- Email: [email protected]
Susceptibility of clinical mastitis in successive lactations
Livestock Production Science, 34 ( 1993 ) 175-180
175
Elsevier Science Publishers B.V., Amsterdam
Short Communication
Susceptibility of clinical mastitis in successive lactations M.Z. Firat Department of Animal Science, University of Cukurova, Faculty"of Agriculture, Balcali, Adana, Turkey (Accepted 17 September 1992 )
ABSTRACT Firat, M.Z., 1993. Susceptibility of clinical mastitis in successive lactations. Livest. Prod. Sci., 34: 175-180. Milk and disease records were used from 1275 lactations of British Friesian cows. The records were made at Sonning farm of Reading University between 1984 and 1989. Eight hundred and forty pairs of successive lactations were available from the total recorded to develop a statistical model that considers the predictability of a cow having mastitis in the second lactation ('current') of the pairs given the mastitis history of the same cow in the first lactation (preceding). Logistic analysis indicated that cows with mastitis in the preceding lactation were almost twice as susceptible to clinical mastitis in the 'current' lactation than those without mastitis in the preceding lactation, with probabilities of 0,46 and 0.29, respectively. Keywords: clinical mastiffs, susceptibility, dairy cows.
INTRODUCTION
Mastitis is the most troublesome disease in many parts of the world. It brings down milk yield, shortens the productive life of the cow and causes severe economic losses to the dairy farmer. Many factors contribute to mastitis, and infectious agents set the character of this disease; however, it is essentially influenced by management (Firat, 1991 ). It is therefore crucial for the herdsman to know the probability of his cows contracting mastitis in the current lactation given that the same cows were infected or free from infection in the preceding lactation, so that he could improve management systems already operating in his farm to control the disease and receive significant benefits. Correspondence to: M.Z. Firat, Department of Mathematics and Statistics, University of Edinburgh, JCMB, King's Buildings, Mayfield Road, Edinburgh, UK.
0301-6226/93/$06.00 © 1993 Elsevier Science Publishers B.V. All rights reserved.
17 6
M.Z. FIRAT
Three requirements for the evaluation of a disease control program have been suggested by Morris ( 1971 ), namely: (a) knowledge of the frequency of disease; (b) information about the biological effect of disease; and (c) information about the effectiveness of various control procedures. These same requirements apply to evaluating the effects of management practices on disease rates and production efficiency. Several studies (e.g., Cobo-Abreu et al., 1979; Rowlands et al., 1986; Bunch et al., 1984) have reported susceptibility to clinical mastitis using different models, but none has attempted to apply a generalised linear model that uses information on the same animal. This paper examines the incidence of clinical mastitis in pairs of successive lactations and provides more detailed prediction of whether a cow will contract mastitis in the current lactation given that the same cow was infected or free from infection in the preceding lactation. MATERIALS A N D M E T H O D S
Data Milk and disease records were used from 1275 lactations of British Friesian cows, belonging to Sonning Farm of Reading University, resulting from calvings that occurred between 1984 and 1989. A dairy cow was considered to have at least two lactations during the study period. Cows with only a single lactation were ignored. Pairs involving lactations numbers 11 and 12 were also ignored due to the fact that the number of cows in these lactations was very few. Many cows contributed to more than one pair of lactations in the analysis. This means that 840 pairs of successive lactations were available for analysis from a total of 1275 lactations recorded. Feeding and management methods are described in a separate publication (Firat, 1991 ). Cows go on to the winter ration soon after calving in October and are housed night and day until the end of April. They are grazed between April and October. The majority of cows in the herd calved during the autumn and winter seasons. Cows were milked into a pipeline milking system and milk yields were recorded monthly. Mastiffs incidence was determined by the herdsman using the method which measures clinical signs. Statistical analysis Eight hundred and forty pairs of successive lactations were analysed to find the probability that a cow is going to have clinical mastiffs in the 'current' lactation given whether or not the same cow had clinical mastitis in the preceding lactation. For the purpose of analysis, the variable for presence or absence of clinical mastiffs in the 'current' lactation (2nd) is regarded as a response variable and the obvious distributional assumption for this variable is that it is binomially distributed with the binomial parameter, n2ijk~, assumed
