Background: In February 2020, a coronavirus disease 2019 (COVID-19) outbreak was reported in fitness centers in Cheonan, Korea. Methods: From February 24 to March 13, an epidemiological investigation was conducted on the fitness center outbreak. All those who were screened were tested for severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) using real-time reverse transcriptase polymerase chain reaction. Contacts were traced and self-isolated for 14 days. We determined the epidemiological characteristics of confirmed cases of SARS-CoV-2 infection, and estimated the time-dependent reproduction number to assess the transmission dynamics of the infection. Results: A total of 116 cases were confirmed, and 1,687 contacts were traced. The source cases were 8 Zumba instructors who led aerobics classes in 10 fitness centers, and had the largest average number of contacts. A total of 57 Zumba class participants, 37 of their family members, and 14 other contacts were confirmed as cases. The attack rate was 7.3%. The contacts at Zumba classes and homes had a higher attack rate than other contacts. The mean serial interval (± standard deviation) were estimated to be 5.2 (± 3.8) days. The timedependent reproduction number was estimated to be 6.1 at the beginning of the outbreak, but it dropped to less than 1, 2 days after the epidemiological investigation was launched. Conclusion: The results suggest that the COVID-19 outbreak was effectively contained with rigorous contact tracing, isolating, and testing in combination with social distancing without a lock-down.

No abstract

No abstract

Computational image analysis is used in many areas of biological and medical research, but advanced techniques including machine learning remain underutilized. Here, we used automated segmentation and shape analyses, with pre-defined features and with computer generated components, to compare nuclei from various premature aging disorders caused by alterations in nuclear proteins. We considered cells from patients with Hutchinson-Gilford progeria syndrome (HGPS) with an altered nucleoskeletal protein; a mouse model of XFE progeroid syndrome caused by a deficiency of ERCC1-XPF DNA repair nuclease; and patients with Werner syndrome (WS) lacking a functional WRN exonuclease and helicase protein. Using feature space analysis, including circularity, eccentricity, and solidity, we found that XFE nuclei were larger and significantly more elongated than control nuclei. HGPS nuclei were smaller and rounder than the control nuclei with features suggesting small bumps. WS nuclei did not show any significant shape changes from control. We also performed principle component analysis (PCA) and a geometric, contour based metric. PCA allowed direct visualization of morphological changes in diseased nuclei, whereas standard, feature-based approaches required pre-defined parameters and indirect interpretation of multiple parameters. Both methods yielded similar results, but PCA proves to be a powerful pre-analysis methodology for unknown systems.