Use of COVIDTests.gov At-Home Test Kits Among Adults in a National Household Probability Sample - United States, 2022.

At-home rapid antigen COVID-19 tests were first authorized by the Food and Drug Administration in late 2020 (1-3). In January 2022, the White House launched COVIDTests.gov, which made all U.S. households eligible to receive free-to-the-user at-home test kits distributed by the U.S. Postal Service (2). By May 2022, more than 70 million test kit packages had been shipped to households across the United States (2); however, how these kits were used, and which groups were using them, has not been reported. Data from a national probability survey of U.S. households (COVIDVu), collected during April-May 2022, were used to evaluate awareness about and use of these test kits (4). Most respondent households (93.8%) were aware of the program, and more than one half (59.9%) had ordered kits. Among persons who received testing for COVID-19 during the preceding 6 months, 38.3% used a COVIDTests.gov kit. Among kit users, 95.5% rated the experience as acceptable, and 23.6% reported being unlikely to have tested without the COVIDTests.gov program. Use of COVIDTests.gov kits was similar among racial and ethnic groups (42.1% non-Hispanic Black or African American [Black]; 41.5% Hispanic or Latino [Hispanic]; 34.8% non-Hispanic White [White]; and 53.7% non-Hispanic other races [other races]). Use of other home COVID-19 tests differed by race and ethnicity (11.8% Black, 44.4% Hispanic, 45.8% White, 43.8% other races). Compared with White persons, Black persons were 72% less likely to use other home test kits (adjusted relative risk [aRR] = 0.28; 95% CI = 0.16-0.50). Provision of tests through this well-publicized program likely improved use of COVID-19 home testing and health equity in the United States, particularly among Black persons. National programs to address availability and accessibility of critical health services in a pandemic response have substantial health value.

Characterizing superspreading events and age-specific infectiousness of SARS-CoV-2 transmission in Georgia, USA.

It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and superspreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatiotemporal mechanistic framework to integrate individual surveillance data with geolocation data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the state of Georgia. First, our results show that the reproductive number reduced to below one in about 2 wk after the shelter-in-place order. Superspreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance toward later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected nonelderly cases (<60 y) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of superspreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of superspreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.

Prenatal and early-life exposure to the Great Chinese Famine increased the risk of tuberculosis in adulthood across two generations.

Global food security is a major driver of population health, and food system collapse may have complex and long-lasting effects on health outcomes. We examined the effect of prenatal exposure to the Great Chinese Famine (1958-1962)-the largest famine in human history-on pulmonary tuberculosis (PTB) across consecutive generations in a major center of ongoing transmission in China. We analyzed >1 million PTB cases diagnosed between 2005 and 2018 in Sichuan Province using age-period-cohort analysis and mixed-effects metaregression to estimate the effect of the famine on PTB risk in the directly affected birth cohort (F1) and their likely offspring (F2). The analysis was repeated on certain sexually transmitted and blood-borne infections (STBBI) to explore potential mechanisms of the intergenerational effects. A substantial burden of active PTB in the exposed F1 cohort and their offspring was attributable to the Great Chinese Famine, with more than 12,000 famine-attributable active PTB cases (>1.23% of all cases reported between 2005 and 2018). An interquartile range increase in famine intensity resulted in a 6.53% (95% confidence interval [CI]: 1.19-12.14%) increase in the ratio of observed to expected incidence rate (incidence rate ratio, IRR) in the absence of famine in F1, and an 8.32% (95% CI: 0.59-16.6%) increase in F2 IRR. Increased risk of STBBI was also observed in F2. Prenatal and early-life exposure to malnutrition may increase the risk of active PTB in the exposed generation and their offspring, with the intergenerational effect potentially due to both within-household transmission and increases in host susceptibility.

Severe Acute Respiratory Syndrome Coronavirus 2 Cumulative Incidence, United States, August 2020-December 2020.