SUSCEPTIBILITY OF CLINICAL MASTITIS IN SUCCESSIVE LACTATIONS
[ 77
to vary with the other variables in the model. A logistic analysis using a generalised linear model was fitted by maximum likelihood, which avoids transformation problems. A suitable linear logistic model considered in this paper is constructed by writing the logit of ne~jkzas a linear combination of all main effects. Such a model can be written in subscript notation as follows. logit (n2okt) = / z + year/+ seasonj + lactationk +mastitislt+ (mastitis×year)~.+yieldlijkt
(1)
Where year, is the ith year defined as a period between 1984 and 1989 ( i = 16), seasonj is the jth calving season ( j = 1-4), lactationk is the kth pair of lactations ( k = 1 and 2-9 and 10), mastitis~t is the absence ( l = 0) or presence ( l = 1 ) of clinical mastitis in the preceding year, (mastitis × year)ltg is the interaction between mastitis in the preceding lactation and the year and yieldwkz is the milk yield in kg for the ith year, jth season of calving and kth pair of lactation. From Eqn. 1
7"(,20.kl r/2ijkt= log( ( 1 -- n2ij~l) )
(2 )
implying
erl2ijkl ~2~jkt- (1 + e "2ijk/)
(3)
which is the probability of contracting mastitis in the current lactation, where x2~jk~is the binomial parameter and r/=ijktis the logistic transform. The model is constructed starting from the basic mean response using the GENSTAT computer program (GENSTAT 5, 1988 ), i.e. logit (x2ijk~)=/~, then systematically including the explanatory variables into the model. The model is built up hierarchically such that if the importance of the two factor interaction is to be considered then the associated main effects must be included in the model. Alternative models including all the main terms and interactions associated with them showed that only the interaction term for (mastitis×year)~, was significant. Therefore non-significant interactions were dropped out of the model. The change in residual deviance between two nested models is compared to the Z 2 distribution to determine whether there is evidence of the added variable being a significant source of variation in the response. In order to adjust for overdispersion, the ratio of the residual deviance of the final model to the residual degrees of freedom (the residual mean square) can be obtained. This ratio should be approximately unity when the linear logistic model is thought to be correct.
17 8
M.Z. FIRAT
RESULTS
The terms in model ( 1 ) are fitted in the order in which they occur in the model and the resulting analysis of the deviance is given in Table 1. The overall fit of the complete model is tested by comparing the deviance of 1017.32 with X2 distribution on 816 degrees of freedom. The conclusion would be that the model fits the data quite adequately and since the mean residual deviance is very close to unity the data are not overdispersed. The individual contributions to the fitted model can then be examined to assess which are significant. The final term in the model, total milk yield of preceding lactation, shows no evidence of significant effect when the deviance of 2.143 is compared with the X z distribution on 1 degree of freedom. Similarly, the other terms can be compared. Interection between occurrence of clinical mastitis and year was significant, indicating that the occurrence of mastitis varied from one year to another. Among the main effects, lactation pairs and the occurrence of disease were highly significant ( P < 0.01 ). Finally, it was found that the overall probability of a cow having clinical mastitis in the current lactation given that she did not have one in the preceding lactation was 0.29. A cow with clinical mastitis in the preceding lactation was almost twice as susceptible to infection in the current lactation with the probability of 0.46. Table 2 illustrates the fitted probabilities of clinical mastitis in the current lactation by year, season of calving and lactation pair depending on whether or not the cow was infected in the preceding lactation. In general, infected cows in the preceding lactation are one and a half to two times as susceptible to mastitis in the current lactation by year, lactation pair and season in comparison with uninfected cows. In particular, the probability of mastitis in cows previously uninfected has decreased over time, while the probability of clinical mastitis in cows previously infected has remained relatively stable. This decrease can be attributed to better feeding and management methods throughout years. Probabilities increase by lactation pair, indicating that the older cows have an increased risk of clinical mastitis. However, there is no obvious pattern in the probabilities by season for the current lactation. TABLEI Analysis of deviance on susceptibility of clinical mastitis in successive lactations Change
d.f.
