Undergraduate students have an intuitive understanding that contact between an infectious individual and a susceptible individual can cause parasite transmission or infection. While undergraduate students can describe factors that facilitate parasite transmission, such as differences in immunity or contact patterns among hosts, it can be challenging to teach the mathematical representations that connect these processes to population-level outcomes that are of interest to public and environmental health experts. Here, we present an inquiry-based laboratory exercise where students construct a contact network based on shared courses, extracurricular activities, and residential housing. We first contrast this approach with the “classic” compartment or SIR-type (Susceptible-Infected-Recovered) model that ignores variation in contact patterns. Students then simulate epidemics through their self-generated network using dice to illustrate the role of demographic stochasticity (i.e., luck or chance) in the progression of epidemic clusters. Once familiar with infection spread in the network, students make predictions about the size of epidemics that begin at different nodes of the network with and without public health interventions (e.g., masking, social distancing). These exercises have been adapted for non-major and upper-level biology undergraduates and have been implemented successfully in-person and in remote teaching modalities.
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