QUESTION

article critque    

1 RTI International, Research Triangle Park, NC, USA

2 Department of Health Policy & Administration, Gillings School of Global

Public Health, University of North Carolina, Chapel Hill, NC, USA

3 Department of Epidemiology, Gillings School of Global Public Health,

University of North Carolina, Chapel Hill, NC, USA

Corresponding Author:

Lauren A. McCormack, PhD, MSPH, RTI International, 3040 E Cornwallis

Rd, Research Triangle Park, NC 27709, USA.

Email: lmac@ rti. org

Research

Public Health Reports

2021, Vol. 136(1) 107-116

c 2020, Association of Schools and

Programs of Public Health

All rights reserved.

Article reuse guidelines:

sagepub. com/ journals-permissions

DOI: 10. 1177/ 0033 3549 20970182

journals. sagepub. com/ home/ phr

Gaps in Knowledge About COVID-19

Among US Residents Early in

the Outbreak

Lauren A. McCormack, PhD, MSPH1,2 ‍‍; Linda Squiers, PhD1; Alicia M. Frasier, MPH1;

Molly Lynch, MPH1; Carla M. Bann, PhD1; and Pia D.M. MacDonald, PhD, MPH, CPH1,3

Abstract

Objectives: The novel coronavirus disease 2019 (COVID-19) resulting from severe acute respiratory syndrome coronavirus 2

began to affect the United States in early 2020. This study aimed to assess the US public’s initial understanding about the disease and

virus to inform public health communication efforts.

Methods: We conducted a survey of US households from February 28 through March 2, 2020, using a probability-based

web-panel

survey of 1021 US residents. To assess knowledge about COVID-19, we asked respondents a series of 16 true/false questions. We

conducted descriptive statistics and linear regression analyses to examine differences in knowledge scores based on demographic and

background characteristics.

Results: Knowledge about COVID-19 and the virus was relatively low overall at the beginning of the outbreak, with average scores

of 62% on a 16-item

knowledge index (ie, answers for 6 of the 16 questions were incorrect or unknown). Knowledge was especially

low among people who had low education and income levels, were unemployed, were Hispanic, were non-Hispanic

Black, were aged

18-24 and 35-49, indicated having “other” health insurance, and had limited exposure to information about the pandemic. Non-Hispanic

Black respondents were less knowledgeable about COVID-19 and the virus at every education level compared with non-Hispanic

White respondents at higher education levels. Non-Hispanic

Black respondents with <high school degree were the least

knowledgeable of all subgroups.

Conclusions: The findings of our study highlight the need for widespread, ongoing public health education about the virus and

COVID-19, especially among certain populations. It is critical to effectively translate complex clinical and epidemiologic evidence into

messages that most people can understand and act on during a pandemic, that combat misinformation about the virus and COVID-19,

and that consider low levels of health literacy.

Keywords

COVID-19, public health communication, public understanding of science, disparities, pandemic, emerging infectious disease

In early 2020, much of the world was focused on news

about the novel coronavirus disease 2019 (COVID-19),

caused by severe acute respiratory syndrome coronavirus 2

(SARS-CoV-

2). The epicenter of the outbreak was in

Wuhan, Hubei Province, China. On January 30, 2020, the

World Health Organization declared the novel coronavirus

outbreak a Public Health Emergency of International

Concern.1 In the United States, the first confirmed case of

travel-associated

COVID-19 was reported on January 20,

2020,2 and the first media statement of a COVID-19–

related death in the United States appeared on February

29, 2020.3 On March 13, 2020, the President of the United

States declared a national emergency.4

The challenges of educating and communicating with the

public about a pandemic of a novel viral pathogen and new

disease are substantial. In late February and early March, the

108 Public Health Reports 136(1)

scientific understanding of COVID-19 and SARS-CoV-

2

was limited, including lack of clarity about how the virus is

transmitted, the incubation period, peak infectiousness, risk

factors, basic epidemiology, and effective transmission prevention.

Findings from the early outbreak in Wuhan showed

that some groups were at increased risk of serious complications,

hospitalization, and death from COVID-19, including

people aged >60 and people with underlying health conditions,

such as diabetes, hypertension, cancer, cardiovascular

disease, and chronic respiratory diseases.5-7

Research from previous viral outbreaks of novel pathogens

identified knowledge gaps in transmission and prevention.

A systematic review of community knowledge about

the 2009 pandemic influenza A (H1N1) found that knowledge

about transmission of the virus was “moderate” and

knowledge about prevention was “reasonable.” However,

levels of knowledge differed for certain subgroups.

