Visualization analysis of the characteristics of COVID-19 clinical trial

Abstract

Objectives: This article points out the characteristics and trends of COVID-19 clinical trials through data collection, translation, mining and visualization to help in clinical trial design.Method: The registered data of COVID-19 clinical trials are gathered from the Chinese Clinical Trial Registry and ClinicalTrials.gov website transformed by Python, further demonstrated by visual tools.Results: As of 24:00 on March 28, 2020, totally 732 trial registration records have been retrieved. Overall, there are 406 (55.46%) interventional studies and 271 (37.02%) observational studies. Among interventional studies, 38.93% are randomized parallel trials, 55 (13.55%) trials considered time condition for clinical recovery as the primary endpoint, and 46 (11.33%) trials through clinical parameters and laboratory index as the primary endpoint. In the selection of intervention measures, chemical or biological agents was under the responsibility of 43.60%, of which antivirals accounted for 14.53%, antimalarials accounted for 8.87%, and 98 cases (24.14%) of studies involving Traditional Chinese Medicine or Integrated Medicine. In addition, joint network analysis of antivirals to explore the combination of drugs is further conducted.Conclusions: By Mining characteristic information of topical COVID-19 clinical trial registration, this article deserves further trial design ideas for researchers to enhance the effects.

Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare

“…The outbreak of COVID-19 coincides with China’s Lunar New Year holiday, a period of mass migration. The “Baidu Migration Map” big data platform launched by Baidu map uses massive location service data to display the trajectory and characteristics of population migration around the Spring Festival in a complete, dynamic, instant, and intuitive manner [ 243 , 244 ]. During the Spring Festival, users can intuitively understand the short-term population flow between cities.…”