  Disruptions resulting from an epidemic might often appear to amount to chaos
but, in reality, can be understood in a systematic way through the lens of
"epidemic psychology". According to Philip Strong, the founder of the
sociological study of epidemic infectious diseases, not only is an epidemic
biological; there is also the potential for three psycho-social epidemics: of
fear, moralization, and action. This work empirically tests Strong's model at
scale by studying the use of language of 122M tweets related to the COVID-19
pandemic posted in the U.S. during the whole year of 2020. On Twitter, we
identified three distinct phases. Each of them is characterized by different
regimes of the three psycho-social epidemics. In the refusal phase, users
refused to accept reality despite the increasing number of deaths in other
countries. In the anger phase (started after the announcement of the first
death in the country), users' fear translated into anger about the looming
feeling that things were about to change. Finally, in the acceptance phase,
which began after the authorities imposed physical-distancing measures, users
settled into a "new normal" for their daily activities. Overall, refusal of
accepting reality gradually died off as the year went on, while acceptance
increasingly took hold. During 2020, as cases surged in waves, so did anger,
re-emerging cyclically at each wave. Our real-time operationalization of
Strong's model is designed in a way that makes it possible to embed epidemic
psychology into real-time models (e.g., epidemiological and mobility models).
