Globally, mastitis is an important production disease in the dairy industry and has a great economic impact due to reduced milk yield, milk quality deterioration, treatment costs, culling, risk for antimicrobial resistance and reduced animal welfare. A cohort study was conducted on 24 randomly selected dairy farms in Chittagong during six months to (1) estimate the incidence of clinical mastitis (CM) at cow level, (2) identify risk factors and (3) isolate causative pathogens. CM was defined as grade-I (changes in milk), grade-II (changes in milk and udder) and grade-III (changes in milk and udder along with systemic changes).

1. www.uhb.org.bd
Investigation of clinical mastitis and
characterization of its causal agents in
dairy cows in Chattogram
Shuvo Singha
MS Candidate
Reg: 0526
Roll: 118/02
Session: 2018-19

2. Supervisory team

3. Presentation outlines
Background
Materials and methods
Results and discussion
Conclusions and recommendations
Further studies
Acknowledgements

4. India
India
India
Myanmar
Bay of Bengal
Chattogram division
Population:168.0million
Totalarea:1,47,570sq.Km
Livestock
sector
1.5% of
GNI
24.1
million
heads
cattle
Needs
15,000
million
litres
Production
9,000
million
litres
Milk target
250 ml
Milk
availability
150 ml
Huge gap between production and demand
Background
WHO
recommendation
6,000 million
litres

5. Government Initiative
Recently 500 million
USD investment for
livestock and dairy
development
Involvement into farming
Educated Youth
becoming interested in
dairy farming
Dairy farms with better
management are
increasing
To meet the gap between demand and production
Current drivers in dairy development
Background

6. Holstein Friesian X Jersey
Holstein Friesian X Shahiwal
Local X Holstein Friesian
Local X Shahiwal2,55,744 heads1,551 dairy farms
Inspiration from
Elite people
Veterinary care Govt. support
Chattogram is one of the dairy hubs in Bangladesh
Cross breeds
Background

7. Prevalence of mastitis reports in Bangladesh: Sharma et al., 2012
Prodhan et
al, 1996
Nooruddin et
al, 1997
Kader et al,
2002
Rahman et
al, 2009
16.5
21.2
46.6 44.8
Intensive farming system
Cross bred cows
Fluctuation in temp. and humidity
Feed scarcity
Challenges Mastitis picture
Mastitis is a major challenge for dairying in Bangladesh
Research gaps Few studies on clinical mastitis
Background

8. Objectives
CM associated risk factors
Involved causal agents
1 Clinical mastitis (CM) incidence rate and grading
2
3
Spin of the objectives
Bulk milk somatic cell count (BMSCC)

9. Materials and methods
 Lactating cows
 Selected farms in Chattogram
Metropoliton and surrounding areas
Farm Cow Quarter
Epi unit
Source population

10. Location of selected 24 dairy farms under the study
Chattogram
6Months
Study duration
Sampling frame: 102 dairy farms
Materials and methods

11. Baseline data
Population size
Milking animals
Current Milk Yield
Lactation Stage
Age, Parity, BCS
Farm Data
Animal Data
Pregnant/Non-pregnant
animals
Days after Parturition
Pregnant heifer turned into lactating
Newly introduced cows
Culled lactating cows
Dried cows
Cases of CM
Temperature and humidity
Dynamic data
June July August September October
1st
2nd 3rd 4th 5th
Data were collected at one month interval
Data Collection
Baseline sample size:
1383 lactating cows with 5,532 quarters
Materials and methods
EntryintothestudyExitfromthestudy

12. Clinical
mastitis?
If yes
Grading
Collect and
store milk
samples with
ID
Data collection
Inform CVASU
mastitis team
Lab
Work
Requests to
farmers
Searching for clinical mastitis
Isolation of CM
pathogens
MALDI-TOF
confirmation
Determination of
MIC
Materials and methods

13. General Information
Date of recording: _____/_____/__________
Cow identification number:
Pregnant 1=Yes; 2=No
Suckled by calf 1=Yes; 2=No
Was the cow treated with antibiotics before the last dry period?
1=Yes; 2=No
If yes, how dry cow therapy is applied?
Observable characteristics of clinical mastitis
No of quarters affected: _____________
Mild (Grade 1): Abnormal milk
Moderate (Grade 2): Abnormal milk accompanied by swelling or
redness of mammary gland:
Severe (Grade 3): Exhibited systemic signs of illness such as
depression, anorexia, dehydration, or fever:
If any other udder/teat lesions, what are those?
Head
Tail
A B
C D
A= Front left
B= Front right
C= Hind left
D= Hind right
Mastitis Grading Record Form for Dairy Farmers
Materials and methods

14. Grade-I
23%
Grade-II
60%
Grade-III
17%
CM Cases (N=204)
Grade Number of
cases
I 47
II 122
III 35
Results and discussion
Clinical mastitis grading
Grade Number of cases
I 63.1%
II 29.3%
III 7.0%
Verbeke et al., 2014

15. Animal level Quarter level
10.5
2.8
25.5
6.5
7.8
2.4
Cow level and quarter level incidence rate at 100 unit/year
Overall
Grade-I
Grade-II
Grade-III
Overall43.9 cases//100
cows/year
11.6 cases/100
quarters/year
Clinical mastitis incidence rate
Country IRCM/100
cows/year
UK 47
Tanzenia 43.3
Netherlands 32.5
Canada 26.3
Bradley et al., 2007
Kivaria et al., 2007
Thompson-Crispi et al. 2003
Results and discussion

