Does receiving a SARS-CoV-2 antibody test result change COVID-19 protective behaviors? Testing risk compensation in undergraduate students with a randomized controlled trial.

BACKGROUND: Risk compensation, or matching behavior to a perceived level of acceptable risk, can blunt the effectiveness of public health interventions. One area of possible risk compensation during the SARS-CoV-2 pandemic is antibody testing. While antibody tests are imperfect measures of immunity, results may influence risk perception and individual preventive actions. We conducted a randomized control trial to assess whether receiving antibody test results changed SARS-CoV-2 protective behaviors. PURPOSE: Assess whether objective information about antibody status, particularly for those who are antibody negative and likely still susceptible to SARS-CoV-2 infection, increases protective behaviors. Secondarily, assess whether a positive antibody test results in decreased protective behaviors. METHODS: In September 2020, we enrolled 1076 undergraduate students, used fingerstick tests for SARS-CoV-2 antibodies, and randomized participants to receive their results immediately or delayed by 4 weeks. Two weeks later, participants completed a survey about their engagement in 4 protective behaviors (mask use, social event avoidance, staying home from work/school, ensuring physical distancing). We estimated differences between conditions for each of these behaviors, stratified by antibody status. For negative participants at baseline, we also estimated the difference between conditions for seroconversion over 8 weeks of follow-up. RESULTS: For the antibody negative participants (n = 1029) and antibody positive participants (n = 47), we observed no significant differences in protective behavior engagement between those who were randomized to receive test results immediately or after 4 weeks. For the baseline antibody negative participants, we also observed no difference in seroconversion outcomes between conditions. CONCLUSIONS: We found that receiving antibody test results did not lead to significant behavior change in undergraduate students whether the SARS-CoV-2 antibody result was positive or negative.

The association between social factors and COVID-19 protective behaviors and depression and stress among midwestern US college students.

PURPOSE: The aim of this cross-sectional study was to examine the relationship between social factors and COVID-19 protective behaviors and two outcomes: depressive and perceived stress symptoms. METHODS: In September 2020, 1,064 randomly selected undergraduate students from a large midwestern university completed an online survey and provided information on demographics, social activities, COVID-19 protective behaviors (i.e., avoiding social events and staying home from work and school), and mental health symptoms. Mental health symptoms were measured using the Center for Epidemiological Studies Depression-10 questionnaire for depression and the Perceived Stress Scale-10 for stress symptoms. RESULTS: The results showed respondents who were males and also the respondents who were "hanging out" with more people while drinking alcohol reported significantly lower depressive symptoms and lower stress symptoms. On the contrary, staying home from work or school "very often" was associated with higher stress symptoms, compared with "never/rarely" staying home from work/school. Similarly, having a job with in-person interaction was also associated with increased stress. CONCLUSIONS: These findings suggest that lack of social engagement was associated with depression and stress symptoms among college students during the COVID-19 pandemic. Planning social activities that align with recommended safety precautions, as well as meet students' social needs, should be an important priority for higher education institutions.

The relationship between acquaintance with a SARS-CoV-2 death, positive SARS-CoV-2 test results, and sleep duration among college students in fall 2020.

Background: The aim of this study was to test whether two SARS-CoV-2 experiences, knowing someone who had died of SARS-CoV-2 infection and having received a positive SARS-CoV-2 test result, were associated with shorter sleep duration among undergraduate students. Methods: An online cross-sectional study was conducted at a large public Midwestern university in September 2020 (fall semester). Self-reported average sleep duration and the exposures of interest, knowing someone who died from a SARS-CoV-2 infection and their own SARS-CoV-2 test result, were collected from 1,058 undergraduate study participants. Results: Respondents who knew someone who had died of a SARS-CoV-2 infection were more likely to report having a short sleep duration, compared to respondents who did not know someone who had died of a SARS-CoV-2 infection (aOR = 1.80, 95% CI: 1.14, 2.79). However, those with a positive SARS-CoV-2 test result were less likely to report a short sleep duration, compared to respondents without a positive test history (aOR = 0.47, 95% CI: 0.21, 0.91). Conclusions: These findings suggest that college students' knowing someone who had died of SARS-CoV-2 infection and having received a positive SARS-CoV-2 test result are associated with sleep duration. However, different experiences may impact sleep differently, so further research is warranted to better understand how unusual events impact the sleep of college students.

SARS-CoV-2 reinfections in a US university setting, Fall 2020 to Spring 2021.

