The use of mathematical modeling as a tool for disease control has
historically relied on threshold results, in which a certain factor
related to disease transmission must be changed beyond a given level
in order to eradicate the disease. The most well-known threshold criterion
is the basic reproductive number of a disease, typically denoted
, which represents the average number of secondary infections
caused by one infective in a pool of susceptibles. In simple epidemic models
when
the disease-free equilibrium is often globally stable
which suggests that it is sufficient to reduce
below one and
the disease will disappear from the population. I consider a simple ODE model
of hepatitis C as an illustration. However, several recent studies have shown
that the
criterion is not always sufficient to control the
spread of a disease. Dynamically it is possible that the transcritical
bifurcation that occurs at
may change directions, creating what
has become known in the literature as a ``backward'' bifurcation, in which the
endemic equilibrium arises from the disease-free equilibrium for
rather than for
as in the simplest cases. From a control point
of view when backward bifurcation occurs it is not sufficient to lower
below one but below another threshold value which is the leftmost
point on the bifurcation curve for which an endemic equilibrium exists. I
consider a structured model for a disease with a progressing and a quiescent
exposed class and variable susceptibility to super-infection. The model
exhibits backward bifurcations under certain conditions, which allow for both
stable and unstable endemic states when the basic reproduction number is smaller
than one.