Hogeveen, H.

Poelarends, J.J.

Sampimon, O.C.

Sol, J.

English

NARCIS 

Monitoring subclinical mastitis in Dutch dairy herds

Wageningen Yield 

MONITORING SUBCLINICAL MASTITIS IN DUTCH DAIRY HERDS 
Judith J. Poelarends1, Henk Hogeveen2, Otlis C. Sampimon3, Jan Sol3 
'Research Institute for Animal Husbandry, Lelystad, The Netherlands 
2Current address: Farm Management Group, Wageningen University, The Netherlands 
3Animal Health Service, Deventer, The Netherlands 
World-wide the cow somatic cell count (SCC) in milk is used as an indicator of udder health. 
Cow SCC records are available to every farmer that participates in the milk-recording program 
of the Dairy Herd Improvement Association (DHIA). The bacteriological causes of increased 
cow SCC can only be revealed by bacteriological culturing of the milk. Culturing results can be 
used to take effective measures to treat and prevent (sub)clinical mastitis. 
Since the end of 1996 Dutch dairy farmers have the possibility to participate in a bacteriological 
monitoring program (BMP) for high SCC cows, offered by the Animal Health Service. The 
results of this BMP give an excellent opportunity to get an overview of the bacteriological causes 
of subclinical mastitis in the Netherlands from 1996 till 1999. 
The objective of this study was to examine the main causes of subclinical mastitis in the 
Netherlands and the relationships between culturing results and dairy cow characteristics. 
Data Collection 
During the years 1996 -1999, 3,542 dairy farmers participated in the BMP for high SCC cows. 
They took quarter milk samples from all or a part of the cows that had a SCC above 250,000 
cells/ml for at least two of the last three milk recordings. The quarter milk samples were sent to 
the Animal Health Service for bacteriological culturing according to IDF procedures (1981). 
Isolates were classified as Staphylococcus aureus (SAU), Streptococcus agalactiae (SAG), 
Streptococcus uberis (SUB), Streptococcus dysgalactiae (SDY), Arcanobacterium pyogenes 
(AP Y), Escherichia coli, (ECO), Staphylococcus non aureus (CNS), combination of streptococci 
(MSTR) and negative (NEG). Isolates like Proteus, Pseudomonas spp., yeasts, Listeria etc. were 
classified as OTHER. Isolation of three or more types of pathogens in one quarter was defined as 
contaminated (CONT). When two pathogens were isolated in one quarter sample, the culturing 
result was coded according to the pathogen listed first in the following order: SAU, SAG, SUB, 
SDY, APY, ECO, CNS, MSTR, OTHER, NEG. This list is based on a ranking according to their 
assumed impact on SCC and udder health. The same ranking order was used to assign cows with 
more than one infected quarter to one pathogen. 
Besides BMP data, monthly milk-recording data consisting of daily milk production, cow SCC, 
days in milk (DIM) and parity were also available. 
Statistical Analysis 
For cows with DHIA records, DIM at the time of culturing, parity, mean geometric SCC and 
mean daily milk production of all milk recordings were calculated for the current lactation. The 
Proceedings of the 2" International Symposium on Mastitis and Milk Quality (2001) 145 
SCC's were transformed with the natural logarithm to obtain better statistical properties. The 
number of cows infected with APY and MSTR was not sufficient for statistical analysis and 
were therefore excluded from analysis. Also CONT cases were excluded from analysis. 
Model [1] was used to estimate relationships between isolated pathogens and mean SCC in 
lactation, after corrections for milk production and parity. Cows that were sampled for culturing 
in more than one lactation, were left out of model [1], because of the interdependence of SCC 
between lactations. The model was fitted using the REML method (Genstat 5 Release 4.1,1998). 
Model [1]: 
Yjkimnop = M + HERDj + COWk + MILK, + PAR* + PATHn + YRo 
+ PATH„*( MILK, + PARm + YRo) + ejklmn0p 
where: Yjkîmnop = natural logarithm of the mean geometric SCC in the lactation (InSCC); // = 
overall mean; HERDj = random effect of herd j (j = 1.. .3,402); COWk = random effect of cow k 
(k = 1...38,444); MILK, = fixed effect of mean daily milk yield 1 (1 = <21, 21-26, 26-30, >30 
kg/day); PAR« = fixed effect of parity m (m = 1, 2, 3, 4, 5, >6); PATHn = fixed effect of isolated 
pathogen (n = SAU, SAG, SUB, SDY, ECO, CNS, OTHER, NEG); YRo = fixed effect of year o 
(o = 1996,1997, 1998, 1999); ejkimnop = random error term. 
Model [2] was used to estimate relationships between prevalence of pathogens, year, parity and 
stage of lactation. The model was fitted using regression analysis with Poisson distribution. 
