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Mastitis is a bacterial disease common in dairy farms. Although knowledge about mastitis and its optimal technical management and treatment is now available, some dairy farmers still use antibiotics in inappropriate ways. Antibiotic use by farmers can be influenced by personal restraints and motivations, but it can be assumed that external drivers are also influential. The main purpose of this article is thus to analyse the choices of antibiotic and alternative medicine use for mastitis treatment and investigate the possible influence of two unexplored external drivers in dairy farms: (i) the health advice offered to farmers by farm advisors and veterinarians, (ii) the dairy farming system, as defined by combining the market valuation chosen for the milk, the level of intensification, and the perceived pressure related to investments. Research was based on 51 individual semi-structured interviews with farmers and their corresponding veterinarians and farm advisors. Based on verbatim, the use of antibiotics and alternative medicine by farmers for mastitis treatment, the vet-farmers interactions, and the dairy farming systems are described. The advisory relationships between farmers and farm advisors and between farmers and veterinarians influenced the implementation of selective dry cow therapy, but had very little effect on the use of alternative medicines by farmers, who were more willing to experiment alternative medicines than their advisors. The dairy farming system had very little influence on antibiotic use: some misuse of antibiotics was found whatever the farming system. Systematic dry cow therapy was also a widespread habit in all dairy farming systems except organic. The use of alternative medicine was common in all farming systems.

Models have been developed to represent the spread of bovine viral diarrhoea virus (BVDV) in cattle herds. Whereas the herd dynamics is well known, biological data are missing to estimate the parameters of the infection process. Our objective was to identify the parameters of the infection process that highly influence the spread of BVDV in a dairy herd. A stochastic compartmental model in discrete time represented BVDV infection in a typical Holstein dairy herd structured into five groups (calves, young versus older heifers, lactating versus dry cows). Model sensitivity was analysed for variations in the probability of birth of persistently infected ( P ) calves ( b P ), mortality of P animals ( m P ), within- and between-group transmission rates for P and transiently infected ( T ) animals (respectively, β w P , β b P , β w T , β b T ). Three to five values were tested per parameter. All possible combinations of parameter values were explored, representing 3840 scenarios with 200 runs for each. Outputs were: virus persistence 1 year after introduction, time needed to reach a probability of 80% for the herd to be virus-free, epidemic size, mean numbers of immune dams carrying a P foetus, of P and of T animals in infected herds. When considered together, m P and β b P accounted for 40–80% of variance of all outputs; b P and β w T accounted each for less than 20% of variance; β b T and β w P accounted for almost no percent of variance of the outputs. Parameters β w T and b P needed to be more precisely estimated. The influence of m P indicated the effectiveness of culling P calves, the influence of β b P indicated the role of the herd structure in BVDV spread, whereas the influence of b P indicated the possible role of vaccination programs in controlling within-herd BVDV spread.

The efficiency of a test-and-cull programme to control BVDV spread within a dairy herd was assessed using a stochastic model. A single virus introduction by a non-PI dam carrying a PI foetus was simulated in a typical western-France dairy herd. Herd monitoring in test-and-cull programme enabled us to detect virus spread within 1 year after introduction in 87% of the replications. The test-and-cull programme reduced the length of the virus persistence. The extent of infection was moderately reduced.

Production losses and treatment expenditures consecutive to bovine viral diarrhoea virus (BVDV) infection in a dairy herd were calculated by partial budgeting based on published estimates of production effects. Overall costs (losses plus expenditures) resulted in a decreased gross margin of 10.7 euros and 19.0 per 1000 l of milk for an average and severe infection, respectively. With a milk quota system allowing no lease of quota, assuming adjustment of the herd size by the farmer to produce the quota, decrease in gross margin was limited to 7.9 euros and 13.9 per 1000 l of milk.

A collective zoo-sanitary control scheme for BVDV has been implemented in Brittany in successive steps since 1998. Prior evaluation of prevalence and dynamics of infection through bulk-milk ELISA showed that 40% of the dairy herds were likely to be free of BVDV but that, in the long term, no improvement was to be expected without control of new infections. The next step was a test-and-cull programme for PI animals in ELISA positive herds. Ten percentage of the herds were found to have at least one PI animal. The incidence decreased during this step. To lower costs of testing traded animals, a database was developed to collect all the available information to trace animals already known to be non-PI.

