The containment of potential outbreaks triggered by imported Chikungunya cases in Italy: a cost utility epidemiological assessment of vector control measures

Abstract

The arrival of infected travelers from endemic regions can trigger sustained autochthonous transmission of mosquito-borne pathogens in Europe. In 2007 a Chikungunya outbreak was observed in central Italy, mostly affecting two villages characterised by a high density of Aedes albopictus. The outbreak was mitigated through intervention strategies reducing the mosquito abundance. Ten years later, in 2017, sustained Chikungunya transmission was documented in both central and southern Italy. The proposed analysis identifies suitable reactive measures for the containment and mitigation of future epidemics by combining epidemiological modeling with a health economic approach, considering different arrival times of imported infections and possible delays in the notification of cases. Obtained estimates suggest that, if the first notification will occur in the middle of the mosquito breeding season, the combination of larvicides, adulticides and breeding sites removal represents the optimal strategy. In particular, we found that interventions implemented in 2007 were cost-effective, with about 3200 prevented cases, 1450 DALYs averted and €13.5 M saved. Moreover, larvicides are proven to be more cost beneficial in early summer and warmer seasons, while adulticides should be preferred in autumn and colder seasons. Our results provide useful indications supporting urgent decision-making of public health authorities in response to emerging mosquito-borne epidemics.

Figure 1

Posterior distribution of the Net Health Benefit (NHB) for each intervention strategy considered versus the hypothetical scenario where no intervention is implemented, under the assumption that the willingness to pay for the healthcare system is €30000. Intervention strategies associated with positive values of the NHB should be considered as cost-effective. BS refers to breeding sites removal, LA to larvicides and AD to adulticides, while No Int refers to the scenario without any intervention.

Figure 2

(a) Sampling distribution of dates of arrival of CHIKV cases from endemic area. (b) Sampling distribution of time elapsed between the arrival and the notification of CHIKV cases to public health authorities. (c) Posterior distribution of time elapsed between the arrival of the first case, either symptomatic or asymptomatic, and the first notification to public health authorities. (d) Posterior distribution of time elapsed between the observation of the last symptomatic case and the last infected vector.

Figure 3

Top panels show probabilities of being the most cost effective of all possible strategies for different times at first notifications when considering temperature records observed during the Italian outbreak in 2007 (a), with temperatures decreased (b) or increased (c) by 1.5 °C. Bottom panels show probabilities of being the most cost effective among the considered single strategies for different times at first notifications with the observed temperature records (d), with temperatures decreased (e) or increased (f) by 1.5 °C

Figure 4

Decision tree used to classify simulated CHIKV cases. Transition probabilities to different states of the tree are reported in the circles.