Model [2]: 
Yjjkimn = M + 2&3-way interaction (YRj * SEASON) * PARk * DIM,) + PATHm + 
PATHm* (YRi + SEASONj + PARk + DIM,)+ eijkimn 
where: Yykimn = logarithm of number of cows; ß = overall mean; YRi = year i (i = 1996, 1997, 
1998, 1999); SEASONj = season j (j = winter, spring, summer, autumn); PAR* = parity k (k = 1, 
2, 3, 4, 5, >6); DIM, = days in milk at the time of culturing (1 = <100, 100-200, >300); PATHm = 
isolated pathogen m (m = SAU, SAG, SUB, SDY, ECO, CNS, OTHER, NEG); eijWmn = random 
error term. 
Results 
During the years 1996-1999 quarter milk samples were collected from 46,015 cows, 45,285 of 
which had DHIA records. Some cows were sampled more than once for bacteriological 
culturing, resulting in a total of 57,892 cow records. In some cases not all quarters of a cow were 
sampled. The total number of cultured quarters was 204,767. In Table 1 the number of quarters 
per pathogen, the number of animals that were assigned to a certain pathogen (including 
percentage of total) and the mean number of infected quarters of these cows are presented. The 
most prevalent pathogen was SAU, followed by SUB and CNS. 
On average, rear quarters were more often infected (57%) than front quarters (43%). SUB, SDY, 
APY and ECO were more frequently isolated from rear quarters than from front quarters (68% 
vs 32% for APY and 60% vs 40% for SDY, SUB and ECO). 
146 Proceedings of the 2nd International Symposium on Mastitis and Milk Quality (2001 ) 
The percentage of quarters with SCC above 250,000 cells/ml in bacteriologically negative cows 
was 27.8% of all right front quarters and 25.6%, 37.0% and 36.3% of respectively left front, right 
rear and left rear quarters. This indicates that quarter SCC can be above 250,000 cells/ml while 
no pathogens can be isolated. 
Table 1. The number of quarters per pathogen, the number of animals that were assigned to 
a pathogen and the mean number of infected quarters of these cows. 
Pathogen No. of quarters % of quarters No. of animals % of animals No. of infected 
quarters 
SAU 
SAG 
SUB 
SDY 
APY 
ECO 
CNS 
MSTR 
OTHER 
NEG 
CONT 
TOTAL 
21,823 
1,694 
7,239 
4,007 
253 
1,478 
6,901 
248 
678 
157,920 
2,526 
204,767 
10.7 
0.8 
3.5 
2.0 
0.1 
0.7 
3.4 
0.1 
0.3 
77.1 
1.2 
100 
15,846 
865 
4,986 
2,574 
205 
1,206 
3,607 
126 
370 
27,660 
447 
57,892 
27.4 
1.5 
8.6 
4.5 
0.4 
2.1 
6.2 
0.2 
0.6 
47.8 
0.8 
100 
1.6 
1.9 
1.4 
1.3 
1.2 
1.1 
1.3 
1.1 
1.3 
Table 2. Estimated mean SCC for every pathogen, across milk production and parity groups 
(x 1000 cells/ml). 
Pathogen 
SAU 
SAG 
SUB 
SDY 
ECO 
CNS 
OTHER 
NEG 
"•
b
'
tÄe
 Estin 
Mean 
372 
329 
340 
294 
199 
270 
277 
212 
îated m 
Milk 
<21 
399 
369a 
372a 
324a 
257a 
260 
255a 
233a 
production (kg/day) 
21-26 
369 
344a 
314" 
305a 
178" 
257 
287 
217 
26-30 
361 
351a 
344 
284 
194" 
270 
255a 
196" 
>30 
354 
265" 
330 
265" 
178" 
290 
321" 
204 
eans with different superscript 
Parity 
1 
284a 
233a 
237a" 
204a 
123a 
237a 
219a 
150a 
2 
317aB 
290" 
279" 
221a 
151" 
245a 
211a 
171a 
.s within each 
3 
340b 
324bc 
3 2 j be 
287" 
171" 
240a 
265" 
204" 
4 
399e 
344e 
365e 
337"° 
202° 
287" 
302" 
233be 
5 
441e 
399d 
428ed 
340e 
245d 
290" 
262" 
255e 
row differ (P<0.05). 
>6 
488e 
424d 
464d 
437d 
395e 
330" 
469e 
296cd 
Since cows, which were sampled for culturing in more than one lactation were left out of the 
analysis, model 1 included a data set of 38,444 cows. Of all cows 28% were sampled within the 
first 100 DIM, 32% between 100 and 200 DIM, 24% between 200 and 300 DIM and 16% after 
300 DIM. Mean daily milk production was 26.6 kilograms per day. Of all cows 21% were 
heifers, 20% of second parity, 19% of third parity, 15% of fourth parity, 11% of fifth parity and 
14% of parity >6. Differences between herds explained 17% of total variance in InSCC and 83% 
of total variance was explained by differences between cows. The InSCC differed by parity, 
mean daily milk production, DIM at the time of culturing, isolated pathogen and year of 
culturing (PO.05). The estimated mean SCC (xlOOO cells/ml) for every pathogen, milk 
production and parity group is presented in Table 2. For most pathogens, the SCC was 
Proceedings of the 2nd International Symposium on Mastitis and Milk Quality (2001) 147 
significantly lower as the mean daily milk production was higher. Parity had a significant 
increasing effect on SCC for every pathogen category. In general SCC was lowest for cows 
infected with ECO and bacteriologically negative cows and highest for cows infected with SAU. 
