Machine learning forecasting for COVID-19 pandemic-associated effects on paediatric respiratory infections.

OBJECTIVE: The COVID-19 pandemic and subsequent government restrictions have had a major impact on healthcare services and disease transmission, particularly those associated with acute respiratory infection. This study examined non-identifiable routine electronic patient record data from a specialist children's hospital in England, UK, examining the effect of pandemic mitigation measures on seasonal respiratory infection rates compared with forecasts based on open-source, transferable machine learning models. METHODS: We performed a retrospective longitudinal study of respiratory disorder diagnoses between January 2010 and February 2022. All diagnoses were extracted from routine healthcare activity data and diagnosis rates were calculated for several diagnosis groups. To study changes in diagnoses, seasonal forecast models were fit to prerestriction period data and extrapolated. RESULTS: Based on 144 704 diagnoses from 31 002 patients, all but two diagnosis groups saw a marked reduction in diagnosis rates during restrictions. We observed 91%, 89%, 72% and 63% reductions in peak diagnoses of 'respiratory syncytial virus', 'influenza', 'acute nasopharyngitis' and 'acute bronchiolitis', respectively. The machine learning predictive model calculated that total diagnoses were reduced by up to 73% (z-score: -26) versus expected during restrictions and increased by up to 27% (z-score: 8) postrestrictions. CONCLUSIONS: We demonstrate the association between COVID-19 related restrictions and significant reductions in paediatric seasonal respiratory infections. Moreover, while many infection rates have returned to expected levels postrestrictions, others remain supressed or followed atypical winter trends. This study further demonstrates the applicability and efficacy of routine electronic record data and cross-domain time-series forecasting to model, monitor, analyse and address clinically important issues.

Exploring the Psychological Impacts of COVID-19 Social Restrictions on International University Students: A Qualitative Study.

The global COVID-19 pandemic has impacted on the mental well-being of university students, but little attention has been given to international students, who may have a unique experience and perspective. The aim of this study was to explore the views of international students and university staff towards COVID-19 restrictions, self-isolation, their well-being, and support needs, through eight online focus groups with international students (n = 29) and semi-structured interviews with university staff (n = 17) at a higher education institution in England. Data were analysed using an inductive thematic approach, revealing three key themes and six subthemes: (1) practical, academic, and psychological challenges faced during self-isolation and the COVID-19 pandemic; (2) coping strategies to self-isolation and life during the pandemic; and (3) views on further support needed for international students. International students faced practical, academic, and psychological challenges during the COVID-19 pandemic, particularly relating to the rapid transition to online learning and the impact of social restrictions on integration with peers and well-being. Online social connections with peers, family, or new acquaintances reduced feelings of isolation and encouraged involvement in university life. Despite raising mental health concerns, most international students did not access mental health support services. Staff related this to perceived stigma around mental health in certain cultural groups. In conclusion, international students experienced specific practical and emotional challenges during the pandemic, and are at risk of mental ill-health, but may not actively seek out support from university services. Proactive and personalised approaches to student support will be important for positive student experiences and the retention of students who are studying abroad in the UK higher education system.

An exploration of 11 years of seasonality in diagnoses at GOSH

BackgroundWith the extensive impact of the COVID-19 pandemic and subsequent government interventions on the development, diagnosis and treatment of illnesses, building an understanding of ‘typical’ diagnosis trends at GOSH is critical for predicting future demands and potential clinical challenges. Seasonality analysis is an effective method with which one can explore, model and predict the occurrence of events over time when – as with many common diagnoses at GOSH – they generally exhibit a periodic trend over the year.MethodsTo investigate diagnosis seasonality at GOSH, we have extracted all diagnoses recorded in the Legacy and Epic systems, since the year 2010. We have developed an analytics pipeline that uses these data to compute historical rates for any given diagnosis, or group of diagnoses. Based on these diagnosis rates, our pipeline applies a widely used regressive, multiplicative, seasonal decomposition model with integrated model evaluation.ResultsFor the analysis, a total of 3,480,887 diagnosis events were considered across 29,529 patients between receiving a diagnosis between 1stJanuary 2010 and 30th September 2021. This exploration presents data on many of the common diagnoses at GOSH that exhibit a clear seasonal trend in combination with a statistically significant deviation from that trend since March 2020, likely due to the pandemic. In addition, we illustrate how the available data and model allow us to predict the diagnostic shortfall during the same period.

