Age-specific associations between underlying health conditions and hospitalisation, death and in-hospital death among confirmed COVID-19 cases: a multi-country study based on surveillance data, June to December 2020.

BackgroundUnderlying conditions are risk factors for severe COVID-19 outcomes but evidence is limited about how risks differ with age.AimWe sought to estimate age-specific associations between underlying conditions and hospitalisation, death and in-hospital death among COVID-19 cases.MethodsWe analysed case-based COVID-19 data submitted to The European Surveillance System between 2 June and 13 December 2020 by nine European countries. Eleven underlying conditions among cases with only one condition and the number of underlying conditions among multimorbid cases were used as exposures. Adjusted odds ratios (aOR) were estimated using 39 different age-adjusted and age-interaction multivariable logistic regression models, with marginal means from the latter used to estimate probabilities of severe outcome for each condition-age group combination.ResultsCancer, cardiac disorder, diabetes, immunodeficiency, kidney, liver and lung disease, neurological disorders and obesity were associated with elevated risk (aOR: 1.5-5.6) of hospitalisation and death, after controlling for age, sex, reporting period and country. As age increased, age-specific aOR were lower and predicted probabilities higher. However, for some conditions, predicted probabilities were at least as high in younger individuals with the condition as in older cases without it. In multimorbid patients, the aOR for severe disease increased with number of conditions for all outcomes and in all age groups.ConclusionWhile supporting age-based vaccine roll-out, our findings could inform a more nuanced, age- and condition-specific approach to vaccine prioritisation. This is relevant as countries consider vaccination of younger people, boosters and dosing intervals in response to vaccine escape variants.

Compliance with local travel restrictions and face masks during first phase of COVID-19 pandemic in Ireland: a national survey.

BACKGROUND: This study examines compliance with local travel restrictions and assesses early uptake of mask wearing, during the initial phase of the coronavirus disease of 2019 (COVID-19) pandemic in Ireland, to inform the ongoing outbreak response. METHODS: A series of four nationally representative telephone surveys were developed. Information was collected at a household level and from primary respondents. Multivariable logistic regression estimated the association between sociodemographic characteristics and compliance with the local travel restriction and with mask use in primary respondents. RESULTS: Household compliance with local travel restrictions was similar by region, household size and social position. 73.4% of all household members complied, with high levels maintained over time. Higher proportions reported travelling for non-permitted reasons with time. Older age, female gender and attending higher education were independently associated with compliance to local travel restrictions. Among primary respondents, no factors were independently associated with mask use. CONCLUSION: High compliance with local travel restrictions during the early stages of the pandemic demonstrates the engagement of the population with public health guidance. Although high compliance with local travel restrictions was generally maintained over time, non-permitted activities increased. Early adoption of mask use before required by national policy or legislation provides further evidence of the responsiveness of the population.

Increasing risk of breakthrough COVID-19 in outbreaks with high attack rates in European long-term care facilities, July to October 2021.

We collected data from 10 EU/EEA countries on 240 COVID-19 outbreaks occurring from July-October 2021 in long-term care facilities with high vaccination coverage. Among 17,268 residents, 3,832 (22.2%) COVID-19 cases were reported. Median attack rate was 18.9% (country range: 2.8-52.4%), 17.4% of cases were hospitalised, 10.2% died. In fully vaccinated residents, adjusted relative risk for COVID-19 increased with outbreak attack rate. Findings highlight the importance of early outbreak detection and rapid containment through effective infection prevention and control measures.

Establishing a COVID-19 pandemic severity assessment surveillance system in Ireland.

We developed a COVID-19 pandemic severity assessment (PSA) monitoring system in Ireland, in order to inform and improve public health preparedness, response and recovery. The system based on the World Health Organization (WHO) Pandemic Influenza Severity Assessment (PISA) project included a panel of surveillance parameters for the following indicators: transmissibility, impact and disease severity. Age-specific thresholds were established for each parameter and data visualised using heat maps. The findings from the first pandemic wave in Ireland have shown that the WHO PISA system can be adapted for COVID-19, providing a standardised tool for early warning and monitoring pandemic severity.

Characteristics of SARS-CoV-2 variants of concern B.1.1.7, B.1.351 or P.1: data from seven EU/EEA countries, weeks 38/2020 to 10/2021.

We compared 19,207 cases of SARS-CoV-2 variant B.1.1.7/S gene target failure (SGTF), 436 B.1.351 and 352 P.1 to non-variant cases reported by seven European countries. COVID-19 cases with these variants had significantly higher adjusted odds ratios for hospitalisation (B.1.1.7/SGTF: 1.7, 95% confidence interval (CI): 1.0-2.9; B.1.351: 3.6, 95% CI: 2.1-6.2; P.1: 2.6, 95% CI: 1.4-4.8) and B.1.1.7/SGTF and P.1 cases also for intensive care admission (B.1.1.7/SGTF: 2.3, 95% CI: 1.4-3.5; P.1: 2.2, 95% CI: 1.7-2.8).

Underlying conditions and risk of hospitalisation, ICU admission and mortality among those with COVID-19 in Ireland: A national surveillance study.

