ABSTRACT
BACKGRUOUND: The first large coronavirus disease 2019 (COVID-19) outbreak outside China occurred in Daegu. In response, we developed infection prevention measures for surgical patients during the outbreak at our hospital and retrospectively reviewed the outcomes of COVID-19-related surgical patients. METHODS: We reviewed the medical records of 118 COVID-19-related surgical patients and monitored their clinical outcomes until March 31, 2021. We also interviewed healthcare workers who participated in their perioperative care at Kyungpook National University Chilgok Hospital. The perioperative management guidelines for COVID-19-related patients were prepared through multidisciplinary discussions, including the infection control department, surgical departments, and anesthesiology department before and during the COVID-19 outbreak. RESULTS: One standard operating room was temporarily converted to a negative-pressure room by increasing the exhaust air volume, creating a relative pressure of -11.3 Pa. The healthcare workers were equipped with personal protective equipment according to the patient's classification of the risk of COVID-19 transmission. The 118 COVID-19-related patients underwent emergent surgery in the negative-pressure room, including three COVID-19-confirmed patients and five COVID-19-exposed patients. CONCLUSION: All surgeries of the COVID-19-related patients were performed without specific adverse events or perioperative COVID-19 transmission. Our experience setting up a negative-pressure operating room and conservative perioperative protocol to prevent COVID-19 transmission will help plan and execute infection control measures in the future.
ABSTRACT
Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace.