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.

COVID-19 research priorities for non-pharmaceutical public health and social measures.

Europe is in the midst of a COVID-19 epidemic and a number of non-pharmaceutical public health and social measures have been implemented, in order to contain the transmission of severe acute respiratory syndrome coronavirus 2. These measures are fundamental elements of the public health approach to controlling transmission but have proven not to be sufficiently effective. Therefore, the European Centre for Disease Prevention and Control has conducted an assessment of research gaps that can help inform policy decisions regarding the COVID-19 response. We have identified research gaps in the area of non-pharmaceutical measures, physical distancing, contact tracing, transmission, communication, mental health, seasonality and environment/climate, surveillance and behavioural aspects of COVID-19. This prioritisation exercise is a step towards the global efforts of developing a coherent research road map in coping with the current epidemic but also developing preparedness measures for the next unexpected epidemic.

Testing the identification effectiveness of an unknown outbreak of the Infectious Diseases Seeker (IDS) using and comparing the novel coronavirus disease (COVID-19) outbreak with the past SARS and MERS epidemics.

BACKGROUND: The aim of this research is to assess the predictive accuracy of the Infectious Diseases Seeker (IDS) - an innovative tool for prompt identification of the causative agent of infectious diseases during outbreaks - when field epidemiological data collected from a novel outbreak of unknown origin are analysed by the tool. For this reason, it has been taken into account the novel coronavirus disease (COVID-19) outbreak, which began in China at the end of December 2019, has rapidly spread around the globe, and it has led to a public health emergency of international concern (PHEIC), declared to the 30th of January 2020 by the World Health Organization (WHO). METHODS: The IDS takes advantage of an off-line database, built before the COVID-19 pandemic, which represents a pivotal characteristic for working without an internet connection. The software has been tested using the epidemiological data available in different and progressive stages of the COVID-19 outbreak. As a comparison, the results of the tests performed using the epidemiological data from the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) epidemic in 2002 and Middle East Respiratory Syndrome coronavirus (MERS-CoV) epidemic in 2012, are shown. RESULTS: The overall outcomes provided by the software are comforting, as a matter of the fact that IDS has identified with a good accuracy the SARS and MERS epidemics (over 90%), while, as expected, it has not provided erroneous and equivocal readings after the elaboration COVID-19 epidemic data. CONCLUSIONS: Even though IDS has not recognized the COVID-19 epidemic, it has not given to the end user a false result and wrong interpretation, as expected by the developers. For this reason, IDS reveals itself as useful software to identify a possible epidemic or outbreak. Thus, the intention of developers is to plan, once the software will be released, dedicated updates and upgrades of the database (e.g., SARS-CoV-2) in order to keep this tool increasingly useful and applicable to reality.