Knowledge about H1N1 was highest for people in older age

groups, with higher education levels, and higher socioeconomic

status than among people who were younger and had

lower education levels and socioeconomic status.8 One study

found that although much of the public had a good understanding

of H1N1 and how to prevent contracting it, gaps in

knowledge about transmission and signs and symptoms of

the virus existed for people whose income and education levels

were low and who reported their race as non-White.

9

Effective communication about a new virus and associated

disease is paramount for reducing morbidity and mortality

and helping communities prepare for an outbreak and

prevent transmission. The objective of this study was to elucidate

what US residents did and did not understand about

the virus and COVID-19 to help inform health communications

campaigns. We assessed (1) what the general public

knows and does not know about COVID-19 and (2) how this

knowledge differs for vulnerable populations, including

racial/ethnic minority groups, people with low levels of education

or income, and people without health insurance.

Methods

To examine knowledge, we conducted a survey of US households

from February 28 through March 2, 2020, using a prerecruited,

address-based

web panel consisting of 55 000

members. The panel is based on probability sampling of the

US population. Households received a computer and/or

internet access if needed to participate in the panel. The

resulting sample includes households with listed and unlisted

telephone numbers, telephone and nontelephone households,

cell phone–only households, and households with and without

internet access. The survey was conducted in English.

To assess knowledge about the virus and COVID-19, we

asked respondents a series of 16 true/false questions. We calculated

a mean knowledge index score as the number of

items answered correctly, with values ranging from 0% to

100%. We developed the questions based on the existing scientific

evidence available from authoritative sources at the

time of the survey, including the Centers for Disease Control

and Prevention10 and the World Health Organization.5 The

knowledge index had a Cronbach α11 of .85, indicating high

internal consistency.

We also asked participants to respond to the following

statement, “I know what actions to take to prevent myself

and my family from becoming infected with the coronavirus”

using a 4-point

Likert scale (from 1 = strongly agree

to 4 = strongly disagree) and the following question, “How

much have you seen, read, or heard about the coronavirus

first detected in Wuhan, China?” (1 = a great deal, 2 = a

fair amount, 3 = not very much, 4 = nothing at all). We also

collected information from all respondents on age (18-24,

25-34, 35-49, 50-64, ≥65), sex (male, female), education

(<high school graduate, high school graduate, some college,

≥bachelor’s degree), annual household income (<$25

000, $25 000-$49 999, $50 000-$99 999, $100 000-$149

999, ≥$150 000), race/ethnicity (non-Hispanic

White, non-Hispanic

Black, Hispanic, non-Hispanic

“other”), and

region of the country (Midwest, South, West, Northeast).

In this analysis, race/ethnicity are combined. The data set

also included responses to questions about current employment

(employed, unemployed), self-reported

health status

(excellent/very good, good, fair/poor, unknown), type of

health insurance (employer/union, Medicaid, Medicare/

Veterans Affairs, other, none, unknown), and which sources

of health information respondents had used in the past 12

months (eg, physician, relative/friend/coworker, social

media, newspaper).

At the end of the survey, participants were told that the

purpose of the survey was to understand what people in the

United States do and do not know about the virus and

COVID-19 and that some of the information on true/false

questions was in fact false. To prevent misinformation,

respondents were encouraged to learn what is known about

how to protect themselves and their families from getting

infected. All 1021 respondents received a link to the CDC

website.

The panel provider drew a random sample of 2857 members

from the panel. A total of 1021 (excluding respondents

who did not complete the survey) adults aged ≥18 responded

to the invitation, all of whom qualified for the survey, yielding

a final stage completion rate of 36%. Once the survey

sample was selected and fielded and all the study data were

collected and finalized, the panel provider used a poststratification

process to adjust for survey nonresponse and for any

noncoverage, undersampling, or oversampling resulting

from the study-specific

sample design based on the Current

Population Survey12 and weighted all respondents to these

distributions. The panel provider scaled the sample size to

the number of qualified respondents and used the following

benchmark distributions for this poststratification adjustment:

sex, age, race/ethnicity, education level, geographic

McCormack et al 109

region, annual household income, metropolitan area, and

homeownership status.

