Longitudinal study of an emerging COVID-19 stigma: Media exposure, danger appraisal, and stress

Media coverage of coronavirus disease (COVID-19) has played a critical role throughout the pandemic: sharing news about the novel virus, policies and practices to mitigate it, and the race to create and distribute vaccines. The media coverage, however, has been critiqued as stigmatizing. Although this critique is not new, there is limited understanding of how and why new stigmas emerge from exposure to media coverage. Drawing upon the model of stigma communication (Smith et al., 2019) and the attribution model of stigma (Corrigan et al., 2003), we investigated a novel model of stigma emergence that delineates two kinds of longitudinal processes: (a) a message-effects process, in which exposure to mediated messages about COVID-19 leads to public stigma through danger appraisal and (b) a coping process in which stress and rumination shape later perceptions of public stigma. To test the model, we tracked an emerging COVID-19 stigma with a two-wave survey of a prospective, longitudinal cohort living in one county in a mid-Atlantic state (N = 883). The results supported this model. The longitudinal processes of stigma emergence and implications for COVID-19 stigma are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Using artificial intelligence to support rapid, mixed-methods analysis: Developing an automated qualitative assistant (AQUA).

Context: Qualitative research - crucial for understanding human behavior - remains underutilized, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those burdens. Older AI techniques (Latent Semantic Indexing / Latent Dirichlet Allocation (LSI/LDA)) have fallen short, in part because qualitative data is rife with idiom, non-standard expressions, and jargon. Objective: To develop an AI platform using updated techniques to augment qualitative data coding. Study Design and Analysis: We previously completed traditional qualitative analysis of a large dataset, with 11 qualitative categories and 72 subcategories (categories), and a final Cohen's kappa ≥ 0.65 as a measure of human inter-coder reliability (ICR) after coding. We built our Automated Qualitative Assistant (AQUA) using a semi-classical approach, replacing LSI/LDA with a graph-theoretic topic extraction and clustering method. AQUA was given the previously-identified qualitative categories and tasked with coding free-text data into those categories. Item coding was scored using cosine-similarity. Population Studied: Pennsylvanian adults. Instrument: Free-text responses to five open ended questions related to the COVID-19 pandemic (e.g. "What worries you most about the COVID-19 pandemic?"). Outcome Measures: AQUA's coding was compared to human coding using Cohen's kappa. This was done on all categories in aggregate, and also on category clusters to identify category groups amenable to AQUA support. AQUA's time to complete coding was compared to the time taken by the human coding team. Dataset: Five unlimited free-text survey answers from 538 responders. Results: AQUA's kappa for all categories was low (kappa~0.45), reflecting the challenge of automated analysis of diverse language. However, for several 3-category combinations (with less linguistic diversity), AQUA performed comparably to human coders, with an ICR kappa range of 0.62 to 0.72 based on test-train split. AQUA's analysis (including human interpretation) took approximately 5 hours, compared to approximately 30 person hours for traditional coding. Conclusions: AQUA enables qualitative researchers to identify categories amenable to automated coding, and to rapidly conduct that coding on the entirety of very large datasets. This saves time and money, and avoids limitations inherent in limiting qualitative analysis to limited samples of a given dataset.

A mixed methods study exploring requests for unproven COVID therapies such as ivermectin and healthcare distrust in the rural South.

The COVID-19 pandemic has led to contentious discourse regarding unproven COVID-19 therapies (UCTs),(e.g. ivermectin). Despite recommendations against it, ivermectin remains, in some areas, highly demanded. The goal of this study is to understand patient and provider perspectives about UCTs (e.g., ivermectin) and how responses to requests for UCTs impact healthcare distrust. This mixed methods observational study was conducted in a rural healthcare system in the Southern United States. Adults (n = 26) with a history of COVID-19 or clinicians (n = 8) from the same system were interviewed using questionnaires assessing healthcare distrust and qualitatively interviewed exploring perceptions about UCTs. Patient themes were: 1) Importance of anecdotal stories for decision-making; 2) Use of haphazard approaches to 'research'; 3) Strong distrust of government and healthcare organizations; 4) Inherent trust in local healthcare; 5) Decision-making as weighing pros/cons; and 6) Feeling a right to try medications. High survey medians indicated high distrust with differences of 8.5 points for those who requested/used ivermectin versus those who did not (p = 0.027). Clinician themes were: 1) Frustration when patients trust social media over clinicians; 2) Acceptance of community beliefs about UCTs; 3) Distrust originating outside of the healthcare system; 4) Feeling torn about prescribing UCTs to build trust; and 5) Variable educational strategies. When clinicians are perceived as aligned with government, this may void patients' trust of clinicians. Clinicians should leverage trust in local healthcare and distance themselves from distrusted information sources. Ethical questions arise regarding appropriateness of acquiescing to patient requests for ivermectin for building trust.

