Riesgo de infección por SARS-CoV-2 en trabajadores sanitarios altamente expuestos / Risk of sars-cov-2 infection in highly exposed health workers

Objetivos: El presente estudio permite establecer el perfil de trabajador más susceptible a la infección por SARS-CoV-2, describir la seroprevalencia y conocer la presencia de anosmia y/o disgeusia. Material y Métodos: Se realizó un estudio epidemiológico descriptivo, transversal y retrospectivo durante 263 días en una UCI de un hospital terciario. Se incluyeron 146 trabajadores de 11 categorías distintas. Se consultaron los resultados de las pruebas diagnósticas de infección y se realizó una entrevista telefónica. Resultados: 56 trabajadores se infectaron (39,4%). El riesgo de infección en sanitarios fue superior (OR 3,38). El personal de enfermería y el trabajo a turnos presentó una tasa de infección más elevada (p= 0, 000). Se detectaron anticuerpos Anti SARS-CoV-2 (AntiN) IgG durante más de 4 meses. El 38,1% desarrolló anosmia y/o disgeusia con una recuperación de 117,41 días de media. Conclusiones: Los datos obtenidos pueden resultar de interés para la evaluación del riesgo ocupacional frente al SARS-CoV-2 en el ámbito sanitario. (AU)

Objectives: The present study makes it possible to establish the profile of the worker most susceptible to SARS-CoV-2 infection, describe seroprevalence and determine the presence of anosmia and / or dysgeusia. Material and Methods: A descriptive, cross-sectional, and retrospective epidemiological study was carried out for 263 days in an ICU of a tertiary hospital. One hundred forty-six workers from 11 different categories were included. The results of the diagnostic tests for infection were consulted, and a telephone interview was carried out. Results: Fifty-six workers were infected (39.4%). The risk of infection in healthcare workers was higher (OR 3.38). Nursing staff and shift workers had a higher infection rate (p = 0, 000). Anti SARS-CoV-2 (AntiN) IgG antibodies were detected for more than four months. 38.1% developed anosmia and/or dysgeusia with a recovery of 117.41 days on average. Conclusions: The data obtained may be of interest for assessing occupational risk against SARS-CoV-2 in the health field. (AU)

Overlapping of Independent SARS-CoV-2 Nosocomial Transmissions in a Complex Outbreak.

SARS-CoV-2 nosocomial outbreaks in the first COVID-19 wave were likely associated with a shortage of personal protective equipment and scarce indications on control measures. Having covered these limitations, updates on current SARS-CoV-2 nosocomial outbreaks are required. We carried out an in-depth analysis of a 27-day nosocomial outbreak in a gastroenterology ward in our hospital, potentially involving 15 patients and 3 health care workers. Patients had stayed in one of three neighboring rooms in the ward. The severity of the infections in six of the cases and a high fatality rate made the clinicians suspect the possible involvement of a single virulent strain persisting in those rooms. Whole-genome sequencing (WGS) of the strains from 12 patients and 1 health care worker revealed an unexpected complexity. Five different SARS-CoV-2 strains were identified, two infecting a single patient each, ruling out their relationship with the outbreak; the remaining three strains were involved in three independent, overlapping, limited transmission clusters with three, three, and five cases. Whole-genome sequencing was key to understand the complexity of this outbreak. IMPORTANCE We report a complex epidemiological scenario of a nosocomial COVID-19 outbreak in the second wave, based on WGS analysis. Initially, standard epidemiological findings led to the assumption of a homogeneous outbreak caused by a single SARS-CoV-2 strain. The discriminatory power of WGS offered a strikingly different perspective consisting of five introductions of different strains, with only half of them causing secondary cases in three independent overlapping clusters. Our study exemplifies how complex the SARS-CoV-2 transmission in the nosocomial setting during the second COVID-19 wave occurred and leads to extending the analysis of outbreaks beyond the initial epidemiological assumptions.