We conducted the Rao-Scott

χ2 test of significance and

linear regression analyses to examine differences in knowledge

scores and other survey questions based on the following

demographic and background characteristics: sex; age;

education; annual household income; employment status;

race/ethnicity; self-reported

health status; type of health

insurance; geographic region; the amount of information

seen, read, or heard about “the coronavirus”; and the number

of sources of health information. Reference groups were

female, age ≥65, bachelor’s degree, annual household

income ≥$150 000, being employed, non-Hispanic

White,

excellent/very good health, employer-sponsored/

union

health insurance, residing in the West, and reporting “a great

deal of information about the coronavirus.” In addition to the

main effects regression model, we tested for possible interactions

between demographic characteristics to identify potentially

vulnerable subgroups. We modeled differences in

overall knowledge and differences within categories or

knowledge domains. We report 95% CIs for coefficients and

considered P < .05 to be significant. We incorporated survey

weights into the analyses, and we conducted all analyses

using SAS version 9.3 (SAS Institute Inc).

The RTI International Institutional Review Board

reviewed the study protocol and determined it to be exempt

from human subjects approval.

Results

The distribution of the survey participants across sociodemographic

characteristics and health-related

variables suggests

that a nationally representative sample was achieved

(Table 1). Most respondents had seen, read, or heard about

COVID-19: 50% (weighted n = 496) of respondents reported

a fair amount of knowledge and 36% (weighted n = 364)

reported a great deal of knowledge. We found significant differences

in how much respondents had seen, read, or heard

about COVID-19 by age, education, annual household

income, and health insurance. A significantly higher percentage

of non-Hispanic

Black respondents than non-Hispanic

White respondents answered “not very much/nothing at all”

(23% vs 12%), χ2(2) = 14.0, P = .01.

The mean score on the 16-item

knowledge index was

61.7% (95% CI, 59.9%-63.4%; Table 2). The percentage of

correct responses for the 16 questions ranged from 36.2% to

90.3%, with a sizeable proportion of respondents indicating

that they did not know the correct answer to several questions

(the source of the correct answer is noted after each

question). US residents had knowledge gaps about the potential

severity and associated mortality of COVID-19: 58.8%

knew that most people would recover after getting the virus,

and 40.5% were either incorrect (9.7%) or did not know the

answer (30.8%). About one-third

(32.6%) of respondents

Table 1. Sociodemographic characteristics of respondents to a

survey about COVID-19 knowledge (N = 1021), United States,

February 28–March 2, 2020a

Characteristic

Unweighted Weightedb

No. (%)c No. (%)c

Sex

Male 514 (50) 484 (48)

Female 507 (50) 516 (52)

Age, y

18-24 107 (10) 127 (13)

25-34 154 (15) 153 (15)

35-49 255 (25) 248 (25)

50-64 283 (28) 268 (26)

≥65 222 (22) 211 (21)

Race/ethnicity

Non-Hispanic

White 722 (71) 632 (63)

Non-Hispanic

Black 95 (9) 118 (12)

Hispanic 123 (12) 164 (16)

Non-Hispanic

other 81 (8) 86 (9)

Education

≥Bachelor degree 417 (41) 323 (33)

Some college 282 (28) 278 (28)

High school graduate 258 (25) 283 (28)

<High school graduate 64 (6) 106 (11)

Annual household income, $

<25 000 119 (12) 135 (14)

25 000-49 999 158 (15) 182 (18)

50 000-99 999 328 (32) 307 (31)

100 000-149 999 197 (19) 170 (17)

≥150 000 219 (21) 206 (21)

Employment status

Employed 687 (67) 656 (66)

Unemployed 334 (33) 344 (34)

Health insurance

Employer/union 524 (51) 484 (48)

Medicaid 190 (19) 183 (18)

Medicare/Veterans Affairs 55 (5) 69 (7)

Other 71 (7) 74 (7)

None 62 (6) 71 (7)

Unknown 119 (12) 120 (12)

Self-reported

health status

Excellent/very good 493 (48) 467 (47)

Good 322 (32) 315 (31)

Fair/poor 131 (13) 139 (14)

Unknown 75 (7) 79 (8)

Geographic region

Midwest 243 (24) 208 (21)

South 351 (34) 379 (38)

West 236 (23) 238 (24)

Northeast 191 (19) 175 (18)

(continued)

110 Public Health Reports 136(1)

incorrectly believed (11.9%) or did not know (20.7%) that

most people would die from getting the virus, and 63.1% of

respondents were unclear that most people who are infected

would have only mild symptoms (25.0% answered incorrectly

and 38.1% did not know).

Most people understood that the virus can affect people of all

ages (90.3%) and racial/ethnic groups (88.8%), but some did not.

About 1 in 5 respondents did not know that coughing and sneezing

can spread the virus (2.9% incorrect, 18.5% did not know)

and that it is very contagious (3.0% incorrect, 14.1% did not

know). Most respondents thought a vaccine was available

(68.3%) or were not sure (26.9%). Some respondents believed

that certain behaviors would protect them from the virus and others

were unsure; for example, 40.0% of respondents did not

know that hand dryers were ineffective at killing the virus (3.7%

answered incorrectly, 43.4% did not know), and 50.3% of

respondents either believed or did not know that spraying alcohol

or chlorine on your body would not kill the virus.