BACKGROUND: To date, over 2 million people worldwide have died with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To describe the experience in Ireland, this study examined associations between underlying conditions and the following outcomes: mortality, admission to hospital or admission to the intensive care unit (ICU) among those infected with COVID-19. METHODS: This study used data from the Health Protection Surveillance Centre in Ireland and included confirmed cases of COVID-19 from the first wave of the pandemic between March and July 2020. Two cohorts were included: all cases (community and hospital) and hospital admissions only. For all cases, health outcome data included mortality and hospitalisation. For hospitalised cases, outcome data included mortality and ICU admission. Logistic regression was used to examine associations between underlying conditions and outcomes across both cohorts. Results are presented as adjusted odds ratios (OR) and 95% confidence intervals (CIs). FINDINGS: There were 19,789 cases included in analysis, which encompassed 1,476 (7.5%) deaths, 2,811 (14.2%) hospitalisations, and 438 (2.2%) ICU admissions of whom 90 (20.5%) died. Significantly higher risk of mortality, hospitalisation and ICU admission was associated with having chronic heart disease, a BMI ≥40kg/m2 and male sex. Additionally, diagnosis of a chronic neurological condition (OR 1.41; 95%CI:1.17, 1.69), chronic kidney disease (OR 1.74; 95%CI:1.35, 2.24) and cancer (OR 2.77; 95%CI:2.21, 3.47) were significantly associated with higher risk of mortality among all cases, with similar patterns of association observed for mortality among hospitalised cases. INTERPRETATION: The identification of underlying conditions among COVID-19 cases may help identify those at highest risk of the worst health outcomes and inform preventive strategies to improve outcomes. FUNDING: This study was supported by the Health Service Executive, Health Protection Surveillance Centre. KEB and MM are funded by the Health Research Board (RL-15-1579 and EIA-2019-012 respectively).

Epidemiology of COVID-19 and public health restrictions during the first wave of the pandemic in Ireland in 2020.

BACKGROUND: We describe the epidemiological trends and report and review the public health restrictions implemented during the first wave of the COVID-19 pandemic in Ireland. METHODS: The study reviewed confirmed cases of COVID-19 notified from 1 March to 18 July 2020. Data were obtained from the national COVID-19 Data Hub, the National Health Protection Surveillance Centre, the National Contact Management Programme and the European Centre for Disease Prevention and Control. RESULTS: A total of 25 617 cases were notified during the study period. Weekly cases and deaths peaked in mid-April 2020 at 5701 and 316, respectively. Mean number of close contacts per case was lowest at 0.7 in April, rising to 6.6 by July. Outbreak settings shifted from travel and workplace in March, to healthcare in April. Restrictions implemented on 12 March extended to full lockdown on 27 March. Phased relaxation of restrictions commenced 18 May. Effective suppression of community transmission of COVID-19 was achieved by June 2020. CONCLUSION: Lockdown is a crude population-level restriction effective in controlling COVID-19. Phased relaxation of restrictions in Ireland, however, led to an immediate increase in mean number of contacts per case, which facilitates viral transmission unless individual-level restrictions are adhered to. This demonstrates a limitation of lockdown as a long-term mechanism of pandemic control.

A large national outbreak of COVID-19 linked to air travel, Ireland, summer 2020.

An outbreak of 59 cases of coronavirus disease (COVID-19) originated with 13 cases linked by a 7 h, 17% occupancy flight into Ireland, summer 2020. The flight-associated attack rate was 9.8-17.8%. Spread to 46 non-flight cases occurred country-wide. Asymptomatic/pre-symptomatic transmission in-flight from a point source is implicated by 99% homology across the virus genome in five cases travelling from three different continents. Restriction of movement on arrival and robust contact tracing can limit propagation post-flight.

Covid-19 Estimating the burden of symptomatic disease in the community and the impact of public health measures on physical, mental and social wellbeing: a study protocol.

Introduction: Covid-19 was declared a pandemic in March 2020. Since then, governments have implemented unprecedented public health measures to contain the virus. This study will provide evidence to inform responses to the pandemic by: i) estimating population prevalence and trends of self-reported symptoms of Covid-19 and the proportions of symptomatic individuals and household contacts testing positive for Covid-19; ii) describing acceptance and compliance with physical-distancing measures, explore effects of public health measures on physical, mental and social wellbeing; iii) developing a mathematical network model to inform decisions on the optimal levels of physical distancing measures. Methods: Two cross-sectional nationally-representative telephone surveys will be conducted in Ireland using random digit-dialling, with response rates estimates based on proportion of non-operational and non-answering numbers. The first survey with four waves in May and June will address adherence to social distancing measures and whether the respondent or other household members are or have been unwell during the preceding two weeks with one or more symptoms of Covid-19. The second survey with three waves in June, July and September will address knowledge, attitudes, and compliance towards physical-distancing measures and physical, mental and social wellbeing. The mathematical network model will be developed for all-Ireland (on various levels of spatial granularity including the scale of counties and electoral divisions) based on outputs from both cross-sectional surveys and relevant publicly available data to inform decisions on optimal levels and duration of physical distancing measures. Discussion: This study will contribute to our understanding of the impact and sustainability of public health measures of the Covid-19 pandemic. Findings will have long-lasting benefits, informing decision-making on the best levels, and duration of physical-distancing measures, balancing a range of factors including capacity of the health service with the effects on individuals' wellbeing and economic disruption. Findings will be shared with key policy-makers.