COVID-19 Pandemic-Associated Changes in the Acuity of Brain MRI Findings: A Secondary Analysis of Reports Using Natural Language Processing.

RATIONALE AND OBJECTIVES: We aimed to assess early COVID-19 pandemic-associated changes in brain MRI examination frequency and acuity of imaging findings acuity. METHODS: Using a natural language processing model, we retrospectively categorized reported findings of 12,346 brain MRI examinations performed during 6-month pre-pandemic and early pandemic time periods across a large metropolitan health system into 3 acuity levels: (1) normal or near normal; (2) incidental or chronic findings not requiring a management change; and (3) new or progressive findings requiring a management change. Brain MRI frequency and imaging finding acuity level were compared over time. RESULTS: Between March and August of 2019 (pre-pandemic) and 2020 (early pandemic), our health system brain MRI examination volumes decreased 17.0% (6745 vs 5601). Comparing calendar-matched 6-month periods, the proportion of higher acuity findings increased significantly (P< 0.001) from pre-pandemic (22.5%, 43.6% and 34.0% in acuity level 1, 2, and 3, respectively) to early pandemic periods (19.1%, 40.9%, and 40.1%). During the second 3 months of the early pandemic period, as MRI volumes recovered to near baseline, the proportion of higher acuity findings remained high (42.6% vs 34.1%) compared with a similar pre-pandemic period. In a multivariable analysis, Black (B coefficient, 0.16) and underinsured population (B coefficient, 0.33) presented with higher acuity findings (P< 0.05). CONCLUSIONS: As the volume of brain MRI examinations decreased during the early COVID-19 pandemic, the relative proportion of examinations with higher acuity findings increased significantly. Pandemic-related changes in patient outcomes related to reduced imaging access merits further attention.

The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing

The COVID-19 pandemic is a major challenge for society as a whole, and analyzing the impact of the spread of the epidemic and government control measures on the travel patterns of urban residents can provide powerful help for city managers to designate top-level epidemic prevention policies and specific epidemic prevention measures. This study investigates whether it is more appropriate to use groups of POIs with similar pedestrian flow patterns as the unit of study rather than functional categories of POIs. In this study, we analyzed the hour-by-hour pedestrian flow data of key locations in Beijing before, during, and after the strict epidemic prevention and control period, and we found that the pedestrian flow patterns differed greatly in different periods by using a composite clustering index;we interpreted the clustering results from two perspectives: groups of pedestrian flow patterns and functional categories. The results show that depending on the specific stage of epidemic prevention and control, the number of unique pedestrian flow patterns decreased from four before the epidemic to two during the strict control stage and then increased to six during the initial resumption of work. The restrictions on movement are correlated with most of the visitations, and the release of restrictions led to an increase in the variety of unique pedestrian flow patterns compared to that in the pre-restriction period, even though the overall number of visitations decreased, indicating that social restrictions led to differences in the flow patterns of POIs and increased social distance.