Extending the Theory of Normative Social Behavior: Collective Norms, Opinion Leadership, and Masking During the COVID-19 Pandemic.

Novel, public behaviors, such as masking, should be susceptible to normative influence. This paper advances the theory of normative social behavior by considering a new set of moderators of normative influence - superdiffuser traits - and by clarifying the antecedents and consequences of exposure to collective norms. We use data from a two-wave survey of a cohort living in one U.S. county during the pandemic (N = 913) to assess normative effects on masking. We also used a bipartite network (based on people shopping for food in the same stores) to examine exposure to collective norms. The results show different superdiffuser traits have distinct effects on the relationship between perceived injunctive norms and masking intentions. Exposure to collective norms influences masking, but this influence depends on how people interact with their social environments. Network analysis shows that behavioral homophily is a significant predictor of selective exposure to collective norms earlier (but not later) in the pandemic. Implications for understanding normative influence in a context where opinion leadership matters are discussed.

Mixed-methods Analysis of Adults Likely versus Unlikely to Get a COVID-19 Vaccination.

Objectives: This mixed-methods study compared perspectives of those 'very likely' versus 'very unlikely' to receive a hypothetical COVID-19 vaccine. Methods: We used an explanatory, sequential, mixed- methods design to analyze quantitative data from a rural Pennsylvania sample. Of the 976 participants, 67 selected 'very unlikely' to get the COVID-19 vaccine. Responses to open-ended questions: "What worries you the most about the COVID 19 pandemic?" and "What are your thoughts about a potential COVID 19 vaccine?" were qualitatively compared to answers from the 67 participants who selected 'very likely' to get the COVID-19 vaccine. We used descriptive content analysis to compare themes across the 2 groups. Results: Both groups had thematic commonalities related to their concerns. Themes that were more common among those 'very unlikely' to get vaccinated included concern for politics overriding vaccine safety and rushed vaccine development timeline, whereas themes related to hope and optimism about vaccination were exclusive to the 'very likely' group. Conclusions: Shared beliefs existed across groups with different intents to vaccinate; yet, identification with vaccine spokespersons differed. Messaging campaigns can use these commonalities to address vaccine hesitancy.

Perceptions and knowledge regarding the COVID-19 pandemic between U.S. and China: a mixed methods study.

BACKGROUND: SARS-CoV-2, a new coronavirus first reported by China on December 31st, 2019, has led to a global health crisis that continues to challenge governments and public health organizations. Understanding COVID-19 knowledge, attitudes, and practices (KAP) is key for informing messaging strategies to contain the pandemic. Cross-national studies (e.g.: comparing China to the U.S.) are needed to better understand how trans-cultural differences may drive differences in pandemic response and behaviors. The goal of the study is to compare knowledge and perceptions of COVID-19 between adults in China and the U.S. These data will provide insight into challenges these nations may face in coordinating pandemic response. METHODS: This is a convergent mixed methods study comparing responses from China and the U.S. to a multinational COVID-19 KAP online survey. The survey included five quantitative constructs and five open-ended questions. Chinese respondents (n = 56) were matched for gender, age, education, perceived social standing, and time of survey completion with a U.S. cohort (n = 57) drawn from 10,620 U.S. RESPONDENTS: Quantitative responses were compared using T-test & Fisher-Exact tests. Inductive thematic analysis was applied to open-ended questions. RESULTS: Both U.S. and Chinese samples had relatively high intention to follow preventive behaviors overall. Differences in intended compliance with a specific recommendation appear to be driven by the different cultural norms in U.S. and China. Both groups expressed trepidation about the speed of COVID-19 vaccine development, driven by concern for safety among Chinese respondents, and concern for efficacy among U.S. RESPONDENTS: The Chinese cohort expressed worries about other countries' passive handling of the pandemic while the U.S. cohort focused on domestic responses from individuals and government. U.S. participants appeared more knowledgeable on some aspects of COVID-19. Different perspectives regarding COVID-19 origins were identified among the two groups. Participants from both samples reported high trust in health professionals and international health organizations. CONCLUSIONS: Mixed methods data from this cross-national analysis suggests sociocultural differences likely influence perceptions and knowledge of COVID-19 and its related public health policies. Discovering and addressing these culturally-based differences and perceptions are essential to coordinate a global pandemic response.

