High Rates of COVID-19 Infection Among Indigenous Maya at a US Safety-Net Health System in California.

Coronavirus disease 2019 (COVID-19) has disproportionately and negatively affected communities of color in the United States, especially Black, Latinx, and Indigenous populations. We report a cluster of COVID-19 cases among the Maya in Alameda County, California, most of whom were misclassified in public health data as nonindigenous Spanish-speaking people. We conducted a retrospective cohort study of all COVID-19 tests performed from April 1 through May 31, 2020, at Alameda Health System. A total of 1561 tests from 1533 patients were performed, with an overall test positivity rate of 17.0% (N = 265). We used the language field from the electronic health record to identify 29 patients as speaking an indigenous Mayan language; by medical record review, we identified 52 additional Maya patients. Maya patients had a test positivity rate of 72.8% as compared with 27.1% (P < .001) for nonindigenous Latinx patients and 8.2% (P < .001) for all other patients. In our sample, 39.6% of patients who had a positive test result for COVID-19 were hospitalized, 11.3% required admission to the intensive care unit (ICU), and 4.9% died of COVID-19. Maya patients had lower rates of hospitalization, ICU admission, and 30-day in-hospital mortality than non-Maya patients. We shared our data with the county health department to inform responses for education, testing, and isolation for Maya patients in Alameda County. Ongoing COVID-19 public health efforts should assess the community prevalence of COVID-19 in the Maya community and other indigenous communities and implement interventions that are linguistically and culturally appropriate.

Racial/ethnic disparities in COVID-19 disease burden & mortality among emergency department patients in a safety net health system.

BACKGROUND: We sought to examine racial and ethnic disparities in test positivity rate and mortality among emergency department (ED) patients tested for COVID-19 within an integrated public health system in Northern California. METHODS: In this retrospective study we analyzed data from patients seen at three EDs and tested for COVID-19 between April 6 through May 4, 2020. The primary outcome was the test positivity rate by race and ethnicity, and the secondary outcome was 30 day in-hospital mortality. We used multivariable logistic regression to examine associations with COVID-19 test positivity. RESULTS: There were 526 patients tested for COVID-19, of whom 95 (18.1%) tested positive. The mean age of patients tested was 54.2 years, 54.7% were male, and 76.1% had at least one medical comorbidity. Black patients accounted for 40.7% of those tested but 16.8% of the positive tests, and Latinx patients accounted for 26.4% of those tested but 58.9% of the positive tests. The test positivity rate among Latinx patients was 40.3% (56/139) compared with 10.1% (39/387) among non-Latinx patients (p < 0.001). Latinx ethnicity was associated with COVID-19 test positivity (adjusted odds ratio 9.6, 95% confidence interval: 3.5-26.0). Mortality among Black patients was higher than non-Black patients (18.7% vs 1.3%, p < 0.001). CONCLUSION: We report a significant disparity in COVID-19 adjusted test positivity rate and crude mortality rate among Latinx and Black patients, respectively. Results from ED-based testing can identify racial and ethnic disparities in COVID-19 testing, test positivity rates, and mortality associated with COVID-19 infection and can be used by health departments to inform policy.

Transferability of Virtual Reality, Simulation-Based, Robotic Suturing Skills to a Live Porcine Model in Novice Surgeons: A Single-Blind Randomized Controlled Trial.

STUDY OBJECTIVE: To assess whether a robotic simulation curriculum for novice surgeons can improve performance of a suturing task in a live porcine model. DESIGN: Randomized controlled trial (Canadian Task Force classification I). SETTING: Academic medical center. PATIENTS: Thirty-five medical students without robotic surgical experience. INTERVENTIONS: Participants were enrolled in an online session of training modules followed by an in-person orientation. Baseline performance testing on the Mimic Technologies da Vinci Surgical Simulator (dVSS) was also performed. Participants were then randomly assigned to the completion of 4 dVSS training tasks (camera clutching 1, suture sponge 1 and 2, and tubes) versus no further training. The intervention group performed each dVSS task until proficiency or up to 10 times. A final suturing task was performed on a live porcine model, which was video recorded and blindly assessed by experienced surgeons. The primary outcomes were Global Evaluative Assessment of Robotic Skills (GEARS) scores and task time. The study had 90% power to detect a mean difference of 3 points on the GEARS scale, assuming a standard deviation (SD) of 2.65, and 80% power to detect a mean difference of 3 minutes, assuming an SD of 3 minutes. MEASUREMENTS AND MAIN RESULTS: There were no differences in demographics and baseline skills between the 2 groups. No significant differences in task time in minutes or GEARS scores were seen for the final suturing task between the intervention and control groups, respectively (9.2 [2.65] vs 9.9 [2.07] minutes, p = .406; and 15.37 [2.51] vs 15.25 [3.38], p = .603). The 95% confidence interval for the difference in mean task times was -2.36 to .96 minutes and for mean GEARS scores -1.91 to 2.15 points. CONCLUSIONS: Live suturing task performance was not improved with a proficiency-based virtual reality simulation suturing curriculum compared with standard orientation to the da Vinci robotic console in a group of novice surgeons.