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. 2023 Dec 6;9:e37102. doi: 10.2196/37102

Prevalence of COVID-19 Mitigation Behaviors in US Adults (August-December 2020): Nationwide Household Probability Survey

Travis Sanchez 1,✉, Eric Hall 1, Aaron J Siegler 1, Radhika Prakash-Asrani 1, Heather Bradley 2, Mansour Fahimi 3, Benjamin Lopman 1, Nicole Luisi 1, Kristin N Nelson 1, Charles Sailey 4, Kayoko Shioda 1, Mariah Valentine-Graves 1, Patrick S Sullivan 1
Editor: Amaryllis Mavragani
Reviewed by: Chenyu Sun, Minjung Lee, Sherif Badawy
PMCID: PMC10702689  PMID: 38055314

Abstract

Background

COVID-19 mitigation behaviors, such as wearing masks, maintaining social distancing, and practicing hand hygiene, have been and will remain vital to slowing the pandemic.

Objective

This study aims to describe the period prevalence of consistent mask-wearing, social distancing, and hand hygiene practices during the peak of COVID-19 incidence (August-December 2020) and just before COVID-19 vaccine availability, overall and in demographic subgroups.

Methods

We used baseline survey data from a nationwide household probability sample to generate weighted estimates of mitigation behaviors: wearing masks, maintaining social distancing, and practicing hand hygiene. Weighted logistic regression explored differences in mitigation behaviors by demographics. Latent class analysis (LCA) identified patterns in mitigation behaviors.

Results

Among 4654 participants, most (n=2727, 58.6%) were female, were non-Hispanic White (n=3063, 65.8%), were aged 55 years or older (n=2099, 45.1%), lived in the South (n=2275, 48.9%), lived in metropolitan areas (n=4186, 89.9%), had at least a bachelor’s degree (n=2547, 54.7%), had an income of US $50,000-$99,000 (n=1445, 31%), and were privately insured (n=2734, 58.7%). The period prevalence of consistent mask wearing was 71.1% (sample-weighted 95% CI 68.8-73.3); consistent social distancing, 42.9% (95% CI 40.5-45.3); frequent handwashing, 55.0% (95% CI 52.3-57.7); and frequent hand sanitizing, 21.5% (95% CI 19.4-23.8). Mitigation behaviors were more prevalent among women, older persons, Black or Hispanic persons, those who were not college graduates, and service-oriented workers. LCA identified an optimal-mitigation class that consistently practiced all behaviors (n=2656, 67% of US adults), a low-mitigation class that inconsistently practiced all behaviors (n=771, 20.6%), and a class that had optimal masking and social distancing but a high frequency of hand hygiene (n=463, 12.4%).

Conclusions

Despite a high prevalence of COVID-19 mitigation behaviors, there were likely millions who did not consistently practice these behaviors during the time of the highest COVID-19 incidence. In future infectious disease outbreak responses, public health authorities should also consider addressing disparities in mitigation practices through more targeted prevention messaging.

Keywords: COVID-19, mask, social distancing, handwashing, hand sanitizer, public health, pandemic, mitigation behavior, risk factor, disease prevention, health policy, latent class analysis, hygiene

Introduction

The COVID-19 pandemic was first documented in China in December 2019, with cases identified in the United States shortly afterward [1,2]. As of December 2020, there were more than 20 million COVID-19 cases and more than 360,000 COVID-19–related deaths in the United States [3]. Because the vaccine did not become available to select groups until late December 2020, the primary means of preventing COVID-19 infection during the first year of the pandemic included the consistent use of mitigation behaviors of mask wearing, social distancing, and hand hygiene [4].

Multiple published studies have explored the prevalence of mitigation behaviors among US adults during the first year of the pandemic, but many of these are convenience samples or from limited geographic areas. Those that explored mask usage in public settings have reported a highly variable prevalence (40%-90%) of usage by the type of public setting for mask wearing and the timing of local mask mandates [5-10]. Social distancing, which can encompass limiting exposure to persons outside of one’s household and keeping at least 6 feet apart from others when outside the home, has been reported by a few previous studies, and estimates have also been prone to variation (70%-87%) due to rapidly changing local mandates for limiting travel and closure of public venues [11,12]. Recommended hand hygiene practices, such as frequent handwashing or the use of alcohol-based hand sanitizers, have been infrequently reported by studies of the general population but have more consistently shown high variation (74%-93%) [13-15].

The COVID Impact Survey is one of the most comprehensive and well-published studies of mitigation behaviors using cross-sectional samples and emailed surveys at multiple time points [12]. The study found that mask usage grew significantly from 78% in April 2020 to 89% in June 2020. The authors also found reductions in attending public venues, and >80% of participants reported keeping at least 6 feet apart from others, although there was a decreasing trend in these behaviors between April and July 2020, likely associated with the easing of local travel restrictions and business closures. Finally, the authors found that the proportion of US adults who frequently washed or sanitized hands was the highest (90%) in April 2020 but declined through July 2020 [12].

Just as there has been substantial heterogeneity in COVID-19 cases, morbidity, and mortality among US adults from various demographic backgrounds [16-19], there have also been some reported differences in the uptake of mitigation practices during the COVID-19 pandemic. Mask wearing may be more prevalent among women, non-White persons, and those who do not live in rural areas [5,9]. Handwashing may also be more prevalent among women, older adults, and those who identify as Black or Hispanic/Latinx [15]. Evidence from ecological analyses of mobility data found that social distancing was higher in counties with lower levels of poverty, a larger proportion of Black residents, and a higher population density [20].

Despite these high-quality studies of COVID-19 mitigation practices, there remain substantial gaps in our knowledge. Currently published estimates of the prevalence of mitigation practices were from before the peak of COVID-19 incidence, and few were from probability-based samples of the general US population. Having minimally biased information at multiple time points during the pandemic is critical to understanding the ongoing needs for public health communications regarding these mitigation practices. Having additional reliable estimates from later time points during the pandemic are also useful parameters for COVID-19 modeling activities.

We collected and analyzed baseline assessment data of a prospective cohort of a representative household-based sample of US adults. The main objective of this study was to describe the period prevalence of consistent mask-wearing, social distancing, and hand hygiene practices during the peak of COVID-19 incidence (August-December 2020) and just before COVID-19 vaccine availability, overall and in demographic subgroups. We also explored whether people engage in mitigation practices as a set of activities or as individual unconnected behaviors.

Methods

Participants and Procedures

COVIDVu is a prospective observational cohort study with a nationwide household probability sample of US adults using sampling methods that have been previously described [21]. A total of 39,500 US households were sampled using addresses derived from the US Postal Service Computerized Delivery Sequence File, including oversampling of households with census tracts comprising >50% Black residents and households with surnames likely to represent Hispanic ethnicity. The sampled households also include oversamples in California (16.5%) and Georgia (30.4%) to allow state-level estimation. All sampled households were shipped a study kit each. One adult resident enumerated the number of household members and each person’s age. One enumerated household member aged ≥18 years was randomly selected and offered participation in the study. Consenting participants were asked to complete an online survey, self-collect an anterior nares swab and a dried blood spot card, and return the specimens to a central laboratory via a prepaid mailer. Participants who returned the specimens were compensated at least US $40. Using procedures previously described for this study, sample and design weights were applied to estimate unbiased measures for noninstitutionalized, housed US adults in 2020 [21].

Ethical Considerations

Informed consent was obtained from each participant in the study. The study was conducted in compliance with federal regulations governing protection of human subjects and was reviewed and approved by Emory University’s Institutional Review Board (protocol 00000695).

Measures

The following primary dependent measures were used in this study: mask wearing, social distancing, handwashing, and hand sanitizer use. Mask wearing was defined by the question “When you go out, do you wear a face mask?” with response options of always, often, sometimes, rarely, and never. Social distancing was defined by the question “How often are you trying to keep at least 6 feet between you and other people you don’t live with to avoid spreading illness?” with response options of always, often, sometimes, rarely, and never. Those who reported always wearing masks or maintaining social distancing were defined as consistently practicing these behaviors. Handwashing was defined by the question “In the past 24 hours, about how many times did you wash your hands with soap and water?” Hand sanitizer use was defined by the question “In the past 24 hours, about how many times did you use an alcohol-based hand sanitizer spray, gel, or wipes?” Based on a prior study examining handwashing effectiveness at preventing seasonal coronavirus [22], we categorized handwashing and hand sanitizer use as 0-5 times per day (the prior study referent group), 6-10 times per day (the prior study effective intervention group), and ≥11 times per day (the prior study intervention group that was not effective). For dichotomous analyses, those in the categories of 6-10 and ≥11 times per day were defined as frequently practicing hand hygiene.

