Establishing severe acute respiratory infection (SARI) surveillance in a sentinel hospital, Ireland, 2021 to 2022.

BackgroundIn 2020, due to the COVID-19 pandemic, the European Centre for Disease Prevention and Control (ECDC) accelerated development of European-level severe acute respiratory infection (SARI) surveillance.AimWe aimed to establish SARI surveillance in one Irish hospital as part of a European network E-SARI-NET.MethodsWe used routine emergency department records to identify cases in one adult acute hospital. The SARI case definition was adapted from the ECDC clinical criteria for a possible COVID-19 case. Clinical data were collected using an online questionnaire. Cases were tested for SARS-CoV-2, influenza and respiratory syncytial virus (RSV), including whole genome sequencing (WGS) on SARS-CoV-2 RNA-positive samples and viral characterisation/sequencing on influenza RNA-positive samples. Descriptive analysis was conducted for SARI cases hospitalised between July 2021 and April 2022.ResultsOverall, we identified 437 SARI cases, the incidence ranged from two to 28 cases per week (0.7-9.2/100,000 hospital catchment population). Of 431 cases tested for SARS-CoV-2 RNA, 226 (52%) were positive. Of 349 (80%) cases tested for influenza and RSV RNA, 15 (4.3%) were positive for influenza and eight (2.3%) for RSV. Using WGS, we identified Delta- and Omicron-dominant periods. The resource-intensive nature of manual clinical data collection, specimen management and laboratory supply shortages for influenza and RSV testing were challenging.ConclusionWe successfully established SARI surveillance as part of E-SARI-NET. Expansion to additional sentinel sites is planned following formal evaluation of the existing system. SARI surveillance requires multidisciplinary collaboration, automated data collection where possible, and dedicated personnel resources, including for specimen management.

Identification of Distinct Long COVID Clinical Phenotypes Through Cluster Analysis of Self-Reported Symptoms.

Background: We aimed to describe the clinical presentation of individuals presenting with prolonged recovery from coronavirus disease 2019 (COVID-19), known as long COVID. Methods: This was an analysis within a multicenter, prospective cohort study of individuals with a confirmed diagnosis of COVID-19 and persistent symptoms >4 weeks from onset of acute symptoms. We performed a multiple correspondence analysis (MCA) on the most common self-reported symptoms and hierarchical clustering on the results of the MCA to identify symptom clusters. Results: Two hundred thirty-three individuals were included in the analysis; the median age of the cohort was 43 (interquartile range [IQR], 36-54) years, 74% were women, and 77.3% reported a mild initial illness. MCA and hierarchical clustering revealed 3 clusters. Cluster 1 had predominantly pain symptoms with a higher proportion of joint pain, myalgia, and headache; cluster 2 had a preponderance of cardiovascular symptoms with prominent chest pain, shortness of breath, and palpitations; and cluster 3 had significantly fewer symptoms than the other clusters (2 [IQR, 2-3] symptoms per individual in cluster 3 vs 6 [IQR, 5-7] and 4 [IQR, 3-5] in clusters 1 and 2, respectively; P < .001). Clusters 1 and 2 had greater functional impairment, demonstrated by significantly longer work absence, higher dyspnea scores, and lower scores in SF-36 domains of general health, physical functioning, and role limitation due to physical functioning and social functioning. Conclusions: Clusters of symptoms are evident in long COVID patients that are associated with functional impairments and may point to distinct underlying pathophysiologic mechanisms of disease.