Some different works have been done to help evaluate automatic fact-checking during the pandemic. This research intends to review the bibliography and investigate its details, with particular attention to the needs to be explored and justify some future research contribution. For this purpose, randomized trials on fact-checking technologies used during the pandemic shall be reviewed with Scopus, Web of Science, and Google Scholar to foster opportunities and the journalistic position in the media ecosystem regarding health disinformation. In English, Portuguese, and Spanish, studies were selected if published during the most critical Covid-19 pandemic years (2020 and 2021). They could be categorized as presenting automation used to monitor, spot, check, and publish fact-checked hoaxes. After using the possibilities given by machine learning concerning automation, the options bring an inflection point on how technologies lead to assertiveness or even greater credibility in creating and publishing alerts to citizens. A mixed method is used as a methodology, combining qualitative survey case analysis and structured technique as a systematic literature review (SLR), following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. We found two fact-checking institutions to be qualitatively analyzed, proposing the description and modeling of relevant solutions that empower access to verified fact-checked content. As a result, the research aims to scrutinize and reveal ways to boost new possibilities for highlighting fact-checking results and finding ways to use synthetic media that help communicate health risks.

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