Essential and non-essential US workers' health behaviors during the COVID-19 pandemic.

We seek to quantify the relationship between health behaviors and work-related experiences during the COVID-19 pandemic by predicting health behaviors as a function of essential worker status, job loss, change in work hours, and COVID-19 experiences. We use multivariate models and survey data from 913 employed adults in a semi-rural mid-Atlantic US county, and test whether essential worker results vary by gender, parenthood, and/or university employment. Multivariate models indicate that essential workers used tobacco on more days (4.5; p <.01) and were less likely to sleep 8 h (odds ratio [OR] 0.6; p <.01) than non-essential workers. The risk of sleeping less than 8 h is concentrated among essential workers in the service industry (OR 0.5; p <.05) and non-parents (OR 0.5; p <.05). Feminine essential workers exercised on fewer days (-0.8; p <.05) than feminine non-essential workers. Workers with reduced work hours consumed more alcoholic drinks (0.3; p <.05), while workers with increased work hours consumed alcohol (0.3; p <.05) and exercised (0.6; p <.05) on more days. Essential worker status and changes in work hours are correlated with unhealthy behaviors during the COVID-19 pandemic.

Stress-Related Disorders of Family Members of Patients Admitted to the Intensive Care Unit With COVID-19.

Importance: The psychological symptoms associated with having a family member admitted to the intensive care unit (ICU) during the COVID-19 pandemic are not well defined. Objective: To examine the prevalence of symptoms of stress-related disorders, primarily posttraumatic stress disorder (PTSD), in family members of patients admitted to the ICU with COVID-19 approximately 90 days after admission. Design, Setting, and Participants: This prospective, multisite, mixed-methods observational cohort study assessed 330 family members of patients admitted to the ICU (except in New York City, which had a random sample of 25% of all admitted patients per month) between February 1 and July 31, 2020, at 8 academic-affiliated and 4 community-based hospitals in 5 US states. Exposure: Having a family member in the ICU with COVID-19. Main Outcomes and Measures: Symptoms of PTSD at 3 months, as defined by a score of 10 or higher on the Impact of Events Scale 6 (IES-6). Results: A total of 330 participants (mean [SD] age, 51.2 [15.1] years; 228 [69.1%] women; 150 [52.8%] White; 92 [29.8%] Hispanic) were surveyed at the 3-month time point. Most individuals were the patients' child (129 [40.6%]) or spouse or partner (81 [25.5%]). The mean (SD) IES-6 score at 3 months was 11.9 (6.1), with 201 of 316 respondents (63.6%) having scores of 10 or higher, indicating significant symptoms of PTSD. Female participants had an adjusted mean IES-6 score of 2.6 points higher (95% CI, 1.4-3.8; P < .001) than male participants, whereas Hispanic participants scored a mean of 2.7 points higher compared with non-Hispanic participants (95% CI, 1.0-4.3; P = .002). Those with graduate school experience had an adjusted mean score of 3.3 points lower (95% CI, 1.5-5.1; P < .001) compared with those with up to a high school degree or equivalent. Qualitative analyses found no substantive differences in the emotional or communication-related experiences between those with high vs low PTSD scores, but those with higher scores exhibited more distrust of practitioners. Conclusions and Relevance: In this cohort study, symptoms of PTSD among family members of ICU patients with COVID-19 were high. Hispanic ethnicity and female gender were associated with higher symptoms. Those with higher scores reported more distrust of practitioners.

'Us-Versus-Them': Othering in COVID-19 public health behavior compliance.