COVID-19 knowledge was lower for some subgroups

than for others based on the regression models. For example,

people who had lower education levels (eg, some college vs

a bachelor’s degree (β = –4.14; SE = 1.89; P = .03), had

lower income levels (eg, annual household income <$50 000

vs $≥150 000; β = –8.95; SE = 2.62; P < .001), were unemployed

versus employed (β = –3.91; SE = 1.99; P = .49),

were Hispanic (β = –7.19; SE = 2.46; P = .004) or non-Hispanic

Black (β = –13.88; SE = 2.76; P < .001) versus

non-Hispanic

White, were younger (eg, 18-24 vs ≥65; β =

–9.48; SE = 3.89; P = .02), indicated having “other” health

insurance versus private health insurance (β = –6.23; SE =

2.86; P = .03), and had limited exposure to information about

the pandemic (eg, exposed to not very much/nothing at all vs

a great deal; β = –17.78; SE = 2.89; P < .001; Table 3).

Scores on knowledge domains also differed by subgroup.

Knowledge was significantly lower among Hispanic and non-Hispanic

Black respondents than among non-Hispanic

White

respondents and lower-income

respondents across all domains

except susceptibility. Respondents who were aged <65 and who

had Medicaid or Veterans Affairs health insurance were less

knowledgeable about items about misinformation than respondents

who were younger and had employer-sponsored

health

Characteristic

Unweighted Weightedb

No. (%)c No. (%)c

How much have you seen, read,

or heard about the coronavirus

first detected in Wuhan, China?

A great deal 380 (37) 364 (36)

A fair amount 512 (50) 496 (50)

Not very much/nothing at all 128 (13) 139 (14)

Unknown 1 (0) 1 (0)

aData source: RTI International–funded survey on coronavirus disease

2019 (COVID-19).

bSurvey weights were calculated to represent the US population based on

estimates from the Current Population Survey.12

cSome percentages do not sum to 100 because of rounding.

Table 1. (continued)

Table 2. Sixteen-item

knowledge index and percentage correct and incorrect, by knowledge domain, in a survey about COVID-19 (N =

1021), United States, February 28–March 2, 2020a

Survey question (answer) Correct Incorrect Don’t know

Most people who are infected with the coronavirus only have mild symptoms (True)13 36.2 25.0 38.1

Most people who are infected with the coronavirus recover from it (True)13 58.8 9.7 30.8

Most people who are infected with the coronavirus die from it (False)13 66.6 11.9 20.7

People of all racial and ethnic groups can become infected with the coronavirus (True)14 88.8 2.3 8.3

People of all ages can become infected with the coronavirus (True)15 90.3 2.0 6.8

The coronavirus is spread through coughing and sneezing (True)13 77.6 2.9 18.5

The coronavirus is very contagious (True)13 82.1 3.0 14.1

Antibiotics can be used to treat the coronavirus (False)16 45.6 14.4 39.3

Antibiotics can be used to prevent infection from the coronavirus (False)16 57.2 7.0 34.9

A vaccine is now available to prevent infection from the coronavirus (False)16 68.3 4.1 26.9

You can become infected with the coronavirus by touching a package sent from China (False)15 42.8 13.2 43.1

The coronavirus was deliberately created (False)17 43.2 11.7 44.4

Spraying alcohol or chlorine on your body kills the coronavirus (False)15 48.7 6.4 43.9

Rinsing your nose with saline prevents infection from coronavirus (False)15 52.2 3.7 43.4

Hand dryers are effective at killing the coronavirus (False)15 59.1 4.3 35.7

Eating garlic can lower your chances of getting infected with the coronavirus (False)15 62.6 2.9 33.7

aData source: RTI International–funded survey on coronavirus disease 2019 (COVID-19). All values are percentages. Some percentages do not sum to 100

because of rounding. Overall mean knowledge index score is 61.7% correct (95% CI, 59.9%-63.4%).

