The goal of this dissertation was to integrate realistic human social networks into a standard epidemiological disease transmission model. Toward that goal, I presented the potential benefits of network-based computational epidemiological simulations.
Starting from theoretical complex network topology, I gave a possible explanation for why infectious diseases are extinguished at small transmission rates, even in scale-free networks. The study results suggest the possibility of controlling the spread of epidemics in scale-free networks by manipulating resources and costs associated with an infection event. I then proposed a multilayer network-based computational epidemiological framework called MEDSim, whose development I assisted with, to integrate realistic social networks into traditional epidemiological models. To demonstrate and test model flexibility and generalizability, the 2009 A/H1N1 influenza epidemic was used to compute outbreak locations and to simulate intervention scenarios. Results indicate that the proposed MEDSim framework can help public health organizations decide when to implement intervention strategies by simultaneously analyzing multilayer interactions. For novices studying computational epidemiology and public health principles, I worked with three other authors to describe an instruction program for building network-based epidemic models. The
goal is to help individuals with less advanced computing skills to build epidemiological models, determine appropriate simulation parameters, and construct operational procedures.
To build on this positive beginning, in the future I will work with the researchers cited in this dissertation to expand the multilayer framework in order to make it suitable for other acute diseases, and to make it responsive to complex human contact structures.
I have five goals:
1. To model future disease spreading activity, I will work on modifying MEDSim parameters to include dynamic variables that change over time.
2. To account for vaccinations—specifically among school-age children, but also among other age groups—I will add one more state to the first MEDSim layer.
3. I will add transportation routes (e.g., highways, railways, air routes) to the fourth MEDSim layer.
4. I will work on adding an “international layer” to MEDSim in order to model cross-border epidemic dynamics.
5. I will work on extending MEDSim for use as a general purpose disease modeling framework—for example, modifying contact structures such as human-mosquito contact in order to model vector-borne diseases such as
dengue fever and malaria, and human-animal contact to model zoonotic diseases such as rabies and Japanese encephalitis.
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Bio
Yu-Shiuan Tsai received his B.S. degree in Mathematics (2002) and M.S. in
Mathematics (2005) from National Taiwan University. He recently was awarded a Ph.D.
in Computer Science by National Chiao Tung University. His current research interests
in Computer Science by National Chiao Tung University. His current research interests