Age Specific Associations Between Underlying Conditions and Hospitalisation, Death and In-Hospital Death Among Confirmed COVID-19 Cases: A Multi-Country Study Based on Surveillance Data (preprint)

Background: Underlying conditions have been found to be associated with severe COVID-19 outcomes, such as hospitalisation and death. This study aimed to estimate age-specific adjusted relative and absolute effects of individual underlying conditions on hospitalisation, death and in-hospital death among COVID-19 cases.Methods: We analysed case-based COVID-19 data submitted to The European Surveillance System (TESSy) between 2 June and 13 December 2020 by nine European countries. We individually assessed the association between 11 underlying conditions with hospitalisation, death and in-hospital death. Two additional categorical exposures were created: number of underlying conditions (1,2, ≥ 3) and the presence of any underlying condition (≥ 1). Adjusted ORs (aOR) for the association between each exposure condition and outcome were estimated using two multivariable logistic regression models: 1) an age-adjusted model and 2) an age-interaction model (exposure condition*age). All models were adjusted for sex, reporting period (June-September; October-December) and reporting country. From the age-interaction model we estimated the predicted probability of the three outcomes for each level of condition and age-group, marginalised over the levels of each covariable.Findings: After controlling for age, sex, reporting period and reporting country in the age-adjusted models, cases with cancer, cardiac disorder, diabetes, immune deficiency disorder, kidney disease, liver disease, lung disease, neurological disorders, obesity, any underlying condition or up to three or more conditions were between 1·5 and 5·6 times more likely to be hospitalised or die than cases with no underlying condition. Asthma was associated with increased overall risk of hospitalisation, not death. Age was an important modifier of these associations, with an age interaction present in the majority of models. For all outcomes, age-specific aOR in the age-interaction models tended to decrease with increasing age, whereas predicted probabilities of the outcome increased with age. For instance, individuals aged <20 years with any underlying condition were significantly more likely to be hospitalised (aOR: 5·16, 95%CI: 4·42 - 6·02) and die (aOR: 33·77, 95%CI: 12·57 - 90·75) compared to same-aged individuals without condition. The aOR fell to 1·77 (95%CI: 1·71 - 1·83) and 1·61 (95%CI: 1·55 - 1·68) respectively in individuals 80 years and older. Conversely, the predicted probabilities of hospitalisation and death among cases aged <20 years were 5·69% (95%CI: 4·97 - 6·51) and 0.15% (95%CI: 0·08 - 0·31), respectively, while they were 44·55% (95%CI: 43·68 - 45·43) and 16·31% (95%CI: 15·44 - 17·21), respectively for individuals aged 80 years and older. For some conditions, the probability of the outcome was at least as high in younger individuals with the condition as older cases without the condition.Interpretation: Several underlying conditions were found to have a significant independent effect on severe COVID-19 outcomes. Age is an important effect modifier in these associations. Interpretation of the results in this study is facilitated by considering together the estimates of relative (aOR) and absolute (predicted probabilities) effects that are presented. The presence of underlying conditions tended to have a larger relative effect in the young than the old, but the absolute probability of being hospitalised or dying increased with age. The finding that for some conditions, a younger person may have the same or even higher probability of severe outcome than an older person without it, has relevance for age and risk-factor based prioritisation of vaccination, particularly in the young.Funding Information: This study was funded through ECDC internal funding.Declaration of Interests: None to declare.

SARS-CoV-2 Transmission in Educational Settings During an Early Summer Epidemic Wave in Luxembourg (preprint)

Background: The role of schools and children in the transmission of SARS-CoV-2 remains to be determined. Following a first wave in spring and gradual easing of lockdown, Luxembourg experienced an early second epidemic wave before the start of summer school holidays on 15th July. This provided the opportunity to study the role of school-age children and school settings in SARS-CoV-2 transmission. More specifically, we compared the incidence in school-age children, teachers and the general working population, and estimated the number of secondary transmissions occurring at schools using contact tracing data.Findings: While SARS-CoV-2 incidence was much higher in adults aged 20 and above than in children aged 0 to 19 during the first wave in spring, no significant difference was found during the second wave in early summer. The incidence during the second wave was similar for pupils, teachers and the general working population. Based on a total of 424 reported confirmed COVID-19 cases in school-age children and teachers, we estimate that 179 index cases caused 49 secondary transmissions in schools. While some small clusters of mainly student-to-student transmission within the same class were identified, we did not observe any large outbreaks with multiple generations of infection.Interpretation: Transmission of SARS-CoV-2 within Luxembourg schools was limited during the early summer epidemic wave in 2020. Precautionary measures including physical distancing as well as easy access to testing, systematic contact tracing appears to have been successful in mitigating transmission within educational settings.Funding Statement: LV is supported by the Luxembourg National Research Fund grant COVID-19/2020- 1/14701707/REBORN, LM is supported by Luxembourg National Research Fund grant COVID19/14863306/PREVID, PW is supported by the European Research Council (ERC-CoG 863664).Declaration of Interests: No competing interests.Ethics Approval Statement: The Health Directorate has the legal permission to process patient confidential information for national surveillance of communicable diseases in general and contact tracing for the COVID-19 pandemic and individual patient consent is not required.