Eurosurveillance - Volume 28, Issue 16, 20 April 2023

The Epidemic Intelligence from Open Sources (EIOS) system, jointly developed by the World Health Organisation (WHO), the Joint Research Centre (JRC) of the European Commission and various partners, is a web-based platform that facilitate the monitoring of information on public health threats in near real-time from thousands of online sources.

To assess the capacity of the EIOS system to strengthen data collection for neglected diseases of public health importance, and to evaluate the use of EIOS data for improving the understanding of the geographic extents of diseases and their level of risk.

A Bayesian additive regression trees (BART) model was implemented to map the risk of Crimean-Congo haemorrhagic fever (CCHF) occurrence in 52 countries and territories within the European Region between January 2012 and March 2022 using data on CCHF occurrence retrieved from the EIOS system.

The model found a positive association between all temperature-related variables and the probability of CCHF occurrence, with an increased risk in warmer and drier areas. The highest risk of CCHF was found in the Mediterranean basin and in areas bordering the Black Sea. There was a general decreasing risk trend from south to north across the entire European Region.

The study highlights that the information gathered by public health intelligence can be used to build a disease risk map. Internet-based sources could aid in the assessment of new or changing risks and planning effective actions in target areas.

During the COVID-19 pandemic, international shipping activity was disrupted as movement of people and goods was restricted. The Port of Rotterdam, the largest port in Europe, remained operational throughout.

We describe the burden of COVID-19 among crew on sea-going vessels at the port and recommend improvements in future infectious disease event notification and response at commercial ports.

Suspected COVID-19 cases on sea-going vessels were notified to port authorities and public health (PH) authorities pre-arrival via the Maritime Declaration of Health. We linked data from port and PH information systems between 1 January 2020 and 31 July 2021, derived a notification rate (NR) of COVID-19 events per arrival, and an attack rate (AR) per vessel (confirmed cases). We compared AR by vessel type (workship/tanker/cargo/passenger), during wildtype-, alpha- and delta-dominant calendar periods.

Eighty-four COVID-19 events were notified on ships, involving 622 cases. The NR among 45,030 new arrivals was 173 per 100,000 impacting 1% of vessels. Events per week peaked in April 2021 and again in July 2021, when the AR was also highest. Half of all cases were notified on workships, events occurring earlier and more frequently than on other vessels.

Notification of COVID-19 events on ships occurred infrequently, although case under-ascertainment was likely. Pre-agreed protocols for data-sharing between stakeholders locally and across Europe would facilitate more efficient pandemic response. Public health access to specimens for sequencing and environmental sampling would give greater insight into viral spread on ships.

There are conflicting reports on the performance of rapid antigen detection tests (RDT) in the detection of the SARS-CoV-2 Omicron (B.1.1.529) variant; however, these tests continue to be used frequently to detect potentially contagious individuals with high viral loads.

The aim of this study was to investigate comparative detection of the Delta (B.1.617.2) and Omicron variants by using a selection of 20 RDT and a limited panel of pooled combined oro- and nasopharyngeal clinical Delta and Omicron specimens.

We tested 20 CE-marked RDT for their performance to detect SARS-CoV-2 Delta and Omicron by using a panel of pooled clinical specimens collected in January 2022 in Berlin, Germany.

We observed equivalent detection performance for Delta and Omicron for most RDT, and sensitivity was widely in line with our previous pre-Delta/Omicron evaluation. Some variation for individual RDT was observed either for Delta vs Omicron detection, or when compared with the previous evaluation, which may be explained both by different panel sizes resulting in different data robustness and potential limitation of batch-to-batch consistency. Additional experiments with three RDT using non-pooled routine clinical samples confirmed comparable performance to detect Delta vs Omicron. Overall, RDT that were previously positively evaluated retained good performance also for Delta and Omicron variants.

Our findings suggest that currently available RDT are sufficient for the detection of SARS-CoV-2 Delta and Omicron variants.