T. Reluga, E, Shim. Population viscosity suppresses disease emergence by preserving local herd immunity. Proceedings. Biological Sciences. The Royal Society. 2014; 281(1796):20141901.
T. Reluga, A. Shaw .Resource distribution drives the adoption of migratory, partially migratory, or residential strategies. Theoretical Ecology, March, 2015. doi:10.1007/s12080-015-0263-y
T. Reluga. Equilibria of an epidemic game with piecewise linear social distancing cost. Bulletin of mathematical biology. 2013; 75(10):1961-84.
T. Reluga, J. Li. Games of age-dependent prevention of chronic infections by social distancing. Journal of mathematical biology. 2013; 66(7):1527-53.
T. Reluga. Solutions of an epidemic game with linear social distancing cost. Bulletin of Mathematical Biology, August, 2013. doi:10.1007/s11538-013-9879-5
T. Reluga and A. Galvani. A general approach to population games with application to vaccination. Mathematical Biosciences, 2011, volume 230(2), 67-78. doi:10.1016/j.mbs.2011.01.003
D. M. Cornforth, T. C. Reluga, E. Shim, C. T. Bauch, A. P. Galvani, and L. A. Meyers. Erratic flu vaccination emerges from short-sighted behaviour in contact networks PLOS Computational Biology, 2010, volume 7(1): e1001062. doi:10.1371/journal.pcbi.1001062
T. Reluga, H. Dahari, and A. S. Perelson. Analysis of hepatitis C virus infection models with hepatocyte homeostasis. SIAM Journal on Applied Mathematics, 69 (4): 999-1023, 2009. doi:10.1137/080714579
T. Reluga. Branching processes and non-commuting random variables in population biology . Canadian Applied Math Quarterly Quarterly, 2009, volume 17 (2), 387.
T. Reluga, J.Medlock, and A. Galvani. The discounted reproductive number for epidemiology. Mathematical Biosciences and Engineering, 6 (2): 377-393, 2009. doi:10.3934/mbe.2009.6.377,
T. Reluga, J.Medlock, and A. Galvani. A model of spatial epidemic spread when individuals move within overlapping home ranges. Bulletin of Mathematical Biology, 68 (2): 401-416, February 2006. doi:10.1007/s11538-005-9027-y,
T. Reluga On antibiotic cycling and optimal heterogeneity. Mathematical Medicine and Biology, June 2005. doi:10.1093/imammb/dqi002
My research interests concern the description, understand, and prediction of the dynamics of biological systems. Over the coming century, human civilization will be profoundly effected by the interactions among ecosystems, human populations, and the environment. We must understand these interactions if we hope to manage and administer a stable and sustainable society. With the help of a robust theory of biological systems, we can successfully confront the challenges of medicine, public health maintenance, sustainable resource usage, and environmental management. To this end, I use applied mathematics to create qualitative and quantitative descriptions of these complex biological processes. In general, my work is driven by personnel curiosity and the intellectual appeal of a problem. Population biology is my core research interest, but my work encompasses topics in
- applied mathematics
- evolutionary biology
- computer science
Much of my most recent research has focussed on incorporating social and behavioral factors into our theories of infectious disease dynamics and management.