McCormack et al 111

Table 3. Regression models of knowledge index scores, by knowledge domain, in a survey of knowledge about COVID-19 (N = 1021),

United States, February 28–March 2, 2020a

Characteristic

Coefficient (SE) [P value]b

Overall Severity and mortality Susceptibility Transmission

Vaccines and

treatment Misinformation

Sex

Male 2.20 (1.54) [.15] 6.89 (2.30) [.003] 3.33 (1.94) [.09] 2.90 (2.34) [.22] 2.61 (2.53) [.30] –0.97 (2.20) [.66]

Female 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Age, y

18-24 –9.48 (3.89) [.02] –11.02 (5.33) [.04] –6.73 (5.22) [.20] –0.35 (5.64) [.95] –12.46 (6.40) [.05] –11.17 (5.29) [.04]

25-34 –5.43 (3.17) [.09] –1.76 (4.75) [.71] –1.93 (3.98) [.63] 2.18 (4.62) [.64] –7.05 (5.31) [.18] –10.16 (4.54) [.03]

35-49 –7.14 (2.82) [.01] –3.90 (4.46) [.38] –1.92 (3.25) [.56] 5.55 (3.93) [.16] –13.30 (4.73) [.01] –11.64 (4.12) [.01]

50-64 –3.97 (2.50) [.11] 0.90 (4.05) [.82] 1.04 (2.83) [.71] 4.71 (3.63) [.20] –6.79 (4.25) [.11] –9.57 (3.74) [.01]

≥65 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Race/ethnicity

Non-Hispanic

White 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Non-Hispanic

Black –13.88 (2.76) [<.001] –22.76 (4.06) [<.001] –6.62 (3.93) [.09] –11.50 (4.61) [.01] –18.44 (4.39) [<.001] –10.37 (3.74) [.01]

Hispanic –7.19 (2.46) [.004] –14.76 (3.65) [<.001] 5.58 (3.02) [.07] 0.20 (3.87) [.96] –11.27 (4.16) [.01] –8.09 (3.53) [.02]

Non-Hispanic

other –4.63 (3.28) [.16] –10.76 (4.61) [.02] –5.35 (4.48) [.23] 1.47 (4.55) [.75] –5.55 (5.25) [.29] –2.88 (4.64) [.54]

Education

<High school

graduate

–16.56 (3.83) [<.001] –27.98 (5.79) [<.001] –14.59 (5.85) [.01] –4.96 (5.87) [.40] –19.39 (6.27) [.002] –13.96 (4.68) [.003]

High school graduate –1.30 (2.18) [<.001] –19.11 (3.41) [<.001] –3.97 (2.52) [.12] 0.12 (3.06) [.97] –17.66 (3.61) [<.001] –15.04 (3.24) [<.001]

Some college –4.14 (1.89) [.03] –9.96 (3.02) [.001] 0.10 (2.29) [.96] –0.12 (2.77) [.97] –1.82 (3.21) [.57] –5.15 (2.65) [.05]

≥Bachelor’s degree 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Annual household

income, $

<50 000 –8.95 (2.62) [<.001] –14.98 (4.22) [<.001] –5.78 (3.40) [.09] –8.29 (3.82) [.03] –11.13 (4.38) [.01] –6.14 (3.58) [.09]

50 000-99 999 –6.20 (1.99) [.002] –4.51 (3.22) [.16] –1.36 (2.40) [.57] –6.30 (2.99) [.04] –7.19 (3.42) [.04] –8.12 (2.88) [.01]

100 000-149 999 –3.56 (2.21) [.11] –8.34 (3.54) [.02] –1.87 (2.33) [.42] –0.66 (3.03) [.83] 0.75 (3.57) [.83] –4.84 (3.23) [.13]

≥150 000 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Employment status

Unemployed –3.91 (1.99) [.049] –1.12 (2.93) [.70] –1.40 (2.56) [.59] –1.55 (2.94) [.60] –2.48 (3.10) [.42] –7.65 (2.72) [.01]

Employed 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Health insurance

Employer/union 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Medicaid –6.03 (3.67) [.10] –4.83 (6.20) [.44] –3.18 (5.26) [.55] –2.14 (6.31) [.73] 1.90 (6.87) [.78] –12.83 (4.61) [.01]

Medicare/Veterans

Affairs

–4.09 (2.61) [.12] –0.09 (3.91) [.98] 1.68 (2.81) [.55] 3.03 (3.48) [.38] –7.20 (4.48) [.11] –8.83 (3.95) [.03]

Other –6.23 (2.86) [.03] –9.03 (4.12) [.03] –1.10 (3.91) [.78] 1.19 (4.21) [.78] –9.75 (4.77) [.04] –7.26 (4.14) [.08]

None –5.21 (3.92) [.18] –8.84 (4.89) [.07] 1.21 (5.12) [.81] –1.62 (6.01) [.79] –4.98 (6.24) [.42] –6.85 (4.96) [.17]

Unknown 5.65 (11.01) [.61] 15.48 (19.38) [.43] –2.31 (8.71) [.55] 1.20 (24.92) [.96] 8.32 (28.21) [.77] 5.75 (20.51) [.78]