The relationships between the herd-somatic-cell count (SCC) pattern on a test day and the incidence of clinical mastitis in the subsequent period were studied by collecting health data and monthly records from 2 years (1995-1997) from 121 farms located in the west of France. A total of 980 herd-periods (from one test day to the following one) were analyzed. The outcome variable was the incidence density of clinical mastitis (ICM) within the herd-period. The herd-SCC pattern on a test day was described by cross-combining the proportions of cows with low SCC (50,000 cells/ml) or with high SCC (250,000 cells/ml). The relationship between herd-SCC pattern and subsequent ICM was assessed using a generalized linear mixed model. A sensitivity analysis evaluated the effect of different proportions of cows with low SCC on significance and magnitude of the relationship. Risk of clinical mastitis was expressed as a risk ratio (RR) in comparison to a moderate herd-SCC level (with low proportions of cows with low or high SCC). Median ICM was 0.38 cases per 365 cow-days at risk (first and third quartiles: 0 and 0.88). In the situations where few cows (15%) had SCC250,000 cells/ml, ICM was higher (RR1.31) when the proportion of cows with low SCC exceeded 50% than in the reference situation. Risk ratios increased as the proportion of cows with low SCC increased from 40 to 60%. In the situations where the proportion of cows with SCC250,000 cells/ml exceeded 15%, ICM was higher compared to the reference situation (whatever the proportion of low SCC). Risk ratios were also higher when the proportion of cows with low SCC were40-60%, compared to the pattern with the proportion of cows with low SCC below 40%. Herd situations with a high proportion of cows with low SCC appeared to be at increased risk of clinical mastitis.

The study describes the profiles of culled cows in order to assess the possible contribution to economic losses due to health disorders. Data regarding dates of birth, final calving and culling, parity at culling, milk yield at the two first test-days of the final lactation and reason(s) for culling were collected in a 5-year survey, carried out from 1989 to 1994 in 84 commercial Holstein farms in western France. Polytomous logistic regression was used to assess the relationship between parity, calving-to-culling interval, milk yield and eight groups of primary culling reasons (i.e. udder disorders; infertility or reproductive disorders; lameness or foot/leg defects; emergency culling reasons; other health disorders; low milk yield; sales for dairy purpose; and other voluntary culling reasons). Out of a total of 5133 culled cows, the proportions of culls, for each of these groups of reasons, were 12.4, 28.4, 2.7, 3.9, 4.6, 16.7, 5.9, and 25.4%, respectively. Cows culled for udder disorders left the herd earlier in lactation and were more frequently at parities 4–6 than cows culled for voluntary reasons. In contrast, cows culled for infertility were younger and culled later within lactation. They were also higher yielding cows than those culled for other reasons. Cows culled for lameness were similar to those of the voluntarily culling group. Cows culled for emergency reasons were more frequently younger cows in early lactation. Cows culled for other health disorders left the herd early in lactation, but at a higher parity than the voluntarily culled cows. These results suggest that most of the culls related to health could be contributing to economic loss. However, special priority should be given to reduce culling for reproductive problems, which is the most costly exit reason.

The analysis of binary data originating from clustered observations is often a problem in epidemiological studies. In most epidemiological studies on cattle, clustering occurs at two levels: cows are clustered within herds and lactation records are clustered within cows. This paper proposes and assesses a method of eliminating one level of clustering in regression analysis. Data from an observational study were used to assess the relationships between health disorders and culling, by means of logistic regression analysis, in two different ways. In the Random One Lactation (ROL) analysis, ten random selections of one lactation record per cow were done. Logistic regression analysis was performed in each sample separately. Results showed qualitative and quantitative variations between the ten final models. From the ten random samples, a disease was considered as significantly associated with culling, if present in at least four final models. Using a single random sample might give incomplete information. In the All Lactations (AL) analysis, all the available lactation records were included in one model, despite the dependency between lactations. The two methods generally agreed. All diseases significantly related in the AL analysis, except one, were also significantly associated with culling with the ROL analysis. However, differences in the regression coefficients between the ROL and the AL analyses showed the importance of dispersion parameters.