Deviance
Mean deviance
Ratio
+ Year + Season + Lactation + Mastitis + Mastitis.year + Yield Residual
5 3 8 1 5 1 816
7.308 5.101 22.237 21.993 11.609 2.143 1017.320
1.462 1.700 2.780 21.993 2.322 2.143 1.247
1.17 1.36 2.23 17.64 1.86 1.72
Total
839
1087.710
1.296
179
SUSCEPTIBILITY OF CLINICAL MASTITIS IN SUCCESSIVE LACTATIONS
TABLE 2
Fitted probabilities of clinical mastiffs in the current lactation by year, lactation pair and season of calving depending on whether or not the cow was infected in the preceding lactation Mastitis incidence in the preceding lactation Uninfected
Infected
Overall
Year
1984 1985 1986 1987 1988 1989
0.43 0.39 0.31 0.27 0.31 0.19
0.59 0.43 0.54 0.51 0.30 0.49
0.48 0.41 0.39 0.36 0.30 0.29
Lactation pair
1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10
0.27 0.22 0.26 0.30 0.32 0.34 0.36 0.47 0.53
0.43 0.38 0.43 0.47 0.49 0.51 0.53 0.65 0.70
0.32 0.28 0.32 0.36 0.38 0.40 0.42 0.53 0.59
Season
Jan.-Mar. Apr.-Jun. Jul.-Sep. Oct.-Dec.
0.30 0.27 0.29 0.28
0.47 0.44 0.45 0.45
0.36 0.33 0.35 0.34
DISCUSSION
The probability of a cow having clinical mastitis in the current lactation was 29% if the cow was free from infection in the preceding lactation. The probability that she will have one in the current lactation given that she had infection in the preceding lactation was 46%. These findings are almost in agreement with those of Bunch et al. (1984) and Rowlands et al. (1986). Bunch et al. (1984) found that the average incidence of clinical mastiffs in cows in the second lactation which did not have mastiffs in the first was 16% compared with 39% in cows which had previously had clinical mastitis. Rowlands et al. ( 1986 ) reported that the proportion of cows with clinical mastitis in the study lactation was 0.38 or 0.23, depending on whether or not the cows had clinical mastiffs in the preceding lactation. Similar increased tendencies to infection have also been found by Cobo-Abreu et al. (1979) and Dohoo and Martin (1984). This effect could be due to two factors: either an increased susceptibility to further outbreaks, or prolongation of a sub-clinical infection through the dry period and into the next lactation. A clear increase in the incidence of clinical mastitis was observed with lactation number (age) which agrees with the findings of a number of previous studies (Batra et al., 1977; Cobro-Abreu et al., 1979; Martin et al., 1982; Bunch
180
M.Z.FIRAT
et al., 1984; Lucey and Rowlands, 1984). This is partly due to the increased susceptibility to disease in those animals in which the disease has already occurred. The above findings could also be hypothesised to imply a general physiological effect of aging such that as milk production increased with age, resistance to clinical mastiffs decreased. The generalised linear model used in this paper could be equally well applied to estimate the susceptibility to other diseases.