Independent analysis measures included standard demographic characteristics of gender, race/ethnicity, age group, US Census region, ZIP code–based urbanicity, highest education, annual household income, and current health insurance. For those working, the job type was collected using 2018 US Bureau of Labor Statistics major job categories [23]. Some types of jobs, such as food service, education, health care, retail, and transportation services, may have had additional recommendations about mask wearing and hand hygiene [24]. These job types were differentiated from others in the analyses. For those who leave home for work, we assessed whether their jobs were completely indoors or outdoors/mix/other.

Analyses

We developed sample weights to represent noninstitutionalized, housed adults (aged ≥18 years, US population). In brief, hierarchical hot deck imputation was performed to ensure no participants were missing data for key variables needed for weighting, such as gender, education, race, ethnicity, and marital status; each had <3% missingness [25]. Design weights, adjusted with classification and regression tree (CART) analysis for a differential nonresponse, were developed to facilitate population inference. A raking procedure aligned weighted distributions to the observed distributions from the Census along the lines including age, race-ethnicity, education, and income [26]. To address outlier weights, those at the 99th percentile of each distribution side were trimmed.

Using the sampling weights, we estimated the weighted prevalence and 95% modified Wilson score confidence limits for (1) consistent mask wearing, (2) social distancing, (3) handwashing, and (4) hand sanitizer use. Prevalence estimates were descriptively summarized by sociodemographic factors (race, sex, age, region, urbanicity, highest level of education, annual income, health insurance, job type), personal behaviors (leaving home for work), knowledge of mitigation behaviors, and month of sampling. To identify significant differences in the prevalence of mitigation behaviors by sociodemographic factors, prevalence ratios (PRs) and corresponding 95% CIs were estimated using weighted logistic regression procedures. All prevalence analyses were performed using SAS v9.4 (SAS Institute) and SUDAAN (RTI International).

People may follow all public health recommendations for mitigation practices similarly, or there may be individual variations in mitigation practices. This information may be useful for understanding how different groups respond to multicomponent prevention messages. We therefore conducted latent class analysis (LCA) with polytomous outcomes variables to classify participants based on their responses to the 4 primary dependent measures (mask wearing, social distancing, handwashing, and hand sanitizer use). Each measure was included as a single item. Considering we did not know the number of classes represented by these data, we fit several models with a different number (1-6) of classes. All models were fit using the polCA package in R v4.1.0 (R Foundation for Statistical Computing), which uses maximum likelihood parameter estimation with robust SEs. Each model was estimated with 30 different sets of starting values and allowed a maximum of 3000 iterations for convergence. To select the final model, we compared fit statistics (ie, Bayesian information criteria [BIC], Akaike information criteria [AIC], adjusted BIC) and accuracy statistics (eg, entropy) [27]. Each participant was classified into a latent class (ie, mitigation) group by the largest posterior probability for belonging to each class indicated by the final model. We estimated the weighted prevalence of each latent class group in the entire sample and by sociodemographic characteristics. Finally, as a minimal internal validity check, we examined whether class membership was associated with answering the following statements with “true”: “Consistently wearing a face mask will provide me with 95% or better protection from getting infected with the new coronavirus” and “It is not necessary for children and young adults to take measures to prevent infection by the COVID-19 virus.” PRs and corresponding 95% CIs were estimated using weighted logistic regression procedures in SUDAAN to identify any differences by sociodemographic characteristics.

Results

Participants

A total of 4654 participants completed baseline enrollment procedures and were included in this study (Table 1). These participants represented 242,875,582 US adults in 2020. Most were female, were non-Hispanic White, aged 55 years or older, lived in the South, lived in metropolitan areas, had at least a bachelor’s degree, had an income of US $50,000-$99,000, and were privately insured. The highest monthly enrollment occurred in November 2020. Among the available response options in this study for job types, most respondents worked in health care and social services; however, most had other job types not available for selection in the study. Most of those whose jobs required leaving home worked completely indoors.

Table 1.

Prevalence of consistent mask wearing among a household probability sample of 4654 US adults (August-December 2020).

Characteristics Unweighted Weighted


Prevalence, n/N (%) Prevalence, n/N (%); 95% CI PRa (95% CI)
Overall 3351/4654 (72.0) 172,749,029/242,875,582 (71.1); 68.8-73.3 N/Ab
Sex

Male 1315/1927 (68.2) 76,820,491/115,613,214 (66.4); 62.7-70.0 Reference (N/A)

Female 2036/2727 (74.7) 95,928,538/127,262,368 (75.4); 72.6-77.9 1.15 (1.08-1.22)
Race/ethnicity

Hispanic 475/607 (78.3) 31,465,187/40,277,007 (78.1); 72.1-83.1 1.15 (1.07-1.25)

Non-Hispanic Black 540/683 (79.1) 21,964,396/27,643,982 (79.5); 71.2-85.8 1.16 (1.05-1.28)

Non-Hispanic White 2113/3063 (69.0) 104,453,228/153,881,404 (67.9); 65.1-70.5 Reference (N/A)

Other 223/301 (74.1) 14,866,219/21,073,189 (70.5); 61.9-77.9 1.06 (0.94-1.18)
Age (years)

18-34 699/1013 (69.0) 45,256,658/67,946,989 (66.6); 61.5-71.3 0.83 (0.77-0.91)

35-44 528/777 (68.0) 26,925,908/40,347,844 (66.7); 60.9-72.1 0.85 (0.77-0.93)

45-54 528/765 (69.0) 27,180,059/39,524,761 (68.8); 63.0-74.0 0.87 (0.80-0.95)

55-64 685/926 (74.0) 30,521,571/41,638,646 (73.3); 68.2-77.9 0.93 (0.87-1.01)

≥65 911/1173 (77.7) 42,864,834/53,417,341 (80.2); 76.4-83.6 Reference (N/A)
US Census region

Northeast 359/476 (75.4) 32,878,801/42,937,799 (76.6); 71.2-81.2 1.05 (0.96-1.14)

Midwest 381/591 (64.5) 31,994,649/51,141,237 (62.6); 57.1-67.8 0.86 (0.78-0.96)

South 1607/2275 (70.6) 65,323,037/90,171,242 (72.4); 68.7-75.9 0.99 (0.92-1.07)

West 1004/1312 (76.5) 42,552,543/58,625,304 (72.6); 68.1-76.6 Reference (N/A)
Urbanicity

Micropolitan/small town/rural 282/468 (60.3) 17,718,426/32,292,975 (54.9); 47.8-61.8 Reference (N/A)

Metropolitan 3069/4186 (73.3) 155,030,603/210,582,607 (73.6); 71.2-75.9 1.30 (1.14-1.48)
Education

High school/General Educational Development (GED) or less 482/698 (69.1) 60,604,634/85,965,483 (70.5); 65.4-75.1 1.01 (0.93-1.10)

Some college/associate’s degree 992/1409 (70.4) 48,068,329/69,226,861 (69.4); 65.6-73.0 0.98 (0.91-1.06)

Bachelor’s degree 1036/1430 (72.4) 39,476,277/55,756,279 (70.8); 67.0-74.3 Reference (N/A)

Graduate degree 841/1117 (75.3) 24,599,790/31,926,958 (77.1); 73.3-80.4 1.07 (1.00-1.15)
Annual income (US $)

0-24,999 512/721 (71.0) 21,167,549/29,566,723 (71.6); 65.2-77.2 1.04 (0.94-1.14)

25,000-49,999 659/916 (71.9) 28,730,742/41,443,877 (69.3); 63.3-74.7 0.99 (0.89-1.09)

50,000-99,999 1054/1445 (72.9) 51,366,352/73,211,031 (70.2); 65.8-74.2 Reference (N/A)

100,000-199,999 817/1125 (72.6) 48,935,593/67,795,060 (72.2); 67.8-76.2 1.02 (0.94-1.10)

≥200,000 309/447 (69.1) 22,548,792/30,858,891 (73.1); 66.8-78.5 1.03 (0.93-1.13)
Health insurance

No health insurance 173/263 (65.8) 8,652,878/13,358,208 (64.8); 53.5-74.7 Reference (N/A)

Medicare/Medicaid/other 992/1352 (73.4) 50,432,470/66,230,875 (76.1); 72.2-79.7 1.20 (1.01-1.42

Private insurance/parent’s plan 1958/2734 (71.6) 101,517,515/147,299,448 (68.9); 65.9-71.8 1.08 (0.91-1.28)

Do not know 228/305 (74.8) 12,146,167/15,987,051 (76.0); 67.7-82.7 1.18 (0.98-1.44)
Month of sample collection

