  It is possible to model vector-borne infection using the classical
Ross-Macdonald model. This attempt, however fails in several respects. First,
using measured (or estimated) parameters, the model predicts a much greater
number of cases than what is usually observed. Second, the model predicts a
single huge outbreaks that is followed after decades of much smaller outbreaks.
This is not what is observed. Usually towns or cities report a number of cases
that recur for many years, even when environmental changes cannot explain the
disappearance of the infection in-between the peaks. In this paper we continue
to examine the pitfalls in modeling this class of infections, and explain that,
in fact, if properly used, the Ross-Macdonald model works, can be used to
understand the patterns of epidemics and even, to some extents, to make some
predictions. We model several outbreaks of dengue fever and show that the
variable pattern of year recurrence (or absence of it) can be understood and
explained by a simple Ross-Macdonald model modified to take into account human
movement across a range of neighborhoods inside a city. In addition, we analyze
the effect of seasonal variations in the parameters determining the number,
longevity and biting behavior of mosquitoes. Based on the size of the first
outbreak, we show that it is possible to estimate the proportion of the
remaining susceptibles and predict the likelihood and magnitude of eventual
subsequent outbreaks. The approach is exemplified by actual dengue outbreaks
with different recurrence patterns from some Brazilian regions.
