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The COVID-19 pandemic has caused significant changes in dermatologic care, likely exacerbating health disparities for specific minority populations. The use of teledermatology has also become more prevalent during this period. The aim of this study was to determine if the proportion of teledermatology versus office-based visits varied significantly during three study periods of the COVID-19 pandemic. The secondary objective was to determine whether there are significant differences in the use of office-based dermatology versus teledermatology care across the following demographic subgroups: insurance type, race/ethnicity, age, and language during the same periods. A chart review of dermatology visits in electronic medical records at a tertiary referral center in Washington, DC, was conducted. The overall telehealth visit rate was 0% in the prequarantine period, 61.12% during the quarantine period, and 10.59% in the postquarantine period. After assessing telehealth utilization rates among the demographic subgroups, we noted that Medicaid users, Black patients, 64-year-olds or older, and English speakers may benefit the least from telehealth services. Teledermatology use necessitated by the COVID-19 pandemic may have promoted health care disparities for specific marginalized populations.

Objectives Bicycling and helmet surveillance, research, and programme evaluation depend on accurate measurement by direct observation, but it is unclear whether weather and other exogenous factors introduce bias into observed counts of cyclists and helmet use. Methods To address this issue , a time series was created of cyclists observed at two observation points in Washington, DC, at peak commuting times and locations between September 2012 and February 2013. Using multiple linear regression with Newey-West SEs to account for possible serial correlation, the association between various factors and cyclist counts and helmet use was investigated. Results The number of cyclists observed per 1 h session was significantly associated with predicted daily high temperature, chance of rain, and actual rain. Additionally, fewer cyclists were observed on Fridays. Helmet use was significantly lower during evening commutes than morning and also lower on Fridays. Helmet use was not associated with weather variables. Controlling for observable cyclists characteristics weakened the association between helmet use and the time of day and day of the week, but it did not eliminate that association. Conclusions Direct observation to measure commuter cycling trends or evaluate interventions should control for weather and day of week. Measurement of helmet use is unlikely to be meaningfully biased by weather factors, but time of day and day of week should be taken into account. Failing to control for these factors could lead to significant bias in assessments of the level of, and trends in, commuter cycling and helmet use.