August 830/1195 (69.5) 68,382,130/98,937,128 (69.1); 65.3-72.6 Reference (N/A)

September 301/406 (74.1) 23,861,095/33,460,432 (71.3); 64.3-77.4 1.03 (0.93-1.15)

October 596/812 (73.4) 40,495,885/55,101,083 (73.5); 68.7-77.8 1.06 (0.98-1.14)

November 1569/2165 (72.5) 39,080,513/53,835,755 (72.6); 68.1-76.6 1.06 (0.98-1.14)

December 55/76 (72.4) 929,406/1,541,184 (60.3); 35.2-81.0 0.99 (0.68-1.44)
Job typec

Accommodation and food services 61/86 (70.9) 3,947,552/6,572,047 (60.1); 43.8-74.4 0.87 (0.66-1.14)

Educational services 261/334 (78.1) 8,107,735/10,277,744 (78.9); 71.9-84.5 1.12 (1.02-1.23)

Health care and social assistance 308/433 (71.1) 15,317,980/21,216,123 (72.2); 65.8-77.8 1.03 (0.93-1.14)

Retail trade 91/131 (69.5) 6,651,265/11,147,959 (59.7); 45.8-72.2 0.89 (0.71-1.12)

Transportation and warehousing 70/104 (67.3) 2,959,476/6,340,795 (46.7); 31.6-62.4 0.67 (0.47-0.96)

Other 1118/1606 (69.6) 60,001,477/86,625,204 (69.3); 65.3-72.9 Reference (N/A)
Work locationd

Completely indoors 735/1032 (71.2) 38,924,489/57,197,182 (68.1); 63.2-72.6 1.18 (1.03-1.35)

Completely outdoor/mixture/other 362/571 (63.4) 18,622,285/32,017,239 (58.2); 51.1-64.9 Reference (N/A)
Open in a new tab

aPR: prevalence ratio.

bN/A: not applicable.

cAmong those who were employed.

dAmong those who were employed and left home for work.

Mask Wearing

The estimated national period prevalence of consistently wearing a mask from August through December 2020 was 71.1% (95% CI 68.8-73.3; Table 1). Consistent mask wearing was significantly more prevalent among those who were female; were Hispanic or non-Hispanic Black; lived in a metropolitan area; had a graduate degree, were insured through Medicare, Medicaid, or other public health insurance; worked in educational services; or worked completely indoors (among those who were working from somewhere other than at home). Consistent mask wearing was significantly less prevalent among those who were less than 65 years old, lived in the Midwest (compared to the West), and worked in transportation or warehouse services.

Social Distancing

The estimated national prevalence of consistently practicing social distancing was 42.9% (95% CI 40.5-45.3; Table 2). Consistent social distancing was significantly more prevalent among those who were female, were Hispanic or non-Hispanic Black, lived in the South (compared to the West), had a graduate degree or some college education, or had an annual income of less than US $25,000. Consistent social distancing was significantly less prevalent among those aged 18-34 years (compared to ≥65 years) or lived in the Midwest (compared to the West).

Table 2.

Prevalence of consistent social distancing among a household probability sample of 4654 US adults (August-December 2020).

Characteristics Unweighted Weighted


Prevalence, n/N (%) Prevalence, n/N (%); 95% CI PRa (95% CI)
Overall 2138/4654 (45.9) 104,253,682/242,875,582 (42.9); 40.5-45.3 N/Ab
Sex

Male 833/1927 (43.2) 46,015,009/115,613,214 (39.8); 36.2-43.5 Reference (N/A)

Female 1305/2727 (47.9) 58,238,673/127,262,368 (45.8); 42.6-48.9 1.15 (1.03-1.29)
Race/ethnicity

Hispanic 274/607 (45.1) 18,911,041/40,277,007 (47.0); 40.5-53.5 1.19 (1.02-1.39)

Non-Hispanic Black 441/683 (64.6) 16,316,928/27,643,982 (59.0); 50.3-67.2 1.49 (1.27-1.76)

Non-Hispanic White 1298/3063 (42.4) 60,824,958/153,881,404 (39.5); 36.8-42.3 Reference (N/A)

Other 125/301 (41.5) 8,200,755/21,073,189 (38.9); 31.0-47.4 0.98 (0.78-1.23)
Age (years)

18-34 351/1013 (34.6) 21,618,778/67,946,989 (31.8); 27.2-36.8 0.67 (0.56-0.81)

35-44 314/777 (40.4) 17,333,281/40,347,844 (43.0); 37.3-48.8 0.91 (0.77-1.08)

45-54 346/765 (45.2) 17,811,654/39,524,761 (45.1); 39.3-51.0 0.95 (0.81-1.13)

55-64 499/926 (53.9) 22,270,261/41,638,646 (53.5); 48.0-58.9 1.13 (0.98-1.31)

≥65 628/1173 (53.5) 25,219,708/53,417,341 (47.2); 42.4-52.1 Reference (N/A)
US Census region

Northeast 201/476 (42.2) 18,423,748/42,937,799 (42.9); 37.1-48.9 1.03 (0.86-1.22)

Midwest 233/591 (39.4) 17,432,852/51,141,237 (34.1); 29.4-39.2 0.81 (0.68-0.97)

South 1107/2275 (48.7) 43,864,240/90,171,242 (48.6); 44.5-52.8 1.16 (1.01-1.33)

West 597/1312 (45.5) 24,532,842/58,625,304 (41.8); 37.5-46.3 Reference (N/A)
Urbanicity

Micropolitan/small town/rural 219/468 (46.8) 13,688,195/32,292,975 (42.4); 35.7-49.4 Reference (N/A)

Metropolitan 1919/4186 (45.8) 90,565,487/210,582,607 (43.0); 40.5-45.6 1.01 (0.85-1.20)
Education

High school/General Educational Development (GED) or less 351/698 (50.3) 37,216,103/85,965,483 (43.3); 38.2-48.5 1.13 (0.97-1.32)

Some college/associate’s degree 641/1409 (45.5) 30,576,917/69,226,861 (44.2); 40.1-48.3 1.16 (1.01-1.32)

Bachelor’s degree 605/1430 (42.3) 21,335,935/55,756,279 (38.3); 34.6-42.1 Reference (N/A)

Graduate degree 541/1117 (48.4) 15,124,727/31,926,958 (47.4); 43.0-51.8 1.23 (1.08-1.41)
Annual income (US $)

0-24,999 380/721 (52.7) 15,386,978/29,566,723 (52.0); 45.4-58.6 1.22 (1.03-1.43)

25,000-49,999 418/916 (45.6) 17,864,754/41,443,877 (43.1); 37.3-49.1 1.01 (0.85-1.20)

50,000-99,999 671/1445 (46.4) 31,156,215/73,211,031 (42.6); 38.3-47.0 Reference (N/A)

100,000-199,999 484/1125 (43.0) 26,369,580/67,795,060 (38.9); 34.5-43.5 0.91 (0.78-1.06)

≥200,000 185/447 (41.4) 13,476,156/30,858,891 (43.7); 37.1-50.5 1.02 (0.85-1.23)
Health insurance

No health insurance 118/263 (44.9) 6,131,940/13,358,208 (45.9); 34.9-57.3 Reference (N/A)

Medicare/Medicaid/other 727/1352 (53.8) 33,026,689/66,230,875 (49.9); 45.2-54.5 1.08 (0.83-1.42)

Private insurance/parent’s plan 1155/2734 (42.2) 58,149,331/147,299,448 (39.5); 36.5-42.5 0.86 (0.66-1.11)

Do not know 138/305 (45.2) 6,945,721/15,987,051 (43.4); 34.3-53.0 0.95 (0.68-1.33)
Month of sample collection

August 527/1195 (44.1) 43,165,763/98,937,128 (43.6); 39.8-47.6 Reference (N/A)

September 196/406 (48.3) 15,505,163/33,460,432 (46.3); 39.5-53.3 1.06 (0.89-1.26)

October 348/812 (42.9) 21,917,341/55,101,083 (39.8); 34.9-44.9 0.92 (0.78-1.07)

November 1028/2165 (47.5) 23,238,793/53,835,755 (43.2); 38.7-47.7 0.99 (0.86-1.14)

December 39/76 (51.3) 426,622/1,541,184 (27.7); 14.1-47.2 0.64 (0.33-1.23)
Job typec

Accommodation and food services 31/86 (36.0) 1,889,223/6,572,047.14 (28.7); 17.2-43.9 0.72 (0.43-1.18)

Educational services 148/334 (44.3) 4,010,043/10,277,744.49 (39.0); 31.1-47.6 0.97 (0.77-1.24)

Health care and social assistance 171/433 (39.5) 7,690,760/21,216,123.32 (36.2); 30.0-43.0 0.91 (0.74-1.12)

Retail trade 57/131 (43.5) 5,088,591/11,147,959.41 (45.6); 33.1-58.8 1.14 (0.83-1.56)

Transportation and warehousing 35/104 (33.7) 1,687,619/6,340,794.69 (26.6); 16.1-40.7 0.66 (0.41-1.09)

Other 663/1606 (41.3) 34,585,460/86,625,204.41 (39.9); 36.1-43.9 Reference (N/A)
Work locationd

Completely indoors 384/1032 (37.2) 19,740,169/57,197,182 (34.5); 30.2-39.1 0.96 (0.77-1.21)

Completely outdoor/mixture/other 210/571 (36.8) 11,466,330/32,017,239 (35.8); 29.4-42.7 Reference (N/A)
Open in a new tab

aPR: prevalence ratio.

bN/A: not applicable.

cAmong those who were employed.

dAmong those who were employed and left home for work.

