Risk factors for infection with influenza A(H3N2) virus on a US university campus, October-November 2021.

BACKGROUND: Knowledge of the specific dynamics of influenza introduction and spread in university settings is limited. METHODS: Persons with acute respiratory illness symptoms received influenza testing by molecular assay during October 6-November 23, 2022. Viral sequencing and phylogenetic analysis were conducted on nasal swab samples from case-patients. Case-control analysis of a voluntary survey of persons tested was used to identify factors associated with influenza; logistic regression was conducted to calculate odds ratios and 95% CIs. A subset of case-patients tested during the first month of the outbreak was interviewed to identify sources of introduction and early spread. RESULTS: Among 3268 persons tested, 788 (24.1%) tested positive for influenza; 744 (22.8%) were included in the survey analysis. All 380 sequenced specimens were influenza A (H3N2) virus clade 3C.2a1b.2a.2, suggesting rapid transmission. Influenza (OR [95% CI]) was associated with indoor congregate dining (1.43 [1.002-2.03]), attending large gatherings indoors (1.83 [1.26-2.66]) or outdoors (2.33 [1.64-3.31]), and varied by residence type (apartment with ≥1 roommate: 2.93 [1.21-7.11], residence hall room alone: 4.18 [1.31-13.31], or with roommate: 6.09 [2.46-15.06], or fraternity/sorority house: 15.13 [4.30-53.21], all compared with single-dwelling apartment). Odds of influenza were lower among persons who left campus for ≥1 day during the week before their influenza test (0.49 [0.32-0.75]). Almost all early cases reported attending large events. CONCLUSIONS: Congregate living and activity settings on university campuses can lead to rapid spread of influenza following introduction. Isolating following a positive influenza test or administering antiviral medications to exposed persons may help mitigate outbreaks.

An improved method for determining frequency of multiple variants of SARS-CoV-2 in wastewater using qPCR assays.

Wastewater-based surveillance has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription polymerase chain reaction (RT-PCR) or whole genome sequencing (WGS). Rapid, reliable RT-PCR assays continue to be needed to determine the relative frequencies of VOCs and sub-lineages in wastewater-based surveillance programs. The presence of multiple mutations in a single region of the N-gene allowed for the design of a single amplicon, multiple probe assay, that can distinguish among several VOCs in wastewater RNA extracts. This approach which multiplexes probes designed to target mutations associated with specific VOC's along with an intra-amplicon universal probe (non-mutated region) was validated in singleplex and multiplex. The prevalence of each mutation (i.e. VOC) is estimated by comparing the abundance of the targeted mutation with a non-mutated and highly conserved region within the same amplicon. This is advantageous for the accurate and rapid estimation of variant frequencies in wastewater. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from several communities in Ontario, Canada in near real time from November 28, 2021 to January 4, 2022. This includes the period of the rapid replacement of the Delta variant with the introduction of the Omicron variant in these Ontario communities in early December 2021. The frequency estimates using this assay were highly reflective of clinical WGS estimates for the same communities. This style of qPCR assay, which simultaneously measures signal from a non-mutated comparator probe and multiple mutation-specific probes contained within a single qPCR amplicon, can be applied to future assay development for rapid and accurate estimations of variant frequencies.

Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities.

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

Explaining individual differences in cognitive performance: The role of anxiety, social support and living arrangements during COVID-19.

The present study investigated the relationship between anxiety, social support, living arrangements and cognitive performance of university students during the global pandemic. Two hundred and fifteen students participated by completing online questionnaires. Separate moderated multiple regression models were used to test whether social support (Family, Friends, Significant Other subscales of the Multidimensional Scale of Perceived Social Support) moderated the relationship between anxiety (Anxiety subscale of Depression, Anxiety Stress Scale), living arrangements (Living Alone vs Living with Friends and Family) and cognitive performance (Cognitive Failures Questionnaire), after controlling for comorbid depression. The results for each level of perceived social support suggested that anxiety was negatively associated with cognitive performance. Our most significant finding was that for students living alone, social support from a significant other offered a protective factor, whereby buffering the anxiety related cognitive deficits prevalent in those who reported lower social support. These data have important practical implications for supporting the social-emotional and academic needs of university students during the global pandemic.