BACKGROUND: Reported coronavirus disease 2019 (COVID-19) cases underestimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. We conducted a national probability survey of US households to estimate cumulative incidence adjusted for antibody waning. METHODS: From August-December 2020 a random sample of US addresses were mailed a survey and self-collected nasal swabs and dried blood spot cards. One adult household member completed the survey and mail specimens for viral detection and total (immunoglobulin [Ig] A, IgM, IgG) nucleocapsid antibody by a commercial, emergency use authorization-approved antigen capture assay. We estimated cumulative incidence of SARS-CoV-2 adjusted for waning antibodies and calculated reported fraction (RF) and infection fatality ratio (IFR). Differences in seropositivity among demographic, geographic, and clinical subgroups were explored. RESULTS: Among 39 500 sampled households, 4654 respondents provided responses. Cumulative incidence adjusted for waning was 11.9% (95% credible interval [CrI], 10.5%-13.5%) as of 30 October 2020. We estimated 30 332 842 (CrI, 26 703 753-34 335 338) total infections in the US adult population by 30 October 2020. RF was 22.3% and IFR was 0.85% among adults. Black non-Hispanics (Prevalence ratio (PR) 2.2) and Hispanics (PR, 3.1) were more likely than White non-Hispanics to be seropositive. CONCLUSIONS: One in 8 US adults had been infected with SARS-CoV-2 by October 2020; however, few had been accounted for in public health reporting. The COVID-19 pandemic is likely substantially underestimated by reported cases. Disparities in COVID-19 by race observed among reported cases cannot be attributed to differential diagnosis or reporting of infections in population subgroups.

Efficacy and Safety of Aldafermin, an Engineered FGF19 Analog, in a Randomized, Double-Blind, Placebo-Controlled Trial of Patients With Nonalcoholic Steatohepatitis.

BACKGROUND & AIMS: Aldafermin, an engineered analog of fibroblast growth factor 19, inhibits bile acid synthesis and regulates metabolic homeostasis. We report results from a 24-week, phase 2 study, with serial liver biopsies, of patients with nonalcoholic steatohepatitis (NASH). METHODS: We performed a double-blind study of 78 patients with NASH at 9 centers in the United States. Key inclusion criteria were biopsy-proven NASH with Nonalcoholic Fatty Liver Disease Activity Score ≥4, stage 2 or 3 fibrosis by NASH Clinical Research Network classification, and absolute liver fat content ≥8%, measured by magnetic resonance imaging-proton density fat fraction. Patients were randomly assigned (1:2) to groups given subcutaneous placebo (n = 25) or aldafermin 1 mg (n = 53) daily for 24 weeks. The primary outcome was change in absolute liver fat content from baseline at week 24. Secondary outcomes included serum markers and histologic measures of fibrosis improvement and NASH resolution. RESULTS: At week 24, the aldafermin group had a significant reduction in absolute liver fat content (reduction of 7.7%) compared with placebo (reduction of 2.7%; difference, reduction of 5.0%; 95% confidence interval, reduction of 8.0%-1.9%; P = .002). Aldafermin produced significantly greater decreases in levels of 7α-hydroxy-4-cholesten-3-one, bile acids, alanine and aspartate aminotransferases, and neoepitope-specific N-terminal pro-peptide of type III collagen (Pro-C3) than placebo. Fibrosis improvement (≥1 stage) with no worsening of NASH was achieved in 38% of patients receiving aldafermin vs 18% of patients receiving placebo (P = .10). NASH resolution with no worsening of fibrosis was observed in 24% of patients given aldafermin vs 9% of patients given placebo (P = .20). Discontinuations due to adverse events occurred in no patients in the aldafermin group and 4% of patients in the placebo group. CONCLUSIONS: In a phase 2 trial of patients with NASH, aldafermin reduced liver fat and produced a trend toward fibrosis improvement. ClinicalTrials.gov, Number: NCT02443116.

Quantification of Occupational and Community Risk Factors for SARS-CoV-2 Seropositivity Among Health Care Workers in a Large U.S. Health Care System.

