Epidemiological models are key tools for designing and evaluating detection and control strategies against animal infectious diseases. In France, after decades of decrease of bovine tuberculosis (bTB) incidence, the disease keeps circulating. Increasing prevalence levels are observed in several areas, where the detection and control strategy could be adapted. The objective of this work was to design and calibrate a model of the within-herd transmission of bTB. The proposed model is a stochastic model operating in discrete-time. Three health states were distinguished: susceptible, latent and infected. Dairy and beef herd dynamics and bTB detection and control programs were explicitly represented. Approximate Bayesian computation was used to estimate three model parameters from field data: the transmission parameter when animals are inside (βinside) and outside (βoutside) buildings, and the duration of the latent phase. An independent dataset was used for model validation. The estimated median was 0.43 [0.16–0.84] month−1 for βinside and 0.08 [0.01–0.32] month−1 for βoutside. The median duration of the latent period was estimated 3.5 [2]–[8] months. The sensitivity analysis showed only minor influences of fixed parameter values on these posterior estimates. Validation based on an independent dataset showed that in more than 80% of herds, the observed proportion of animals with detected lesions was between the 2.5% and 97.5% percentiles of the simulated distribution. In the absence of control program and once bTB has become enzootic within a herd, the median effective reproductive ratio was estimated to be 2.2 in beef herds and 1.7 in dairy herds. These low estimates are consistent with field observations of a low prevalence level in French bTB-infected herds.

The performance of dairy herds is affected mainly by factors related to cows' characteristics and herd management practices. However, these factors are interrelated, and as such, the estimation of their individual effect on the performance of dairy herds remains difficult. The aim of this study was to estimate the weight of these factors as well the interactions between them on the reproductive and economic performance of dairy farms. A stochastic dynamic model was used to simulate most physiological and management processes occurring on a dairy farm. A herd of 60 Holstein cows, with a milk yield of 8,000 L/cow-year, representative of French Holstein dairy herds, was simulated. A total of 216 scenarios were run by combining 2 levels of postpartum cyclicity resumption (average: 45 d, high: 75 d), 3 levels of 21-d conception rate of the herd (i.e., proportion of cows pregnant 21 d after insemination; low: 25%, average: 45%, high: 70%), 3 levels of probability of pregnancy loss until 120 d (low: 3%, average: 15%, high: 43%), 3 levels of sensitivity of estrus detection by the farmer (low: 20%, average: 50%, high: 90%), 2 alternative managerial goals (constant number of cows or constant volume of milk sold), and 2 types of management for the sale and purchase of animals (closed or open herd). The effect of each factor was estimated by sensitivity analysis. The parameter that had the greatest effect on reproductive performance was the sensitivity of estrus detection: a 10-percentage-point increase between the low and average levels and between the average and high levels reduced the calving interval by 16 and 5.7 d, respectively. However, the factor that had the greatest effect on economic performance was the 21-d conception rate: a 10-percentage-point increase between the low and average levels and between the average and high levels increased the gross margin by €62.2 and €22.3/cow-year, respectively. The pregnancy loss until 120 d had an effect on economic performance: an increase of 1 percentage point of this parameter decreased the gross margin by €2/cow-year. The other factors studied, and their interactions, did not have a major effect (low value of sensitivity indices). Closed herds or farms with a constant number of cows had economic losses of €58/cow-year compared with open herds or to farms with constant volume of milk sold. Altogether, our data suggest that, in a typical French dairy farm, farmers' efforts on estrus detection will be more profitable when associated with improvement of the conception rate of the cows.

We analysed the spatiotemporal variations of bovine tuberculosis (bTB) incidence between 1965 and 2000 in France at the department level (95 areas). Using a Bayesian space-time model, we studied the association between the evolution of bTB incidence and changes of cattle population structure and of herd management practices. Several spatiotemporal hierarchical Bayesian models were compared, and the deviance information criterion was used to select the best of them. Southern France remained a high-risk area over the analysed period, whereas central and western regions were low-risk areas. Besides the frequency of tuberculin skin testing (fixed according to bTB incidence in the preceding years), four factors were associated with an increased risk of bTB: the average herd density and size, the percentage of dairy cows in the cattle population, and the percentage of permanent grassland in cultivated surfaces area. These four factors are linked to the progressive professionalization and specialization of cattle farming, with the disappearance of family farms and of the intensification of breeding systems (especially in dairy farms after the application of the milk quota system in the 1980s). Both trends probably played a significant role in reducing the risk of bTB in France between 1965 and 2000, besides mandatory detection and control procedures.