- Abusive posts surged alongside rising COVID-19 cases, deaths and major federal policy announcements, especially during the initial emergency response.
- Digital aggression peaked following public health statements on restrictions, testing, vaccination and masking; even compassionate or informational updates drew higher abuse during high-case periods.
- Findings highlight online pressures on health officials and recommend designing resilient public communication strategies for future health crises.
Can J Public Health. 2026 May 29. doi: 10.17269/s41997-026-01219-5. Online ahead of print.
ABSTRACT
OBJECTIVES: This study identifies trends in abusive discourse towards public health professionals (PHPs) during the COVID-19 pandemic and explores associations between abusive digital content, case numbers, deaths, and major policy announcements.
METHODS: Natural language processing (NLP) and large language model (LLM) techniques were used to develop a computational model to detect abusive content on X (formerly Twitter). This model was applied to abusive posts targeting PHPs during COVID-19 by examining over 1.7 million posts from January 2020 to May 2021. Associations between spikes in abuse and the number of COVID-19 cases, deaths, and government monitoring updates were explored.
RESULTS: Pronounced surges in abusive posts coincided with rising case and death counts and the imposition of major federal COVID-19 policies, particularly during the pandemic’s initial emergency response. Digital aggression increased at times of public health statements related to restrictions in social gatherings, testing criteria, vaccinations, and masking. However, during high-case periods, even statements providing case updates, expressing compassion, or urging collective responsibility coincided with higher numbers of abusive posts.
CONCLUSIONS: This work provides insights into the pressures faced by health officials online and offers implications for designing resilient public communication during future crises.
PMID:42213299 | DOI:10.17269/s41997-026-01219-5
Share Evidence Blueprint
Save to Google Notes
Search Google Scholar
Save as PDF
⭐ My Revision List