Handwashing

Among the 4090 participants who were administered the hand hygiene questions, the average number of times the participants washed hands in the past 24 hours was 8.8 (SE 0.3). The estimated national prevalence of individuals frequently washing hands was 55.0% (95% CI 52.3-57.7; Table 3). Frequent handwashing was significantly more prevalent among those who were female, were Hispanic or non-Hispanic Black, were aged 35-54 years (compared to ≥65 years), were enrolled in November 2020 (compared to August 2020), or worked in health care and social assistance services.

Table 3.

Prevalence of frequent handwashing among a household probability sample of 4090 US adults (August-December 2020).

Characteristics Unweighted Weighted


Prevalence, n/N (%) Prevalence, n/N (%); 95% CI PRa (95% CI)
Overall 2226/4090 (54.4) 107,258,747/195,041,917 (55.0); 52.3-57.7 N/Ab
Sex

Male 746/1682 (44.4) 40,507,668/92,525,526 (43.8); 39.7-47.9 Reference (N/A)

Female 1480/2408 (61.5) 66,751,079/102,516,391 (65.1); 61.8-68.3 1.48 (1.34-1.64)
Race/ethnicity

Hispanic 341/584 (58.4) 21,843,430/36,294,202 (60.2); 53.5-66.5 1.17 (1.04-1.32)

Non-Hispanic Black 376/661 (56.9) 14,430,982/23,137,584 (62.4); 53.6-70.4 1.17 (1.01-1.36)

Non-Hispanic White 1367/2578 (53.0) 62,577,192/119,543,448 (52.3); 49.1-55.6 Reference (N/A)

Other 142/267 (53.2) 8,407,143/16,066,683 (52.3); 43.1-61.4 1.02 (0.85-1.22)
Age (years)

18-34 479/900 (53.2) 29,369,641/54,991,956 (53.4); 47.7-59.0 1.05 (0.90-1.21)

35-44 405/685 (59.1) 19,647,980/32,573,737 (60.3); 54.0-66.3 1.23 (1.07-1.41)

45-54 379/656 (57.8) 17,923,525/30,308,444 (59.1); 52.4-65.5 1.18 (1.01-1.37)

55-64 442/825 (53.6) 18,533,469/34,713,815 (53.4); 47.4-59.3 1.07 (0.92-1.24)

≥65 521/1024 (50.9) 21,784,132/42,453,965 (51.3); 46.0-56.6 Reference (N/A)
US Census region

Northeast 159/301 (52.8) 13,690,592/26,689,317 (51.3); 43.8-58.8 0.98 (0.83-1.15)

Midwest 272/462 (58.9) 23,078,467/40,022,544 (57.7); 51.6-63.5 1.08 (0.95-1.22)

South 1081/2018 (53.6) 38,443,937/69,829,637 (55.1); 50.4-59.7 1.02 (0.91-1.14)

West 714/1309 (54.5) 32,045,751/58,500,420 (54.8); 50.3-59.2 Reference (N/A)
Urbanicity

Micropolitan/small town/rural 213/403 (52.9) 13,506,913/26,235,378 (51.5); 43.7-59.2 Reference (N/A)

Metropolitan 2013/3687 (54.6) 93,751,834/168,806,540 (55.5); 52.7-58.4 1.06 (0.91-1.24)
Education

High school/General Educational Development (GED) or less 309/609 (50.7) 36,508,095/69,755,426 (52.3); 46.5-58.1 1.00 (0.88-1.13)

Some college/associate’s degree 729/1268 (57.5) 33,497,775/56,483,039 (59.3); 54.9-63.6 1.08 (0.97-1.20)

Bachelor’s degree 660/1256 (52.5) 24,259,383/43,783,023 (55.4); 51.2-59.5 Reference (N/A)

Graduate degree 528/957 (55.2) 12,993,495/25,020,429 (51.9); 47.0-56.9 0.93 (0.82-1.04)
Annual income (US $)

0-24,999 353/640 (55.2) 12,398,320/22,961,654 (54.0); 46.8-61.1 1.03 (0.88-1.20)

25,000-49,999 428/811 (52.8) 18,172,778/33,333,054 (54.5); 47.9-60.9 1.05 (0.91-1.21)

50,000-99,999 720/1286 (56.0) 32,722,037/61,651,585 (53.1); 48.2-57.9 Reference (N/A)

100,000-199,999 519/966 (53.7) 29,925,499/52,932,785 (56.5); 51.3-61.6 1.04 (0.92-1.18)

≥200,000 206/387 (53.2) 14,040,112/24,162,839 (58.1); 50.8-65.0 1.07 (0.92-1.24)
Health insurance

No health insurance 125/246 (50.8) 5,896,607/11,801,478 (50.0); 38.0-61.9 Reference (N/A)

Medicare/Medicaid/other 616/1191 (51.7) 26,735,424/52,283,277 (51.1); 46.0-56.2 1.04 (0.81-1.35)

Private insurance/parent’s plan 1348/2393 (56.3) 68,204,026/118,431,180 (57.6); 54.2-60.9 1.14 (0.89-1.46)

Do not know 137/260 (52.7) 6,422,690/12,525,982 (51.3); 40.6-61.8 1.05 (0.76-1.45)
Month of sample collection

August 352/655 (53.7) 26,438,562/52,551,995 (50.3); 45.0-55.6 Reference (N/A)

September 224/392 (57.1) 17,794,291/32,683,426 (54.4); 47.3-61.4 1.06 (0.91-1.25)

October 429/806 (53.2) 30,795,988/54,773,380 (56.2); 51.0-61.3 1.07 (0.93-1.22)

November 1176/2161 (54.4) 31,727,178/53,491,933 (59.3); 54.8-63.7 1.15 (1.02-1.31)

December 45/76 (59.2) 502,728/1,541,184 (32.6); 16.4-54.4 0.71 (0.38-1.31)
Job typec

Accommodation and food services 53/79 (67.1) 3,700,939/5,866,155 (63.1); 45.6-77.7 1.19 (0.90-1.57)

Educational services 171/291 (58.8) 4,875,979/7,963,246 (61.2); 51.8-69.9 1.14 (0.96-1.35)

Health care and social assistance 251/384 (65.4) 12,160,332/17,500,465 (69.5); 62.5-75.7 1.30 (1.14-1.47)

Retail trade 67/106 (63.2) 4,897,239/8,228,603 (59.5); 44.0-73.3 1.23 (0.97-1.55)

Transportation and warehousing 58/100 (58.0) 3,279,732/5,854,707 (56.0); 39.4-71.4 1.05 (0.77-1.44)

Other 726/1412 (51.4) 37,061,432/70,086,074 (52.9); 48.4-57.3 Reference (N/A)
Work locationd

Completely indoors 568/907 (62.6) 29,785,987/47,435,209 (62.8); 57.4-67.8 1.11 (0.96-1.29)

Completely outdoor/mixture/other 277/507 (54.6) 14,909,587/26,354,333 (56.6); 49.0-63.9 Reference (N/A)
Open in a new tab

aPR: prevalence ratio.

bN/A: not applicable.

cAmong those who were employed.

dAmong those who were employed and left home for work.

Hand Sanitizer Use

Among the 4090 participants who were administered the hand hygiene questions, the average number of times the participants used a hand sanitizer in the past 24 hours was 4.99 (SE 0.2). The estimated national prevalence of frequently using a hand sanitizer was 21.5% (95% CI 19.4-23.8; Table 4). Frequent use of a hand sanitizer was significantly more prevalent among those who were female, Hispanic or non-Hispanic Black, less than 65 years of age, lived in the South (compared to the West), had an annual income of less than US $25,000, were enrolled in September or November 2020 (compared to August 2020), or worked in accommodation, food services, health care, social assistance, retail trade, or transportation/warehouse services. Frequent use of a hand sanitizer was significantly less prevalent among those who had an annual income of US $100,000-$199,000 or were insured through Medicare, Medicaid, or other public health insurance (compared to those uninsured).