Data from an observational study, carried out during a 4.5 year period (1986–1990), were used to quantify the effects of health disorders on the risk of culling. The study population consisted of 47 commercial Holstein dairy herds from western France, comprising 4123 cows. Logistic regression was used to assess the relationships between health disorders and early and late culling. Fourteen main health disorders with clinical signs and one subclinical disease were studied: abortion, periparturient accident, calving provided with assistance, digestive disorders, ketosis, locomotor disorders, mastitis, metritis, milk fever, cystic ovaries, respiratory disorders, retained placenta, teat injuries, non-traumatic udder disorders and status with respect to milk somatic cell count. Adjustments were made for year, month of calving, parity, breeding value for milk, best of the two first milk production records and reproductive performance. The possible effects of interactions among variables were also studied. The herd effect was taken into account using random effect models. Non-traumatic udder disorders, teat injuries, milk fever and the occurrence of both ketosis and assistance at calving were significantly associated with an increased risk of being early culled (odds ratios (OR) ranging from 1.6 to 10.3). Early and late abortion, late metritis, poor peproductive performance, retained placenta, non-traumatic udder disorders within 45 days post-partum and mastitis occurring in the first 3 months of the lactation were positively associated with a late culling (OR ranging from 1.2 to 6.6). Cows with lower breeding value for milk and higher parities were high risk groups for culling. A lower level of milk production and occurrence of both reproductive disorders and poor reproductive performance were risk factors for late culling.

International audience; Inactivated virus vaccines have been widely used to control bluetongue after introduction of serotype 8 of the bluetongue virus (BTV) in northern Europe in 2006. To evaluate vaccination, quantitative knowledge of its possible side effects is needed. One current adverse reaction with inactivated vaccines is a rise in body temperature, which could reduce cow reproductive performance. The objective of this study was to quantify a possible side effect of vaccination on fertility before the implantation of the embryo of dairy cows under field conditions. The study was performed on herds that were not exposed to BTV. Fertility was assessed by return-to-service following artificial insemination (AI). Biological assumptions for a possible side effect of vaccination were conception failure and embryonic death. Associations between return-to-service rates and vaccine injections were assessed using mixed-logistic regression models and survival analysis. Two models were considered: a 3-week-return-to-service model comparing cows vaccinated between 3 days before and 16 days after AI and unvaccinated cows (assuming an effect on conception failure or early embryonic death), and a 90-day-return-to-service model comparing cows vaccinated between 3 days before and 42 days after AI and unvaccinated cows (assuming an effect on conception failure, early or late embryonic death). Only cows receiving a second vaccine injection between 2 and 7 days after AI had a significantly higher risk of 3-week-returnto- service (RR = 1.19 [1.07–1.33]). This corresponds to an increase of return-to-service by 4 percentage points. A side effect of vaccination could be due to early embryonic death. The slight side effect on fertility associated with vaccination was low compared to effects of BTV-8 exposure on fertility