BACKGROUND: Identifying occupational risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care workers (HCWs) can improve HCW and patient safety. OBJECTIVE: To quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among HCWs in a large health care system. DESIGN: A logistic regression model was fitted to data from a cross-sectional survey conducted in April to June 2020, linking risk factors for occupational and community exposure to coronavirus disease 2019 (COVID-19) with SARS-CoV-2 seropositivity. SETTING: A large academic health care system in the Atlanta, Georgia, metropolitan area. PARTICIPANTS: Employees and medical staff members elected to participate in SARS-CoV-2 serology testing offered to all HCWs as part of a quality initiative and completed a survey on exposure to COVID-19 and use of personal protective equipment. MEASUREMENTS: Demographic risk factors for COVID-19, residential ZIP code incidence of COVID-19, occupational exposure to HCWs or patients who tested positive on polymerase chain reaction test, and use of personal protective equipment as potential risk factors for infection. The outcome was SARS-CoV-2 seropositivity. RESULTS: Adjusted SARS-CoV-2 seropositivity was estimated to be 3.8% (95% CI, 3.4% to 4.3%) (positive, n = 582) among the 10 275 HCWs (35% of the Emory Healthcare workforce) who participated in the survey. Community contact with a person known or suspected to have COVID-19 (adjusted odds ratio [aOR], 1.9 [CI, 1.4 to 2.6]; 77 positive persons [10.3%]) and community COVID-19 incidence (aOR, 1.5 [CI, 1.0 to 2.2]) increased the odds of infection. Black individuals were at high risk (aOR, 2.1 [CI, 1.7 to 2.6]; 238 positive persons [8.3%]). LIMITATIONS: Participation rates were modest and key workplace exposures, including job and infection prevention practices, changed rapidly in the early phases of the pandemic. CONCLUSION: Demographic and community risk factors, including contact with a COVID-19-positive person and Black race, are more strongly associated with SARS-CoV-2 seropositivity among HCWs than is exposure in the workplace. PRIMARY FUNDING SOURCE: Emory COVID-19 Response Collaborative.

Pre-detection history of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa.

Antimicrobial-resistant (AMR) infections pose a major threat to global public health. Similar to other AMR pathogens, both historical and ongoing drug-resistant tuberculosis (TB) epidemics are characterized by transmission of a limited number of predominant Mycobacterium tuberculosis (Mtb) strains. Understanding how these predominant strains achieve sustained transmission, particularly during the critical period before they are detected via clinical or public health surveillance, can inform strategies for prevention and containment. In this study, we employ whole-genome sequence (WGS) data from TB clinical isolates collected in KwaZulu-Natal, South Africa to examine the pre-detection history of a successful strain of extensively drug-resistant (XDR) TB known as LAM4/KZN, first identified in a widely reported cluster of cases in 2005. We identify marked expansion of this strain concurrent with the onset of the generalized HIV epidemic 12 y prior to 2005, localize its geographic origin to a location in northeastern KwaZulu-Natal ∼400 km away from the site of the 2005 outbreak, and use protein structural modeling to propose a mechanism for how strain-specific rpoB mutations offset fitness costs associated with rifampin resistance in LAM4/KZN. Our findings highlight the importance of HIV coinfection, high preexisting rates of drug-resistant TB, human migration, and pathoadaptive evolution in the emergence and dispersal of this critical public health threat. We propose that integrating whole-genome sequencing into routine public health surveillance can enable the early detection and local containment of AMR pathogens before they achieve widespread dispersal.

Rapid Review of Social Contact Patterns During the COVID-19 Pandemic.

BACKGROUND: Physical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic. METHOD: We conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures. RESULTS: We identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults. CONCLUSION: Information on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.

Estimating the Cumulative Incidence of SARS-CoV-2 Infection and the Infection Fatality Ratio in Light of Waning Antibodies.

BACKGROUND: Serology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serologic assays (which is not necessarily equivalent to the duration of protective immunity). We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City and Connecticut. METHODS: We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March to October 2020 and population-level cross-sectional seroprevalence data from April to August 2020 in New York City and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection. RESULTS: The estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval, 1.0%, 1.2%) in New York City and 1.4% (1.1, 1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2%, 29.7%) at the end of September in New York City and 8.8% (7.1%, 11.3%) in Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively. CONCLUSIONS: The cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.

Narrativity and Referential Activity Predict Episodic Memory Strength in Autobiographical Memories.

