Abstract

Bovine abortion is the main clinical sign of bovine brucellosis, a disease of which France has been declared officially free since 2005. To ensure the early detection of any brucellosis outbreak, event-driven surveillance relies on the mandatory notification of bovine abortions and the brucellosis testing of aborting cows. However, the under-reporting of abortions appears frequent. Our objectives were to assess the aptitude of the bovine abortion surveillance system to detect each and every bovine abortion and to identify factors influencing the system's effectiveness. We evaluated five attributes defined by the U.S. Centers for Disease Control with a method suited to each attribute: (1) data quality was studied quantitatively and qualitatively, as this factor considerably influences data analysis and results; (2) sensitivity and representativeness were estimated using a unilist capture–recapture approach to quantify the surveillance system's effectiveness; (3) acceptability and simplicity were studied through qualitative interviews of actors in the field, given that the surveillance system relies heavily on abortion notifications by farmers and veterinarians. Our analysis showed that (1) data quality was generally satisfactory even though some errors might be due to actors’ lack of awareness of the need to collect accurate data; (2) from 2006 to 2011, the mean annual sensitivity – i.e. the proportion of farmers who reported at least one abortion out of all those who detected such events – was around 34%, but was significantly higher in dairy than beef cattle herds (highlighting a lack of representativeness); (3) overall, the system's low sensitivity was related to its low acceptability and lack of simplicity. This study showed that, in contrast to policy-makers, most farmers and veterinarians perceived the risk of a brucellosis outbreak as negligible. They did not consider sporadic abortions as a suspected case of brucellosis and usually reported abortions only to identify their cause rather than to reject brucellosis. The system proved too complex, especially for beef cattle farmers, as they may fail to detect aborting cows at pasture or have difficulties catching them for sampling. By investigating critical attributes, our evaluation highlighted the surveillance system's strengths and needed improvements. We believe our comprehensive approach can be used to assess other event-driven surveillance systems. In addition, some of our recommendations on increasing the effectiveness of event-driven brucellosis surveillance may be useful in improving the notification rate for suspected cases of other exotic diseases.

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