COVID-19 infection and diffusion among the healthcare workforce in a large university-hospital in northwest Italy: Gli operatori sanitari con ruolo di coordinamento - Garzaro, Giacomo; Clari, Marco; Ciocan, Catalina; Grillo, Eugenio; Mansour, Ihab; Godono, Alessandro; Borgna, Lorenza Giuditta; Sciannameo, Veronica; Costa, Giuseppe; Raciti, Ida Marina; Bert, Fabrizio; Berchialla, Paola; et al. (La Medicina del Lavoro, 2020)
Backgroud: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, healthcare workers (HCWs) have been the workers most likely to contract the disease. Intensive focus is therefore needed on hospital strategies that minimize exposure and diffusion, confer protection and facilitate early detection and isolation of infected personnel. Methods: To evaluate the early impact of a structured risk-management for exposed COVID-19 HCWs and describe how their characteristics contributed to infection and diffusion. Socio-demographic and clinical data, aspects of the event-exposure (date, place, length and distance of exposure, use of PPE) and details of the contact person were collected. Results: The 2411 HCWs reported 2924 COVID-19 contacts. Among 830 HCWs who were at ‘high or medium risk’, 80 tested positive (9.6%). Physicians (OR=2.03), and non-medical services resulted in an increased risk (OR=4.23). Patient care did not increase the risk but sharing the work environment did (OR=2.63). There was a significant time reduction between exposure and warning, exposure and test, and warning and test since protocol implementation. HCWs with management postitions were the main source of infection due to the high number of interactions. Discussion: A proactive system that includes prompt detection of contagious staff and identification of sources of exposure helps to lower the intra-hospital spread of infection. A speedier return to work of staff who would otherwise have had to self-isolate as a precautionary measure improves staff morale and patient care by reducing the stress imposed by excessive workloads arising from staff shortages.