Research Interests

I am a research scientist in the field of mathematical epidemiology. I develop and construct simulation models of infectious disease dynamics to assist with policy decision making. My current focus is on understanding how host travel patterns contribute to epidemiological patterns: how does routine commuting or infrequent long-distance travel drive and sustain outbreaks of infectious disease? I am currently working to develop data sets which will allow epidemiologists access to quantitative estimates of how travel contributes to contact and mixing across geographical space.

My graduate training is in physics. During my doctoral studies I focused on topics related to interdisciplinary computational science and network science. Half of my research was related to simulation modeling of infectious diseases on networks, exploring how contact network structure can affect outbreaks of endemic disease by changing the population's critical community size. The other half of my research was related to studying the patterns that arise in scientific literature - identifying networks of scientific articles connected through plagiarized content, and using machine learning to identify networks of scientific subdisciplines and mapping how they grow over time.

My postdoctoral research is related to building simulations of malaria transmission as analytical tools for policy makers. From 2017-2019, I worked with the Bioko Island Malaria Elimination Program to develop a simulation model for quantifying the impact of future interventions on Bioko Island in Equatorial Guinea. This work required understanding the epidemiological data and then collaborating with programmers to develop and calibrate our simulation model. We were able to quantify the important role that imported cases play in maintaining high prevalence on the island.

Understanding human movement and travel patterns is crucial for understanding disease transmission in many different settings. The recent availability of new data streams, in the form of movement history data collected from mobile phone usage, presents an exciting opportunity to understand travel patterns at an unprecedented geographical scale. I am currently working as a visiting researcher alongside the Facebook Data for Good team to develop new data sets on human travel for epidemiological purposes.


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