Bovine echinococcosis in non-endemic area of Northern Italy: an example of integrated analysis of passive surveillance data

The province of Reggio Emilia (Emilia-Romagna Region, Northern Italy), located in the Po Valley, is one of the Italian areas with the highest farming activity, especially as far as swine and cattle are concerned. In 2006 the number of cattle was reckoned to be about 150,000 (dairy cattle about 90,000). Considering the type of farming, the scanty presence of traditional sheep farming, the low level of dog straying and of family slaughtering, the province is historically considered as an area at low risk of cystic echinococcosis (CE), both in animals and man. Aim of the study was to assess the occurrence of bovine CE in the province, integrating administrative data-bases, passive surveillance data and geographical information system. During the 5-year period 2001-2005, 229 cases of bovine CE (from 180 farms of the province), found at slaughtering, were reported to the Veterinary Service of the Local Health Unit. In order to estimate the prevalence of CE, all the data about cattle from the province slaughtered in the above-mentioned period (218,726 records from 2781 farms) were retrieved from the national data bank . Since all the reports of the disease concerned cows over 2 years of age and became from only two big slaughterhouses in Lombardy region, the dataset and all the subsequent analyses were restricted only to the cows slaughtered in these two slaughterhouses (48,390 cows from 2003 farms), considering them as a random sample (about 46%) of all the cows over 2 years of age sent to the slaughterehouse from farms in the province. Both empirical Bayes estimates and kernel smoothing techniques were used to investigate the pattern of spatial distribution of the cases. The CE prevalence in cows was 4.7 cases/1000 animals. The analysis revealed a heterogeneity in the prevalence estimates by municipality which was not attributable to the effect of chance alone. In particular, a cluster of cases was identified in the north-western area of the province, corresponding to 6 municipalities, where the highest prevalence reached 13.9 cases/1000 cows. It is worth noting that, in the same area and in the same period, uncontrolled and illegal grazing of infected ovine flocks caused an outbreak of Brucella melitensis infection in cattle, sheep and goats. These findings could suggest that uncontrolled flock grazing could have represented a risk factor for CE in cattle coming from the area considered, especially due to the possible presence of infected dogs or the abandoned carcasses and viscera of sheep. An important aspect of the study was the effort of gathering and coherently assembling data from different sources (passive surveillance, geographical information system and administrative data-bases, such as the National Data Bank). This was possible using the software ‘R’ (www.r-project.org). This study also attempts to exemplify how integration of data from different sources could provide an effective support in the epidemiological analysis of animal echinococcosis, even in small-scale areas.