Network Modeling for Epidemics (NME) is a 5-day short course at the University of Washington that provides training in stochastic network models for infectious disease transmission dynamics.
This is a ”hands-on” course, using the EpiModel software package in R (www.epimodel.org). EpiModel provides a unified framework for statistically based modeling of dynamic networks from empirical data, and simulation of epidemic dynamics on these networks. It is a flexible open-source platform for learning and building epidemic models (including deterministic compartmental, stochastic individual-based, and stochastic network models). Resources include simple models that run in a browser window, built-in generic models that provide basic control over population contact patterns, pathogen properties and demographics, and templates for user-programmed modules that allow EpiModel to be extended for advanced research to the full range of pathogens, hosts, and disease dynamics.
We use a mix of lectures, tutorials, and labs with students working in small groups. On the final day, students work to develop an EpiModel prototype model (either individually or in groups based on shared research interests), with input from the instructors, including the lead EpiModel software developer, Dr. Samuel Jenness.
We assume students have some previous background in epidemic modeling and are comfortable using R. Examples include:
Research-level (post classroom) experience with epidemic modeling of any kind
A clearly defined modeling project, ideally with an associated network dataset
Previous experience with EpiModel (for example, have taken NME before, or worked through our online training materials on your own)
Dates and location: The course will be taught from Monday, August 8 to Friday, August 12, in-person on the University of Washington Seattle Campus.
Costs: Course fee is $1000. We offer a limited number of fee waivers for attendees from low income countries.
April 15: Application deadline.
May 1: Decisions will be announced.
June 15: Registration deadline. Late registration is possible through July 15 with a late fee of $250.
A waitlist will be established along with rolling admission through June 15 as space allows.
Application: Apply online at https://forms.gle/rgm4Nxfv5ZtweyQo9
Course website and more information: http://statnet.github.io/nme