Katia Koelle, Assistant Professor of Biology

Katia Koelle
Office Location:  130 Science Drive
Office Phone:  (919) 660-9457
Email Address: send me a message
Web Page:  http://www.biology.duke.edu/koellelab/index.html

Teaching (Fall 2013):

Education:

PhDUniversity of Michigan- Ann Arbor2005
BSStanford University1997
Specialties:

Ecology and Population Biology
Evolution
Research Interests: Theoretical biology; ecology and evolution of infectious diseases

My research focuses on the ecology and evolution of infectious diseases. I use a combination of mathematical and statistical approaches to understand the processes that give rise to the dynamic and evolutionary patterns of pathogens. More specifically, my interests fall into three main areas: 1) The regulation of infectious disease dynamics, 2) The determinants of genetic and antigenic diversity patterns in pathogen populations, and 3) Pathogen adaptation to environmental change. The systems I have worked most closely with include Vibrio cholerae (the bacterium that causes cholera) and influenza. Most of my current research focuses on the development of quantitative models to further our understanding of rapidly-mutating RNA viruses.

Current Ph.D. Students  

  • Rotem Ben-Shachar  
  • Ashley Sobel  
  • Shishi Luo  
  • Stacy Scholle  
  • Christopher Castorena  
  • David A. Rasmussen  
  • Sean Yuan  
Postdocs Mentored

  • Jayna Raghwani (February, 2012 - present)  
  • Oliver Ratmann (October, 2009 - July, 2012)  
  • Virginia Pasour (August, 2008 - October, 2009)  
Recent Publications

  1. Volz, E.M., Koelle, K., Bedford, T., Viral phylodynamics, PLoS Computational Biology (Accepted, 2012)
  2. Scholle, S.O., Ypma, R., Lloyd, A.L., Koelle, K., The effect of epidemiological dynamics on viral substitution rates, in review in The American Naturalist (Submitted, 2012)
  3. Yuan, H., Koelle, K., The evolutionary dynamics of receptor binding avidity in influenza A: a mathematical model for a new antigenic drift hypothesis, Philosophical Transactions of the Royal Society B. (Accepted, 2012)
  4. Ratmann, O., Donker, G., Meijer, A., Fraser, C., Koelle, K., Phylodynamic inference and model assessment with Approximate Bayesian Computation: influenza as a case study, PLoS Computational Biology (Accepted, 2012)
  5. WHO-VMI Dengue Vaccine Modeling Group (including K. Koelle), Assessing the potential of a candidate dengue vaccine with mathematical modeling, PLoS Neglected Tropical Diseases, vol. 6 no. 3 (2012), pp. e1450 [doi]