Aedes albopictus (Diptera: Culicidae) Monitoring in the Lazio Region (Central Italy)

Abstract

The Asian tiger mosquito Aedes albopictus (Skuse 1894) is assuming an ever-increasing importance as invasive species in Europe and consequently as human health and nuisance concern. In Central Italy, the species has been recently involved in a chikungunya outbreak. A 3 yr Ae. albopictus monitoring was carried out in 21 municipalities of the Lazio region (Central Italy), belonging to three provinces. Samplings were performed on a weekly basis using ovitraps, in order to investigate climatic and spatial variables driving egg abundance and Ae. albopictus period of activity. A temperature of 10.4°C was indicated as lower threshold for the onset of egg-laying activity, together with a photoperiod of 13:11 (L:D) h. The whole oviposition activity lasted 8 mo (May-December), with 95% of eggs laid between early June and mid-November and a peak at the end of August. Egg abundance was positively influenced by accumulated temperature (AT) of the 4 wk preceding sampling and negatively by precipitation during the week before. Egg-laying activity dropped with decreasing AT, increasing rainfall, and with a photoperiod below 10:14 (L:D) h. Our results pinpointed the importance of fine-scaled spatial features on egg abundance. Some of these fine-scaled characteristics have been highlighted, such as the presence of vegetation and human footprint index. Our model estimated an almost doubled maximum number of laid eggs for the maximum value of human footprint. Compelling evidence of the relevance of fine-scaled characteristics was reported, describing cases where human-made breeding sites driven the abundance of Ae. albopictus.

Keywords: mosquito; ovitrap; phenology; rainfall; temperature.

Fig. 1.

(a) map of the Lazio region with the 21 municipalities where the 83 ovitraps were placed; (b) map of the human footprint index for the Lazio region.

Fig. 2.

Relationship between egg count and weather variables during the onset of egg-laying activity: (a) mean minimum temperature for the second week before sampling (W₂), with highlighted threshold temperature (10.35°C) and equation (P < 0.05); (b) hours of light with nonlinear models equations, which highlighted the same threshold value: 13.12 (L:D) h of light. The P-values of the nonlinear models coefficients were respectively: a (P < 0.01), b (P = 0.52), c (P < 0.01), for the Power equation; a (P < 0.01), b (P < 0.01), c (P = 0.29) for the von Bertalanffy.

Fig. 3.

Relationships between egg count and weather variables during the end of egg-laying activity: (a) cumulative precipitation (P < 0.01), AT (W₁: P < 0.01, W_{1 + 2}: P < 0.01), means of maximum (P < 0.01) and minimum (P < 0.01) weekly temperatures, with highlighted threshold values (see text for details); (b) hours of light with selected models equations. Thresholds values were 9.95 and 9.97 h of light, estimated respectively by Power and linear regression (P < 0.01) (Table 1, b). The P-values of Power coefficients were: a (P < 0.01), b (P < 0.01), c (P < 0.01).

Fig. 4.

Annual egg count trend over the 3 yr sampling. Solid black line represents the estimated Ae. albopictus phenology according to the Gaussian model, with the peak indicated by the vertical solid black line. Dashed thin vertical lines indicate the extent of the time interval within which 95% of eggs have been laid. Upper line (a) shows the trend for the AT over the 4 wk before sampling and lower line (b) indicates the cumulated precipitation for the week before sampling, during the 95% time interval. Shaded areas indicate the 95% confidence intervals of the lines.

Fig. 5.

Relationship between maximum egg count and human footprint according to the GLM result, with indicated (by horizontal line) the expected count for the higher threshold value of human footprint and shaded areas indicating the 95% confidence interval.