OBJECTIVE: We explored public perceptions about the COVID-19 pandemic to learn how those attitudes may affect compliance with health behaviors. METHODS: Participants were Central Pennsylvania adults from diverse backgrounds purposively sampled (based on race, gender, educational attainment, and healthcare worker status) who responded to a mixed methods survey, completed between March 25-31, 2020. Four open-ended questions were analyzed, including: "What worries you most about the COVID-19 pandemic?" We applied a pragmatic, inductive coding process to conduct a qualitative, descriptive content analysis of responses. RESULTS: Of the 5,948 respondents, 538 were sampled for this qualitative analysis. Participants were 58% female, 56% with ≥ bachelor's degree, and 50% from minority racial backgrounds. Qualitative descriptive analysis revealed four themes related to respondents' health and societal concerns: lack of faith in others; fears of illness or death; frustration at perceived slow societal response; and a desire for transparency in communicating local COVID-19 information. An "us-versus-them" subtext emerged; participants attributed non-compliance with COVID-19 behaviors to other groups, setting themselves apart from those Others. CONCLUSION: Our study uncovered Othering undertones in the context of the COVID-19 pandemic, occurring between groups of like-minded individuals with behavioral differences in 'compliance' versus 'non-compliance' with public health recommendations. Addressing the 'us-versus-them' mentality may be important for boosting compliance with recommended health behaviors.

Developing and testing an automated qualitative assistant (AQUA) to support qualitative analysis.

Qualitative research remains underused, in part due to the time and cost of annotating qualitative data (coding). Artificial intelligence (AI) has been suggested as a means to reduce those burdens, and has been used in exploratory studies to reduce the burden of coding. However, methods to date use AI analytical techniques that lack transparency, potentially limiting acceptance of results. We developed an automated qualitative assistant (AQUA) using a semiclassical approach, replacing Latent Semantic Indexing/Latent Dirichlet Allocation with a more transparent graph-theoretic topic extraction and clustering method. Applied to a large dataset of free-text survey responses, AQUA generated unsupervised topic categories and circle hierarchical representations of free-text responses, enabling rapid interpretation of data. When tasked with coding a subset of free-text data into user-defined qualitative categories, AQUA demonstrated intercoder reliability in several multicategory combinations with a Cohen's kappa comparable to human coders (0.62-0.72), enabling researchers to automate coding on those categories for the entire dataset. The aim of this manuscript is to describe pertinent components of best practices of AI/machine learning (ML)-assisted qualitative methods, illustrating how primary care researchers may use AQUA to rapidly and accurately code large text datasets. The contribution of this article is providing guidance that should increase AI/ML transparency and reproducibility.

Lower Intent to Comply with COVID-19 Public Health Recommendations Correlates to Higher Disease Burden in Following 30 Days.

OBJECTIVES: We sought to determine whether self-reported intent to comply with public health recommendations correlates with future coronavirus disease 2019 (COVID-19) disease burden. METHODS: A cross-sectional, online survey of US adults, recruited by snowball sampling, from April 9 to July 12, 2020. Primary measurements were participant survey responses about their intent to comply with public health recommendations. Each participant's intent to comply was compared with his or her local COVID-19 case trajectory, measured as the 7-day rolling median percentage change in COVID-19 confirmed cases within participants' 3-digit ZIP code area, using public county-level data, 30 days after participants completed the survey. RESULTS: After applying raking techniques, the 10,650-participant sample was representative of US adults with respect to age, sex, race, and ethnicity. Intent to comply varied significantly by state and sex. Lower reported intent to comply was associated with higher COVID-19 case increases during the following 30 days. For every 3% increase in intent to comply with public health recommendations, which could be achieved by improving average compliance by a single point for a single item, we estimate a 9% reduction in new COVID-19 cases during the subsequent 30 days. CONCLUSIONS: Self-reported intent to comply with public health recommendations may be used to predict COVID-19 disease burden. Measuring compliance intention offers an inexpensive, readily available method of predicting disease burden that can also identify populations most in need of public health education aimed at behavior change.

Voices from the Pandemic: A Qualitative Study of Family Experiences and Suggestions regarding the Care of Critically Ill Patients.

