Highlights SARS-CoV-2 seroprevalence was high compared to community in a cohort of health care workers at a single institution in the Bronx after the surge. Symptomatic participants had a higher rate of seroconversion compared to those without symptoms. Health care workers with anosmia and ageusia had increased odds of seroconversion in comparison to those without these symptoms. It is likely that a combination of healthcare and community exposure contributed to the seroprevalence.

Introduction: New York City is one of the areas most affected by the COVID-19 pandemic in the United States. Healthcare workers are among those at high risk of contracting the virus, and a vital source of information and trust in vaccines to the community. Methods: This study was conducted about attitudes towards COVID-19 vaccination among healthcare workers at a public hospital in New York City during the beginning of COVID-19 vaccination. 428 hospital employees responded. Results: Several factors were significantly associated with vaccine attitudes, including demographics such as gender (p = 0.002), age (p = 0.005), race (p < 0.001) and home location (p < 0.001), role within the hospital (p < 0.001), knowledge about the virus (p < 0.001) and confidence in and expectations about personal protective equipment and behaviors (p < 0.001). Structural equation modeling revealed that the most predictive factors were prior vaccine attitudes and concern with the speed of testing and approval of the vaccines (p < 0.001). Multivariate analysis reinforced these, while also identifying perceived personal risk as significant (p = 0.033). Conclusions: Several modifiable factors that reflect confidence in science, scientific knowledge, personal risk perception, experience and medical authority are correlated with vaccine attitudes, indicating that a holistic educational approach to improve trust in science is likely to be effective in long-term reduction in vaccine hesitancy.

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ObjectiveDynamics of humoral immune responses to SARS-CoV-2 antigens following infection suggest an initial decay of antibody followed by subsequent stabilisation. We aim to understand the longitudinal humoral responses to SARS-CoV-2 nucleocapsid (N) protein and spike (S) protein and to evaluate their correlation to clinical symptoms among healthcare workers (HCWs).DesignA prospective longitudinal study.SettingThis study was conducted in a New York City public hospital in the South Bronx, New York.ParticipantsHCWs participated in phase 1 (N=500) and were followed up 4 months later in phase 2 (N=178) of the study. They underwent SARS-CoV-2 PCR and serology testing for N and S protein antibodies, in addition to completion of an online survey in both phases. Analysis was performed on the 178 participants who participated in both phases of the study.Primary outcome measureEvaluate longitudinal humoral responses to viral N (qualitative serology testing) and S protein (quantitative Mount Sinai Health System ELISA to detect receptor-binding domain and full-length S reactive antibodies) by measuring rate of decay.ResultsAnti-N antibody positivity was 27% and anti-S positivity was 28% in phase 1. In phase 1, anti-S titres were higher in symptomatic (6754 (5177–8812)) than in asymptomatic positive subjects (5803 (2825–11 920)). Marginally higher titres (2382 (1494–3797)) were seen in asymptomatic compared with the symptomatic positive subgroup (2198 (1753–2755)) in phase 2. A positive correlation was noted between age (R=0.269, p<0.01), number (R=0.310, p<0.01) and duration of symptoms (R=0.434, p<0.01), and phase 1 anti-S antibody titre. A strong correlation (R=0.898, p<0.001) was observed between phase 1 titres and decay of anti-S antibody titres between the two phases. Significant correlation with rate of decay was also noted with fever (R=0.428, p<0.001), gastrointestinal symptoms (R=0.340, p<0.05), and total number (R=0.357, p<0.01) and duration of COVID-19 symptoms (R=0.469, p<0.001).ConclusionsHigher initial anti-S antibody titres were associated with larger number and longer duration of symptoms as well as a faster decay between the two time points.

