Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models (preprint)

During the SARS-CoV2 pandemic, epidemic models have been central to policy-making. Public health responses have been shaped by model-based projections and inferences, especially related to the impact of various non-pharmaceutical interventions. Accompanying this has been increased scrutiny over model performance, model assumptions, and the way that uncertainty is incorporated and presented. Here we consider a population-level model, focusing on how distributions representing host infectiousness and the infection-to-death times are modelled, and particularly on the impact of inferred epidemic characteristics if these distributions are misspecified. We introduce an SIR -type model with the infected population structured by ‘infected age’, i.e. the number of days since first being infected, a formulation that enables distributions to be incorporated that are consistent with clinical data. We show that inference based on simpler models without infected age, which implicitly misspecify these distributions, leads to substantial errors in inferred quantities relevant to policy-making, such as the reproduction number and the impact of interventions. We consider uncertainty quantification via a Bayesian approach, implementing this for both synthetic and real data focusing on UK data in the period 15 Feb–14 Jul 2020, and emphasising circumstances where it is misleading to neglect uncertainty.

Prospective examination of mental health in university students during the COVID-19 pandemic (preprint)

Background: The impact of changing social restrictions on the mental health of students during the COVID-19 pandemic warrants exploration. Aims: To prospectively examine changes to university students mental health during the pandemic. Methods: Students completed repeated online surveys at three time points (October 2020 (baseline), February 2021, March 2021) to explore relationships between demographic and psychological factors (loneliness and positive mood) and mental health outcomes (depression, anxiety, and stress). Results: A total of 893 students participated. Depression and anxiety levels were higher at all timepoints than pre-pandemic normative data (p

Students’ Views Towards SARS-CoV-2 Mass Asymptomatic Testing, Social Distancing and Self-Isolation in a University Setting during the COVID-19 Pandemic: A Qualitative Study (preprint)

We aimed to explore university students’ perceptions and experiences of SARS-CoV-2 mass asymptomatic testing, social distancing and self-isolation during the COVID-19 pandemic. This qualitative study comprised of four rapid online focus groups conducted at a higher education institution in England during high alert (tier 2) national COVID-19 restrictions. Data were analysed thematically. Participants were purposively sampled university students (n = 25) representing a range of gender, age, living circumstances (on/off campus) and SARS-CoV-2 testing/self-isolation experiences. Six themes with 16 sub-themes emerged from the analysis of the qualitative data: ‘Term-time Experiences’, ‘Risk Perception and Worry’, ‘Engagement in Protective Behaviours’, ‘Openness to Testing’, ‘Barriers to Testing’ and ‘General Wellbeing’. Students described feeling safe on campus, believed most of their peers are adherent to protective behaviours and were positive towards asymptomatic testing in university settings. University communications about COVID-19 testing and social behaviours need to be timely and presented in a more inclusive way to reach groups of students who currently feel marginalised. Barriers to engagement with SARS-CoV-2 testing, social distancing and self-isolation were primarily associated with fear of the mental health impacts of self-isolation, including worry about how they will cope, high anxiety, low mood, guilt relating to impact on others and loneliness. Loneliness in students could be mitigated through increased intra-university communications and a focus on establishment of low COVID-risk social activities to help students build and enhance their social support networks. These findings are particularly pertinent in the context of mass asymptomatic testing programmes being implemented in educational settings and high numbers of students being required to self-isolate. Universities need to determine the support needs of students during self-isolation and prepare for the long-term impacts of the pandemic on student mental health and welfare support services.

Experiences of the COVID-19 pandemic: cross-sectional analysis of risk perceptions and mental health in a student cohort (preprint)

Objective: This study examined the COVID-19 risk perceptions and mental health of university students on returning to campus in the midst of the COVID-19 pandemic. Methods: An online survey was completed during the first four weeks of the academic year (October 2020) by 897 university students. The survey included demographics and measures of experiences of COVID-19 testing, self-isolation, shielding, perceived risk, mental health and indices capturing related psychological responses to the pandemic. Results: We observed higher levels of depression and anxiety, but not stress, in students compared with pre-pandemic normative data, but lower than levels reported earlier in the pandemic in other similar cohorts. Depression, anxiety and stress were independently associated with greater loneliness and reduced positive mood. Greater worry about COVID-19 was also independently associated with anxiety and stress. Female students and those with pre-existing mental health disorders were at greatest risk of poor mental health outcomes. Conclusion: Although students perceived themselves at only moderate risk of COVID-19, the prevalence of depression and anxiety among university students should remain a concern. Universities should provide adequate support for students mental health during term-time. Interventions to reduced loneliness and worry, and improve mood, may benefit students overall mental well-being.