Rationale: Intensive care unit (ICU) visitation restrictions during the coronavirus disease (COVID-19) pandemic have drastically reduced family-engaged care. Understanding the impact of physical distancing on family members of ICU patients is needed to inform future policies. Objectives: To understand the experiences of family members of critically ill patients with COVID-19 when physically distanced from their loved ones and to explore ways clinicians may support them. Methods: This qualitative study of an observational cohort study reports data from 74 family members of ICU patients with COVID-19 at 10 United States hospitals in four states, chosen based on geographic and demographic diversity. Adult family members of patients admitted to the ICU with COVID-19 during the early phase of the pandemic (February-June 2020) were invited to participate in a phone interview. Interviews followed a semistructured guide to assess four constructs: illness narrative, stress experiences, communication experiences, and satisfaction with care. Interviews were transcribed verbatim and analyzed using an inductive approach to thematic analysis. Results: Among 74 interviewees, the mean age was 53.0 years, 55% were white, and 76% were female. Physical distancing contributed to substantial stress and harms (nine themes). Participants described profound suffering and psychological illness, unfavorable perceptions of care, and weakened therapeutic relationship between family members and clinicians. Three communication principles emerged as those most valued by family members: contact, consistency, and compassion (the 3Cs). Family members offered suggestions to guide clinicians faced with communicating with physically distanced families. Conclusions: Visitation restrictions impose substantial psychological harms upon family members of critically ill patients. Derived from the voics of family members, our findings warrant strong consideration when implementing visitation restrictions in the ICU and advocate for investment in infrastructure (including staffing and videoconferencing) to support communication. This study offers family-derived recommendations to operationalize the 3Cs to guide and improve communication in times of physical distancing during the COVID-19 pandemic and beyond.

Perceptions of Diseases of Despair by Members of Rural and Urban High-Prevalence Communities: A Qualitative Study.

Importance: Diseases of despair (ie, mortality or morbidity from suicidality, drug abuse, and alcoholism) were first characterized as increasing in rural White working-class populations in midlife with low educational attainment and associated with long-term economic decline. Excess mortality now appears to be associated with working-class citizens across demographic and geographic boundaries, but no known qualitative studies have engaged residents of rural and urban locales with high prevalence of diseases of despair to learn their perspectives. Objective: To explore perceptions about despair-related illness and potential intervention strategies among diverse community members residing in discrete rural and urban hotspots. Design, Setting, and Participants: In this qualitative study, high-prevalence hotspots for diseases of despair were identified from health insurance claims data in Central Pennsylvania. Four focus groups were conducted with 60 community members in organizations and coalitions from 3 census block group hotspot clusters in the health system between September 2019 and January 2020. Focus groups explored awareness and beliefs about causation and potential intervention strategies. Main Outcomes and Measures: A descriptive phenomenological approach was applied to thematic analysis, and a preliminary conceptual model was constructed to describe how various factors may be associated with perpetuating despair and with public health. Results: In total, 60 adult community members participated in 4 focus groups (44 women, 16 men; 40 White non-Hispanic, 17 Black, and 3 Hispanic/Latino members). Three focus groups with 43 members were held in rural areas with high prevalence of diseases of despair, and 1 focus group with 17 members in a high-prevalence urban area. Four themes emerged with respect to awareness and believed causation of despair-related illness, and participants identified common associated factors, including financial distress, lack of critical infrastructure and social services, deteriorating sense of community, and family fragmentation. Intervention strategies focused around 2 themes: (1) building resilience to despair through better community and organizational coordination and peer support at the local level and (2) encouraging broader state investments in social services and infrastructure to mitigate despair-related illness. Conclusions and Relevance: In this qualitative study, rural and urban community members identified common factors associated with diseases of despair, highlighting the association between long-term political and economic decline and public health and a need for both community- and state-level solutions to address despair. Health care systems participating in addressing community health needs may improve processes to screen for despair (eg, social history taking) and codesign primary, secondary, and tertiary interventions aimed at addressing factors associated with distress. Such actions have taken on greater urgency with the COVID-19 pandemic.

Exploring Behavioral Typologies to Inform COVID-19 Health Campaigns: A Person-Centered Approach.