Self-reported

health

status

Excellent/very good 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

Good –2.16 (1.74) [.22] –1.50 (2.61) [.57] –0.41 (2.20) [.85] –1.12 (2.58) [.66] –5.21 (2.92) [.08] –1.90 (2.37) [.42]

Fair/poor –0.35 (2.66) [.89] –4.55 (3.80) [.23] 0.99 (3.25) [.76] –4.41 (3.94) [.26] 0.45 (4.09) [.91] 2.25 (3.65) [.54]

Unknown –7.03 (4.01) [.08] –7.51 (7.83) [.34] –2.31 (8.71) [.79] 6.84 (8.01) [.39] –22.92 (8.14) [.01] –5.03 (7.50) [.50]

Geographic region

Midwest –0.62 (2.38) [.80] 0.44 (3.56) [.90] 5.34 (3.03) [.08] –3.26 (3.43) [.34] –2.75 (3.85) [.48] –1.18 (3.21) [.71]

Northeast –1.95 (2.39) [.42] –8.96 (3.58) [.01] 5.01 (2.64) [.06] 3.96 (3.26) [.23] 0.74 (4.00) [.85] –4.07 (3.39) [.23]

South –2.38 (2.10) [.26] –2.21 (3.18) [.49] 3.69 (2.80) [.19] –2.49 (3.19) [.43] –0.84 (3.42) [.81] –5.23 (2.84) [.07]

West 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

How much have you

seen, read, or

heard about the

coronavirus first

detected in Wuhan,

China?

(continued)

112 Public Health Reports 136(1)

insurance, respectively, and male respondents had higher knowledge

scores about severity and mortality than female respondents.

Respondents who reported seeing or hearing a greater

amount of information about COVID-19 had higher knowledge

scores across all domains than respondents who were exposed to

less information, and respondents who used more sources of

information had higher scores across all domains except vaccines

than respondents who used fewer sources of information.

The mean knowledge index score was 43% for respondents

with <high school degree and 61% for respondents

with ≥bachelor’s degree. The mean knowledge score was

42% for non-Hispanic

Black respondents and 58% for non-Hispanic

White respondents. The impact of education on

knowledge varied by race/ethnicity (Figure 1). Across all

racial/ethnic groups, respondents with ≥bachelor’s degree

were most knowledgeable. Non-Hispanic

Black respondents

Characteristic

Coefficient (SE) [P value]b

Overall Severity and mortality Susceptibility Transmission

Vaccines and

treatment Misinformation

A great deal 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]

A fair amount –4.33 (1.57) [.01] –5.98 (2.48) [.02] –0.40 (1.69) [.81] –3.81 (2.33) [.10] –7.26 (2.64) [.01] –3.51 (2.32) [.13]

Not very much/

nothing at all

–17.78 (2.89) [<.001] –21.13 (4.12) [<.001] –9.26 (4.07) [.02] –10.96 (4.44) [.01] –22.33 (4.61) [<.001] –18.95 (3.67) [<.001]

Number of

sources of health

information

1.84 (0.54) [<.001] 2.26 (0.90) [.01] 1.39 (0.64) [.03] 2.15 (0.83) [.01] 1.38 (0.90) [.13] 1.90 (0.80) [.02]

Abbreviation: SE, standard error.

aData source: RTI International–funded survey on coronavirus disease 2019 (COVID-19). Total N = 868 for overall model. R2 = 0.36. Means are adjusted for sex, age, education, annual household

income, employment status, race/ethnicity, self-reported

health status, health insurance, and geographic region; amount of information seen, read, or heard about the coronavirus; and number of

sources of information.

bBased on linear regression analysis, with P < .05 considered significant.

Table 3. (continued)

Figure 1. Adjusted mean knowledge index scores, by race/ethnicity and education, from a 16-item

knowledge assessment survey about

coronavirus disease 2019 (COVID-19) knowledge, United States, February 28–March 2, 2020. Sample size for regression model was 868

and R2 = 0.39. The overall F-test

for race × education interaction is F(9, 867) = 3.04, P < .001. Values for “other” race/ethnicity not shown

because of small sample size. Means are adjusted for sex, age, education, annual household income, employment status, race/ethnicity, self-reported

health status, and geographic region; amount of information seen, read, or heard about the coronavirus; number of information

sources; and interaction of race/ethnicity and education. Error bars indicate 95% CIs.

McCormack et al 113

across all education levels were less knowledgeable than

non-Hispanic

White respondents. Non-Hispanic

Black

respondents with <high school education were the least

knowledgeable of all subgroups.