Despite the development of several effective vaccines, SARS-CoV-2 continues to spread, causing serious illness among the unvaccinated. Healthcare professionals are trusted sources of information about vaccination, and therefore understanding the attitudes and beliefs of healthcare professionals regarding the vaccines is of utmost importance. We conducted a survey-based study to understand the factors affecting COVID-19 vaccine attitudes among health care professionals in NYC Health and Hospitals, at a time when the vaccine was new, and received 3759 responses. Machine learning and chi-square analyses were applied to determine the factors most predictive of vaccine hesitancy. Demographic factors, education, role at the hospital, perceptions of the pandemic itself, and location of work and residence were all found to significantly contribute to vaccine attitudes. Location of residence was examined for both borough and neighborhood, and was found to have a significant impact on vaccine receptivity. Interestingly, this borough-level data did not correspond to the number or severity of cases in the respective boroughs, indicating that local social or other influences likely have a substantial impact. Local and demographic factors should be strongly considered when preparing pro-vaccine messages or campaigns.

Community hospitals with limited resources struggle to engage physicians in Quality improvement initiatives. We introduced Quality Improvement (QI) curriculum for residents in response to ACGME requirements and surveyed the residents understanding of QI and their involvement in QI projects before and after the introduction of the curriculum. The current article describes our experiences with the process, the challenges and possible solutions to have a successful resident led QI initiative in a community hospital. Methods: A formal QI curriculum was introduced in the Department of Internal Medicine from September to October 2015 using the Model for Improvement from Institute for Health care Improvement (IHI). Learners were expected to read the online modules, discuss in small group sessions and later encouraged to draft their QI projects using the Charter form and PDSA form available on the HI website. Online surveys were conducted a week prior and 3 months after completion of the curriculum Results: 80% (100/117) of residents completed the pre-curriculum survey and 52% (61/117) completed the survey post curriculum. 96.7% of residents report that physicians should lead QI projects and training rather than the hospital administrators. Residents had 20% increase in understanding and confidence in leading quality improvement projects post curriculum once initiated. Most Residents (72%) feel QI should be taught during residency. Active involvement of residents with interest was seen after the initiation of Open School Institute of health improvement (IHI) curriculum as compared to Institutional led QI’s. The resident interventions, pitfalls with change processes with an example of PDSA cycle are discussed. Conclusion: A Dedicated QI curriculum is necessary to prepare the physicians deliver quality care in an increasing complex health care delivery system. The strength of the curriculum is the ease of understanding the material, easily available to all, and can be easily replicated in a Community Hospital program with limited resources. Participation in QI by residents may promote constructive competitiveness among related hospitals in public system to improve delivery of safe care. Abbreviations: ACGME: Accreditation Council for Graduate Medical Education; IHI: Institute of Healthcare Improvement; PDSA: Plan-Do-Study-Act; PGY: QI: Quality improvement

Predicting the mortality risk of patients with Coronavirus Disease 2019 (COVID-19) can be valuable in allocating limited medical resources in the setting of outbreaks. This study assessed the role of a chest X-ray (CXR) scoring system in a multivariable model in predicting the mortality of COVID-19 patients by performing a single-center, retrospective, observational study including consecutive patients admitted with a confirmed diagnosis of COVID-19 and an initial CXR. The CXR severity score was calculated by three radiologists with 12 to 15 years of experience in thoracic imaging, based on the extent of lung involvement and density of lung opacities. Logistic regression analysis was used to identify independent predictive factors for mortality to create a predictive model. A validation dataset was used to calculate its predictive value as the AUROC. A total of 628 patients (58.1% male) were included in this study. Age (p < 0.001), sepsis (p < 0.001), S/F ratio (p < 0.001), need for mechanical ventilation (p < 0.001), and the CXR severity score (p = 0.005) were found to be independent predictive factors for mortality. We used these variables to develop a predictive model with an AUROC of 0.926 (0.891, 0.962), which was significantly higher than that of the WHO COVID severity classification, 0.853 (0.798, 0.909) (one-tailed p-value = 0.028), showing that our model can accurately predict mortality of hospitalized COVID-19 patients.

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