Impacts of the COVID-19 Pandemic and Self-Isolation on Students and Staff in Higher Education: A Qualitative Study.

This qualitative study explored the impact of COVID-19 self-isolation and social restriction measures on university students, through the perspectives of both students and the staff supporting them. The study comprised 11 focus groups (students) and 26 individual interviews (staff) at a higher education institution in England during a period of national lockdown (January-March 2021). Participants were university students (n = 52) with self-isolation experiences and university staff (n = 26) with student-facing support roles. Focus group and interview data were combined and analysed using an inductive thematic approach. Four themes emerged: 'Adaptation during the pandemic', 'Practical, environmental, and emotional challenges of self-isolating', 'Social factors and their impact on COVID-19 testing and self-isolation adherence', and 'Supporting self-isolation'. Students and staff struggled with the imposed restrictions and shift to online education. Students found it difficult to adapt to new expectations for university life and reported missing out on professional and social experiences. Students and staff noted concerns about the impact of online teaching on educational outcomes. Students endorsed varied emotional responses to self-isolation; some felt unaffected whilst others experienced lowered mood and loneliness. Students were motivated by pro-social attitudes; campaigns targeting these factors may encourage continued engagement in protective behaviours. Staff struggled to manage their increased workloads delivering support for self-isolating students. Universities must consider the support needs of students during self-isolation and prepare for the long-term impacts of the pandemic on student wellbeing and educational attainment. Greater support should be provided for staff during transitional periods, with ongoing monitoring of workforce stress levels warranted.

Perceptions and Experiences of the University of Nottingham Pilot SARS-CoV-2 Asymptomatic Testing Service: A Mixed-Methods Study.

We aimed to explore student and staff perceptions and experiences of a pilot SARS-CoV-2 asymptomatic testing service (P-ATS) in a UK university campus setting. This was a mixed-method study comprised of an online survey, and thematic analysis of qualitative data from interviews and focus groups conducted at the mid-point and end of the 12-week P-ATS programme. Ninety-nine students (84.8% female, 70% first year; 93.9% P-ATS participants) completed an online survey, 41 individuals attended interviews or focus groups, including 31 students (21 first year; 10 final year) and 10 staff. All types of testing and logistics were highly acceptable (virus: swab, saliva; antibody: finger prick) and 94.9% would participate again. Reported adherence to weekly virus testing was high (92.4% completed ≥6 tests; 70.8% submitted all 10 swabs; 89.2% completed ≥1 saliva sample) and 76.9% submitted ≥3 blood samples. Students tested to "keep campus safe", "contribute to national efforts to control COVID-19", and "protect others". In total, 31.3% had high anxiety as measured by the Generalized Anxiety Disorder scale (GAD-7) (27.1% of first year). Students with lower levels of anxiety and greater satisfaction with university communications around P-ATS were more likely to adhere to virus and antibody tests. Increased adherence to testing was associated with higher perceived risk of COVID-19 to self and others. Qualitative findings revealed 5 themes and 13 sub-themes: "emotional responses to COVID-19", "university life during COVID-19", "influences on testing participation", "testing physical and logistical factors" and "testing effects on mental wellbeing". Asymptomatic COVID-19 testing (SARS-CoV-2 virus/antibodies) is highly acceptable to students and staff in a university campus setting. Clear communications and strategies to reduce anxiety are likely to be important for testing uptake and adherence. Strategies are needed to facilitate social connections and mitigate the mental health impacts of COVID-19 and self-isolation.