As the United States continues to be ravaged by COVID-19, it becomes increasingly important to implement effective public health campaigns to improve personal behaviors that help control the spread of the virus. To design effective campaigns, research is needed to understand the current mitigation intentions of the general public, diversity in those intentions, and theoretical predictors of them. COVID-19 campaigns will be particularly challenging because mitigation involves myriad, diverse behaviors. This study takes a person-centered approach to investigate data from a survey (N = 976) of Pennsylvania adults. Latent class analysis revealed five classes of mitigation: one marked by complete adherence with health recommendations (34% of the sample), one by complete refusal (9% of the sample), and three by a mixture of adherence and refusal. Statistically significant covariates of class membership included relatively positive injunctive norms, risk due to essential workers in the household, personal knowledge of someone who became infected with COVID-19, and belief that COVID-19 was a leaked biological weapon. Additionally, trait reactance was associated with non-adherence while health mavenism was associated with adherence. These findings may be used to good effect by local healthcare providers and institutions, and also inform broader policy-making decisions regarding public health campaigns to mitigate COVID-19.

Unique Predictors of Intended Uptake of a COVID-19 Vaccine in Adults Living in a Rural College Town in the United States.

PURPOSE: To explore public confidence in a COVID-19 vaccine. DESIGN: Cross-sectional survey. SETTING: A rural college town in central Pennsylvania. SUBJECTS: Adult residents without minor children. MEASURES: The primary outcome was COVID-19 vaccination intention. Secondary measures included vaccination attitudes, norms, efficacy, past behavior, trust in the vaccination process, and sociodemographic variables of education, financial standing, political viewpoint, and religiosity. ANALYSIS: Descriptive statistics were used to describe quantitative data. Multivariate ordinal regression was used to model predictors of vaccine intention. RESULTS: Of 950 respondents, 55% were "very likely" and 20% "somewhat likely" to take a coronavirus vaccine, even though 70% had taken the flu vaccine since September 2019. The strongest predictors of vaccine acceptance were trust in the system evaluating vaccines and perceptions of local COVID-19 vaccination norms. The strongest predictors of negative vaccine intentions were worries about unknown side-effects and positive attitudes toward natural infection. Sociodemographic factors, political views, and religiosity did not predict vaccine intentions. CONCLUSION: Fewer adults intend to take a coronavirus vaccine than currently take the flu vaccine. Traditional sociodemographic factors may not be effective predictors of COVID-19 vaccine uptake. Although based on a small sample, the study adds to our limited understanding of COVID-19-specific vaccine confidence among some rural Americans and suggests that traditional public health vaccination campaigns based on sociodemographic characteristics may not be effective.

Knowledge, Perceptions, and Preferred Information Sources Related to COVID-19 Among Healthcare Workers: Results of a Cross Sectional Survey.

PURPOSE: To compare COVID-19 related knowledge, perceptions, and preferred information sources between healthcare workers and non-healthcare workers. DESIGN: Cross-sectional survey. SETTING: Web-based. SUBJECTS: Convenience sample of Pennsylvanian adults. MEASURES: Primary outcomes were binary responses to 15 COVID-19 knowledge questions weighted by a Likert scale assessing response confidence. ANALYSIS: Generalized linear mixed-effects models to assess comparisons between clinical decision makers (CDM), non-clinical decision makers working in healthcare (non-CDM) and non-healthcare workers (non-HCW). RESULTS: CDMs (n = 91) had higher overall knowledge than non-CDMs (n = 854; OR 1.81 [1.51, 2.17], p < .05). Overall knowledge scores were not significantly different between non-CDMs (n = 854) and non-HCW (n = 4,966; OR 1.03 [0.97, 1.09], p > .05). CONCLUSION: The findings suggest a need for improved education about COVID-19 for healthcare workers who are not clinical decision makers, as they play key roles in patient perceptions and compliance with preventive medicine during primary care visits.

Knowledge, Perceptions, and Preferred Information Sources Related to COVID-19 Among Central Pennsylvania Adults Early in the Pandemic: A Mixed Methods Cross-Sectional Survey.

