Iterative modeling can be formulated in several steps that include: empirical observations and data collection; formalization of properties; formalization of uncertainty/variability in model and data; model analysis. In this talk we will discuss the previous steps in the context of contact processes, with illustrations that pertain to social interactions and transmission of infectious diseases. Modeling and simulation are illustrated with results of drinking dynamics (epidemics of problem drinkers). We illustrate model validation with an example that revisits how Feynman diagrams were adopted in three communities of theoretical physicists. Statistical error structure and post-analysis are discussed in the context of parameter estimation from outbreak data. The role of identifiability analysis is illustrated with an example of seasonal epidemics.
Modeling, Simulation, and Validation of Contact Processes
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