Eurosurveillance - Volume 28, Issue 1, 05 January 2023

Since the beginning of the war in Ukraine in February 2022, Ukrainians have been seeking shelter in other European countries.

We aimed to investigate the prevalence and the molecular epidemiology of multidrug-resistant Gram-negative (MDRGN) bacteria and meticillin-resistant Staphylococcus aureus (MRSA) in Ukrainian patients at admittance to the University Hospital Frankfurt, Germany.

We performed screening and observational analysis of all patients from March until June 2022. Genomes of MDRGN isolates were analysed for antimicrobial resistance, virulence genes and phylogenetic relatedness.

We included 103 patients (median age: 39 ± 23.7 years), 57 of whom were female (55.3%; 95% confidence interval (CI): 45.2–5.1). Patients were most frequently admitted to the Department of Paediatrics (29/103; 28.2%; 95% CI: 19.7–37.9). We found 34 MDRGN isolates in 17 of 103 patients (16.5%; 95% CI: 9.9–25.1). Ten patients carried 21 carbapenem-resistant (CR) bacteria, five of them more than one CR isolate. Four of six patients with war-related injuries carried eight CR isolates. In six of 10 patients, CR isolates caused infections. Genomic characterisation revealed that the CR isolates harboured at least one carbapenemase gene, blaNDM-1 being the most frequent (n = 10). Core genome and plasmid analysis revealed no epidemiological connection between most of these isolates. Hypervirulence marker genes were found in five of six Klebsiella pneumoniae CR isolates. No MRSA was found.

Hospitals should consider infection control strategies to cover the elevated prevalence of MDRGN bacteria in Ukrainian patients with war-related injuries and/or hospital pre-treatment and to prevent the spread of hypervirulent CR isolates.

During the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.

To develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.

Data were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms’ performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.

We estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.

Implementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.