SVEPM 2009 - Papers presented at the 2009 annual meeting of the Society for Veterinary Epidemiology and Preventive Medicine (SVEPM); International audience; Control strategies of infectious diseases at a regional level can rely on vaccination. When the decision to vaccinate is made by each farmer on a voluntary basis, a farmer vaccinates to protect his own herd. If the vaccinated herds are protected against infection, the risk for other herds is reduced, creating a positive externality (i.e. an impact on a third party not directly involved in the decision). The objectives of this study are to evaluate the effectiveness at a regional level of voluntary vaccination and to analyse the effect of financial incentives and compensation for losses due to disease considering the externalities due to vaccination. We developed a dynamic deterministic model, based on a decision model interacting with an epidemiological state transition model. It determines the proportion of farmers who vaccinate over time, and the evolution of the prevalence of infected herds in a population of herds exposed to the same risk. The behaviour of farmers is modelled assuming perfect information (farmers are fully informed about prevalence, costs of disease and costs of vaccination). The decision to vaccinate is made according to a rational economic behaviour: farmers make their choices to maximize their expected utility, considering their risk aversion. The expected utility is calculated with a decision tree. The epidemiological model is based on a SIR (Susceptible, Infectious, Recovered) model modified to consider imperfect vaccination that protects herds for one year. The model is studied analytically and by simulation. For simulations, we define the epidemiological parameters of the model (transmission rate and average duration of the infectious and recovered states), the herd level effectiveness of the vaccination, the cost of vaccination, the reduction of income due to the disease, the incomes of the farmers and the risk aversion of the farmers. These parameters are based on an endemic disease, BVD (Bovine Viral Diarrhoea). The model shows that voluntary vaccination cannot eradicate the modelled disease. Risk aversion of farmers leads to a lower prevalence at the equilibrium than when farmers are risk neutral. Incentives for vaccination decrease the prevalence but do not result in eradication of the disease. Compensating for disease losses in newly infected farms leads to an increase in prevalence, due to moral hazard (farmers behave less carefully than if they were fully exposed to the risk), except if it is restricted to vaccinated herds.

Variations in test-day bulk milk somatic cell count (BMSCC) according to bovine viral diarrhoea virus (BVDV) infection status of the herd were quantified. Infection statuses were defined, based on bulk-milk antibodies measured twice 4 months apart. On each test-day, BMSCC was calculated as the weighted mean of the individual cow-level somatic cell counts. A total of 97,985 test-days in 7252 herds were considered. The effect of the BVDV-infection on BMSCC was assessed using mixed linear models, controlling for herd (random), proportion of primiparous cows and average days in milk on test-day. Considering test-days contemporary to the BVDV-status definition-period, the increase in BMSCC was 12,000 (P < 0.001), 27,000 (P < 0.001) and 6000 (P = 0.97) cells/ml in past-infected recently recovered, past-but-still-infected and recently infected herds respectively, compared with not recently infected herds. A carry-over effect (at least 1 year) of BVDV-infection on BMSCC was also evidenced in past-infected recently recovered, past-but-still-infected and recently infected herds.

Estimates of milk losses consequent to dystocia, stillbirth, milk fever, retained placenta, metritis, cystic ovaries, ketosis, displaced abomasum and locomotor disorders were reviewed. Papers were selected if they provided quantitative estimates of losses based on data collected after 1965, with a sample size resulting in a minimum number of disease cases of 25. Thirty-five papers fulfilled the selection criteria. Milk losses were expressed in kg/day over the period under study to allow comparison of results. Milk fever and cystic ovaries were not associated with yield losses (six studies for each disease). Less than half of the studies found losses associated with dystocia, retained placenta, and metritis, with, respectively, five studies out of 13 (0.3-2.3 kg/day across the lactation), five studies out of 13 (0.8 kg/day across the lactation to 2.5 kg/day across 100 days in milk), and two studies out of 10 (0.4 kg/day across the lactation, and 2.3 kg/day across 119 days in milk). More than half of the studies found losses associated with stillbirth, clinical ketosis, ketosis evidenced by a diagnostic test, and locomotor disorders, with, respectively, three studies out of five (0.7-1.3 kg/day across the lactation), seven studies out of 11 (2.6-5.7 kg/day short-term, and 1.2 kg/day across the lactation), five studies out of seven (1-7 kg/day on the day of diagnosis, and around 1 kg/day across 200 days in milk), and six studies out of 11 (0.3-3.3 kg/day across the lactation). All the five studies, investigating effects of displaced abomasum, found losses (3.5-10.9 kg/day across 80 days in milk, or 0.8-2.5 kg/day across the lactation).

