COVID-19 pandemic. Data analysis took place from December 2020 through June 2021. The analysis included 952 hospital-level entities with an average payment of $33.6 million, most of which was received during the first payment round. Wide ranges existed in CARES Act funding, with 24% of matched hospitals receiving less than $5 million in funding and 8% receiving more than $50 million. Academic-affiliated hospitals, hospitals with higher pre-COVID-19 assets and hospitals with higher COVID-19 cases received higher levels of funding, while critical access hospitals received lower levels of financial assistance. A 10% increase in hospital assets, endowment size, and COVID-19 cases was associated with 1.4% (95% CI, 0.8% to 2.0%; P = .003), 0.2% (95% CI, 0.1% to 0.3%; P < .001), and 3.5% (95% CI, 2.8% to 4.2%; P < .001) increases in CARES Act funding, respectively. In this cross-sectional study of US hospitals and health systems, findings suggest that High-Impact Distribution CARES Act funds may have disproportionately gone to hospitals that were in a stronger financial situation prior to the pandemic compared with those that were not, but funds also went disproportionately to those that eventually had the most cases.