ABSTRACT
This chapter introduces a number of key concepts in infectious disease dynamics including patterns of incidence in space and time, the importance of age-structure and seasonality, the basic reproductive ratio, and compartmental models for the transmission cycle of pathogens. The interplay between nonlinearity, stochasticity, and seasonality can result in a range of dynamical patterns, ranging from stable levels of infection, periodically recurrent epidemics, and sometimes quasi-periodic or even chaotic changes in levels of infection. The chapter further discusses how spatial structure can lead to emergent spatiotemporal patterns. Hands-on examples of analysis of data and models, with datasets and R-code are provided, including wavelet analysis, the chain-binomial, catalytic model for age-prevalence data, and susceptible-infected-recovered flows.
