Potential Risk of Dengue and Chikungunya Outbreaks in Northern Italy Based on a Population Model of Aedes albopictus (Diptera: Culicidae)

Abstract

The rapid invasion and spread of Aedes albopictus (Skuse, 1894) within new continents and climatic ranges has created favorable conditions for the emergence of tropical arboviral diseases in the invaded areas. We used mosquito abundance data from 2014 collected across ten sites in northern Italy to calibrate a population model for Aedes albopictus and estimate the potential of imported human cases of chikungunya or dengue to generate the condition for their autochthonous transmission in the absence of control interventions. The model captured intra-year seasonality and heterogeneity across sites in mosquito abundance, based on local temperature patterns and the estimated site-specific mosquito habitat suitability. A robust negative correlation was found between the latter and local late spring precipitations, indicating a possible washout effect on larval breeding sites. The model predicts a significant risk of chikungunya outbreaks in most sites if a case is imported between the beginning of summer and up to mid-November, with an average outbreak probability between 4.9% and 25%, depending on the site. A lower risk is predicted for dengue, with an average probability between 4.2% and 10.8% for cases imported between mid-July and mid-September. This study shows the importance of an integrated entomological and medical surveillance for the evaluation of arboviral disease risk, which is a precondition for designing cost-effective vector control programs.

Fig 1. Geographic distribution of trap locations (red circles) and municipalities in the study area.

Fig 2. Model estimates for densities of adult females by study site; grey bars represent 95% CI calculated over 200 samples of the posterior distribution of parameters and 50 stochastic iterations.

Fig 3. Boxplots of the errors between observed and simulated captures at each capture session in the ten study sites.

The errors are normalized by the maximum number of captured females throughout the season.

Fig 4. Scatterplots of the predicted peak of R₀ for chikungunya at different sites and corresponding local variables; dashed lines represent regression lines.

Fig 5. Scatterplots of the predicted peak of R₀ for dengue at different sites and corresponding local variables; dashed lines represent regression lines.

Fig 6. Model predictions for the probability of occurrence (average and 95% CI) of an outbreak of sustained chikungunya transmission caused by a single importation of an infected case occurred at different times of the year in the ten study sites.

Fig 7. Model predictions for the probability of occurrence (average and 95% CI) of an outbreak of sustained dengue transmission caused by a single importation of an infected case occurred at different times of the year in the ten study sites.

Fig 8. Peak values of the predicted outbreak risk over the study region under the maximum value of the larval carrying capacity estimated by our model in the 10 capture sites (a = 95).

A) chikungunya; B) dengue.