Table 4.

Prevalence of frequent hand sanitizer use among a household probability sample of 4090 US adults (August-December 2020).

Characteristics Unweighted Weighted


Prevalence, n/N (%) Prevalence, n/N (%); 95% CI PRa (95% CI)
Overall 846/4090 (20.7) 41,964,720/195,041,917 (21.5); 19.4-23.8 N/Ab
Sex

Male 293/1682 (17.4) 17,369,555/92,525,526 (18.8); 15.7-22.3 Reference (N/A)

Female 553/2408 (23.0) 24,595,165/102,516,391 (24.0); 21.1-27.1 1.26 (1.02-1.56)
Race/ethnicity

Hispanic 176/584 (30.1) 11,525,753/36,294,202 (31.8); 25.8-38.4 1.92 (1.51-2.44)

Non-Hispanic Black 197/661 (29.8) 7,287,691/23,137,584 (31.5); 23.8-40.3 1.84 (1.37-2.48)

Non-Hispanic White 422/2578 (16.4) 20,054,567/119,543,448 (16.8); 14.6-19.2 Reference (N/A)

Other 51/267 (19.1) 3,096,709/16,066,683 (19.3); 13.5-26.8 1.16 (0.80-1.68)
Age (years)

18-34 233/900 (25.9) 14,220,072/54,991,956 (25.9); 21.2-31.1 2.14 (1.48-3.11)

35-44 177/685 (25.8) 9,327,426/32,573,737 (28.6); 23.4-34.5 2.48 (1.71-3.60)

45-54 150/656 (22.9) 6,848,252/30,308,444 (22.6); 17.5-28.6 1.92 (1.28-2.88)

55-64 163/825 (19.8) 6,460,726/34,713,815 (18.6); 14.6-23.4 1.62 (1.09-2.41)

≥65 123/1024 (12.0) 5,108,245/42,453,965 (12.0); 8.7-16.4 Reference (N/A)
US Census region

Northeast 59/301 (19.6) 5,660,463/26,689,317 (21.2); 15.8-27.9 1.12 (0.80-1.57)

Midwest 73/462 (15.8) 6,519,188/40,022,544 (16.3); 12.5-20.9 0.83 (0.60-1.13)

South 478/2018 (23.7) 18,042,211/69,829,637 (25.8); 21.9-30.2 1.31 (1.03-1.68)

West 236/1309 (18.0) 11,742,858/58,500,420 (20.1); 16.6-24.0 Reference (N/A)
Urbanicity

Micropolitan/small town/rural 81/403 (20.1) 4,709,547/26,235,378 (18.0); 13.0-24.3 Reference (N/A)

Metropolitan 765/3687 (20.7) 37,255,173/168,806,540 (22.1); 19.7-24.6 1.21 (0.87-1.69)
Education

High school/General Educational Development (GED) or less 141/609 (23.2) 16,518,098/69,755,426 (23.7); 19.2-28.9 1.69 (1.27-2.25)

Some college/associate’s degree 309/1268 (24.4) 13,288,148/56,483,039 (23.5); 20.1-27.4 1.60 (1.24-2.06)

Bachelor’s degree 210/1256 (16.7) 6,499,265/43,783,023 (14.8); 12.1-18.0 Reference (N/A)

Graduate degree 186/957 (19.4) 5,659,209/25,020,429 (22.6); 18.4-27.5 1.50 (1.13-1.99)
Annual income (US $)

0-24,999 156/640 (24.4) 6,956,140/22,961,654 (30.3); 23.8-37.6 1.36 (1.01-1.81)

25,000-49,999 188/811 (23.2) 7,970,726/33,333,054 (23.9); 18.8-29.9 1.07 (0.79-1.43)

50,000-99,999 267/1286 (20.8) 13,913,036/61,651,585 (22.6); 18.6-27.1 Reference (N/A)

100,000-199,999 179/966 (18.5) 8,941,815/52,932,785 (16.9); 13.6-20.8 0.73 (0.55-0.96)

≥200,000 56/387 (14.5) 4,183,004/24,162,839 (17.3); 12.3-23.8 0.75 (0.51-1.09)
Health insurance

No health insurance 69/246 (28.0) 3,625,449/11,801,478 (30.7); 20.6-43.1 Reference (N/A)

Medicare/Medicaid/other 196/1191 (16.5) 9,517,303/52,283,277 (18.2); 14.4-22.8 0.62 (0.40-0.97)

Private insurance/parent’s plan 510/2393 (21.3) 25,573,342/118,431,180 (21.6); 18.9-24.5 0.71 (0.48-1.05)

Do not know 71/260 (27.3) 3,248,626/12,525,982 (25.9); 18.2-35.5 0.88 (0.53-1.46)
Month of sample collection

August 101/655 (15.4) 9,075,148/52,551,995 (17.3); 13.6-21.7 Reference (N/A)

September 106/392 (27.0) 8,760,306/32,683,426 (26.8); 21.0-33.5 1.51 (1.09-2.10)

October 144/806 (17.9) 11,226,992/54,773,380 (20.5); 16.6-25.0 1.12 (0.82-1.53)

November 479/2161 (22.2) 12,787,219/53,491,933 (23.9); 20.1-28.2 1.34 (1.01-1.79)

December 16/76 (21.1) 115,054/1,541,184 (7.5); 2.6-19.6 0.46 (0.15-1.42)
Job typec

Accommodation and food services 26/79 (32.9) 2,105,92/5,866,155 (35.9); 21.9-52.8 1.86 (1.14-3.06)

Educational services 72/291 (24.7) 1,926,548/7,963,246 (24.2); 17.5-32.4 1.24 (0.86-1.78)

Health care and social assistance 164/384 (42.7) 7,894,448/17,500,465 (45.1); 37.9-52.6 2.35 (1.84-3.00)

Retail trade 37/106 (34.9) 3,108,150/8,228,603 (37.8); 24.4-53.4 2.15 (1.40-3.29)

Transportation and warehousing 32/100 (32.0) 2,187,560/5,854,707 (37.4); 22.7-54.8 1.94 (1.18-3.18)

Other 262/1412 (18.6) 13,321,475/70,086,074 (19.0); 15.7-22.8 Reference (N/A)
Work locationd

Completely indoors 297/907 (32.7) 16,448,119/47,435,209 (34.7); 29.8-39.9 1.14 (0.87-1.49)

Completely outdoor/mixture/other 143/507 (28.2) 8,086,420/26,354,333 (30.7); 24.2-38.1 Reference (N/A)
Open in a new tab

aPR: prevalence ratio.

bN/A: not applicable.

cAmong those who were employed.

dAmong those who were employed and left home for work.

Mitigation Classifications

The final classification model identified 3 latent classes: (1) optimal mitigation, (2) optimal mitigation with additional hand hygiene, and (3) lowest mitigation. Optimal mitigation was consistent mask wearing, consistent social distancing, and handwashing or hand sanitizer use 6-10 times per day. Optimal mitigation with additional hand hygiene was consistent mask wearing, consistent social distancing, and handwashing or hand sanitizer use >11 times per day. The lowest mitigation was inconsistent mask wearing, inconsistent social distancing, and handwashing or hand sanitizer use 0-5 times per day. There were no classes that had suboptimal use of only some mitigation strategies but optimal use of others. All participants were categorized into these classes. Two-thirds (n=2656, 67%) practiced optimal mitigation by consistently wearing a mask, consistently following social distancing, and frequently washing their hands or using a hand sanitizer (Tables 5-7). Furthermore, 1 in 5 (n=771, 20.6%) practiced the lowest mitigation by inconsistently or infrequently engaging in all mitigation practices. The final class made up the remainder (n=463, 12.4%) who consistently wore masks and maintained social distance but had the highest frequency of handwashing or sanitizer use (>11 times per day). Compared to optimal mitigation practices, the likelihood of being in the lowest-mitigation class was significantly greater among those who were male, less than 65 years of age, lived in the Midwest (compared to the West), lived outside a metropolitan area, had no health insurance (compared to Medicare, Medicaid, or other public insurance), worked in transportation or warehouse services, or worked somewhere other than completely indoors (Table 8). Compared to just the optimal-mitigation class, the likelihood of being in the class with optimal mask wearing and social distancing but with additional handwashing or sanitizer use was significantly greater among those who were Hispanic or non-Hispanic Black, were less than 65 years of age, had less than a bachelor’s degree, or worked in any of the selected job types (compared to other jobs).

