Using standard celeration makes COVID-19 data more meaningful

The fourth sudden acute respiratory syndrome (SARS) virus, COVID-19, emerged in late 2019, leading to the most devastating pandemic since the Spanish influenza (H1N1) of 1918, which seized 50 million lives worldwide (https://www.cdc.gov/flu/pandemic-resources/1918-pandemic-h1n1.html). Elected officials must make critical system-level decisions for stymieing the spread of the virus. Businesspersons must make personnel, financial, and operational decisions to minimize transmission while preserving their business's vitality. Members of the public must make personal decisions about personal protective equipment and changing social, recreational, occupational, and spiritual behavior to protect themselves and others. The scientific community can shift how they illustrate the virus's behavior to the public in an appropriate and understandable way so that the public can make informed decisions. This article suggests the use of a single-case design and logarithmic analyses to improve the current methodologies for COVID-19 analysis and illustration.

The Standard Celeration Chart was used with Theil's incomplete regression and a 7-point change analysis; the authors demonstrate a suitable virus-tracking and mitigation methodology.

Analysis and data visualization are standardized, providing an accurate depiction of the virus's growth for public dissemination and decision-making. An analytic strategy is demonstrated for retrospectively detecting meaningful changes in viral growth or prospectively measuring such changes that coincide with known mitigation strategies.

The authors suggest improvements in bridging science to application by making COVID-19 informatics more meaningful and actionable by lawmakers, businesspersons, and the public. Limitations and future directions for COVID-19 informatics are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).