Healthcare-associated COVID-19 across 3 pandemic waves: patient characterisation and validation of clinical definitions using genome sequencing

Abstract

BackgroundWorldwide, healthcare-associated SARS-CoV-2 infections are a major problem: they are associated with increased morbidity, mortality, and hospitalization costs. In-depth studies across the pandemic are crucial to understand and prevent transmission in hospital settings. The principal aims of this study were to characterise patients and validate ECDC definitions of healthcare-associated COVID-19 infections.MethodsWe set up a retrospective observational study spanning the first three waves of the COVID-19 pandemic in a Belgian university hospital: it describes the characteristics of COVID-19 patients admitted, with either healthcare- or community-associated infections. We performed a cluster analysis through epidemiological and viral genome analyses of the healthcare-associated infections, in order to validate the ECDC definitions of healthcare-associated COVID-19 infections.ResultsBetween week 10 of 2020 and week 22 of 2021, 168 patients were hospitalized with healthcare-associated COVID-19. The following factors were found more often in symptomatic healthcare- than in community-associated hospitalized patients: older age, increased frailty, smoking habits, and comorbidities. The genome-based cluster analyses showed that different viral lineages predominated in different timeframes. We observed a good correlation of epidemiological data with genome sequencing results in at least 12 different outbreaks in our hospital, thus validating the ECDC definitions. ConclusionsThis in-depth characterization sheds new light on the problem of healthcare-associated COVID-19 infections, in particular on patients’ characteristics, epidemiology, and cluster dynamics. Even though epidemiological evaluation of nosocomial infections is vital, management of nosocomial outbreaks can undoubtedly benefit from genome sequencing analyses to reinforce their strategy.