Table 5.

“Optimal mitigation” latent class of combined strategies to prevent COVID-19 among a household probability sample of 4090 US adults (August-December 2020).

Characteristics Total sample Optimal mitigation (consistent masking and social distancing, hand hygiene 6-10 times/day)


Unweighted, N Weighted, N Unweighted prevalence, n (%) Weighted prevalence, n (%)
Overall 3863 183,171,244 2656 (68.8) 122,800,910 (67.0)
Sex

Male 1603 86,348,193 1102 (68.7) 56,182,229 (65.1)

Female 2260 96,823,051 1554 (68.8) 66,618,681 (68.8)
Race/ethnicity

Hispanic 551 33,539,313 364 (66.1) 21,961,242 (65.5)

Non-Hispanic Black 607 22,219,194 423 (69.7) 15,006,373 (67.5)

Non-Hispanic White 2454 112,449,529 1678 (68.4) 74,776,252 (66.5)

Other 251 14,963,209 191 (76.1) 11,057,042 (73.9)
Age (years)

18-34 869 52,755,525 538 (61.9) 32,268,979 (61.2)

35-44 643 29,840,688 405 (63.0) 17,937,534 (60.1)

45-54 608 28,183,232 400 (65.8) 17,959,527 (63.7)

55-64 774 31,700,429 542 (70.0) 21,137,563 (66.7)

≥65 969 40,691,370 771 (79.6) 33,497,307 (82.3)
US Census region

Northeast 279 24,075,803 203 (72.8) 17,676,409 (73.4)

Midwest 438 37,524,032 285 (65.1) 23,288,505 (62.1)

South 1896 65,519,953 1249 (65.9) 43,782,348 (66.8)

West 1250 56,051,456 919 (73.5) 38,053,648 (67.9)
Urbanicity

Micropolitan/small town/rural 374 24,397,071 231 (61.8) 14,006,081 (57.4)

Metropolitan 3489 158,774,173 2425 (69.5) 108,794,829 (68.5)
Education

High school/General Educational Development (GED) or less 543 63,033,498 350 (64.5) 39,876,092 (63.3)

Some college/associate’s degree 1189 53,702,228 766 (64.4) 34,863,092 (64.9)

Bachelor’s degree 1203 42,013,058 862 (71.7) 29,934,515 (71.3)

Graduate degree 928 24,422,460 678 (73.1) 18,127,211 (74.2)
Annual income (US $)

0-24,999 586 21,039,489 396 (67.6) 13,895,746 (66.0)

25,000-49,999 756 30,682,885 504 (66.7) 18,888,597 (61.6)

50,000-99,999 1220 57,414,158 841 (68.9) 37,446,727 (65.2)

100,000-199,999 934 50,966,442 663 (71.0) 35,542,740 (69.7)

≥200,000 367 23,068,271 252 (68.7) 17,027,100 (73.8)
Health insurance

No health insurance 230 11,173,450 138 (60.0) 6,510,927 (58.3)

Medicare/Medicaid/other 1101 47,572,527 824 (74.8) 35,945,737 (75.6)

Private insurance/parent’s plan 2294 112,869,879 1535 (66.9) 72,421,450 (64.2)

Do not know 238 11,555,388 159 (66.8) 7,922,797 (68.6)
Month of sample collection

August 619 48,004,288 430 (69.5) 32,876,252 (68.5)

September 372 30,679,522 242 (65.1) 18,957,076 (61.8)

October 775 52,803,927 557 (71.9) 36,692,789 (69.5)

November 2026 50,370,899 1376 (67.9) 33,317,935 (66.1)

December 71 1,312,608 51 (71.8) 956,860 (72.9)
Job typea

Accommodation and food services 77 5,669,023 44 (57.1) 3,208,728 (56.6)

Educational services 283 7,801,317 195 (68.9) 5,538,379 (71.0)

Health care and social assistance 363 16,769,318 193 (53.2) 8,084,708 (48.2)

Retail trade 98 7,256,895 57 (58.2) 3,524,372 (48.6)

Transportation and warehousing 93 5,661,875 56 (60.2) 2,458,090 (43.4)

Other 1354 66,741,897 925 (68.3) 44,833,174 (67.2)
Work locationb

Completely indoors 868 44,926,729 519 (59.8) 25,143,068 (56.0)

Completely outdoor/mixture/other 485 24,905,513 276 (56.9) 11,660,499 (46.8)
Open in a new tab

aAmong those who were employed.

bAmong those who were employed and left home for work.

Table 7.

“Lowest mitigation” latent class of combined strategies to prevent COVID-19 among a household probability sample of 4090 US adults (August-December 2020).

Characteristics Total sample Lowest mitigation (inconsistent masking and social distancing, hand hygiene 0-5 times/day)


Unweighted, N Weighted, N Unweighted prevalence, n (%) Weighted prevalence, n (%)
Overall 3863 183,171,244 771 (20.0) 37,822,170 (20.6)
Sex

Male 1603 86,348,193 383 (23.9) 21,741,804 (25.2)

Female 2260 96,823,051 388 (17.2) 16,080,366 (16.6)
Race/ethnicity

Hispanic 551 33,539,313 84 (15.2) 5,249,241 (15.7)

Non-Hispanic Black 607 22,219,194 79 (13.0) 2,769,462 (12.5)

Non-Hispanic White 2454 112,449,529 571 (23.3) 27,606,210 (24.5)

Other 251 14,963,209 37 (14.7) 2,197,256 (14.7)
Age (years)

18-34 869 52,755,525 210 (24.2) 12,799,555 (24.3)

35-44 643 29,840,688 149 (23.2) 6,910,373 (23.2)

45-54 608 28,183,232 122 (20.1) 5,806,302 (20.6)

55-64 774 31,700,429 142 (18.3) 6,654,996 (21.0)

≥65 969 40,691,370 148 (15.3) 5,650,944 (13.9)
US Census region

Northeast 279 24,075,803 48 (17.2) 4,032,338 (16.7)

Midwest 438 37,524,032 113 (25.8) 10,525,924 (28.1)

South 1896 65,519,953 407 (21.5) 12,460,175 (19.0)

West 1250 56,051,456 203 (16.2) 10,803,732 (19.3)
Urbanicity

Micropolitan/small town/rural 374 24,397,071 99 (26.5) 7,311,317 (30.0)

Metropolitan 3489 158,774,173 672 (19.3) 30,510,853 (19.2)
Education

High school/General Educational Development (GED) or less 543 63,033,498 118 (21.7) 13,979,692 (22.2)

Some college/associate’s degree 1189 53,702,228 245 (20.6) 11,265,970 (21.0)

Bachelor’s degree 1203 42,013,058 247 (20.5) 8,657,800 (20.6)

Graduate degree 928 24,422,460 161 (17.3) 3,918,708 (16.0)
Annual income (US $)

0-24,999 586 21,039,489 104 (17.7) 3,112,863 (14.8)

25,000-49,999 756 30,682,885 153 (20.2) 7,428,650 (24.2)

50,000-99,999 1220 57,414,158 238 (19.5) 12,830,279 (22.3)

100,000-199,999 934 50,966,442 186 (19.9) 10,356,193 (20.3)

≥200,000 367 23,068,271 90 (24.5) 4,094,185 (17.7)
Health insurance

No health insurance 230 11,173,450 60 (26.1) 3,114,654 (27.9)

Medicare/Medicaid/other 1101 47,572,527 181 (16.4) 7,108,109 (14.9)

Private insurance/parent’s plan 2294 112,869,879 487 (21.2) 25,464,690 (22.6)

Do not know 238 11,555,388 43 (18.1) 2,134,717 (18.5)
Month of sample collection

August 619 48,004,288 138 (22.3) 10,783,244 (22.5)

September 372 30,679,522 71 (19.1) 6,715,153 (21.9)

October 775 52,803,927 148 (19.1) 10,452,603 (19.8)

November 2026 50,370,899 404 (19.9) 9,550,142 (19.0)

December 71 1,312,608 10 (14.1) 321,027 (24.5)
Job typea

Accommodation and food services 77 5,669,023 15 (19.5) 1,539,660 (27.2)

Educational services 283 7,801,317 48 (17.0) 1,310,424 (16.8)

Health care and social assistance 363 16,769,318 69 (19.0) 2,819,957 (16.8)

Retail trade 98 7,256,895 14 (14.3) 1,214,943 (16.7)

Transportation and warehousing 93 5,661,875 22 (23.7) 2,029,152 (35.8)

Other 1354 66,741,897 325 (24.0) 16,575,342 (24.8)
Work locationb

Completely indoors 868 44,926,729 192 (22.1) 11,122,278 (24.8)

Completely outdoor/mixture/other 485 24,905,513 137 (28.2) 8,446,810 (33.9)
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aAmong those who were employed.

bAmong those who were employed and left home for work.