Finally, although 81% of respondents agreed or strongly

agreed that they knew what actions to take to prevent themselves

and their families from becoming infected with

COVID-19, non-Hispanic

Black respondents were less likely

than non-Hispanic

White respondents (P < .001) and respondents

of other racial/ethnic groups (P = .004) to endorse this

statement (Figure 2).

Discussion

These findings offer a unique perspective about knowledge

levels at the beginning of the COVID-19 epidemic in the

United States. Although one survey assessed the public’s

knowledge of COVID-19,18 few surveys were administered

as the United States had its first death caused by COVID-19

and before the White House declared a public health emergency

on March 13, 2020. Overall, knowledge levels were

low, with respondents scoring, on average, 62% on the 16-item

knowledge index, meaning that answers for 6 of the 16

questions were incorrect or not known. Although respondent

knowledge was higher about certain topics than about others

(eg, who is susceptible to becoming infected), knowledge

about other questions indicated deficiencies. We found gaps

in knowledge about disease severity and mortality rates, with

respondents believing the mortality rate to be higher than initially

indicated. Our study findings align with the results of

another study that assessed knowledge of people living in the

United States and the United Kingdom 1 week before our

study was fielded.19 Because we conducted our study early in

the pandemic, it is likely that knowledge levels changed over

time given media coverage and state- and local-level

guidance

to socially distance and wear face coverings. Our findings

can serve as a baseline of knowledge among various

subgroups in the United States in the early days of the

pandemic.

Our findings highlight that some vulnerable subgroups

had limited knowledge overall and in certain knowledge

domains. Respondents who had low income levels and were

unemployed at the time of the survey were less knowledgeable

than their higher-income,

employed counterparts.

Lower-income

people include many frontline employees

deemed “essential”—such as grocery store clerks, hospital

housekeepers, food service staff, and employees at food-processing

plants and in the transportation industry.20 Lower-income

workers may not have employer-sponsored

health

insurance and may wait to seek health care.21-24 Ensuring

that workers are aware of protective actions is important to

their safety and the safety of their households and

Figure 2. Percentage of US residents who said they know how to prevent getting infected with coronavirus, by race/ethnicity, in a survey

about coronavirus disease 2019 (COVID-19) knowledge, United States, February 28–March 2, 2020 (N = 1021). Errors bars indicate 95%

CIs. Data source: RTI International–funded survey on COVID-19.

114 Public Health Reports 136(1)

communities. COVID-19 and SARS-CoV-

2 education

efforts should be developed for workplace education, and

employers should be encouraged to provide access to ongoing

education as information about transmission and prevention

evolves.

Respondents who were non-Hispanic

Black and had low

education levels had the lowest knowledge level, potentially

putting them at high risk of becoming infected with SARS-CoV-

2. Data from multiple states and some cities show that

racial/ethnic minority populations have disproportionately

higher rates of SARS-CoV-

2 infection and mortality than

non-Hispanic

White people.25,26 Developing and implementing

SARS-CoV-

2 and COVID-19 education campaigns

that use trusted messengers, sources of information, and

channels most frequently accessed by these and other

groups—such as unemployed people—should be prioritized

because they may not rely on mainstream media for their

information.

Other subgroups had low knowledge in some domains, which

suggests the need for targeted communication efforts. For example,

people aged <65 and people with Medicaid/Veterans Affairs

health insurance were more prone to misinformation than older

adults and people with employer-sponsored

or union health

insurance. Our results show that substantial misinformation and

uncertainty about the virus and COVID-19 existed at the time of

the survey (end of February/early March 2020), particularly

about transmission and risk-reduction

strategies. As misinformation

proliferates during the pandemic, directing communication

efforts to specific populations, including younger adults and via

Medicaid/Veterans Affairs channels, could be beneficial to providing

these groups with accurate information. Finally, respondents

who reported seeing or hearing more information about

COVID-19 and used more sources of information generally had

higher knowledge levels about COVID-19 than respondents who

reported seeing or hearing less information about COVID-19.

Lack of interest, strongly held beliefs, and information-processing

capabilities may also influence the successful uptake and application

of information regardless of the amount of information

disseminated.27

Certain subgroups may be susceptible to both lack of

information about public health topics and negative effects

of epidemics. According to the Kaiser Family Foundation,

Black people in the United States have been disproportionately

affected by HIV/AIDS since the beginning of the epidemic,

and that disparity has deepened over time.28 National

public health education and social marketing campaigns

have been implemented for major public health issues such

as HIV, because exposure to targeted public health information

can positively influence attitudes, beliefs, and behaviors.

