Mentor: Dr. John Drake
Abstract: Superspreading in disease dynamics arises when a small number of individuals contribute disproportionately to transmission. Macroparasites, including both internal parasites (e.g., worms) and ectoparasites (e.g. fleas), are widely understood to exhibit the skewed infection burdens that give rise to superspreading. Although causal drivers of different burden distributions within the same host species have often been examined, our understanding of the broader biological and macroecological conditions responsible for shaping such distributions is minimal. Following the model of a previous student who cataloged the wide range of “transmission trees” (another way of quantifying superspreading, see their work here: https://outbreaktrees.ecology.uga.edu/), this student will seek to develop the first meta-database of macroparasite burdens. This database will enable us to ask, for the first time, whether there are ecological or biological traits of hosts and parasites that govern the shape of these distributions and therefore the propensity for superspreading.
The ideal student for this project is one who likes to play around with data — to collect it, categorize it, think about it, and analyze it. If you like looking for patterns in the world, this project is you. 
Is the project computational, empirical, or both? Computational (creating a database from existing published literature; requires working at a computer, but less coding expertise than some other computational projects).