Dynamics in Time: The dynamic nature of infectious disease transmission means that the state of a system now – e.g. the population size, number infected, number and age distribution of those immune – will influence the future behavior of the system – e.g. future cases. The practical relevance of these dynamic effects, for immunizing infections, is clearly illustrated by the so-called “honey-moon effect” following the introduction of vaccination Mclean 1988, whereby the lowered prevalence of infection due to vaccination also depresses the rate of natural immunity, leading to a prolonged period of low disease incidence followed by a gradual increase to a new endemic level of transmission if vaccine coverage is not sufficient to achieve the herd immunity threshold.  Thus, the observation of infection rates increasing following an initial decline due to a vaccine intervention is not necessarily consistent with poor vaccine program performance. Bhattacharryya et al BHATTACHARYYA 2016 recently revisited this phenomenon in the context of age-dependent transmission and showed that even if vaccination coverage is sufficient to maintain immunity below the critical herd immunity threshold, that demographic processes could result in a transient increase in RE above 1, as the susceptible cohorts protected by herd immunity following the introduction of vaccination age through the high contact life stages (e.g. school ages) during which they contribute to, and are exposed to, high rates of contact. While these analyses rarely rise to the level of prediction, they provide a qualitative assessment of the future consequences of current interventions.