Visualizing the features of inflection point shown on a temporal bar graph using the data of COVID-19 pandemic. Issue 5 (4th February 2022)

• Record Type: Journal Article
• Authors: Ho, Sam Yu-Chieh; Chien, Tsair-Wei; Shao, Yang; Hsieh, Ju-Hao
• Other Names: Kumar. Pavan section editor.
• Is Part Of: Medicine. Volume 101:Issue 5(2022)
• Publication Date: 2022-02-04
• Subjects: burst strength -- Collatz conjecture -- COVID-19 -- infection point -- item response theory -- temporal bar graph; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000028749
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract: Background: Exponential-like infection growth leading to peaks (denoted by inflection points [IP] or turning points) is usually the hallmark of infectious disease outbreaks, including coronaviruses. To determine the IPs of the novel coronavirus (COVID-19), we applied the item response theory model to detect phase transitions for each country/region and characterize the IP feature on the temporal bar graph (TBG). Methods: The IP (using the item difficulty parameter to locate) was verified by the differential equation in calculus and interpreted by the TBG with 2 virtual and real empirical data (i.e., from Collatz conjecture and COVID-19 pandemic in 2020). Comparisons of IPs, R 2, and burst strength [BS = ln( ) denoted by the infection number at IP(Nip) and the item slope parameter(a) in item response theory were made for countries/regions and continents on the choropleth map and the forest plot. Results: We found that the evolution of COVID-19 on the TBG makes the data clear and easy to understand, the shorter IP (=53.9) was in China and the longest (=247.3) was in Europe, and the highest R 2 (as the variance explained by the model) was in the US, with a mean R 2 of 0.98. We successfully estimated the IPs for countries/regions on COVID-19 in 2020 and presented them on the TBG. Conclusion: Temporal visualization is recommended for researchers in future relevant studies (e.g., the evolution of keywords in a specific discipline) and is not merely limited to the IP search in COVID-19 pandemics as we did in this study. Abstract : Supplemental Digital Content is available in the text