In model 2 all 45,285 cow records were used to examine whether the occurrence of pathogens 
varied across parities, DIM and years. The analysis of deviance revealed that interactions 
between pathogen and year, pathogen and season, pathogen and parity and pathogen and DIM 
were all significant (P < 0.001). 
The occurrence of SAU showed a decrease from 31% of all isolates in 1997 to 28% in 1998 and 
25% in 1999. In contrast the prevalence of negative culturing results increased over the years 
(45%, 47% and 50% of culturing results in 1997, 1998 and 1999 respectively). The other 
pathogens did not show a specific time trend in occurrence. 
The prevalence of SUB increased significantly with parity. In heifers 6% of all isolates was SUB 
and this percentage increased to 13% of all isolates in cows of parity >6. The prevalence of CNS 
was significantly higher in heifers (11%) compared to other parities (mean prevalence 6%). This 
makes that SAU (29%) and CNS (11%) are the most common pathogens in heifers. 
ECO and SUB occurred more often in early lactation (2.6% and 9.2%) and less often at the end 
of the lactation (1.4% and 8.0% for ECO and SUB respectively). 
Discussion 
This study gave an overview of 4 years monitoring of subclinical mastitis in the Netherlands. 
Although a large number of cows have been cultured, it is not a random sub sample of all cows 
in The Netherlands, but only those cows of interest to the farmer. The results of the present study 
indicate that SAU is by far the most common cause of subclinical mastitis in The Netherlands. 
This is also found in other European countries (Booth, 1995). Most of the samples submitted for 
culturing appeared to be negative. A reason for this may be that the number of colony forming 
units in milk is below the detection limit of the assay. This may be the case in cows infected with 
SAU, due to the cyclic nature of shedding pattern of this pathogen (Sears et al., 1990). Another 
reason for the negative results may be spontaneous bacteriological recovery. It is important to 
monitor SCC after a negative culturing result is obtained. If the SCC remains increased, a 
consecutive sampling may improve the probability of an accurate diagnosis. 
The present study showed that the number of infected rear quarters was higher for SUB, SDY, 
ECO and APY compared to the front quarters. The higher occurrence of SUB and SDY in rear 
quarters was also reported by Barkema et al. (1998), but in their study SAU and CNS were also 
isolated more frequently from rear quarters. They also found that right quarters were more often 
infected than left quarters. This was not the case in the present study (50-50%). 
Results showed increasing SCC with parity, which is in accordance to a study described by 
Sheldrake et al. (1983). Besides, a relatively large part of the sampled cows were of parity >5 
(25%). This indicates that older cows probably have more problems with udder health. 
148 Proceedings of the 2nd International Symposium on Mastitis and Milk Quality (2001) 
The fact that SUB was isolated more frequently in older cows compared to heifers was also 
reported by Jayarao et al. (1999). Fox et al. (1995) and Nickerson et al. (1995) also found a high 
isolation frequency of CNS in heifers followed by SAU. In this study SAU was more frequently 
isolated in heifers followed by CNS. 
Conclusion 
Data from the bacteriological monitoring program for high SCC cows, showed that most cows 
had a negative bacteriological result (47.8%). Cows with a positive bacteriological result were 
most often infected with SAU (27.4%). Also SUB and CNS were found in many cases (8.6 and 
6.2% respectively). 
Acknowledgements 
The authors wish to thank the Dairy Herd Improvement Association for providing the milk 
recording data. 
References 
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Proceedings of the 2°" International Symposium on Mastitis and Milk Quality (2001) 149 


Epidemiology of Streptococcus über is intramammary infections in a dairy herd.

Estimation of interdependence among quarters of the bovine udder with subclinical mastitis and implications for analysis.

Laboratory methods for use in mastitis work.

Lactation stage, parity, and infection affecting somatic cells, electrical conductivity, and serum albumin in milk.

Mastitis in dairy heifers: Initial studies on prevalence and control.

Progress in the control of mastitis.

Survey of intramammary infections in dairy heifers at breeding age and first parturition.

Monitoring subclinical mastitis in Dutch dairy herds

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