16. 34.9
42.1
30.8
55
51.4
45.7
42.9
38.6
33.8
56.2
51
37.5
38.8
31.7
38.3
51.8
73
29.7
51.4
BCS Parity Milk yield Lactation stage Days after parturition
Cow level incidence rate at 100 cows/year
CM incidence rate by factors
3 or less
3.1-3.25
3.26 or more
1
2
3
4
5 or more
10 or less
10.1-13
13.1-17
17.1or more
Early
Mid
Late
27 or less
28-90
91-185
186 or more
Results and discussion

17. 10391.277.166.762.759.152.149.943.14341.739.138.631.33027.226.9925.624.824.112.64.7300
55
2329
9
402
43
34
112
28
76
23302133
21
116
55
393637
19
59
3132
123456789101112131415161718192021222324
Incidence rate (100 cows/year) Farm size
Within farm level incidence rate
Results and discussion
Canada: 0-97 cases/100 cows/year
Olde Riekerink et al., 2008

18. Multivariable logistic regression model using farm as a random effect (N=196
cases of Clinical mastitis)
Variable Categories N=1383 Odd Ratio p-value 95% CI
BCS
3 or less 427 Ref
3.1-3.25 488 1.2 0.4 0.8-1.8
3.26 or more
468
1.4 0.1 0.9-2.1
Lactation
Stage
Late 352 Ref
Mid 283 1.1 0.7 0.7-1.8
Early 748 1.3 0.2 0.9-2.0
Milk Yield
(Liters)
10 or less 462 Ref
10.1-13 266 1.3 0.2 0.8-2.1
13.1-17 328 1.4 0.1 0.9-2.24
17.1or more
327
2.6 <0.001 1.6-4.0
Animal level risk factors
Results and discussion

19. Number of
farms
BMSCC/ mL of milk
(Lowest 50% of the farms)
24 3,54,000-7,77,500
Variable Categories Odd Ratio p-value 95% CI
Source of
animals
Both Ref
Purchase 295.1 0.2 -130.9 to 721.1
Own stock -202.0 0.09 -437.4 to 33.4
Floor
cleanliness
Wet Ref
Dry -244.4 0.1 -382.2 to 46.1
Multivariable linear regression model using BMSCC value with the factors
China: 300,000
EU, Aus, NZ: 400,000
Canada: 500,000
Rodrigues et al., 2005;
USDA, 2013
Bulk milk somatic cell count
Results and discussion

20. 18%
24%
4%20%
6%
4%
2%
4%
16%
2%
Frequency distribution (%) of isolated bacteria
(n=167)
Streptococcus (31)
NAS (40)
S. aureus (6)
Bacillus (33)
E. coli (10)
Pseudomonas (7)
Enterobacter (3)
Klebsiella (7)
No growth (27)
Contaminated (3)
NAS: 4.5-19.8%
Str: 18.7%
S. aureus: 0.9-12%
Oliveira et al., 2015;
Tomazi et al., 2018
Ndahetuye et al., 2019
Results and discussion

21. Matrix-Assisted Laser Desorption/Ionization Time of
Flight Mass Spectrometry
MALDI-TOF MS confirmation
n=14 isolates
Bacteria Number (%)
Staphylococcus aureus 2 (14.3)
Staphylococcus haemolyticus 4 (28.6)
Staphylococcus arlettae 2 (14.3)
Staphylococcus sciuri 5 (35.7)
Staphylococcus cohnii 1 (7.1)

22. Determination of minimum inhibitory concentration
Antibiotics Isolate-1 (non-MRSA) Isolate-2 (MRSA)
Penicillin S <0.03 R >1
Cefalotin S 1 S 1
Oxacillin+2% Nacl S 0.25 R >1
Cefoxitin S 0.25 R >8
Enrofloxacin S 0.25 S 0.25
Fusidic acid S 0.5 S 0.5
Erythromycin S 0.5 S 0.5
Clindamycin S 0.5 S 0.5
Gentamycin S 0.5 R >4
Nitrofurantoin S 16 S 16
Tetracycline S 0.5 R >4
Trimethoprim + Sulfonamide S <0.03 S <0.03
Results and discussion
Photos: Annica landin, SVA, Sweden

23. Conclusions
High Incidence rate of CM
BCS, lactation stage and milk yield
associated with CM
Large variation between farms
Pathogens: NAS (24%), MRSA
Introduction of newly purchased cows in
farms correlated with higher BMSCC

24. Recommendations
Grading accuracy should be reached
Higher milk yielding cows with higher BCS should be managed carefully
At early lactation stage more restricted hygienic measures are
necessary
Farms having higher CM incidence and higher BMSCC should adopt
management following better farms
Newly purchased cows should be kept in isolation shed

25. Future directions
Longitudinal
study covering
large number of
farms
Nested case
control study for
identifying more
factors
MALDI-TOF
analysis of all
isolated
pathogens
Determination of
MIC against all
isolates

26. Acknowledgements

27. Udder Health Bangladesh
“ Healthy Udder
Safe Milk”
Thank you for your attention!!