Globalization and increasing numbers of students increase the risk for epidemics on different scales. This semester project suggests an approach, based on Agent-Based-Modelling, to optimize classroom size relative to their cost to keep the infection rate low in universities.
- After 7 days are all students recovered, regardless of the timepoint of infection during the 7 days
- At first day of the week 10% of the students randomly infected
- Square Classroom dimension -> Number of students per class must be a squared number
- Students are distributed into classes randomly and the seating is random as well
- Given student is infected in class n, virus can be infect other students in class n+1 and student infected in n will be home from class n+2 until new week starts
- No immunization after an infection
- Infections only in the classroom possible
- Fixed Beta = 0.001
-> What is the optimal classroom size too keep the attendance high and the costs low?
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How does number of students per class affect the infections per week? Prediction: more students lead to more interactions causing higher infection rates
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How does the distance between students affect the infections per week? Prediction: The smaller the distance between students the more infections per week