BACKGROUND
The Coronavirus Aid, Relief, and Economic Security (CARES) Act provided a $600/week
supplement to unemployment benefits which expired July 31. Its extension is controversial.
We examined health and social vulnerabilities among those receiving unemployment benefits
during the COVID-19 outbreak to inform debate on the consequences of allowing the
supplement to lapse.
METHODS
We analyzed the COVID Impact Survey, sponsored by the Federal Reserve Bank of Minneapolis
and foundations.
1
Surveyors contacted a nationally representative random sample of US households by
mail, email, telephone, and field interviews
2
between April 20, 2020, and June 8, 2020. We assessed adults 18–64 receiving (or applying
for) unemployment benefits during the past week and those reporting working in the
past week.
We first analyzed demographic characteristics and three categories of socio-medical
vulnerabilities: food insecurity; lacking health insurance; and financial precarity
(being unable to cover an unexpected $400 expense without selling possessions or going
into debt).
Finally, to assess possible health risks resulting from unemployment beneficiaries’
prematurely returning to work, we examined self-reported health; rates of seven clinical
risk factors for severe COVID-19
3
; and the point prevalence of three major COVID-19 symptoms (fever/chills, cough,
and dyspnea).
We used STATA/SE and weights provided by COVID Impact.
RESULTS
A total of 643 (weighted n = 26.9 million) of the 3480 non-elderly adults in our sample
were unemployment beneficiaries; they were younger, poorer, less educated, and more
often people of color than those at-work (Table 1).
Table 1
Characteristics of US Adults 18–64 Years of Age Receiving or Applying for Unemployment
Insurance and Those Working, April–June 2020 (n = 3480)
Working (%) (n = 2837)
Unemployment insurance beneficiaries (%) (n = 643)
Age
18–24
11.43
19.58
25–34
26.11
26.54
35–44
21.95
22.40
45–54
20.34
19.37
55–64
20.17
12.11
Gender
Male
53.1
51.01
Female
46.90
48.99
Race
White
63.59
52.18
Black
10.84
12.10
Hispanic
15.75
27.33
Other
9.82
8.39
Income
Less than $30,000
17.02
31.52
$30k to less than $60k
24.90
27.71
$60k to less than $125k
40.73
33.24
More than $125k
17.35
7.54
Education
No high school diploma
5.52
18.26
High school graduate or equivalent
22.87
33.79
Some college
27.18
26.29
Bachelor of Arts or above
44.42
21.65
25 individuals in study population were missing data on race/ethnicity
Table 2 displays measures of socio-medical vulnerability for the two groups. Beneficiaries
were more likely to report running out of food because they lacked money (39.0% vs.
17.0%, p < 0.001), or using a food pantry (17.3% vs. 5.1%, p < 0.001) in the past
month; being uninsured (20.5% vs. 9.2%, p < 0.001); and being unable to afford an
unexpected $400 expense (59.6% vs. 38.2%, p < 0.001). However, a larger absolute number
of at-work individuals were vulnerable because many more adults were at-work. For
instance, 26.0 million of those at-work reported problems affording food, versus 13.4
million unemployment beneficiaries.
