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I'm a 3rd year PhD student in Sociology, Public Policy and Complex Systems at the University of Michigan. Within sociology, my subfield is social epidemiology. My interests are in the interaction of social policy and the dynamics of infectious and chronic illness.
There is really very little work on dynamic models of chronic illness epidemiology at the population level. Developing truly bottom-up models that connect individual illness processes with social dynamics are an eventual goal, but for the time being I'm working on developing useful formalisms for understanding the development of chronic illness in social context. My approach - up until this point at least - has been to borrow heavily from infectious disease epidemiology and to try and find the points where the 'traditional' modeling paradigm in epidemiology does a good job of answering some of our questions about chronic illness and where more complicated and fundamentally complex tools become necessary.
For the last several years, I've been working on building and verifying models of the transmission of Norovirus (the most common non-bacterial cause of gastroenteritis worldwide - i.e., a nasty stomach bug) in community context.
Areas of Expertise
I have some background in all of the the following - some more than others:
- Nonlinear stochastic systems
- Modeling infectious disease processes
- Linear models
- Social science arcana
(In order of proficiency)
R, Matlab, Java, Perl, Python
I'm currently trying to come up with a meaningful way of thinking about the 'spread' of depression over social networks. Available evidence seems to indicate that over time individual trait moods become more similar over time. What this really means is that we're thinking about the way the thought processes of individuals influence each other and how these processes combine. I've been borrowing heavily from John Padgett's work on hypercycles in economics and would be interested in parterning up with someone who is interested in either the hypercycle approach to social dynamics or the spread of mood over social networks.
I have a pending pilot grant application to collect data to get at these ideas - the idea is to capture an evolving social network at regular intervals (college freshmen, starting at the beginning of their first academic year) and to compare the performance of different models at capturing variability in and the spread of mood states, so there is potential for this project to start out theoretically but progress towards a more concrete empirical project in relatively short order. Media:Example.ogg