REFERENCES Batra, T.R., Nonnechke, B.J. Newbould, F.H.S. and Hacker, R.R., 1977. Incidence of clinical mastiffs in a herd of Holstein cows. J. Dairy Sci., 60:1169-1172. Bunch, K.J., Heneghan, D.J.S., Hibbitt, K.G. and Rowlands, G.J., 1984. Genetic influences on clinical mastiffs and its relationship with milk yield, season and stage of lactation. Livest. Prod. Sci., 11: 91-104. Cobo-Abreu, R., Martin, S.W., Willoughby, R.A. and Stone, J.B., 1979. The association between disease, production and culling in a university dairy herd. Can. Vet. J., 20:191. Dohoo, I.R. and Martin, S.W., 1984. Disease, production and culling in Holstein-Friesian cows. III. Disease and production as determinants of disease. Prev. Vet. Med., 2:671-690. Firat, M.Z., 1991. An investigation of effects of mastiffs on milk yield. M.Sc. Thesis, Reading University, UK. GENSTAT 5, 1988. GENSTAT 5 Reference Manual. Claredon Press, Oxford. Lucey, S. and Rowlands, G.J., 1984. The association between clinical mastiffs and milk yield in dairy cows. Anim. Prod., 39:165-175. Martin, S.W., Aziz, S.A., Sandals, W.C.D. and Curtis, R.A., 1982. The association between clinical disease, production and culling of Holstein-Friesian cows. Can. J. Anim. Sci., 62: 633-640. Morris, R.S., 1971. Economic aspects of disease control programs for dairy cattle. Aust. Vet. J., 47: 358-363. Rowlands, G.J., Lucey, S. and Russell, A.M., 1986. Susceptibility to disease in the dairy cow and its relationship with occurrences of other diseases in the current or preceding lactation. Prev. Vet. Med., 4: 223-234. RESUME Firat, M.Z., 1993. Sensibilit6 aux mammites cliniques au cours des lactations successives. Livest. Prod. Sci., 34: 175-180, en anglais. On a utilis6 les enregistrements laitiers et sanitaires effectu6s sur 1275 lactations de vaches British Friesian. Les enregistrements ont 6t6 r6alis6s sur la ferme de Sonning de l'Universit6 de Reading entre 1984 et 1989. Parmis tousles enregistrements disponibles, huit cent quarante couples de lactations successives ont 6t6 utilis6s pour mettre en place un module statistique permettant de pr6voir la probabilit6 pour une vache de pr6senter une mammite en seconde lactation (pr6sente) h partir de l'historique mammite de cette vache en premiere lactation (pr6c6dente). L'analyse logistique a indiqu6 que les vaches ayant pr6sent6 une mammite lors de la lactation pr6c6dente avaient deux fois plus de chance de pr6senter une mammite durant la lactation suivante que celles rest6es indemne lors de la lactation pr6c6dente, avec des probabilit6s de 0.46 et 0.29 respectivement.
175
Elsevier Science Publishers B.V., Amsterdam
Short Communication
Susceptibility of clinical mastitis in successive lactations M.Z. Firat Department of Animal Science, University of Cukurova, Faculty"of Agriculture, Balcali, Adana, Turkey (Accepted 17 September 1992 )
ABSTRACT Firat, M.Z., 1993. Susceptibility of clinical mastitis in successive lactations. Livest. Prod. Sci., 34: 175-180. Milk and disease records were used from 1275 lactations of British Friesian cows. The records were made at Sonning farm of Reading University between 1984 and 1989. Eight hundred and forty pairs of successive lactations were available from the total recorded to develop a statistical model that considers the predictability of a cow having mastitis in the second lactation ('current') of the pairs given the mastitis history of the same cow in the first lactation (preceding). Logistic analysis indicated that cows with mastitis in the preceding lactation were almost twice as susceptible to clinical mastitis in the 'current' lactation than those without mastitis in the preceding lactation, with probabilities of 0,46 and 0.29, respectively. Keywords: clinical mastiffs, susceptibility, dairy cows.
INTRODUCTION
Mastitis is the most troublesome disease in many parts of the world. It brings down milk yield, shortens the productive life of the cow and causes severe economic losses to the dairy farmer. Many factors contribute to mastitis, and infectious agents set the character of this disease; however, it is essentially influenced by management (Firat, 1991 ). It is therefore crucial for the herdsman to know the probability of his cows contracting mastitis in the current lactation given that the same cows were infected or free from infection in the preceding lactation, so that he could improve management systems already operating in his farm to control the disease and receive significant benefits. Correspondence to: M.Z. Firat, Department of Mathematics and Statistics, University of Edinburgh, JCMB, King's Buildings, Mayfield Road, Edinburgh, UK.
0301-6226/93/$06.00 © 1993 Elsevier Science Publishers B.V. All rights reserved.
