  In the last two decades dengue cases increased significantly throughout the
world. In several regions dengue re-emerged, particularly in Latin America,
where dengue cases not only increased but also occurred more frequently. It is
therefore necessary to understand the mechanisms that drive epidemic outbreaks
in non-endemic regions, to help in the design of control strategies. We develop
a stochastic model that includes climate variables, social structure, and
mobility between a non-endemic city and an endemic area. We choose as a case
study the non-endemic city of San Ram{\'o}n de la Nueva Or{\'a}n, located in
Northwest Argentina. Human mobility is intense through the border with Bolivia,
where dengue transmission is sustained during the whole year. City population
was modelled as a meta-population taking into account households and population
data for each patch. Climate variability was considered by including rainfall,
relative humidity and temperature time series into the models. Those climatic
variables were input of a mosquito population ecological model, which in turn
is coupled to an epidemiological model. Different hypotheses regarding people's
mobility between an endemic and non-endemic area are tested, taking into
account the local climatic variation, typical of the non-endemic city.
Simulations are qualitatively consistent with weekly clinical data reported
from 2009 to 2016. Our model results allow to explain the observed pattern of
outbreaks, that alternates large dengue epidemics and several years with
smaller outbreaks. We found that the number of vectors per host and an
effective reproductive number are proxies for large epidemics, both related
with climate variability such as rainfall and temperature, opening the
possibility to test these meteorological variables for forecast purposes.
