ABSTRACT
An aerosol-generating medical procedure (AGMP) is any procedure performed on a patient that can induce the production of aerosols of various sizes, including droplet nuclei. AGMPs have become a subject of increasing interest during the COVID-19 pandemic for two critical reasons. First, AGMP likely increases the risk of transmission from patients infected with respiratory infections to healthcare personnel and other patients in their environment. Second, special risk mitigation strategies, including selection of specific types of personal protective equipment and environmental controls, are necessary to protect staff during the performance of AGMPs. Heightened awareness for AGMPs began during the 2003 severe acute respiratory syndrome (SARS) pandemic, where it was noted that, in outbreaks, many frontline HCWs had increased risk of contracting the virus related to certain procedures performed on the respiratory tract (Tran et al. PLoS One 7:e35797, 2012). Numerous clinical guidelines were published attempting to categorize and classify the risk associated with various AGMP. However, while numerous procedures have been identified as "aerosol generating, " the scientific evidence for the creation of aerosols associated with these procedures, the burden of potential viable microbes within the created aerosols, and the mechanism of transmission to the host have not been well studied (Davies et al. J Infect Prev 10:122-6, 2009). Almost 20 years later, there are still large gaps in knowledge around AGMPs - what defines them, what is the added risk associated with them, and which strategies are most effective at mitigating the risks associated with them. Here, we summarize the current knowledge around AGMPs including the types, risk, and mitigation strategies. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
ABSTRACT
Background. Although healthcare worker (HCW) absenteeism due to COVID-19 exposure represents a significant challenge, there are currently no evidence-based criteria for assessing infection risk based on COVID-19 exposure type.We aimed to identify the incidence of acquiring infection following varying exposures to COVID-19 to guide safe return-to-work policies for staff in healthcare settings. Methods. We analyzed prospectively collected data at an academic centre with approximately 17 000 active staff between January 1 - April 30, 2022 during a large BA.1 Omicron surge. More than 99% of staff received >2 vaccine doses. All staff selfreporting household, community, and workplace exposure to confirmed cases of COVID-19 submitted attestation to the Occupational Health department detailing the nature of the exposure, the duration, and setting. Staff were required to report all positive test results by rapid antigen or PCR testing. Results. A total of 3209 staff submitted exposure reports (2493 household, 539 community, and 177 workplace). Of these, 1008 (31.4%) tested positive 2 days prior to or 14 days after the exposure (36% household;19% community, 7% workplace). In the community exposure group, 19% tested positive due to a discrete exposure of < 4 hours and 21% tested positive with an exposure >4 hours. For household exposures and workplace exposures, these values were 25%/27% and 6%/10%, respectively (Figure 1). The median time to testing positive was 2 days for household exposures and 3 days for community and workplace exposures (Figure 2, Panels A-C). By day 4 post-exposure, more than 80% of positive results were reported (Figure 2, Panel D). Risk of testing positive differed based on baseline symptom status at the time of reporting (Table 1). The risk of infection amongst healthcare workers reporting exposures, according to their symptom status at the time of reporting their exposures. Conclusion. Our data suggests that the highest risk of acquiring SARS-CoV-2 was via household contacts, regardless of exposure duration, with workplace exposures carrying less risk. Using a cut-off of 4 hours for exposure duration to delineate risk may be of limited value. These data could help workplaces predict infection risk following exposure and guide return-to-work policies that balance the need to staff workplaces, including hospitals, with reducing risk of on-site transmission during periods of increased community transmission (Figure 3). (Figure Presented).