SIRsim

• Ran simulation on NetLogo for 88 days from December 17, 2019 to March 14, 2020 that accounted for 7.7 billion people
• Divided population into 1,540 agents, each containing 5 million people
• Agents were simulated to travel to 36 major cities and the first agent (patient 0) started in Wuhan and started out as S
• 3 nodes – Susceptible, Infected, Removed – indicated whether agents have come into contact with patient 0 or other infected agents through driving and flying
• Simulation repeated over 100 times

SIRemp

• Used Johns Hopkins Center for Systems Science and Engineering (JHU CSSE) repository for cumulative case counts of over 185 countries from January 22 to March 14, 2020
• Used same assumptions for SIR model – S (all members of world population and thus excluded), I (confirmed cases), and R (deaths cases)

INFOcas

• 675,228 tweets collected from December 31, 2019 to March 14, 2020 that had at least one of the hashtags #coronavirus, #covid19, #ncov
• Information cascades created for retweets, quote tweets (forward with additional information), and replies (comments)
• SIR model – S (excluded since it represents all tweets on Twitter), I (interactions), R (no interactions during the period), new information