Tactical risk communication: Observations from teaching and learning about crisis communication during COVID-19

In a Spring 2020 Technical and Professional Communication (TPC) course on risk communication, we watched the COVID-19 pandemic unfold and discussed how technical communicators can foreground vulnerable and marginalized populations who are often excluded from official communication channels. The article below offers perspectives on tactical communication and/or coalition building during a pandemic, coining the term tactical risk communication (TRC) and examining how TRC functions in the face of a global health crisis. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Using machine learning to predict COVID-19 infection and severity risk among 4510 aged adults: a UK Biobank cohort study.

Many risk factors have emerged for novel 2019 coronavirus disease (COVID-19). It is relatively unknown how these factors collectively predict COVID-19 infection risk, as well as risk for a severe infection (i.e., hospitalization). Among aged adults (69.3 ± 8.6 years) in UK Biobank, COVID-19 data was downloaded for 4510 participants with 7539 test cases. We downloaded baseline data from 10 to 14 years ago, including demographics, biochemistry, body mass, and other factors, as well as antibody titers for 20 common to rare infectious diseases in a subset of 80 participants with 124 test cases. Permutation-based linear discriminant analysis was used to predict COVID-19 risk and hospitalization risk. Probability and threshold metrics included receiver operating characteristic curves to derive area under the curve (AUC), specificity, sensitivity, and quadratic mean. Model predictions using the full cohort were marginal. The "best-fit" model for predicting COVID-19 risk was found in the subset of participants with antibody titers, which achieved excellent discrimination (AUC 0.969, 95% CI 0.934-1.000). Factors included age, immune markers, lipids, and serology titers to common pathogens like human cytomegalovirus. The hospitalization "best-fit" model was more modest (AUC 0.803, 95% CI 0.663-0.943) and included only serology titers, again in the subset group. Accurate risk profiles can be created using standard self-report and biomedical data collected in public health and medical settings. It is also worthwhile to further investigate if prior host immunity predicts current host immunity to COVID-19.

Tactical Risk Communication: Observations from Teaching and Learning about Crisis Communication during COVID-19

In a Spring 2020 Technical and Professional Communication (TPC) course on risk communication, we watched the COVID-19 pandemic unfold and discussed how technical communicators can foreground vulnerable and marginalized populations who are often excluded from official communication channels. The article below offers perspectives on tactical communication and/or coalition building during a pandemic, coining the term tactical risk communication (TRC) and examining how TRC functions in the face of a global health crisis. [ FROM AUTHOR] Copyright of Technical Communication Quarterly is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all Abstracts.)