Table 2
Measures of Sociomedical Vulnerability and Health Among US Adults 18–64 Years of Age
Receiving or Applying for Unemployment Insurance and Those Working, April–June 2020
Working
Unemployment insurance beneficiaries
p value*
Weighted N, thousands(95% CI)
%(95% CI)
Weighted N, thousands(95% CI)
%(95% CI)
Social precarity
Cannot afford $400 expense †
40,631
38.2
15,983
59.6
< 0.001
(37,139, 44,124)
(35.7, 40.9)
(13,549, 18,417)
(53.9, 65.0)
Food security
Worry food will run out ‡
23,606
22.1
12,353
46.1
< 0.001
(20,575, 26,638)
(19.8, 24.7)
(10,124, 14,583)
(40.3, 51.9)
Food ran out §
18,115
17.0
10,351
39.0
< 0.001
(15,461, 20,768)
(14.9, 19.3)
(8313, 12,388)
(33.3, 44.9)
Used food pantry ||
5454
5.1
4642
17.3
< 0.001
(4021, 6886)
(4.0, 6.6)
(3419, 5865)
(13.5, 21.9)
Any food insecurity ¶
25,978
24.4
13,376
50.3
< 0.001
(22,849, 29,107)
(22.0, 27.0)
(11,103, 15,649)
(44.6, 56.1)
Uninsured **
9763
9.2
5485
20.5
< 0.001
(7991, 11,534)
(7.7, 10.9)
(4135, 6835)
(16.3, 25.5)
Possible COVID-19 symptoms ††
Fever or chills
29,313
27.7
7140
26.9
0.79
(26,303, 32,324)
(25.3, 30.2)
(5614, 8667)
(22.2, 32.3)
Cough
14,977
14.1
4737
17.7
0.12
(12,866, 17,087)
(12.3, 16.1)
(3434, 6040)
(13.7, 22.6)
Dyspnea
11,523
10.9
3138
11.8
0.62
(9829, 13,218)
(9.5, 12.6)
(2246, 4030)
(8.9, 15.5)
Triad of all 3 symptoms
1926
1.9
957
3.7
0.057
(1275, 2577)
(1.3, 2.6)
(349, 1566)
(1.9, 6.8)
Self-reported health ‡‡
0.010
Good or better
96,906
90.7
23,051
85.8
(92,351, 101,461)
(89.1, 92.1)
(20,224, 25,877)
(81.5, 89.2)
Fair or worse
9955
9.3
3820
14.2
(8287, 11,624)
(7.9, 10.9)
(2710, 4930)
(10.8, 18.5)
Chronic conditions §§
Diabetes
6780
6.5
2217
8.6
0.23
(5490, 8071)
(5.4, 7.9)
(1271, 3163)
(5.7, 12.8)
COPD
12,824
12.4
2918
11.3
0.62
(10,854, 14,795)
(10.7, 14.3)
(1966, 3870)
(8.3, 15.4)
Heart disease
2404
2.3
1212
4.7
0.034
(1631, 3178)
(1.7, 3.2)
(475, 1948)
(2.6, 8.4)
Asthma
14,701
14.0
3896
15.1
0.61
(12,666, 16,735)
(12.3, 16.0)
(2819, 4973)
(11.6, 19.5)
Liver disease
831
0.8
352
1.3
0.26
(354, 1308)
(0.4,1.4)
(89, 616)
(0.6, 2.8)
Hypertension
23,937
23.0
5688
22.1
0.74
(21,583, 26,292)
(20.9, 25.1)
(4289, 7086)
(17.6, 27.3)
Immunocompromised
4818
4.6
2097
8.2
0.020
(3761, 5874)
(3.7, 5.7)
(1161, 3033)
(5.3, 12.4)
Number of conditions
0.97
0
54,875
56.3
13,194
57.1
(51,178, 58,572)
(53.6, 59.0)
(11,079, 15,310)
(51.0, 63.0)
1
30,506
31.3
7096
30.7
(27,725, 33,287)
(28.9, 33.8)
(5515, 8678)
(25.3, 36.7)
2+
12,086
12.4
2809
12.2
(10,337, 13,835)
(10.8, 14.2)
(1905, 3712)
(8.9, 16.4)
*Pearson chi-square
†Individuals were asked “Suppose that you have an unexpected expense that costs $400.
