Lisa Mariott


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COVID-19 (Disease), Coronavirus, Computational modeling, Communicable diseases -- Epidemiology -- Mathematical models


One of the most significant issues in the COVID-19 pandemic is the reopening of schools while minimizing the transmission of coronavirus. Opportunities for evaluating the effectiveness of policies that might be utilized at such institutions are limited, as the necessary empirical data has not been gathered yet. Agent-based modeling, where various entities within an environment are simulated as agents, offers an opportunity to examine the effectiveness of various policies in a way that drastically minimizes the health and economic risks involved. Agent-based modeling is common within biology, ecology and other fields; and has seen some use within the coronavirus literature. We utilized the Python library Mesa to design and run agent-based models that allow us to examine the efficacy of various protocols that might be implemented, including mask adoption, limited time spent in classrooms, enhanced cleaning schedules, quarantining infected individuals, etc. We measured the amount of agents that were infected, the average basic reproduction number for agents, and several other measures. We found that reducing the number of individuals in the classroom, as well as the number of hours spent in the classroom, had the strongest effects on reducing the basic reproduction number and the peak percentage of people who were infected. Further research may be able to evaluate other protocols and means of measurement as an extension of this model. Our model, which may be utilized as a tool by public health officials and policy makers, is available at:


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This podcast serves to recap our process and results from the altREU experience through the Teuscher Lab at Portland State University. More information, including the source code, is available at

Our final presentation is available to view at

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Abstract.pdf (44 kB)



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