17 6
M.Z. FIRAT
Three requirements for the evaluation of a disease control program have been suggested by Morris ( 1971 ), namely: (a) knowledge of the frequency of disease; (b) information about the biological effect of disease; and (c) information about the effectiveness of various control procedures. These same requirements apply to evaluating the effects of management practices on disease rates and production efficiency. Several studies (e.g., Cobo-Abreu et al., 1979; Rowlands et al., 1986; Bunch et al., 1984) have reported susceptibility to clinical mastitis using different models, but none has attempted to apply a generalised linear model that uses information on the same animal. This paper examines the incidence of clinical mastitis in pairs of successive lactations and provides more detailed prediction of whether a cow will contract mastitis in the current lactation given that the same cow was infected or free from infection in the preceding lactation. MATERIALS A N D M E T H O D S
Data Milk and disease records were used from 1275 lactations of British Friesian cows, belonging to Sonning Farm of Reading University, resulting from calvings that occurred between 1984 and 1989. A dairy cow was considered to have at least two lactations during the study period. Cows with only a single lactation were ignored. Pairs involving lactations numbers 11 and 12 were also ignored due to the fact that the number of cows in these lactations was very few. Many cows contributed to more than one pair of lactations in the analysis. This means that 840 pairs of successive lactations were available for analysis from a total of 1275 lactations recorded. Feeding and management methods are described in a separate publication (Firat, 1991 ). Cows go on to the winter ration soon after calving in October and are housed night and day until the end of April. They are grazed between April and October. The majority of cows in the herd calved during the autumn and winter seasons. Cows were milked into a pipeline milking system and milk yields were recorded monthly. Mastiffs incidence was determined by the herdsman using the method which measures clinical signs. Statistical analysis Eight hundred and forty pairs of successive lactations were analysed to find the probability that a cow is going to have clinical mastiffs in the 'current' lactation given whether or not the same cow had clinical mastitis in the preceding lactation. For the purpose of analysis, the variable for presence or absence of clinical mastiffs in the 'current' lactation (2nd) is regarded as a response variable and the obvious distributional assumption for this variable is that it is binomially distributed with the binomial parameter, n2ijk~, assumed
SUSCEPTIBILITY OF CLINICAL MASTITIS IN SUCCESSIVE LACTATIONS
[ 77
to vary with the other variables in the model. A logistic analysis using a generalised linear model was fitted by maximum likelihood, which avoids transformation problems. A suitable linear logistic model considered in this paper is constructed by writing the logit of ne~jkzas a linear combination of all main effects. Such a model can be written in subscript notation as follows. logit (n2okt) = / z + year/+ seasonj + lactationk +mastitislt+ (mastitis×year)~.+yieldlijkt
(1)
Where year, is the ith year defined as a period between 1984 and 1989 ( i = 16), seasonj is the jth calving season ( j = 1-4), lactationk is the kth pair of lactations ( k = 1 and 2-9 and 10), mastitis~t is the absence ( l = 0) or presence ( l = 1 ) of clinical mastitis in the preceding year, (mastitis × year)ltg is the interaction between mastitis in the preceding lactation and the year and yieldwkz is the milk yield in kg for the ith year, jth season of calving and kth pair of lactation. From Eqn. 1
7"(,20.kl r/2ijkt= log( ( 1 -- n2ij~l) )
(2 )
implying
erl2ijkl ~2~jkt- (1 + e "2ijk/)
(3)
which is the probability of contracting mastitis in the current lactation, where x2~jk~is the binomial parameter and r/=ijktis the logistic transform. The model is constructed starting from the basic mean response using the GENSTAT computer program (GENSTAT 5, 1988 ), i.e. logit (x2ijk~)=/~, then systematically including the explanatory variables into the model. The model is built up hierarchically such that if the importance of the two factor interaction is to be considered then the associated main effects must be included in the model. Alternative models including all the main terms and interactions associated with them showed that only the interaction term for (mastitis×year)~, was significant. Therefore non-significant interactions were dropped out of the model. The change in residual deviance between two nested models is compared to the Z 2 distribution to determine whether there is evidence of the added variable being a significant source of variation in the response. In order to adjust for overdispersion, the ratio of the residual deviance of the final model to the residual degrees of freedom (the residual mean square) can be obtained. This ratio should be approximately unity when the linear logistic model is thought to be correct.
