The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pathogen has spread rapidly across the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism to minimise the effects on human health, and the potential for virus transmission to Antarctic wildlife. We assess the reverse-zoonotic transmission risk to Antarctic wildlife by considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. The environmental conditions in Antarctica seem to be favourable for the virus stability. Indoor spaces such as those at research stations, research vessels or tourist cruise ships could allow for more transmission among humans and depending on their movements between different locations the virus could be spread across the continent. Among Antarctic wildlife previous in silico analyses suggested that cetaceans are at greater risk of infection whereas seals and birds appear to be at a low infection risk. However, caution needed until further research is carried out and consequently, the precautionary principle should be applied. Field researchers handling animals are identified as the human group posing the highest risk of transmission to animals while tourists and other personnel pose a significant risk only when in close proximity (< 5 m) to Antarctic fauna. We highlight measures to reduce the risk as well as identify of knowledge gaps related to this issue.

COVID-19 inequities have been well-documented. We evaluated whether higher rates of severe COVID-19 in racial and ethnic minority groups were driven by higher infection rates by evaluating if disparities remained when analyses were restricted to people with infection. We conducted a retrospective cohort study of adults insured through Kaiser Permanente (Colorado, Northwest, Washington), follow-up in March–September 2020. Laboratory results and hospitalization diagnosis codes identified individuals with COVID-19. Severe COVID-19 was defined as invasive mechanical ventilation or mortality. Self-reported race and ethnicity, demographics, and medical comorbidities were extracted from health records. Modified Poisson regression estimated adjusted relative risks (aRRs) of severe COVID-19 in full cohort and among individuals with infection. Our cohort included 1,052,774 individuals, representing diverse racial and ethnic minority groups (e.g., 68,887 Asian, 41,243 Black/African American, 93,580 Hispanic or Latino/a individuals). Among 7,399 infections, 442 individuals experienced severe COVID-19. In the full cohort, severe COVID-19 aRRs for Asian, Black/African American, and Hispanic individuals were 2.09 (95% CI: 1.36, 3.21), 2.02 (1.39, 2.93), and 2.09 (1.57, 2.78), respectively, compared to non-Hispanic Whites. In analyses restricted to individuals with COVID-19, all aRRs were near 1, except among Asian Americans (aRR 1.82 [1.23, 2.68]). These results indicate increased incidence of severe COVID-19 among Black/African American and Hispanic individuals is due to higher infection rates, not increased susceptibility to progression. COVID-19 disparities most likely result from social, not biological, factors. Future work should explore reasons for increased severe COVID-19 risk among Asian Americans. Our findings highlight the importance of equity in vaccine distribution. Supplementary Information The online version contains supplementary material available at 10.1007/s40615-021-01205-2.

Equal access to novel surgical technologies remains a policy concern as hospitals adopt robotic surgery with increasing prevalence. This study sought to determine whether socioeconomic factors influence access to robotic surgery. All laparoscopic and robotic fundoplications and paraesophageal hernia repairs performed by a surgical group over 6 years at a county and two neighboring private hospitals were identified. Robotic use by hospital setting, age, gender, reported ethnicity, estimated income, insurance payer, and diagnosis were examined. Of 418 patients identified, 180 (43%) presented to the county hospital, where subjects were younger (51.1 versus 56.2 years, p < 0.001) with lower estimated income ($50,289 versus $62,959, p < 0.001). In the county setting, there was no difference in reported ethnicity (p = 0.169), estimated income (p = 0.081), or insurance payer (p = 0.535) between groups treated laparoscopically versus robotically. There was no difference in the treatment groups by estimated income in the private hospital setting (p = 0.308). Overall higher estimated income and insurance payer were associated with a higher chance of undergoing robotic procedures (p < 0.001). Presence of a paraesophageal hernia was associated with increased chance of undergoing robotic therapy in all comparisons (p < 0.001). No disparity in access to robotic surgery offered in the county hospital was observed based on age, gender, reported ethnicity, estimated income, or insurance payer. Patients with higher income and private insurers were more likely to present to the private hospital setting where robotics is utilized more often. The presence of a paraesophageal hernia was a significant factor in determining robotic therapy in both settings.

Purpose To estimate the positive predictive value (PPV) of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD‐10‐CM) diagnosis codes for identifying HF subtypes. Methods We validated ICD‐10‐CM HF diagnosis codes among Kaiser Permanente Washington enrollees who were ≥18 years of age and had an ICD‐10‐CM HF diagnosis code during 2017–2018 and a procedure code for an echocardiogram in the 12 months before through 6 months after the HF code. Left ventricular ejection fraction (LVEF) ascertained from medical chart review was used as the gold standard for classifying patients as having reduced ejection fraction (rEF), mid‐range ejection fraction (mEF), or preserved ejection fraction (pEF). Results Among 6194 eligible patients, we randomly sampled 1000 for medical chart review. A total of 974 patients had LVEF information in their chart. The ICD‐10‐CM HF code group with the highest PPV for rEF was I50.20‐I50.23, “Systolic (congestive) heart failure,” PPV = 41.4% (95% CI, 34.5–48.7%); and the highest PPV for mEF or rEF was also I50.20‐I50.23, PPV = 70.2% (95% CI, 63.1–76.4%). The highest PPV for pEF was the I50.30‐I50.33 group, “Diastolic (congestive) heart failure,” PPV = 92.0% (95% CI, 88.1–94.7%); and the highest PPV for mEF or pEF was also I50.30‐I50.33, PPV = 97.7% (95% CI, 95.1–99.0%). Conclusions If the accuracy measure of greatest interest is PPV, our results suggest that ICD‐10‐CM HF codes alone may not be adequate for identifying patients with rEF but may be adequate for identifying patients with pEF. HF coding practices may vary across settings, which may impact generalizability of our findings.