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The emergence of COVID-19, caused by novel Coronavirus SARS-CoV-2, became a pandemic in just 10 weeks. Without effective medications or vaccines available, authorities turned toward mitigation measures such as use of face masks, school's closings, shelter-in-place, telework and social distancing. People found refuge on the internet and social media apps; however, there was a proliferation of instant messaging containing hoaxed, deliberate misleading information: fake news messaging (FNM). The aim of this study was to assess FNM through content analysis and to discriminate them in a proposed taxonomy structure. A sample of convenience of messages, memes, tweets or cartoons in several languages was selected from the most popular social media outlets, i.e. Facebook, WhatsApp, Twitter etc. More than 300 FNM were identified. Descriptive statistics were used for highlighting potential relationships between variables. Content analysis determined that FNM could be divided into Health- and non-health-related types. There are several sub-types considering, but not limited to, religious beliefs, politics, economy, nutrition, behaviors, prevention of the infection, the origin of the disease and conspiracy theories. The parallel FNM pandemic affected the response from an already debilitated public health system through the confusion created in the community and the erosion in the credibility of genuine media. Public health practitioners had to face people's unpredictable behaviors, panic, tensions with the communities and, in some cases, a hostile climate toward frontline workers. Public health practitioners must adjust ongoing and future health promotion and education interventions including plans to neutralize fake news messages.
Atehortua et al. (Fri,) studied this question.