Mental Health Measurement in a Post Covid-19 World: Psychometric Properties and Invariance of the DASS-21 in Athletes and Non-athletes.

Psychological science faces a call to action researching the implications of the corona virus disease 2019 (Covid-19) pandemic. Rapid reviews have reported that maintaining rigorous research standards is a priority for the field, such as ensuring reliable and valid measurement, when investigating people's experience of Covid-19 (O'Connor et al., 2020). However, no research to date has validated a measure mental health symptomology for an athlete population. The current research addresses this gap by examining the internal consistency, factor structure, invariance, and convergent validity of the Depression Anxiety and Stress Scale (DASS-21; Lovibond and Lovibond, 1995) in two athlete samples. Participants completed the DASS-21 and sport-specific measures of mental health such as the Profile of Mood States - Depression subscale (POMS-D), Sport Anxiety Scale-2 (SAS-2), Athlete Burnout Questionnaire (ABQ), and Athlete Psychological Strain Questionnaire (APSQ). In sample one (n = 894), results of exploratory structural equation modeling indicated that a three-factor model provided good fit to the data, but a bifactor model provided better fit. Factor loadings indicated minimal misspecification and higher loadings on the general-factor. Invariance testing suggested equivalence across gender, athletic expertise, sport type, and injury status. Further, latent mean differences analyses indicated that females and injured athletes scored higher than male and non-injured athletes on all DASS-21 factors reporting higher mental health symptomology, those with more expertise scored higher on the general-factor and depression and those with less expertise scored higher on anxiety and stress, and no differences between team and individual athletes. In sample two (n = 589), the bifactor structure was replicated. Results largely supported the scales convergent validity with depression predicting POMS-D scores, whereas all three subscales predicted the SAS-2, ABQ, and APSQ scores. Internal consistency was acceptable in both samples. The current work provides initial support for use of the DASS-21 as an operationalisation of mental health symptomology in athletes. Theoretical and practical implications of these results are discussed.

Early Warning Measurement of SARS-CoV-2 Variants of Concern in Wastewaters by Mass Spectrometry

Wastewater surveillance has rapidly emerged as an early warning tool to track COVID-19. However, the early warning measurement of new SARS-CoV-2 variants of concern (VOCs) in wastewaters remains a major challenge. We herein report a rapid analytical strategy for quantitative measurement of VOCs, which couples nested polymerase chain reaction and liquid chromatography–mass spectrometry (nPCR-LC-MS). This method showed a greater selectivity than the current allele-specific quantitative PCR (AS-qPCR) for tracking new VOC and allowed the detection of multiple signature mutations in a single measurement. By measuring the Omicron variant in wastewaters across nine Ontario wastewater treatment plants serving over a three million population, the nPCR-LC-MS method demonstrated a better quantification accuracy than next-generation sequencing (NGS), particularly at the early stage of community spreading of Omicron. This work addresses a major challenge for current SARS-CoV-2 wastewater surveillance by rapidly and accurately measuring VOCs in wastewaters for early warning.

The impact of the COVID-19 pandemic on physical activity habits at a residential university.

OBJECTIVE: To assess changes in physical activity (PA) after a COVID-19 shutdown on a primarily residential university campus. METHODS: Eighty students, faculty, and staff (FS) of a university (age: 32.2 ± 13.6 yr) who wore a consumer wearable technology (CWT) device completed an anonymous survey by inputting data for 30 days prior to- and 30 days following an academic break in 2020, in which the university transitioned to remote learning. RESULTS: Steps decreased after spring break in all subjects (p < .001), but steps were impacted to a greater extent in students. 30-day, weekday, and weekend step averages all decreased in students (p < .001). FS were able to maintain their weekend step averages. CONCLUSIONS: PA decreased in a university community after the COVID-19 shutdown. Students, no longer active transport for campus life, saw a greater impact on their PA. These changes could have an impact on health status.