Narrativity has been proposed as an indicator of episodic memory strength when people discuss their past (Nelson and Horowitz in Discourse Processes 31:307-324, 2001. https://doi.org/10.1207/S15326950dp31-3_5 ). Referential Activity, the extent to which words convey a speaker's experience of being present in the event being described, has been independently hypothesized to indicate episodic memory strength (Maskit in J Psycholinguist Res, 2021. https://doi.org/10.1007/s10936-021-09761-8 ). These hypotheses are tested using a linguistic measure of narrativity and a computerized measure of referential activity to predict previous independent ratings of episodic memory strength that used the Levine et al. (Psychol Aging 17(4):677-689, 2002. https://doi.org/10.1037//0882-7974.17.4.677 ) measure of internal details in retold personal memories provided by Schacter (Addis et al. in Psychol Sci 19(1):33-41, 2008. https://doi.org/10.1111/j.1467-9280.2008.02043.x ). Raters scored narrativity on four brief near and far past memories elicited from 32 subjects, using Nelson's narrative temporal sequence method based on Labov's (J Narrat Life Hist 7(1-4):395-415, 1997. https://doi.org/10.1075/jnlh.7.49som ) analysis of spoken narratives of personal experience; computerized weighted scores of referential activity (WRAD) were obtained on these same 128 memories. Data analysis showed that narrative temporal sequences predict internal details and WRAD predict internal details. Adding WRAD to narrative temporal sequences improved the prediction of internal details.

Social Mixing and Clinical Features Linked With Transmission in a Network of Extensively Drug-resistant Tuberculosis Cases in KwaZulu-Natal, South Africa.

BACKGROUND: Tuberculosis (TB) is the leading infectious cause of death globally, and drug-resistant TB strains pose a serious threat to controlling the global TB epidemic. The clinical features, locations, and social factors driving transmission in settings with high incidences of drug-resistant TB are poorly understood. METHODS: We measured a network of genomic links using Mycobacterium tuberculosis whole-genome sequences. RESULTS: Patients with 2-3 months of cough or who spent time in urban locations were more likely to be linked in the network, while patients with sputum smear-positive disease were less likely to be linked than those with smear-negative disease. Associations persisted using different thresholds to define genomic links and irrespective of assumptions about the direction of transmission. CONCLUSIONS: Identifying factors that lead to many transmissions, including contact with urban areas, can suggest settings instrumental in transmission and indicate optimal locations and groups to target with interventions.

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011-2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.

Excess Pneumonia Mortality During a 2014-2015 Legionnaires' Disease Outbreak in Genesee County, Michigan.

BACKGROUND: From June 2014 to October 2015, the Michigan Department of Health and Human Services reported an outbreak of 90 cases of Legionnaires' disease, including 10 deaths, in Genesee County, Michigan. As Legionnaires' disease is not routinely tested for as a cause of community-acquired pneumonia, we hypothesized that the size of the outbreak was underestimated. METHODS: We used Centers for Disease Control and Prevention (CDC) Wide-ranging ONline Data for Epidemiologic Research data to compare pneumonia mortality in Genesee to similar counties from 2011 to 2017. We used data from the Genesee County Vital Records Division to assess geographic overlap of pneumonia mortality with reported Legionnaires disease cases by census tract. RESULTS: We estimated 70.0 excess pneumonia deaths (90% uncertainty interval: 36-103) in Genesee County during the outbreak. Areas of high pneumonia mortality overlapped with those with high Legionnaires' disease incidence. CONCLUSIONS: These findings are consistent with the hypothesis that the Legionnaires' disease outbreak was larger than reported. Earlier outbreak detection and response may have facilitated identification of additional cases.

Spatial Patterns of Extensively Drug-Resistant Tuberculosis Transmission in KwaZulu-Natal, South Africa.

