Unrealistic Optimism and Risk for COVID-19 Disease.

Risk perception and consequently engagement in behaviors to avoid illness often do not match actual risk of infection, morbidity, and mortality. Unrealistic optimism occurs when individuals falsely believe that their personal outcomes will be more favorable than others' in the same risk category. Natural selection could favor overconfidence if its benefits, such as psychological resilience, outweigh its costs. However, just because optimism biases may have offered fitness advantages in our evolutionary past does not mean that they are always optimal. The current project examined relationships among personal risk for severe COVID-19, risk perceptions, and preventative behaviors. We predicted that those with higher risk of severe COVID-19 would exhibit unrealistic optimism and behave in ways inconsistent with their elevated risk of morbidity and mortality. Clinical risk scores for severe COVID-19 were calculated and compared with COVID-19 threat appraisal, compliance with shelter-in-place orders (March 13-May 22, 2020) and travel restrictions, compliance with public health recommendations, and potential covariates like self-rated knowledge about COVID-19 in a robust dataset including 492 participants from McLennan County, TX, USA. While those with high clinical risk acknowledged their greater likelihood of experiencing severe illness if infected, they actually reported lower perceived likelihood of becoming infected in the first place. While it is possible that those with higher clinical risk scores truly are less likely to become infected, the pattern and significance of these results held after controlling for possible occupational exposure, household size, and other factors related to infection probability. Higher clinical risk also predicted more recent travel within Texas and lower distress during the pandemic (i.e., feeling less stressed, depressed, and helpless). Additional behavioral data suggested that those with higher clinical risk scores did not generally behave differently than those with lower scores during the shelter-in-place order. While unrealistic optimism may provide some short-term psychological benefits, it could be dangerous due to improper assessment of hazardous situations; inferring that optimism bias has evolutionary origins does not mean that unrealistic optimism is "optimal" in every situation. This may be especially true when individuals face novel sources (or scales) of risk, such as a global pandemic.

Age-Dependent Relationships Between Disease Risk and Testosterone Levels: Relevance to COVID-19 Disease.

Testosterone levels in men appear to be prognostic of a number of disease outcomes, including severe COVID-19 disease. Testosterone levels naturally decline with age and are lower in individuals with a number of comorbidities and chronic conditions. Low testosterone may therefore be both a cause and a consequence of illness, including COVID-19 disease. The present project examines whether preexisting conditions for severe COVID-19 disease were themselves related to serum-free testosterone levels in men who had not been infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. A clinical risk score for severe COVID-19 disease was computed based on the results of previously published meta-analyses and cohort studies, and relationships between this score and testosterone levels were tested in 142 men ages 19 to 82 years. Greater burden of preexisting conditions for severe COVID-19 disease was related to lower testosterone levels among men younger than 40 years of age. In older men, the decrease in testosterone that accompanies aging attenuated the effect of the clinical risk score on free testosterone levels. Given that older age itself is a predictor of COVID-19 disease severity, these results together suggest that the presence of preexisting conditions may confound the relationship between testosterone levels and COVID-19 disease outcomes in men. Future research examining relationships among testosterone and outcomes related to infectious and chronic diseases should consider potential confounds, such as the role of preexisting conditions.

Waco COVID Survey: A Community-Based SARS-CoV-2 Serological Surveillance Study in Central Texas.

In early-2020, the epidemiology of the SARS-CoV-2 virus was still in discovery and initial reports about the role of asymptomatic individuals were developing. The Waco COVID Survey was implemented in mid-2020 with targeted serological surveillance to assess relationships among risk factors and asymptomatic transmission in McLennan County, Texas, USA. Because large-scale random sampling of the population was not feasible, a targeted and repeated sampling of specific clustered groups of asymptomatic individuals was employed. This included four waves (initial intake [n = 495], two follow-ups separated by a month [n = 348; n = 287], and a final follow-up one year later [n = 313]) of sampling participants in different risk categories: (a) healthcare workers (e.g., physicians, nurses, etc.) and first responders, (b) essential service employees (e.g., convenience and grocery stores, restaurants focused on delivery and carry-out), (c) employees whose businesses began reopening on May 1 (e.g., dine-in restaurants, churches, etc.) including church attendees, and (d) individuals that practiced intensive isolation. The survey collected information on demographics, compliance with public health recommendations, satisfaction with government responses, health history, attitudes regarding the SARS-CoV-2 virus and COVID-19 disease, health behaviors, personality, stress, and general affect. Results illustrate pandemic fatigue over time, the influence of political leniency on opinions and behaviors, the importance of face coverings in preventing infection, and the positive impact of vaccination in the community. This project remains one of the largest longitudinal SARS-CoV-2 antibody seroprevalence surveys in the US, and details for successful implementation and community involvement are discussed.

Exploring links between pathogen avoidance motivation, COVID-19 case counts, and immune function.

