A key question in nonlinear dynamics is how perturbations to a system impact long-term trajectories. Due to the cyclical nature of its host-pathogen life cycle, as well as an abundance of rich data, measles has been analyzed extensively as a paradigm for epidemic dynamics. In particular, measles in London has been the prototypical testbed for such analysis. However, London has traditionally only been analyzed post-Second World War up to the start of vaccination in 1968. This relatively narrow time frame has limited our ability to understand the impact of multiple, large-scale changes to the susceptible population on the overall disease dynamics. Here, we extend the previous analyses to include four major population changes: the First and Second World Wars, the 1918 Influenza Pandemic, and the start of vaccination (1897-1991).
Results/Conclusions:
By extending the London time series through all of these events, we show that a simple stochastic Susceptible-Exposed-Infected-Recovered model, with minimal historical specifications, can capture the nearly 100 years of complexity, including the dynamical change caused by each perturbation. Our analysis further highlights the utility of simple, well-mixed epidemiological models for capturing complex dynamics and transitions.