17 8
M.Z. FIRAT
RESULTS
The terms in model ( 1 ) are fitted in the order in which they occur in the model and the resulting analysis of the deviance is given in Table 1. The overall fit of the complete model is tested by comparing the deviance of 1017.32 with X2 distribution on 816 degrees of freedom. The conclusion would be that the model fits the data quite adequately and since the mean residual deviance is very close to unity the data are not overdispersed. The individual contributions to the fitted model can then be examined to assess which are significant. The final term in the model, total milk yield of preceding lactation, shows no evidence of significant effect when the deviance of 2.143 is compared with the X z distribution on 1 degree of freedom. Similarly, the other terms can be compared. Interection between occurrence of clinical mastitis and year was significant, indicating that the occurrence of mastitis varied from one year to another. Among the main effects, lactation pairs and the occurrence of disease were highly significant ( P < 0.01 ). Finally, it was found that the overall probability of a cow having clinical mastitis in the current lactation given that she did not have one in the preceding lactation was 0.29. A cow with clinical mastitis in the preceding lactation was almost twice as susceptible to infection in the current lactation with the probability of 0.46. Table 2 illustrates the fitted probabilities of clinical mastitis in the current lactation by year, season of calving and lactation pair depending on whether or not the cow was infected in the preceding lactation. In general, infected cows in the preceding lactation are one and a half to two times as susceptible to mastitis in the current lactation by year, lactation pair and season in comparison with uninfected cows. In particular, the probability of mastitis in cows previously uninfected has decreased over time, while the probability of clinical mastitis in cows previously infected has remained relatively stable. This decrease can be attributed to better feeding and management methods throughout years. Probabilities increase by lactation pair, indicating that the older cows have an increased risk of clinical mastitis. However, there is no obvious pattern in the probabilities by season for the current lactation. TABLEI Analysis of deviance on susceptibility of clinical mastitis in successive lactations Change
d.f.
Deviance
Mean deviance
Ratio
+ Year + Season + Lactation + Mastitis + Mastitis.year + Yield Residual
5 3 8 1 5 1 816
7.308 5.101 22.237 21.993 11.609 2.143 1017.320
1.462 1.700 2.780 21.993 2.322 2.143 1.247
1.17 1.36 2.23 17.64 1.86 1.72
Total
839
1087.710
1.296
179
SUSCEPTIBILITY OF CLINICAL MASTITIS IN SUCCESSIVE LACTATIONS
TABLE 2
Fitted probabilities of clinical mastiffs in the current lactation by year, lactation pair and season of calving depending on whether or not the cow was infected in the preceding lactation Mastitis incidence in the preceding lactation Uninfected
Infected
Overall
Year
1984 1985 1986 1987 1988 1989
0.43 0.39 0.31 0.27 0.31 0.19
0.59 0.43 0.54 0.51 0.30 0.49
0.48 0.41 0.39 0.36 0.30 0.29
Lactation pair
1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10
0.27 0.22 0.26 0.30 0.32 0.34 0.36 0.47 0.53
0.43 0.38 0.43 0.47 0.49 0.51 0.53 0.65 0.70
0.32 0.28 0.32 0.36 0.38 0.40 0.42 0.53 0.59
Season
Jan.-Mar. Apr.-Jun. Jul.-Sep. Oct.-Dec.