29 Effective risk communication is a critical component

of protecting public health during an infectious disease epidemic.

30 As noted by Vaughn and Tinker, “The consequences

of pandemic influenza for vulnerable populations will

depend partly on the effectiveness of health risk communications.

If ignored, current communication gaps for vulnerable

populations could result in unequal protection across society

during an influenza pandemic.”31

Limitations

Our study had several limitations. First, the survey completion

rate was only 36%. However, the study was conducted

using a probability-based

web panel to capitalize on an

already existing US population-based

sample and survey

structure, which allowed for speed and representativeness of

data collection. Second, the survey included a small percentage

of Hispanic respondents with <high school degree, and

we did not collect information on English-language

proficiency,

where Hispanic respondents received information

about COVID-19, and their most trusted sources of information

about COVID-19. Having this information could have

provided important insights into message development and

dissemination for this subpopulation. These factors should

be considered in future research.

Conclusion

Our findings provide important insights about how and

where to focus public health education and communications

to inform people about the virus and COVID-19, especially

people who are at high risk of morbidity and mortality from

COVID-19. Understanding how much US residents know

about the virus and COVID-19—including how it spreads,

how to prevent infection, and how to separate myths from

facts—is critical to providing public health education to US

residents so that they know how to protect themselves, their

families, and their communities. Although COVID-19 has

been widely covered by the news media, a science-based

and

strategic public health education campaign is needed to

translate complex clinical and epidemiologic evidence into

messages that most people can understand and act on and

that reach people through multiple channels.

The messaging should be constructed carefully to combat

ongoing myths and misinformation about the virus and

COVID-19, particularly in social media,32 and consider people

with low levels of health literacy. Providing new and

ongoing information about what is known and what is yet to

be known is a best practice for risk communication.33

Monitoring changes in knowledge over time will enable

communication strategies to be refined during the trajectory

of the pandemic and to prepare for the wave of needed information,

such as that related to a vaccine. Accurate and timely

information about the virus and COVID-19 that successfully

reaches the public is a public health intervention that can

change the course of the pandemic for the better.

Acknowledgments

The authors thank Jeffrey Novey for his review and editing of the

article and Ashley Wheeler for her research assistance.

McCormack et al 115

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect

to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support

for the research, authorship, and/or publication of this article: This

study was funded by RTI International.

ORCID iD

Lauren A. McCormack, PhD, MSPH ‍‍ https:// orcid. org/ 0000-

0002- 5362- 0540

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10. 1080/ 7138 51971

The purpose of the article critique assignment is to strengthen your skills at critically assessing

the literature. An assigned article will be given, and students will provide a 1-2 page single-

spaced critique of the article. Two article critique assignments will be given during the semester. 

Questions are listed below each section to guide your critiques (you do not have to answer every

single question). They are mainly to help. The article critique assignment is 4 parts:

I.Article Summary

Provide a brief, one to two paragraph summary of the article. 

Questions to consider:

1.What is the purpose of the research? 

2.What are the research questions/hypotheses?

3.What study design was used?

4.What sampling methodology was used?

5.What are the main, overall results?

6.What limitations are stated?

7.What are the main overall conclusions or recommendations the researchers state?

II.Article Strengths

Write one to two paragraphs on the article’s strengths. 

Questions to consider:

1.What are the strengths of the article’s introduction and research questions? Do they fill an

important research gap? Are they relevant to the field? 

2.What are the strengths of the article’s study design, methodology, or sampling strategy?

Are novel techniques used? Is a strong study design employed?

3.What are the strengths of the article’s results and discussion section? Are the results

presented in a clear manner? Are graphs or charts utilized? Do the researchers make

strong recommendations? Are implications for the field strong? 

III.Article Weaknesses

Write one to two paragraphs on the article’s weaknesses. You can organize this in the

same order the article is written (i.e., discuss weaknesses in the introduction, then the

methods, etc.), or you may organize it by discussing the most important weaknesses

first and the least important weaknesses last. 

Questions to consider:

1.What are the weaknesses in the introduction? Are the research questions not explicitly

stated? 

2.Could a better study design have been utilized? Are the authors lacking their description

of the study design, sampling methodology, and data analysis? Could other statistical

techniques be employed? 

3.Are results unclear? Are tables unorganized? Do the researchers not highlight important

results?

4.What major limitations are discussed that you consider weaknesses of the article? What

limitations in the discussion section are missing or not discussed? 

5.Are recommendations or conclusions lacking? Are there other implications that aren’t

discussed? Did researchers “over reach” regarding their results and conclusions?

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