Based on your current financial situation, how would you pay for this expense?”; 8
non-mutually exclusive response options were provided. We created a binary mutually
exclusive indicator. Those who reported that they would cover the expense with a credit
card that they would pay off in full, or who would use cash or a checking/savings
account, were considered able to afford the $400 expense. Those reporting they would
use a credit card which they would pay off over time; a bank loan or line of credit;
borrow from a family member or friend; use a payday loan, overdraft, or deposit advance;
sell something; or would not be able to pay for it were categorized as unable to pay
the expense, even if they also chose one of the other two responses. N = 20 of 3480
with missing data
‡Individuals were asked whether they were “worried our food would run out before we
got money to buy more.” Those who responded with “never true” were categorized as
not worried, while those who answered “often true” or “sometimes true” were categorized
as worried. N = 8 of 3480 with missing data
§Individuals were asked whether “The food that we bought just didn’t last, and we
didn’t have money to get more.” Those who responded with “never true” were categorized
to not have run out of food, while those who answered “often true” or “sometimes true”
were categorized to have run out. N = 11 of 3480 with missing data
|| Individuals were asked about use (or application for) food pantry benefits in the
past 7 days. Those who answered “did not receive nor apply for any” benefits were
categorized as not using a pantry, while those who answered “received,” “applied for,”
or “tried to apply for” were categorized as using a pantry. N = 19 of 3480 with missing
data
¶Those with one of the three previous measures of food security, compared with those
with none. N = 15 of 3480 with missing data
**Individuals were asked whether they were currently covered by one of the 8 types
of insurance. Individuals reporting being covered by employer/union coverage, directly
purchased insurance, TRICARE or other military care, Medicaid or similar plans, Medicare,
or the Veterans Health Administration were classified as insured. Those reporting
none of these insurance types, even if they reported Indian Health Service or “other”
coverage, were considered uninsured. N = 19 of 3480 individuals with missing data
††Individuals were asked about experiencing 17 symptoms in the past 7 days. We created
three binary variables from responses about four of these symptoms (fever or chills
was considered to be one symptom). We also created a binary variable to indicate those
reporting all three of these symptoms, vs. those with less than three. Number with
missing data: 39 for fever/chills; 29 for cough; 39 for dyspnea; and 95 for all the
three-symptom indicator
‡‡This five-category variable was dichotomized in the typical fashion: poor or fair
vs. excellent, very good, or good. None with missing data
§§ Participants were asked whether “a doctor or other health care provider ever told
you that you have any of the following,” followed by questions about 13 conditions.
From these, we created binary variables for seven conditions identified by the CDC
as risk factors (or possible risk factors) for severe COVID-19.
3
We did not include cystic fibrosis given very low numbers. We also did not include
“overweight or obesity” given that we lacked BMI to differentiate overweight vs. obesity,
only the latter of which the CDC classified as a risk factor. We also created a three-category
variable designating 0, 1, or 2+ of these chronic conditions; for this variable, having
both asthma and COPD was considered only as one condition. Individuals with missing
data out of n = 3480: N = 101 for diabetes; 102 with COPD; 84 with heart disease;
80 with asthma; 48 with liver disease; 90 with hypertension; 97 with immunocompromise;
and 316 for the three-category chronic disease indicator
In total, 3.7% of unemployment beneficiaries had all three potential COVID-19 symptoms,
versus 1.9% of those at-work (p = 0.057); unemployment beneficiaries were more likely
to report fair/poor health (14.2% vs. 9.3%; p = 0.010), heart disease (4.7% vs. 2.3%;
p = 0.034), and immunocompromise (8.2% vs. 4.6%; p = 0.020), but not other conditions.
A total of 9.9 million unemployment beneficiaries had chronic conditions associated
with increased risk of severe COVID-19.
DISCUSSION
Despite the $600/week supplement available to unemployment beneficiaries at the time
of the survey,
4
many experienced financial precarity, and two factors were believed to compromise
clinical outcomes: food insecurity and lack of health insurance. Although rates of
these vulnerabilities were lower among those at-work, the absolute numbers affected
were larger.
While critics of the supplementary unemployment benefits have argued that it disincentivized
work,
1
a recent study cast doubt on that contention.
5
Even if jobs were available, in the context of ongoing community spread of SARS-CoV-2,
forcing individuals back into the workplace under threat of impoverishment may place
them, their co-workers, and the community at risk, since nearly 10 million unemployment
beneficiaries have chronic conditions, and about one million had a triad of symptoms
consistent with respiratory infection.
Our study is limited by the low survey response rate, which could reduce generalizability;
however, the number of unemployment beneficiaries identified corresponds to official
estimates from the Department of Labor.
6
Additionally, symptom data was self-reported, without confirmation by SARS-Cov-2 testing
or clinical assessment. Because the triad of COVID-19 symptoms is non-specific, those
reporting them may have other illnesses. Our data was cross-sectional, and cannot
be used to draw causal inferences about the specific impact of any particular policy,
including the $600 supplement. A notable strength of the study, however, is our use
of timely, nationally representative data, including on medical conditions and specific
symptoms, which, to our knowledge, is not available from any other source.
The economic and medical repercussions of the COVID-19 crisis are interconnected.
The supplemental unemployment benefits provided a safety net for the US economy and
population well-being. The lapse of the $600/week CARES supplement could inflict further
medical and financial harm on millions of American households. Additional policies,
however, are needed to strengthen the social safety net during the pandemic and beyond,
both for the unemployed and for those at-work.