The emergence of the COVID-19 pandemic has resulted in an infodemic– a flood of epidemic-related information- that encompasses a plethora of misinformation that has arisen from rapidly evolving science, uncertainty, information gaps, and special interests. The misinfodemic– epidemic of misinformation, midinformation, and disinformation- has largely kept pace with the pandemic and continues to proliferate across online media and communication channels. The potential risks and dangers of misinformation are well documented in the literature and include adverse health effects like increased disease spread, hospitalization, and death; stigmatization of individuals and groups; increased health inequities; and distrust in government and public health guidance. The goal of the COVID-19 Expert Database was to employ the skills of public health professionals to provide an added layer of expertise for journalists, fact-checking organizations, and media outlets to improve health-reporting capacity, provide accessible COVID-19-related content, and distill complex scientific findings to support local and contextually-relevant communications. Launched in June 2020, the project was designed as an applied research initiative aimed at strengthening the quality of COVID-19-related health information and decreasing circulating misinformation to advance health equity.
How to cite: LaRose E, Shroff A, Huang J, Gyenes N. Mobilizing public health professionals to support journalists and fact-checkers during the Covid-19 pandemic. HPHR. 2021; 33. https://hphr.org/edition-33-larose/
- Online conversations are heavily influenced by news coverage, like the 2022 Supreme Court decision on abortion. The relationship is less clear between big breaking news and specific increases in online misinformation.
- The tweets analyzed were a random sample qualitatively coded as “misinformation” or “not misinformation” by two qualitative coders trained in public health and internet studies.
- This method used Twitter’s historical search API
- The peak was a significant outlier compared to days before it using Grubbs' test for outliers for Chemical Abortion (p<0.2 for the decision; p<0.003 for the leak) and Herbal Abortion (p<0.001 for the decision and leak).
- All our searches were case insensitive and could match substrings; so, “revers” matches “reverse”, “reversal”, etc.