Many epidemiologic studies in the veterinary field aim to quantify the relationships between risk factors and the occurrence of diseases. The strength of the association between a factor and a disease can be measured by (i) a relative risk (RR), or (ii) an odds ratio (OR) which is widely used because it is directly derived from the estimates of logistic regression. RR directly provides the relative increase in the probability of disease occurrence in case of exposure. OR is often interpretated as a multiplicative factor of the risk of disease occurrence when exposed, although it is not a good approximation of RR when the disease is not rare. The objective of this paper is to propose a method to estimate RR of disease from adjusted odds ratios derived from logistic regression when the disease is not rare. The method of estimation is developed for three different cases: (i) the factor and the outcome are dichotomous; (ii) the factor has more than two classes, and the outcome is dichotomous; and (iii) the factor and the outcome both have more than two classes. In all cases, the principles of estimation are the same: in a subpopulation including individuals diseased at level j (Dj) and not diseased (D0), when exposed to level i (Fi) or not exposed to the factor (F0), R R ij can be calculated with adjusted O R ij , and the frequencies of individuals exposed to level i (ni&j), of those not exposed (n0&j) and of those diseased (ni&j) among the individuals exposed to level i and not exposed. R R ij is the positive solution of the formula: n i&j R R 2 ij +[n 0&j −(n &ij (1− O R ij ))−(n i&j O R ij )] R R ij −(n 0&j O R ij )=0 Simulations were done to assess the relative weight of the exposure rate, disease risk and value of O R ij in the difference between R R ij and O R ij . The difference between O R ij and R R ij depends upon (i), first of all, the disease risk in the population, but also (ii) the value of O R ij , and to a less extent (iii) the exposure rate. Simulations also showed that ranking of the risk-factor levels according to their effect cannot always rely on OR.

Episodes of high sow mortality rates affect profitability of swine farms. However, relevant control actions are difficult to implement. The objective of this study was to identify the risk factors for high levels of sow mortality rate (HM) in French swine herds. A case-control study was carried out in 102 swine herds located in Brittany (western France). Level of sow mortality of a herd was quantified by the annual mortality rate using sow-days as denominator. Fifty-five (53.9%) herds which experienced a sow mortality rate over 5% were classified as HM herds. Logistic regression was used to assess associations of managerial practices and disease prevalence with the odds of HM. High prevalence of urinary tract infections, metritis or lameness were significantly associated with a HM herd status (P < 0.10, OR ranging from 3.4 to 5.2). Multiplying herds were herds at higher risk for sow mortality than commercial farrow-to-finish herds. Providing three meals per day instead of two to dry sows decreased the odds of HM. Feeding plans where the maximum daily amount of feed provided to lactating sows was lower than 8 kg and was reached before 15 d in lactation were related to lower odds of HM (P < 0.10). Average age at weaning of 28 d or more and/or small average litter size at birth (12 piglets or less) were associated with higher odds of experiencing HM.

Erreur Année : pdf original en 1996 et version électronique 1997; Many studies of health and production problems in livestock involve the simultaneous evaluation of large numbers of risk factors. These analyses may be complicated by a number of problems including: multicollinearity (which arises because many of the risk factors may be related (correlated) to each other), confounding, interaction, problems related to sample size (and hence the power of the study), and the fact that many associations are evaluated from a single dataset. This paper focuses primarily on the problem of multicollinearity and discusses a number of techniques for dealing with this problem. However, some of the techniques discussed may also help to deal with the other problems identified above. The first general approach to dealing with multicollinearity involves reducing the number of independent variables prior to investigating associations with the disease. Techniques to accomplish this include: (1) excluding variables after screening for associations among independent variables; (2) creating indices or scores which combine data from multiple factors into a single variable; (3) creating a smaller set of independent variables through the use of multivariable techniques such as principal components analysis or factor analysis. The second general approach is to use appropriate steps and statistical techniques to investigate associations between the independent variables and the dependent variable. A preliminary screening of these associations may be performed using simple statistical tests. Subsequently, multivariable techniques such as linear or logistic regression or correspondence analysis can be used to identify important associations. The strengths and limitations of these techniques are discussed and the techniques are demonstrated using a dataset from a recent study of risk factors for pneumonia in swine. Emphasis is placed on comparing correspondence analysis with other techniques as it has been used less in the epidemiology literature.