BACKGROUND: SARS-CoV-2 reinfections are a public health concern because of the potential for transmission and clinical disease, and because of our limited understanding of whether and how well an infection confers protection against subsequent infections. Despite the public health importance, few studies have reported rigorous estimates of reinfection risk. METHODS: Leveraging Indiana University's comprehensive testing program to identify both asymptomatic and symptomatic SARS-CoV-2 cases, we estimated the incidence of SARS-CoV-2 reinfection among students, faculty, and staff across the 2020-2021 academic year. We contextualized the reinfection data with information on key covariates: age, sex, Greek organization membership, student vs faculty/staff affiliation, and testing type. RESULTS: Among 12,272 people with primary infections, we found a low level of SARS-CoV-2 reinfections (0.6%; 0.4 per 10,000 person-days). We observed higher risk for SARS-CoV-2 reinfections in Greek-affiliated students. CONCLUSIONS: We found evidence for low levels of SARS-CoV-2 reinfection in a large multi-campus university population during a time-period prior to widespread COVID-19 vaccination.

Does cigarette or E-cigarette use increase the risk for SARS-CoV-2 seroconversion among Midwestern college students?

OBJECTIVE: This longitudinal study tested the relationship between cigarette and e-cigarette use and SARS-CoV-2 seroconversion among US college students. PARTICIPANTS: Undergraduate students (n = 764), drawn from a randomly selected invitation-only pool from a large Midwestern university, that were initially negative for SARS-CoV-2 antibodies and were re-tested in November were included in this study conducted in Fall 2020. METHODS: Demographics and cigarette and e-cigarette use behaviors (nicotine use) were collected in a baseline survey. SARS-CoV-2 antibody tests were administered in September (baseline) and November (endline) of 2020. Log-binomial regression analyses were conducted to test the association between nicotine use and SARS-CoV-2 seroconversion. RESULTS: SARS-CoV-2 seroconversion was 5.2%. No statistically significant associations were found between nicotine use and SARS-CoV-2 seroconversion. CONCLUSIONS: Contrary to prior results, we found no association between nicotine use and SARS-CoV-2 seroconversion. Nicotine use may not be a key risk factor for COVID-19 acquisition in predominantly healthy college-aged populations.

HIV Testing by Public Health Centers and Municipalities and New HIV Cases During the COVID-19 Pandemic in Japan.

BACKGROUND: During the COVID-19 outbreak, facility capacity for HIV testing has been limited. Furthermore, people may have opted against HIV testing during this period to avoid COVID-19 exposure. We investigated the influence of the COVID-19 pandemic on HIV testing and the number of reported HIV cases in Japan. METHODS: We analyzed quarterly HIV/AIDS-related data from 2015 to the second quarter of 2020 using an anomaly detection approach. The data included the number of consultations, the number of HIV tests performed by public health centers or municipalities, and the number of newly reported HIV cases with and without an AIDS diagnosis. We further performed the same analysis for 2 subgroups: men who have sex with men (MSM) and non-Japanese persons. RESULTS: The number of HIV tests (9,584 vs. 35,908 in the year-before period) and consultations (11,689 vs. 32,565) performed by public health centers significantly declined in the second quarter of 2020, whereas the proportion of new HIV cases with an AIDS diagnosis (36.2% vs. 26.4%) significantly increased after removing the trend and seasonality effects. HIV cases without an AIDS diagnosis decreased (166 vs. 217), but the reduction was not significant. We confirmed similar trends for the men who have sex with men and non-Japanese subgroups. CONCLUSIONS: During the COVID-19 pandemic, the current HIV testing system in Japan seems to have missed more cases of HIV before developing AIDS. Continuously monitoring the situation and securing sufficient test resources by use of self-testing is essential to understand the clear epidemiological picture of HIV incidence during the COVID-19 pandemic.

Relationship between high-risk alcohol consumption and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroconversion: a prospective sero-epidemiological cohort study among American college students.

