  The outbreak of the infectious and fatal disease COVID-19 has revealed that
pandemics assail public health in two waves: first, from the contagion itself
and second, from plagues of suspicion and stigma. Now, we have in our hands and
on our phones an outbreak of moral controversy. Modern dependency on social
medias has not only facilitated access to the locations of vaccine clinics and
testing sites but also-and more frequently-to the convoluted explanations of
how "COVID-19 was a FIFA conspiracy"[1]. The MIT Media Lab finds that false
news "diffuses significantly farther, faster, deeper, and more broadly than
truth, in all categories of information, and by an order of magnitude"[2]. The
question is, how does the spread of misinformation interact with a physical
epidemic disease? In this paper, we estimate the extent to which misinformation
has influenced the course of the COVID-19 pandemic using natural language
processing models and provide a strategy to combat social media posts that are
likely to cause widespread harm.
