Prevalence estimation of Italian ovine cystic echinococcosis in slaughterhouses: A retrospective Bayesian data analysis, 2010-2015.

Cystic echinococcosis (CE) is a complex zoonosis with domestic and sylvatic life-cycles, involving different intermediate and definitive host species. Many previous studies have highlighted the lack of a surveillance system for CE, its persistence in Italy, and endemicity in several Italian regions. Because of the absence of a uniform surveillance program for both humans and animals, disease occurrence is widely underestimated. This study aimed to estimate the prevalence of ovine CE in Italy. Survey data on the prevalence of Echinococcus granulosus complex infections in Italian sheep farms from 2010 to 2015 were obtained in collaboration with Regional Veterinary Epidemiology Observatories (OEVRs). Bayesian analysis was performed to estimate the true CE farm prevalence. The prior true CE prevalence was estimated using data from Sardinia. Second, Bayesian modelling of the observed prevalence in different regions and the true prevalence estimation from the first step were used to ultimately estimate the prevalence of ovine CE in Italy. We obtained survey data from 10 OEVRs, covering 14 Italian regions. We observed that the risk of CE infection decreased over the years, and it was strictly correlated with the density of susceptible species. Using Sardinia as prior distribution, where the disease farm prevalence was approximately 19% (95% CI, 18.82-20.02), we estimated that the highest endemic CE farm prevalence was in Basilicata with a value of 12% (95% BCI: 7.49-18.9%) and in Piemonte 7.64%(95% BCI: 4.12-13.04%). Our results provide spatially relevant data crucial for guiding CE control in Italy. Precise information on disease occurrence location would aid in the identification of priority areas for disease control implementation by the authorities. The current underestimation of CE occurrence should urge the Italian and European governments to become aware of the public health importance of CE and implement targeted interventions for high-risk areas