Abstract
The recent COVID -19 pandemic has raised questions about how a disease may spread in an environment like a college campus or a business. In this paper, an agent-based model is presented which simulates the spread of a disease which starts with one infected agent. The agents in the model are randomly selected to follow social distancing and/or mask-wearing guidelines. Compliance with the guidelines reduces the agent's probability of contracting the modeled disease. A variety of compliance strategies are considered, including constant compliance, a time-based compliance where every agent complies during business hours and a subset does not during evenings and weekends, and a model where the population density is increased on weekends, with the introduced agents not complying with the guidelines. The question examined is, how does time-based compliance of the guidelines affect the size and timing of the outbreaks peak (i.e. maximum number of infected agents)?Funding Statement: The worked contained in this paper is unfunded.Declaration of Interests: The author has not received payment or services from a third party (government, commercial, private foundation, etc.) for any aspect of the submitted work (including but not limited to grants, data monitoring board, study design, manuscript preparation, statistical analysis, etc.). The author does not have any patents pending relevant to this work.
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