AIMS: To estimate the associations between high-risk alcohol consumption and (1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroconversion, (2) self-reported new SARS-CoV-2 infection and (3) symptomatic COVID-19. DESIGN: Prospective cohort study. SETTING: Indiana University Bloomington (IUB), IN, USA. PARTICIPANTS: A total of 1027 IUB undergraduate students (64% female), aged 18 years or older, residing in Monroe County, Indiana, seronegative for SARS-CoV-2 at study baseline. MEASUREMENTS: Primary exposure was high-risk alcohol consumption measured with an Alcohol Use Disorders Identification Test (AUDIT) questionnaire score of 8 or more. Primary outcome was SARS-CoV-2 seroconversion since baseline, assessed with two SARS-CoV-2 antibody tests, at baseline (September 2020) and end-line (November 2020). Secondary outcomes were (a) self-reported new SARS-CoV-2 infection at the study end-line and (b) self-reported symptomatic COVID-19 at baseline. FINDINGS: Prevalence of high-risk alcohol consumption was 32 %. In models adjusted for demographics, students with high-risk alcohol consumption status had 2.44 [95% confidence interval (CI) = 1.35, 4.25] times the risk of SARS-CoV-2 seroconversion and 1.84 (95% CI = 1.04, 3.28) times the risk of self-reporting a positive SARS-CoV-2 infection, compared with students with no such risk. We did not identify any association between high-risk alcohol consumption and symptomatic COVID-19 (prevalence ratio = 1.17, 95% CI = 0.93, 1.47). Findings from sensitivity analyses corroborated these results and suggested potential for a dose-response relationship. CONCLUSIONS: Among American college students, high-risk alcohol consumption appears to be associated with higher risk for severe acute respiratory syndrome coronavirus 2 seroconversion/infection.

Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example.

BACKGROUND: Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT's findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs. METHODS: In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students' self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs. RESULTS: We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys. CONCLUSIONS: REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs. TRIAL REGISTRATION: The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798 , date of registration: November 9, 2020.

If you build it, will they come? Social, economic, and psychological determinants of COVID-19 testing decisions.

BACKGROUND: The efficacy of testing and tracing programs to reduce COVID-19 transmission hinges not only on widespread access to testing, but also on the public's willingness to participate in them. To the extent that testing intentions are patterned by social determinants of health, this constitutes an understudied mechanism of disparities in COVID-19 morbidity and mortality. DESIGN: Using data from a representative household probability sample, the Person to Person Health Interview Study (n = 935), sociodemographic, economic, and psychological determinants of testing considerations were evaluated across six domains: treatment affordability, ability to work if positive, hospital effectiveness, symptom severity, proximity to infected, and risk of transmitting to others. RESULTS: Findings demonstrated significant differences in testing motivations across race/ethnicity, education level, socioeconomic status, and worry about self and loved ones. Notably, Black (p<0.01) and Latino (p<0.05) respondents and those experiencing financial strain (p<0.001) were disproportionately likely to indicate that resource factors would influence their decision to get tested. Desire to reduce transmission and concern about proximity to the infected were reported among those who expressed COVID-19 worries (p<0.001). CONCLUSION: Public health efforts to combat the COVID-19 pandemic must address social, economic, and psychological factors that enable and constrain individual behavior. Increasing access to preventative interventions and technologies, including vaccines, is unlikely to markedly reduce morbidity and mortality without effective messaging and economic support to improve uptake in vulnerable populations.

A Cross-Sectional Analysis of Demographic and Behavioral Risk Factors of Severe Acute Respiratory Syndrome Coronavirus 2 Seropositivity Among a Sample of U.S. College Students.

PURPOSE: Colleges and universities across the United States are developing and implementing data-driven prevention and containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Identifying risk factors for SARS-CoV-2 seropositivity could help to direct these efforts. This study aimed to estimate the associations between demographic factors and social behaviors and SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 diagnostic test. METHODS: In September 2020, we randomly sampled Indiana University Bloomington undergraduate students. Participants completed a cross-sectional online survey about demographics, SARS-CoV-2 testing history, relationship status, and risk behaviors. Additionally, during a subsequent appointment, participants were tested for SARS-CoV-2 antibodies using a fingerstick procedure and SARS-CoV-2 IgM/IgG rapid assay kit. We used unadjusted modified Poisson regression models to evaluate the associations between predictors of both SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 infection history. RESULTS: Overall, 1,076 students were included in the serological testing analysis, and 1,239 students were included in the SARS-CoV-2 infection history analysis. Current seroprevalence of SARS-CoV-2 was 4.6% (95% confidence interval: 3.3%, 5.8%). Prevalence of self-reported SARS-CoV-2 infection history was 10.3% (95% confidence interval: 8.6%, 12.0%). Greek membership, having multiple romantic partners, knowing someone in one's immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day a week, and hanging out with more than five people when drinking alcohol increased both the likelihood of seropositivity and SARS-CoV-2 infection history. CONCLUSION: Our findings have implications for American colleges and universities and could be used to inform SARS-CoV-2 prevention and control strategies on such campuses.

Estimation of the incubation period of COVID-19 using viral load data.

The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI: 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event.