Table 8.

Comparison of participant characteristics by latent classes of combined strategies to prevent COVID-19 among a household probability sample of 4090 US adults (August-December 2020).

Characteristics Additional hand hygienea vs optimal mitigationb, PRc (95% CI) Lowest mitigationd vs optimal mitigation, PR (95% CI)
Sex

Male Reference (N/Ae) Reference (N/A)

Female 1.34 (0.97-1.86) 0.70 (0.56-0.87)
Race/ethnicity

Hispanic 1.89 (1.33-2.68) 0.72 (0.51-1.01)

Non-Hispanic Black 1.93 (1.27-2.92) 0.58 (0.33-1.00)

Non-Hispanic White Reference (N/A) Reference (N/A)

Other 1.13 (0.66-1.93) 0.61 (0.37-1.01)
Age (years)

18-34 4.37 (2.45-7.80) 1.97 (1.42-2.72)

35-44 4.94 (2.76-8.84) 1.93 (1.36-2.72)

45-54 4.48 (2.47-8.14) 1.69 (1.16-2.47)

55-64 3.54 (1.92-6.53) 1.66 (1.16-2.36)

≥65 Reference (N/A) Reference (N/A)
US Census region

Northeast 0.74 (0.44-1.25) 0.84 (0.57-1.25)

Midwest 0.86 (0.55-1.35) 1.41 (1.06-1.87)

South 1.10 (0.78-1.56) 1.00 (0.76-1.32)

West Reference (N/A) Reference (N/A)
Urbanicity

Micropolitan/small town/rural Reference (N/A) Reference (N/A)

Metropolitan 0.84 (0.54-1.32) 0.64 (0.49-0.84)
Education

High school/General Educational Development (GED) or less 1.82 (1.21-2.75) 1.16 (0.87-1.54)

Some college/associate’s degree 1.74 (1.21-2.51) 1.09 (0.86-1.38)

Bachelor’s degree Reference (N/A) Reference (N/A)

Graduate degree 1.13 (0.74-1.72) 0.79 (0.60-1.05)
Annual income (US $)

0-24,999 1.40 (0.92-2.14) 0.72 (0.50-1.02)

25,000-49,999 1.17 (0.77-1.78) 1.11 (0.80-1.53)

50,000-99,999 Reference (N/A) Reference (N/A)

100,000-199,999 0.78 (0.51-1.18) 0.88 (0.66-1.18)

≥200,000 0.64 (0.36-1.13) 0.76 (0.54-1.06)
Health insurance

No health insurance Reference (N/A) Reference (N/A)

Medicare/Medicaid/other 0.58 (0.29-1.16) 0.51 (0.32-0.81)

Private insurance/parent’s plan 0.89 (0.48-1.67) 0.80 (0.53-1.22)

Do not know 0.83 (0.37-1.84) 0.66 (0.37-1.18)
Month of sample collection

August Reference (N/A) Reference (N/A)

September 1.79 (1.12-2.85) 1.06 (0.75-1.50)

October 1.14 (0.73-1.80) 0.90 (0.67-1.21)

November 1.57 (1.04-2.38) 0.90 (0.68-1.19)

December 0.30 (0.11-0.78) 1.02 (0.33-3.11)
Job typef

Accommodation and food services 2.10 (1.05-4.20) 1.20 (0.65-2.22)

Educational services 1.38 (1.05-4.20) 0.71 (0.47-1.08)

Health care and social assistance 3.95 (2.70-5.79) 0.96 (0.68-1.36)

Retail trade 3.92 (2.28-6.74) 0.95 (0.45-1.99)

Transportation and warehousing 3.04 (1.46-6.35) 1.68 (1.04-2.70)

Other Reference (N/A) Reference (N/A)
Work locationg

Completely indoors 0.88 (0.60-1.28) 0.73 (0.55-0.97)

Completely outdoor/mixture/other Reference (N/A) Reference (N/A)
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aOptimal mitigation plus additional hand hygiene is consistent masking and social distancing, as well as hand hygiene ≥11 times/day.

bOptimal mitigation is consistent masking and social distancing, as well as hand hygiene 6-10 times/day.

cPR: prevalence ratio.

dThe lowest mitigation is inconsistent masking and social distancing, as well as hand hygiene 0-5 times/day.

eN/A: not applicable.

fAmong those who were employed.

gAmong those who were employed and left home for work.

Compared to the optimal-mitigation class, those in the lowest-mitigation class were 20% less likely (PR 0.80, CI 0.79-0.90) to agree that masks provide 95% or better protection against COVID-19 and were twice as likely (PR 2.00, CI 1.27-3.15) to state that it was not necessary for youth to take measures to prevent COVID-19 infection (Table 8). There were no significant differences between the optimal-mitigation class and the class with additional hand hygiene for both the mask-wearing (PR 0.93, CI 0.82-1.06) and youth prevention (PR 1.70, CI 0.92-3.16) questions.

Table 6.

“Optimal mitigation plus additional hand hygiene” latent class of combined strategies to prevent COVID-19 among a household probability sample of 4090 US adults (August-December 2020).

Characteristics Total sample Optimal mitigation plus additional hand hygiene (consistent masking and social distancing, hand hygiene ≥11 times/day)


Unweighted, N Weighted, N Unweighted prevalence, n (%) Weighted prevalence, n (%)
Overall 3863 183,171,244 436 (11.3) 22,548,164 (12.3)
Sex

Male 1603 86,348,193 118 (7.4) 8,424,160 (9.8)

Female 2260 96,823,051 318 (14.1) 14,124,004 (14.6)
Race/ethnicity

Hispanic 551 33,539,313 103 (18.7) 6,328,829 (18.9)

Non-Hispanic Black 607 22,219,194 105 (17.3) 4,443,359 (20.0)

Non-Hispanic White 2454 112,449,529 205 (8.4) 10,067,066 (9.0)

Other 251 14,963,209 23 (9.2) 1,708,910 (11.4)
Age (years)

18-34 869 52,755,525 121 (13.9) 7,686,991 (14.6)

35-44 643 29,840,688 89 (13.8) 4,992,781 (16.7)

45-54 608 28,183,232 86 (14.1) 4,417,403 (15.7)

55-64 774 31,700,429 90 (11.6) 3,907,870 (12.3)

≥65 969 40,691,370 50 (5.2) 1,543,119 (3.8)
US Census region

Northeast 279 24,075,803 28 (10.0) 2,367,057 (9.8)

Midwest 438 37,524,032 40 (9.1) 3,709,602 (9.9)

South 1896 65,519,953 240 (12.7) 9,277,429 (14.2)

West 1250 56,051,456 128 (10.2) 7,194,076 (12.8)
Urbanicity

Micropolitan/small town/rural 374 24,397,071 44 (11.8) 3,079,673 (12.6)

Metropolitan 3489 158,774,173 392 (11.2) 19,468,491 (12.3)
Education

High school/General Educational Development (GED) or less 543 63,033,498 75 (13.8) 9,177,714 (14.6)

Some college/associate’s degree 1189 53,702,228 178 (15.0) 7,573,166 (14.1)

Bachelor’s degree 1203 42,013,058 94 (7.8) 3,420,744 (8.1)

Graduate degree 928 24,422,460 89 (9.6) 2,376,540 (9.7)
Annual income (US $)

0-24,999 586 21,039,489 86 (14.7) 4,030,880 (19.2)

25,000-49,999 756 30,682,885 99 (13.1) 4,365,638 (14.2)

50,000-99,999 1220 57,414,158 141 (11.6) 7,137,152 (12.4)

100,000-199,999 934 50,966,442 85 (9.1) 5,067,508 (9.9)

≥200,000 367 23,068,271 25 (6.8) 1,946,986 (8.4)
Health insurance

No health insurance 230 11,173,450 32 (13.9) 1,547,869 (13.9)

Medicare/Medicaid/other 1101 47,572,527 96 (8.7) 4,518,681 (9.5)

Private insurance/parent’s plan 2294 112,869,879 272 (11.9) 14,983,739 (13.3)

Do not know 238 11,555,388 36 (15.1) 1,497,874 (13.0)
Month of sample collection

August 619 48,004,288 51 (8.2) 4,344,792 (9.1)

September 372 30,679,522 59 (15.9) 5,007,293 (16.3)

October 775 52,803,927 70 (9.0) 5,658,534 (10.7)

November 2026 50,370,899 246 (12.1) 7,502,823 (14.9)

December 71 1,312,608 10 (14.1) 34,721 (2.6)
Job typea

Accommodation and food services 77 5,669,023 18 (23.4) 920,635 (16.2)

Educational services 283 7,801,317 40 (14.1) 952,513 (12.2)

Health care and social assistance 363 16,769,318 101 (27.8) 5,864,653 (35.0)

Retail trade 98 7,256,895 27 (27.6) 2,517,580 (34.7)

Transportation and warehousing 93 5,661,875 15 (16.1) 1,174,633 (20.7)

Other 1354 66,741,897 104 (7.7) 5,333,381 (8.0)
Work locationb

Completely indoors 868 44,926,729 157 (18.1) 8,661,383 (19.3)

Completely outdoor/mixture/other 485 24,905,513 72 (14.8) 4,798,204 (19.3)
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aAmong those who were employed.

bAmong those who were employed and left home for work.