0.30 0.27 0.29 0.28
0.47 0.44 0.45 0.45
0.36 0.33 0.35 0.34
DISCUSSION
The probability of a cow having clinical mastitis in the current lactation was 29% if the cow was free from infection in the preceding lactation. The probability that she will have one in the current lactation given that she had infection in the preceding lactation was 46%. These findings are almost in agreement with those of Bunch et al. (1984) and Rowlands et al. (1986). Bunch et al. (1984) found that the average incidence of clinical mastiffs in cows in the second lactation which did not have mastiffs in the first was 16% compared with 39% in cows which had previously had clinical mastitis. Rowlands et al. ( 1986 ) reported that the proportion of cows with clinical mastitis in the study lactation was 0.38 or 0.23, depending on whether or not the cows had clinical mastiffs in the preceding lactation. Similar increased tendencies to infection have also been found by Cobo-Abreu et al. (1979) and Dohoo and Martin (1984). This effect could be due to two factors: either an increased susceptibility to further outbreaks, or prolongation of a sub-clinical infection through the dry period and into the next lactation. A clear increase in the incidence of clinical mastitis was observed with lactation number (age) which agrees with the findings of a number of previous studies (Batra et al., 1977; Cobro-Abreu et al., 1979; Martin et al., 1982; Bunch
180
M.Z.FIRAT
et al., 1984; Lucey and Rowlands, 1984). This is partly due to the increased susceptibility to disease in those animals in which the disease has already occurred. The above findings could also be hypothesised to imply a general physiological effect of aging such that as milk production increased with age, resistance to clinical mastiffs decreased. The generalised linear model used in this paper could be equally well applied to estimate the susceptibility to other diseases.
REFERENCES Batra, T.R., Nonnechke, B.J. Newbould, F.H.S. and Hacker, R.R., 1977. Incidence of clinical mastiffs in a herd of Holstein cows. J. Dairy Sci., 60:1169-1172. Bunch, K.J., Heneghan, D.J.S., Hibbitt, K.G. and Rowlands, G.J., 1984. Genetic influences on clinical mastiffs and its relationship with milk yield, season and stage of lactation. Livest. Prod. Sci., 11: 91-104. Cobo-Abreu, R., Martin, S.W., Willoughby, R.A. and Stone, J.B., 1979. The association between disease, production and culling in a university dairy herd. Can. Vet. J., 20:191. Dohoo, I.R. and Martin, S.W., 1984. Disease, production and culling in Holstein-Friesian cows. III. Disease and production as determinants of disease. Prev. Vet. Med., 2:671-690. Firat, M.Z., 1991. An investigation of effects of mastiffs on milk yield. M.Sc. Thesis, Reading University, UK. GENSTAT 5, 1988. GENSTAT 5 Reference Manual. Claredon Press, Oxford. Lucey, S. and Rowlands, G.J., 1984. The association between clinical mastiffs and milk yield in dairy cows. Anim. Prod., 39:165-175. Martin, S.W., Aziz, S.A., Sandals, W.C.D. and Curtis, R.A., 1982. The association between clinical disease, production and culling of Holstein-Friesian cows. Can. J. Anim. Sci., 62: 633-640. Morris, R.S., 1971. Economic aspects of disease control programs for dairy cattle. Aust. Vet. J., 47: 358-363. Rowlands, G.J., Lucey, S. and Russell, A.M., 1986. Susceptibility to disease in the dairy cow and its relationship with occurrences of other diseases in the current or preceding lactation. Prev. Vet. Med., 4: 223-234. RESUME Firat, M.Z., 1993. Sensibilit6 aux mammites cliniques au cours des lactations successives. Livest. Prod. Sci., 34: 175-180, en anglais. On a utilis6 les enregistrements laitiers et sanitaires effectu6s sur 1275 lactations de vaches British Friesian. Les enregistrements ont 6t6 r6alis6s sur la ferme de Sonning de l'Universit6 de Reading entre 1984 et 1989. Parmis tousles enregistrements disponibles, huit cent quarante couples de lactations successives ont 6t6 utilis6s pour mettre en place un module statistique permettant de pr6voir la probabilit6 pour une vache de pr6senter une mammite en seconde lactation (pr6sente) h partir de l'historique mammite de cette vache en premiere lactation (pr6c6dente). L'analyse logistique a indiqu6 que les vaches ayant pr6sent6 une mammite lors de la lactation pr6c6dente avaient deux fois plus de chance de pr6senter une mammite durant la lactation suivante que celles rest6es indemne lors de la lactation pr6c6dente, avec des probabilit6s de 0.46 et 0.29 respectivement.