OBJECTIVES: The selection pressures exerted by pathogens have played important roles in shaping the biology and behavior of animals, including humans. Immune systems recognize and respond to cues of infection or damage by coordinating cellular, humoral, and metabolic shifts that promote recovery. Moreover, animals also possess a repertoire of behavioral tools to help combat the threat of pathogens, often referred to as the behavioral immune system. Recently, researchers have begun to examine how cognitive, affective, and behavioral disease avoidance mechanisms interact with the biological immune system. METHODS: The present study explored relationships among individual differences in behavioral immune system activity (e.g., pathogen disgust), shifts in SARS-CoV-2 infection risk (i.e., 7-day case averages), and immune function in a community cohort from McLennan County, Texas, USA (n = 387). RESULTS: Levels of disease concern were not consistently associated with immune markers. However, serum levels of IFN-γ, TNF-α, IL-2, and IL-8, as well as serum killing ability of Escherichia coli, each varied with case counts. Additional analyses found that case counts also predicted changes in stress physiology, but not subjective measures of distress. However, follow-up mediation models did not provide evidence that relationships between case counts and immunological outcomes were mediated through levels of stress. CONCLUSIONS: The present project provides initial evidence that markers of immune function may be sensitive to changes in infection risk during the COVID-19 pandemic. This adds to the growing body of research finding relationships among behavioral and biological pathogen management mechanisms.

Survey of COVID-19 isolation cases at a major university campus in the United States.

Objective: Baylor University established a surveillance system to assess the needs of students and faculty in isolation from SARS-CoV-2 as well as any longer-term symptoms. Participants: Overall, there were 309 responses between March 20 and May 19, 2021. Methods: A survey covering experience in isolation, symptoms, vaccination, and demographic characteristics was emailed to individuals on Day 7 of isolation; a follow-up health survey was sent 30 days later. Results: Only 9.6% of respondents reported needing assistance while in isolation. Nearly 75% of respondents experienced COVID-19 symptoms in isolation, and 31.9% had remaining symptoms after isolation. Older age, being male, and more severe symptoms were associated with longer symptom duration. Those vaccinated had lower odds of developing symptoms and having symptoms remaining post-isolation. Conclusions: The present study adds to our understanding of long-COVID in young adult populations, while providing a framework for similar institutions to sustain operations during a global pandemic.

Longitudinal changes in COVID-19 concern and stress: Pandemic fatigue overrides individual differences in caution.

Background: Pandemic fatigue describes a phenomenon whereby individuals experience a decrease in COVID-19 concern over time, despite their risk for infection remaining stable, or even increasing. Individual differences in the experience of pandemic fatigue may have important implications for people's adherence to public health recommendations. Design and methods: Using data collected from a large community cohort in McLennan County, TX, longitudinal changes in COVID-19-related concern, stress, and affect across three appointments separated by approximately 4 weeks (July-November 2020) were examined. About 495, 349, and 286 participants completed one, two, and three appointments, respectively. Changes to stress physiology and local travel over time were also analyzed. Results: Results of a latent class growth analysis revealed four distinct classes of individuals: (a) low concern, low stress, (b) moderate concern, moderate stress, (c) moderate concern, low stress, and (d) high concern, high stress. Despite differences between latent classes in initial levels of concern, stress, and negative affect, levels of each variable decreased over time for all groups. While this reduction of concern did not coincide with changes in local travel, it was reflected in heart rate and blood pressure. Conclusions: Together, these results suggest a general trend of pandemic fatigue in the sample, even for those with moderate-to-high levels of initial COVID-19 stress and concern. Such findings may provide insights into the expected challenges of promoting compliance with public health recommendations as the pandemic continues.

Dynamics of temperature change during experimental respiratory virus challenge: Relationships with symptoms, stress hormones, and inflammation.

Thermoregulation is a complex, dynamic process involving coordination between multiple autonomic, endocrine, and behavioral mechanisms. In the context of infection, this intricate machinery generates fever, a process believed to serve vital functions in the body's defense against pathogens. In addition to increasing core temperature, infection can lead to changes in the dynamic fluctuations in body temperature over time. The patterns of these deviations may convey information about the health of the body and the course of illness. Here, we utilized dynamic structural equation modeling to explore patterns of body temperature change following an experimental respiratory virus challenge in an aggregated, archival dataset of human participants (N = 1,412). We also examined whether temperature dynamics during infection were related to symptom severity, as well as individual differences in biomarkers of inflammation and stress. We found that individuals meeting the criteria for infection exhibited higher but less stable body temperatures over time compared to those not meeting criteria of infection. While temperature parameters did not reliably predict symptom severity, higher levels of nasal proinflammatory cytokines were associated with lower, more consistent temperatures during the study period. Further, levels of salivary cortisol and urinary catecholamines measured at the beginning of the study appeared to have disparate effects on temperature change. In sum, this research highlights the utility of dynamic time series modeling as a framework for studying body temperature change and lends novel insights into how stress may interact with infection to influence patterns of thermoregulation.