Background: Transmission is driving the global drug-resistant tuberculosis (TB) epidemic; nearly three-quarters of drug-resistant TB cases are attributable to transmission. Geographic patterns of disease incidence, combined with information on probable transmission links, can define the spatial scale of transmission and generate hypotheses about factors driving transmission patterns. Methods: We combined whole-genome sequencing data with home Global Positioning System coordinates from 344 participants with extensively drug-resistant (XDR) TB in KwaZulu-Natal, South Africa, diagnosed from 2011 to 2014. We aimed to determine if genomically linked (difference of ≤5 single-nucleotide polymorphisms) cases lived close to one another, which would suggest a role for local community settings in transmission. Results: One hundred eighty-two study participants were genomically linked, comprising 1084 case-pairs. The median distance between case-pairs' homes was 108 km (interquartile range, 64-162 km). Between-district, as compared to within-district, links accounted for the majority (912/1084 [84%]) of genomic links. Half (526 [49%]) of genomic links involved a case from Durban, the urban center of KwaZulu-Natal. Conclusions: The high proportions of between-district links with Durban provide insight into possible drivers of province-wide XDR-TB transmission, including urban-rural migration. Further research should focus on characterizing the contribution of these drivers to overall XDR-TB transmission in KwaZulu-Natal to inform design of targeted strategies to curb the drug-resistant TB epidemic.

Extensively drug-resistant tuberculosis in South Africa: genomic evidence supporting transmission in communities.

Despite evidence that transmission is driving an extensively drug-resistant TB (XDR-TB) epidemic, our understanding of where and between whom transmission occurs is limited. We sought to determine whether there was genomic evidence of transmission between individuals without an epidemiologic connection.We conducted a prospective study of XDR-TB patients in KwaZulu-Natal, South Africa, during the 2011-2014 period. We collected sociodemographic and clinical data, and identified epidemiologic links based on person-to-person or hospital-based connections. We performed whole-genome sequencing (WGS) on the Mycobacterium tuberculosis isolates and determined pairwise single nucleotide polymorphism (SNP) differences.Among 404 participants, 123 (30%) had person-to-person or hospital-based links, leaving 281 (70%) epidemiologically unlinked. The median SNP difference between participants with person-to-person and hospital-based links was 10 (interquartile range (IQR) 8-24) and 16 (IQR 10-23), respectively. The median SNP difference between unlinked participants and their closest genomic link was 5 (IQR 3-9) and half of unlinked participants were within 7 SNPs of at least five participants.The majority of epidemiologically-unlinked XDR-TB patients had low pairwise SNP differences with at least one other participant, consistent with transmission. These data suggest that much of transmission may result from casual contact in community settings between individuals not known to one another.

Comprehensive profiling of social mixing patterns in resource poor countries: A mixed methods research protocol.

BACKGROUND: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. METHODS: To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures. We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. DISCUSSION: Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.

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

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.

Social contact patterns among employees in U.S. long-term care facilities during the COVID-19 pandemic, December 2020 to June 2021.

OBJECTIVE: We measured contact patterns using social contact diaries for 157 U.S. long-term care facility employees from December 2020 - June 2021. These data are crucial for analyzing mathematical transmission models and for informing healthcare setting infection control policy. RESULTS: The median number of daily contacts was 10 (IQR 8-11). Household contacts were more likely partially masked than fully masked, more likely to involve physical contact, and longer in duration compared to facility contacts.

Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.

Non-pharmaceutical interventions minimize social contacts, hence the spread of respiratory pathogens such as influenza and SARS-CoV-2. Globally, there is a paucity of social contact data from the workforce. In this study, we quantified two-day contact patterns among USA employees. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic self-kept diaries. Data were collected over 4 rounds from 2020 to 2021 during the COVID-19 pandemic. Mean (standard deviation) contacts reported by 1456 participants were 2.5 (2.5), 8.2 (7.1), 9.2 (7.1) and 10.1 (9.5) across round 1 (April-June 2020), 2 (November 2020-January 2021), 3 (June-August 2021), and 4 (November-December 2021), respectively. Between round 1 and 2, we report a 3-fold increase in the mean number of contacts reported per participant with no major increases from round 2-4. We then modeled SARS-CoV-2 transmission at home, work, and community settings. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained exceptionally low in work settings. To accurately parameterize models of infection transmission and control, we need empirical social contact data that capture human mixing behavior across time.