The COVID-19 pandemic has had a profound impact on the nation's health care system, including on graduate medical education (GME) training programs. Traditionally, residency and fellowship training program applications involve in-person interviews conducted on-site, with only a minority of programs offering interviews remotely via a virtual platform. However, in light of the COVID-19 pandemic, it is anticipated that most interviews will be conducted virtually for the 2021 application cycle and possibly beyond. Therefore, GME Please see the end of this article for information about the authors.

Unrecognized transmission is a major contributor to ongoing TB epidemics in high-burden, resource-constrained settings. Limitations in diagnosis, treatment, and infection control in health-care and community settings allow for continued transmission of drug-sensitive and drug-resistant TB, particularly in regions of high HIV prevalence. Health-care facilities are common sites of TB transmission. Improved implementation of infection control practices appropriate for the local setting and in combination, has been associated with reduced transmission. Community settings account for the majority of TB transmission and deserve increased focus. Strengthening and intensifying existing high-yield strategies, including household contact tracing, can reduce onward TB transmission. Recent studies documenting high transmission risk community sites and strategies for community-based intensive case finding hold promise for feasible, effective transmission reduction. Infection control in community settings has been neglected and requires urgent attention. Developing and implementing improved strategies for decreasing transmission to children, within prisons and of drug-resistant TB are needed.

Background: During the COVID-19 pandemic, telemedicine use rapidly and dramatically increased for management of diabetes mellitus. It is unknown whether access to telemedicine care has been equitable during this time. This study aimed to identify patient-level factors associated with adoption of telemedicine for subspecialty diabetes care during the pandemic. Methods: We conducted an explanatory sequential mixed-methods study using data from a single academic medical center. We used multivariate logistic regression to explore associations between telemedicine use and demographic factors for patients receiving subspecialty diabetes care between March 19 and June 30, 2020. We then surveyed a sample of patients who received in-person care to understand why these patients did not use telemedicine. Results: Among 1292 patients who received subspecialty diabetes care during the study period, those over age 65 were less likely to use telemedicine (OR: 0.34, 95% CI: 0.22-0.52, P < .001), as were patients with a primary language other than English (OR: 0.53, 95% CI: 0.31-0.91, P = .02), and patients with public insurance (OR: 0.64, 95% CI: 0.49-0.84, P = .001). Perceived quality of care and technological barriers were the most common reasons cited for choosing in-person care during the pandemic. Conclusions: Our findings suggest that, amidst the COVID-19 pandemic, there have been disparities in telemedicine use by age, language, and insurance for patients with diabetes mellitus. We anticipate telemedicine will continue to be an important care modality for chronic conditions in the years ahead. Significant work must therefore be done to ensure that telemedicine services do not introduce or widen population health disparities.

Purpose of review The role of telehealth in the care of people with type 1 diabetes (T1D) has expanded dramatically during the coronavirus pandemic, and is expected to remain a major care delivery modality going forward. This review explores the landscape of recent evidence for telehealth in T1D care. Recent findings Telemedicine for routine T1D care has shown equivalence to standard in-person care, with respect to glycemic control, while also increasing access, convenience, and satisfaction. Telehealth use promotes increased engagement of adolescents with T1D. Telehealth platforms have successfully been used in the care of microvascular complications and to support mental health related to diabetes. Machine learning and advanced decision support will increasingly be used to augment T1D care, as recent evidence suggests increasing capabilities to improve glycemic control. A spectrum of digital connected care services are emerging to support people with diabetes with daily management of diabetes. Finally, policy and systems are required that promote data interoperability, telemedicine provision, and reimbursement to support the ongoing growth of telehealth in T1D. Summary A developing field of evidence supports use of telehealth in T1D. As this care modality scales, it has the potential to increase access to high-quality diabetes care for many people with T1D.