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.