The aim of this study was to explore lameness and the associations between lameness and health/production measures of animal welfare in commercial broiler production, using the Welfare Quality® protocol for broilers. A total of 50 flocks were included in the sample and farm visits were conducted for lameness scoring at a mean age of 28.9 days. The percentage of animals (n=7500) in the six different gait score (GS) categories were GS0: 2.53%, GS1: 44.19%, GS2: 33.84%, GS3: 16.32%, GS4: 2.36% and GS5: 0.53%. Production and other welfare data were collected for each flock after slaughter. Higher gait scores were associated with increased hock burn score (P<0.02), increased footpad dermatitis score (P<0.01), reduced bird cleanliness score (P<0.01) and peat litter (P<0.01). Although not statistically significant, there was a tendency for increased flock gait score being associated with wet litter (P=0.07). In addition, condemnations at postmortem inspection were associated with increasing gait scores (P<0.05), indicating that at least a portion of the lameness cases display pathological changes on the carcasses. In conclusion, 19%of the birds showed moderate-to-severe lameness, which was associated with several production or health and welfare observations including feather cleanliness and condemnations as unfit for human consumption at slaughter. Although stocking density and growth rate are already known key factors for lameness, associations of lameness with hock burns, footpad dermatitis and cleanliness of the birds suggest that a suboptimal physical environment (e.g. litter- and air quality) may be detrimental to leg health. Further studies are needed to explore these associations in more detail.

The objective of this study was to assess the performance of several algorithms for outbreak detection based on weekly proportions of whole carcass condemnations. Data from one French slaughterhouse over the 2005–2009 period were used (177 098 slaughtered cattle, 0.97% of whole carcass condemnations). The method involved three steps: (i) preparation of an outbreak-free historical baseline over 5 years, (ii) simulation of over 100 years of baseline time series with injection of artificial outbreak signals with several shapes, durations and magnitudes, and (iii) assessment of the performance (sensitivity, specificity, outbreak detection precocity) of several algorithms to detect these artificial outbreak signals. The algorithms tested included the Shewart p chart, confidence interval of the negative binomial model, the exponentially weighted moving average (EWMA); and cumulative sum (CUSUM). The highest sensitivity was obtained using a negative binomial algorithm and the highest specificity with CUSUM or EWMA. EWMA sensitivity was too low to select this algorithm for efficient outbreak detection. CUSUM's performance was complementary to the negative binomial algorithm. The use of both algorithms on real data for a prospective investigation of the whole carcass condemnation rate as a syndromic surveillance indicator could be relevant. Shewart could also be a good option considering its high sensitivity and simplicity of implementation.

An innovative and well-adapted statistical method, called multiblock redundancy analysis, is proposed for a complex health-event analysis to account for the thematic block organization of variables. The outcome block contained the condemnation rates of 404 broiler chicken flocks, distinguishing infectious and traumatic condemnation categories. Explanatory variables were organized in blocks related to the different production stages (farm structure and routine husbandry practices; on-farm flock history and characteristics; catching, transport and lairage conditions; slaughterhouse and inspection features). The aim was to determine risk factors for both condemnation categories, and the relative impact of the different production stages on the whole condemnation rate. Results showed that significant factors were either specific to one condemnation category or related to both categories, and each of the explanatory blocks was involved in the explanation of infectious and traumatic condemnation rates. On-farm flock information explained 40% of the overall condemnation process whereas the other explanatory blocks had similar relative impacts.

The feasibility of using risk markers to screen broiler chicken flocks and anticipate their risk of condemnation at meat inspection was examined in 404 randomly selected flocks in 15 French slaughterhouses in 2005. Condemnation rate and information about rearing conditions, health history, catching and loading, transport and slaughtering were collected. The Poisson regression model of the condemnation rate consisted of six simple and biologically relevant predictors: production type, frequency of farmer's visits during the starting period, health disorders during rearing, on-farm mortality, mortality during transport, and slaughter-line speed. Although accurate prediction of the condemnation rate for a given flock was not feasible, flocks with low or high risk of condemnation could be distinguished. These findings could be useful at various stages of chicken production, to monitor and improve farm husbandry practices, minimize the impact of transport conditions, and optimize meat inspection procedures.