Estimation of Covid-19 Prevalence Dynamics from Pooled Data

Estimating the prevalence of a disease, such as COVID-19, is necessary for evaluating and mitigating risks of its transmission. Estimates that consider how prevalence changes with time provide more information about these risks but are difficult to obtain due to the necessary survey intensity and commensurate testing costs. Motivated by a dataset on COVID-19, from the University of Notre Dame, we propose pooling and jointly testing multiple samples to reduce testing costs. A nonparametric, hierarchical Bayesian model is used to infer population prevalence from the pooled test results without needing to retest individuals from pools that test positive. This approach is shown to reduce uncertainty compared to individual testing at the same budget and to produce similar estimates compared to individual testing at a much higher budget through simulation studies and an analysis of COVID-19 infections at Notre Dame.

EXPLORING THE GENOME-WIDE GENETIC OVERLAP BETWEEN ANXIETY AND FEAR DISORDERS

: Background: Twin studies have consistently shown a high genetic overlap amongst anxiety disorders and depression. Some research has also identified modest genetic specificity to fear-based anxiety disorders not shared with general anxiety. Identifying the genetic variants shared amongst all anxiety disorders or specific to one or more requires large sample sizes. Measuring anxiety disorders in large cohorts typically involves in-depth symptom-based diagnoses or minimally phenotyped single-item self-report diagnoses. A trade-off exists between maximising sample size and the level of detail in the phenotyping. Aims: First, to explore genetic correlations between generalised anxiety disorder (GAD) and the fear disorders (panic disorder, agoraphobia, specific phobia and social phobia) using a combination of in-depth and minimal phenotyping. Second, to compare the results from using minimal phenotyping of the anxiety disorders to that of in-depth phenotyping. Methods: We will use two case-only samples for analyses: the Genetic Links to Anxiety and Depression (GLAD) Study (∼N = 18,000) and the Australian Genetics of Depression Study (AGDS) (∼18,000). In addition, we will use three studies that provide both cases and controls: the COVID-19 Psychiatric and Neurological Genetics (COPING) study (N = ∼10,000), the QSkin study (N = ∼18,000) and the UK Biobank (N = ∼157,366). We will conduct three independent sets of case-control anxiety disorder genome-wide association studies (GWAS) before meta-analysing all five samples together (expected N cases ∼53,000, N controls ∼160,000). Results from GWAS meta-analyses of lifetime anxiety disorder, GAD, and fear-based disorders will be used to explore genetic correlations across anxiety disorders and depression and a wide range of complex traits. As sensitivity analyses, we will explore genetic correlations between anxiety phenotypes assessed using minimally phenotyped single-item diagnoses versus in-depth symptom-based diagnoses. Results: We hypothesise that the anxiety disorders will have a SNP-based heritability of approximately 15%. We also hypothesise that GAD and fear-based disorders will be moderately to highly genetically correlated, with some genetic variants that are specific to the fear disorders [1]. Disclosure: Nothing to disclose.

Depression, anxiety and PTSD symptoms before and during the COVID-19 pandemic in the UK.

BACKGROUND: The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors. METHOD: Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change. RESULTS: Prospective symptom analyses showed small decreases in depression (PHQ-9: -0.43 points) and anxiety [generalised anxiety disorder scale - 7 items (GAD)-7: -0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status. CONCLUSIONS: We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

Coronaviruses and Australian bats: A review in the midst of a pandemic

Australia's 81 bat species play vital ecological and economic roles via suppression of insect pests and maintenance of native forests through pollination and seed dispersal. Bats also host a wide diversity of coronaviruses globally, including several viral species that are closely related to SARS-CoV-2 and other emergent human respiratory coronaviruses. Although there are hundreds of studies of bat coronaviruses globally, there are only three studies of bat coronaviruses in Australian bat species, and no systematic studies of drivers of shedding. These limited studies have identified two betacoronaviruses and seven alphacoronaviruses, but less than half of Australian species are included in these studies and further research is therefore needed. There is no current evidence of spillover of coronaviruses from bats to humans in Australia, either directly or indirectly via intermediate hosts. The limited available data are inadequate to determine whether this lack of evidence indicates that spillover does not occur or occurs but is undetected. Conversely, multiple international agencies have flagged the potential transmission of human coronaviruses (including SARS CoV-2) from humans to bats, and the consequent threat to bat conservation and human health. Australia has a long history of bat research across a broad range of ecological and associated disciplines, as well as expertise in viral spillover from bats. This strong foundation is an ideal platform for developing integrative approaches to understanding bat health and sustainable protection of human health. © 2020 Journal Compilation