Author: Reza S. Abhari; Marcello Marini; Ndaona Chokani
Title: COVID-19 Epidemic in Switzerland: Growth Prediction and Containment Strategy Using Artificial Intelligence and Big Data Document date: 2020_4_1
ID: elmagpu4_20
Snippet: Our agent-based simulation framework, EnerPol, which accounts for 100% of the entire population of Switzerland, and that was applied to scenarios of influenza in Switzerland, 4 is used. EnerPol is a holistic agent-based model with choice models, where the agents adapt their behaviour through artificial intelligence as part of the solution. A schematic of EnerPol modules that are used for the agent-based simulation of epidemic spread is shown in F.....
Document: Our agent-based simulation framework, EnerPol, which accounts for 100% of the entire population of Switzerland, and that was applied to scenarios of influenza in Switzerland, 4 is used. EnerPol is a holistic agent-based model with choice models, where the agents adapt their behaviour through artificial intelligence as part of the solution. A schematic of EnerPol modules that are used for the agent-based simulation of epidemic spread is shown in Figure 1 . The mortality rate due to COVID-19 in multiple countries, including South Korea and Italy, has been shown to be strongly coupled to pre-existing conditions, specifically hypertension and heart disease, diabetics and lung disease. 8, 9 Given that the profile of chronic diseases in the Swiss population differs slightly from that in the South Korean population, 10,11 the mortality rates observed in the spread of COVID-19 in South Korea were linearly adjusted for the case of Switzerland.
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