The proposed model has several limitations. We assume exponential distribution for all parameters of model M related to the length of the different periods (e.g. latency, infectiousness, etc.), though it would be preferable to use multiple classes within each group to give more realistic gamma distributed lifetimes (see for instance [56] ). We assume density-dependent growth only in eggs, though other density-dependent regulating processes should be considered for other lifestages of the mosquitoes, e.g. larvae and pupae [25] . These modeling choices are due to the lack of data for parametrizing the model. The lack of information on the actual number of breeding sites -it could be assessed only by performing a field study -prevent us to give precise estimates on the density of mosquitoes over time in the study area. However, we would note that our estimates of R 0 , attack rates and probability of major outbreak are robust with respect to assumptions on the number of breeding sites. Moreover, the temporal dynamics of the vector is qualitatively well captured by model M (though not in terms of absolute abundance) and this allowed us to clarify whether or not the sharp decrease in the number of cases observed after the intervention was due to the intervention itself or to the spontaneous reduction of adults due to decrease of temperature. Definitely, a key lesson learnt from the analysis of the Chikungunya outbreak in Italy is the necessity to improve tools for obtaining reliable, though costly, estimates of the vector density (see for instance [57] ) -thus bypassing the necessity of developing ad-hoc models. The proposed model, describing the temporal dynamics of Aedes albopictus, provides a valid alternative in the absence of reliable field data.