Discussion

Principal Findings

We report the first national probability survey estimates of the prevalence of COVID-19 mitigation strategies among US adults. During the 2020 peak of COVID-19 incidence, nearly three-quarters of adults consistently wore a mask when going out, about half consistently practiced social distancing or frequently washed their hands, and about a quarter frequently used a hand sanitizer. There were 3 distinct patterns of use of these mitigation practices. Two-thirds practiced optimal mitigation, with consistent and frequent use of all mitigation strategies; about 1 in 5 practiced the poorest mitigation practices, with inconsistent or infrequent use of all mitigation strategies; and about 1 in 9 consistently wore a mask and practiced social distancing and may have followed excessive hand hygiene practices. Finally, all mitigation practices and grouping of practices varied substantially among people with different demographic characteristics.

The prevalence of consistently wearing a mask in our population-based study was similar to earlier estimates from polls and convenience samples [5,9,10], but the estimate from our population-based sample was substantially lower than the 89% reported by the online convenience sampling–based COVID Impact Survey in June 2020 [12]. The difference in prevalence could be due to selection bias in the convenience sampling–based COVID Impact Survey if those who were more likely to wear masks were also more likely to respond to the survey. Our survey items were also slightly different, with our survey stipulating mask wearing when going out and asking about the frequency of mask usage, whereas the COVID Impact Survey asked a general question about mask wearing, without regard to context or frequency. It is also possible that mask wearing decreased between June and August 2020 (the beginning of our study), as public facilities reopened and mask requirements in each jurisdiction became more complex and possibly confusing.

There was a similar discrepancy between our findings and those of the COVID Impact Survey for practicing social distancing and washing hands, but for these practices, our estimates were even lower than those of the COVID Impact Survey, which reported >80% prevalence for both [12]. Although the COVID Impact Survey reported a slightly decreased prevalence of social distancing and hand hygiene in June compared to April 2020, a simple extrapolation of that decreasing trend would not explain the difference we found later in 2020. Similar selection biases and differences in survey items for these practices could explain part, but not all, of the difference between the findings of our study and the COVID Impact Survey. ConsumerStyles panel surveys that examined handwashing practices in October 2019 and June 2020 in specific contexts (eg, before eating, after sneezing, or after coughing) also found a substantially higher prevalence of handwashing than we did, providing further evidence that the survey question type (eg, making the questions conditional on situations in which handwashing is recommended even outside of COVID-19 times) can substantially affect prevalence estimates. We structured our questions based on the only published study on the effectiveness of hand hygiene for preventing seasonal coronavirus infection [22]. As we would expect during the COVID-19 pandemic with frequent communications about the importance of hand hygiene, our prevalence estimate of 57.7% who washed their hands 6-10 times in the past 24 hours was substantially higher than the 39.5% reported in the UK study conducted between 2006 and 2009. The prevalence of use of a hand sanitizer in our study was also substantially lower (21.5% vs 70.7%) compared to only 1 other previous paper, by Czeisler et al [14], that reported this as a separate behavior from handwashing. This difference in prevalence was likely due to context-specific differences in behaviors, where Czeisler et al [14] assessed hand sanitizer usage only after contact with high-touch public surfaces.

The distinct sets of mitigation practices (optimal mitigation, lowest mitigation, and optimal mitigation with additional hand hygiene) were also novel findings of our study. Those in the optimal-mitigation and optimal-mitigation-with-additional-hand-hygiene groups frequently wear masks and practice social distancing when they go out in public. Although there was a clear distinction between these groups based on the frequency of handwashing predetermined based on Beale et al’s [22] effectiveness study, there were no differences between these groups in their agreement with the mask-wearing and youth prevention questions. Our findings did indicate that the optimal-mitigation and optimal-mitigation-with-additional-hand-hygiene groups differed on multiple demographic characteristics, which supports the idea that these groups may have fundamental differences in their approaches toward COVID-19 prevention. Further study on the context of hand hygiene practices may clarify some of these issues, and we are now implementing a context-specific set of mitigation practice questions in our 3- and 6-month follow-up surveys with this cohort. The lowest-mitigation group, which was inconsistent in all mitigation practices, comprised an unfortunately large proportion of 1 in 5 US adults. The demographic differences between the optimal- and lowest-mitigation groups were even more pronounced, emphasizing the demographic disparities in COVID-19 mitigation practices.

This heterogeneity in COVID-19 mitigation practices among demographic groups in our study has also been partly reported in other published papers for individual practices [5,9,12,15,20], and those prior published findings are reasonably consistent with the demographic heterogeneity we found. Our study goes a step further to illustrate how persons from various backgrounds combine the individual mitigation recommendations in practice. The demographic heterogeneity in these empirically determined grouping of mitigation practices is even more evident than in individual practices. Compared to men and younger adults, women and older adults are much more likely to optimally use all mitigation practices. These differences in patterns of use may reflect greater risk perception, more exposure to COVID-19 prevention messages, or other contextual factors, such as leaving the home or living in group settings. US adults who were Black or Hispanic (compared to White, non-Hispanic), had no college degree, or worked in service-oriented jobs were more likely to report excessive hand hygiene, while also consistently wearing a mask and maintaining social distancing. These differences might also reflect greater risk perception and prevention message exposure but are more likely due to other contextual factors, such as hand hygiene requirements of their jobs. Finally, US adults who live outside metropolitan areas were likely to engage in all mitigation practices inconsistently. This might be due to differing risk perceptions or exposure to prevention messages in less densely populated areas [28].

Limitations

This study has several limitations. First, there was a lack of contextual information for some mitigation practices that could better clarify whether people are engaging in practices in only some settings or situations but not in others. These situational assessments have been added to our follow-up surveys, which were completed by mid-2021, and will be included in subsequent analyses. Second, some demographic heterogeneity could be explained by confounding, which could be elucidated with additional modeling. Multivariable modeling is planned for follow-up survey analyses. Third, we did not assess the quality of the mitigation behaviors, such as correctly wearing masks, or the effectiveness of those behaviors on preventing COVID-19 infection. The prospective component of the study will directly examine these associations. Fourth, the enrollment and baseline surveys occurred during a 5-month period of substantial changes in the COVID-19 pandemic and response. There may be time frame heterogeneity in the mitigation behaviors during these changes, but we were unable to analyze these baseline data as cross-sectional time series due to sampling method changes and prioritization of the entire survey sample weighting for national estimates [21]. Finally, although household probability sampling methods and weighting allowed for national estimation of these essential mitigation practices, there is likely still selection bias due to nonresponse.

Conclusion

Although the prevalence of consistently wearing a mask was relatively high among US adults, there were still millions who were not doing so during the time of the highest COVID-19 incidence to date in the pandemic. Even greater numbers of US adults did not consistently practice social distancing outside their homes and did not frequently practice hand hygiene. These practices remained crucial to blunting the surge of COVID-19 infections, especially since we had not yet achieved sufficient vaccine coverage to stop the pandemic. Despite clear public health evidence of their importance, the implementation of these practices was further undermined by a confusing array of local jurisdiction messages about mask requirements and restrictions on public gatherings. In future infectious disease outbreak responses, monitoring mitigation practices in a context of changing mandates and messages will help us refine communication strategies to increase the adoption and persistence of effective mitigation behaviors. This monitoring will also help ensure that disparities in mitigation practices do not widen further, leading to even greater disparities in infectious disease incidence and continuation of high-level community transmission.

Acknowledgments

The study was funded by a grant from the National Institutes of Health (3R01AI143875-02S1).

Abbreviations

LCA

latent class analysis

PR

prevalence ratio

Footnotes

Conflicts of Interest: TS, PSS, and HB are members of the Editorial Board of JMIR Public Health and Surveillance. However, they had no involvement in the editorial decisions for this manuscript. The manuscript was reviewed and handled by an independent editor.

References

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