Secondary Cases of Delta Variant Coronavirus Disease 2019 Among Vaccinated Healthcare Workers With Breakthrough Infections is Rare.

In a retrospective, cohort study at 4 medical centers with high coronavirus disease 2019 vaccination rates, we evaluated breakthrough severe acute respiratory syndrome coronavirus 2 Delta variant infections in vaccinated healthcare workers. Few work-related secondary cases were identified. Breakthrough cases were largely due to unmasked social activities outside of work.

Real-world impact of vaccination on coronavirus disease 2019 (COVID-19) incidence in healthcare personnel at an academic medical center.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) vaccination effectiveness in healthcare personnel (HCP) has been established. However, questions remain regarding its performance in high-risk healthcare occupations and work locations. We describe the effect of a COVID-19 HCP vaccination campaign on SARS-CoV-2 infection by timing of vaccination, job type, and work location. METHODS: We conducted a retrospective review of COVID-19 vaccination acceptance, incidence of postvaccination COVID-19, hospitalization, and mortality among 16,156 faculty, students, and staff at a large academic medical center. Data were collected 8 weeks prior to the start of phase 1a vaccination of frontline employees and ended 11 weeks after campaign onset. RESULTS: The COVID-19 incidence rate among HCP at our institution decreased from 3.2% during the 8 weeks prior to the start of vaccinations to 0.38% by 4 weeks after campaign initiation. COVID-19 risk was reduced among individuals who received a single vaccination (hazard ratio [HR], 0.52; 95% confidence interval [CI], 0.40-0.68; P < .0001) and was further reduced with 2 doses of vaccine (HR, 0.17; 95% CI, 0.09-0.32; P < .0001). By 2 weeks after the second dose, the observed case positivity rate was 0.04%. Among phase 1a HCP, we observed a lower risk of COVID-19 among physicians and a trend toward higher risk for respiratory therapists independent of vaccination status. Rates of infection were similar in a subgroup of nurses when examined by work location. CONCLUSIONS: Our findings show the real-world effectiveness of COVID-19 vaccination in HCP. Despite these encouraging results, unvaccinated HCP remain at an elevated risk of infection, highlighting the need for targeted outreach to combat vaccine hesitancy.

Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases Testing.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are poised to transform infectious disease testing. Uniquely, infectious disease testing is technologically diverse spaces in laboratory medicine, where multiple platforms and approaches may be required to support clinical decision-making. Despite advances in laboratory informatics, the vast array of infectious disease data is constrained by human analytical limitations. Machine learning can exploit multiple data streams, including but not limited to laboratory information and overcome human limitations to provide physicians with predictive and actionable results. As a quickly evolving area of computer science, laboratory professionals should become aware of AI/ML applications for infectious disease testing as more platforms are become commercially available. CONTENT: In this review we: (a) define both AI/ML, (b) provide an overview of common ML approaches used in laboratory medicine, (c) describe the current AI/ML landscape as it relates infectious disease testing, and (d) discuss the future evolution AI/ML for infectious disease testing in both laboratory and point-of-care applications. SUMMARY: The review provides an important educational overview of AI/ML technique in the context of infectious disease testing. This includes supervised ML approaches, which are frequently used in laboratory medicine applications including infectious diseases, such as COVID-19, sepsis, hepatitis, malaria, meningitis, Lyme disease, and tuberculosis. We also apply the concept of "data fusion" describing the future of laboratory testing where multiple data streams are integrated by AI/ML to provide actionable clinical knowledge.

Investigation of nosocomial SARS-CoV-2 transmission from two patients to healthcare workers identifies close contact but not airborne transmission events.

OBJECTIVE: To describe the pattern of transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) during 2 nosocomial outbreaks of coronavirus disease 2019 (COVID-19) with regard to the possibility of airborne transmission. DESIGN: Contact investigations with active case finding were used to assess the pattern of spread from 2 COVID-19 index patients. SETTING: A community hospital and university medical center in the United States, in February and March, 2020, early in the COVID-19 pandemic. PATIENTS: Two index patients and 421 exposed healthcare workers. METHODS: Exposed healthcare workers (HCWs) were identified by analyzing the electronic medical record (EMR) and conducting active case finding in combination with structured interviews. Healthcare coworkers (HCWs) were tested for COVID-19 by obtaining oropharyngeal/nasopharyngeal specimens, and RT-PCR testing was used to detect SARS-CoV-2. RESULTS: Two separate index patients were admitted in February and March 2020, without initial suspicion for COVID-19 and without contact or droplet precautions in place; both patients underwent several aerosol-generating procedures in this context. In total, 421 HCWs were exposed in total, and the results of the case contact investigations identified 8 secondary infections in HCWs. In all 8 cases, the HCWs had close contact with the index patients without sufficient personal protective equipment. Importantly, despite multiple aerosol-generating procedures, there was no evidence of airborne transmission. CONCLUSION: These observations suggest that, at least in a healthcare setting, most SARS-CoV-2 transmission is likely to take place during close contact with infected patients through respiratory droplets, rather than by long-distance airborne transmission.