ABSTRACT
Background. We aimed to describe SARS-CoV-2 (COVID-19) infections among employees in a large, academic institution. Methods. We prospectively tracked and traced COVID-19 infections among employees across our health system and university. Each employee with a confirmed positive test and 3 presumed positive cases were interviewed with a standard contact tracing template that included descriptive variables such as high-risk behaviors and contacts, dates worked while infectious, and initial symptoms. Using this information, the most likely location of infection acquisition was adjudicated (Table 1). We compared behavior frequency between community and unknown, likely community and community and unknown cases using descriptive statistics. Results. From 3/2020 to 4/2021 we identified 3,140 COVID-19 infections in 3,119 employees out of a total of 34,562 employees (9.0%) (Figure 1). Of those 3,119 employees 1,685 (54.0%) were clinical employees working in the health system, 916 (29.4%) were non-clinical employees working in the health system, and 518 (16.6%) were university employees. Descriptive characteristics for the COVID-19 infections and adjudications are outlined in Table 2. Severe disease among employees was significantly less frequent compared to patients in the health system (15.3% vs 2.2%, p< 0.01). The frequency of travel within 14 days, masked gatherings and unmasked gatherings/ activities was not significantly different between the community and unknown, likely community groups or the community and unknown groups (Table 3). Conclusion. The majority of COVID-19 infections were linked to acquisition in the community, and few were attributed to workplace exposures. Employees with unknown sources of COVID-19 participated in higher-risk activities at approximately the same frequency as employees with community sources of COVID-19. The most frequently reported initial symptoms were mild and non-specific and rarely included fever. Despite a comprehensive testing and benefit program, a large proportion of COVID-positive employees worked with symptoms, highlighting ongoing challenges with presenteeism in healthcare.
ABSTRACT
Background. Data on occupational acquisition of COVID-19 in healthcare settings are limited. Contact tracing efforts are high resource investments. Methods. Duke Health developed robust COVID-19 contact tracing methods as part of a comprehensive prevention program. We prospectively collected data on HCW exposures and monitored for development of symptomatic (SYX) and asymptomatic (ASYX) COVID-19 infection after documented high-, medium, and low-risk exposures. HCWs were required to self-report exposures or were identified through contact tracing as potentially exposed to COVID-19 positive HCWs, patients or visitors. Contact tracers interviewed exposed HCWs and assessed the risk of exposure as high-, medium-, or low-risk based on CDC guidance (Table 1). Testing was recommended at 6 days after high- or medium-risk exposures and was provided upon HCW request following low-risk exposures. Our vaccination campaign began in 12/2020. Results. 12,916 HCWs registered in the contact tracing database. From March 2020-May 2021, we identified 6,606 occupational exposures (0.51 exposures/HCW). The highest incidence of workplace exposures per number of HCWs in each job category was among respiratory therapists (RT) (0.95 exposures/RT), nursing assistants (NA) (0.79 exposures/NA), and physicians (0.64 exposures/physician). The most common exposure risk level was medium (51.4%), followed by low (35.5%), and then high (13.1%). A total of 260 (2%) HCW had positive tests/conversions;28 (10.8%) were ASYX at the time of testing. High-risk exposures had a significantly greater number of post-exposure infections compared to medium- and low-risk exposures (12.5% vs. 4.2%, vs. 0.4%;p < 0.001). The rate of SYX infection following exposure to a fellow HCW (179/3,198;5.6%) was higher than that following exposure to a patient (81/3,408;2.4%;p< 0.001). Conclusion. Conversion following exposure to COVID-19 in the healthcare setting with appropriate protective equipment was low. Incomplete testing of all exposed individuals was a limitation and our data may under-estimate the true conversion rate. Our findings support our local practice of not quarantining HCWs following non-household exposures. Limiting contact tracing to only high or medium risk exposures may best utilize limited personnel resources.
ABSTRACT
The devastating SARS-CoV2 pandemic is worsening with relapsing surges, emerging mu-tants, and increasing mortalities. Despite enormous efforts, it is not clear how SARS-CoV2 adapts and evolves in a clonal background. Laboratory research is hindered by high biosafety demands. How-ever, the rapid sequence availability opened doors for bioinformatics. Using different bioinformatics programs, we investigated 6305 sequences for clonality, expressions strategies, and evolutionary dynamics. Results showed high nucleotide identity of 99.9% among SARS-CoV2 indicating clonal evolution and genome. High sequence identity and phylogenetic tree concordance were obtained with isolates from different regions. In any given tree topology, ~50% of isolates in a country formed country-specific sub-clusters. However, abundances of subtle overexpression strategies were found including transversions, signature-sequences and slippery-structures. Five different short tracks dominated with identical location patterns in all genomes where Slippery-4 AAGAA was the most abundant. Interestingly, transversion and transition substitutions mostly affected the same amino acid residues implying compensatory changes. To ensure these strategies were independent of sequence clonality, we simultaneously examined sequence homology indicators;tandem-repeats, restriction-site, and 3′ UTR, 5′ UTR-caps and stem-loop locations in addition to stringent alignment parameters for 100% identity which all confirmed stability. Nevertheless, two rare events;a rearrange-ment in two SARS-CoV2 isolates against betacoronavirus ancestor and a polymorphism in S gene, were detected. Thus, we report on abundance of transversions, slippery sequences, and ON/OFF molecular structures, implying adaptive expressions had occurred, despite clonal evolution and genome stability. Furthermore, functional validation of the point mutations would provide insights into mechanisms of SARS-CoV2 virulence and adaptation.