PURPOSE: To explore public knowledge, understanding of public health recommendations, perceptions, and trust in information sources related to COVID-19. METHODS: A cross-sectional survey of central Pennsylvanian adults evaluated self-reported knowledge, and a convergent, mixed methods design was used to assess beliefs about recommendations, intended behaviors, perceptions, and concerns related to infectious disease risk, and trust of information sources. RESULTS: The survey was completed by 5,948 adults. The estimated probability of correct response for the basic knowledge score, weighted with confidence, was 0.79 (95% CI, 0.79-0.80). Knowledge was significantly higher in patients with higher education and nonminority race. While the majority of respondents reported that they believed following CDC recommendations would decrease the spread of COVID-19 in their community and intended to adhere to them, only 65.2% rated social isolation with the highest level of belief and adherence. The most trusted information source was federal public health websites (42.8%). Qualitative responses aligned with quantitative data and described concerns about illness, epidemiologic issues, economic and societal disruptions, and distrust of the executive branch's messaging. The survey was limited by a lack of minority representation, potential selection bias, and evolving COVID-19 information that may impact generalizability and interpretability. CONCLUSIONS: Knowledge about COVID-19 and intended adherence to behavioral recommendations were high. There was substantial distrust of the executive branch of the federal government, however, and concern about mixed messaging and information overload. These findings highlight the importance of consistent messaging from trusted sources that reaches diverse groups.

Characteristics and Outcomes Among Hospitalized COVID-19-Positive Patients in a Nonurban Environment.

INTRODUCTION: Virtually all hospitalized coronavirus disease-2019 (COVID-19) outcome data come from urban environments. The extent to which these findings are generalizable to other settings is unknown. Coronavirus disease-2019 data from large, urban settings may be particularly difficult to apply in military medicine, where practice environments are often semi-urban, rural, or austere. The purpose of this study is compare presenting characteristics and outcomes of U.S. patients with COVID-19 in a nonurban setting to similar patients in an urban setting. MATERIALS AND METHODS: This is a retrospective case series of adults with laboratory-confirmed COVID-19 infection who were admitted to Hershey Medical Center (HMC), a 548-bed tertiary academic medical center in central Pennsylvania serving semi-urban and rural populations, from March 23, 2020, to April 20, 2020 (the first month of COVID-19 admissions at HMC). Patients and outcomes of this cohort were compared to published data on a cohort of similar patients from the New York City (NYC) area. RESULTS: The cohorts had similar age, gender, comorbidities, need for intensive care or mechanical ventilation, and most vital sign and laboratory studies. The NYC's cohort had shorter hospital stays (4.1 versus 7.2 days, P < .001) but more African American patients (23% versus 12%, P = .02) and higher prevalence of abnormal alanine (>60U/L; 39.0% versus 5.9%, P < .001) and aspartate (>40U/L; 58.4% versus 42.4%, P = .012) aminotransferase, oxygen saturation <90% (20.4% versus 7.2%, P = .004), and mortality (21% versus 1.4%, P < .001). CONCLUSIONS: Hospitalists in nonurban environments would be prudent to use caution when considering the generalizability of results from dissimilar regions. Further investigation is needed to explore the possibility of reproducible causative systemic elements that may help improve COVID-19-related outcomes. Broader reports of these relationships across many settings will offer military medical planners greater ability to consider outcomes most relevant to their unique settings when considering COVID-19 planning.

Self-reported influenza and influenza-like symptoms in U.S. adults age 18-64 between September 1, 2019 and April 15, 2020.

BACKGROUND: The Influenza-like Illness Surveillance Network (ILINet) can indicate the presence of novel, widespread community pathogens. Comparing week-to-week reported influenza-like illness percentages may identify the time of year a novel pathogen is introduced. However, changes in health-seeking behavior during the COVID-19 pandemic call in to question the reliability of 2019-2020 ILINet data as a comparison to prior years, potentially rendering this system less reliable as a novel pathogen surveillance tool. Corroboration of trends seen in the 2019-2020 ILINet data lends confidence to the validity of those trends. This study compares predicted versus reported influenza and influenza-like illnesses in vaccinated adults as a surrogate measure of novel pathogen surveillance. METHODS: An online survey was used to ask US adults their influenza vaccination status, whether they were diagnosed with influenza after vaccination, and whether they experienced an influenza-like illness other than flu. RESULTS: Prevalence of self-reported flu diagnosis in adults age 18-64 who received the flu vaccine between September 1, 2019 and April 15, 2020 (n = 3,225) was 5.8 %, while self-reported flu or flu-like illness (without a flu diagnosis) was 17.9 %. CONCLUSION: Flu and flu-like illness in this sample of flu-vaccinated U.S. adults is significantly higher than predicted, consistent with substantially higher ILI's in 2019-20 compared to ILI's from 2018-19, suggesting that the ILI values reported during the COVID-19 pandemic may be appropriate for comparison to prior years.