MASTITIS SIGNS AND DIAGONISTICS IN VARIOUS REGIONS OF MUKONO FARMS .pptx

mastitis research

1. PREVALENCE AND PREDISPOSING FACTORS OF MASTITIS IN DAIRY CATTLE IN NAKISUNGA SUB COUNTY, MUKONO DISTRICT Presented by: KAKEETO MICHEAL Student ID: 19/U/8490/PS BVM V MAKERERE UNIVERSITY Supervisor :DR.GERALD NIZEYIMANA

2. INTRODUCTION-BACKGROUND Key words – Mastitis which include clinical clinical mastitis (CM) & subclinical mastitis (SCM) predisposing factors. Livestock contributes about 4% of GDP and 16% of agricultural sector's GDP in Uganda Western Region leads in milk production (40%), followed by Central Region (34.3%) Uganda produces 2.2 billion liters of milk annually and processes 2.5 million liters per day Small-scale farmers possess more than 90% of the country's cattle population Rising population has increased demand for animal-based foods, leading to adoption of modern farming techniques The Ugandan diary sector is suffering with a major challenge of mastitis which imposes serious financial concerns to the sector The prevalence of mastitis in Uganda is substantial with 86.2% in Kampala ,80.6% in Wakiso district and 76.1% in Kiruhura district

3. PROBLEM STATEMENT M astitis causes significant economic importance in dairy herds in Uganda as reported from previous studies (Abrahmsén & Persson , 2014; Kakooza et al., 2023;Ssajjakambwe et al., 2017). The prevention and control of mastitis require a clear understanding of the prevalence patterns and the predisposing factors. However, this information, for the  Nakisunga sub-county is not available . Therefore, this study avails the information which will inform on the control strategies of mastitis for dairy farmers in the study area.

4. STUDY OBJECTIVES General objective To determine the prevalence and associated risk factors of mastitis in Nakisunga sub county ,Mukono district Specific objectives To determine the prevalence of clinical and subclinical mastitis in cattle in Nakisunga Subcounty To determine the associated predisposing factors of subclinical mastitis in cattle in Nakisunga Sub county.

5. JUSTIFICATION Data on prevalence and predisposing risk factors of mastitis in dairy cattle in Nakisunga sub-county will guide stakeholders in implementation of Effective mastitis control measures leading to improved milk quality quantity reduced treatment costs

6. METHODS AND MATERIALS study design-Cross sectional study Study area- Nakisunga sub county ,Mukono district study population- 162 lactating cows under different grazing systems except those in dry off period and those that have taken less than three days post-calving, to avoid testing colostrum.) Sample size -163 cows Sampling procedure :Snow ball sampling for farms and simple random sampling for selecting cows.

7. METHODS AND MATERIALS Data Collection Structured questionnaire (Kobo toolbox) for farm practices and attributes Determination of SCM- California Mastitis Test Determination of CM-clinical examination Data Analysis Logistic regression model to establish risk factors for subclinical mastitis Stata version 14.2 for statistical analysis.

8. CMT SCORE INTERPRETATION CMT score Interpretation Visible reaction Total cell count/ml Negative Mixture remains liquid ,no slime or gel 0 – 200000 T Trace Slight precipitation 150000 – 500 000 1 Weak positive Distinct precipitation but no gel formation 400 000 – 1 500 000 2 Distinct positive Mixture thickens with gel formation 800 000 – 5 000 000 3 Strong positive Viscosity greatly increased Strong gel that is cohesive &convex surface , color change >5 000 000

9. METHODOLOGY screening for SCM obtaining milk sample Adding CMT reagent to the sample Observing the results Results

10. METHODOLOGY Observing teat size Examining teat ulcers Observing cow with leaking milk Cow with damaged udder

11. METHODOLOGY –Examining cows for CM Palpating the udder Examining teat with bloody milk discharge Examining udder with coagulated milk

12. METHODS AND MATERIALS Ethical considerations: Permission was obtained from the district veterinary officer and local leaders. Verbal informed consent was also secured from the farmers after explaining the study's purpose, benefits, and advantages Study limitations Lack of records and data making it difficult to ascertain certain risk factors.

13. DATA COLLECTION POINTS Map of Nakisunga showing different farms that were sampled

14. DATA COLLECTION POINTS CONT’

15. RESULTS Of the 67 farms included in the study majority 82.09% were owned by men most (29.85%) were aged 36 to 45 years 50.75% had attained tertiary education majority (85.07%) were married. Variable (n = 67) Frequency (n) Percent (%) Dairy farmer characteristics Sex Male 55 82.09 Female 12 17.91 Age (years) 25 – 35 13 19.4 36 – 45 20 29.85 46 – 55 9 13.43 56 – 65 16 23.88 > 65 9 13.43 Education Primary 15 22.39 Secondary 18 26.87 Tertiary 34 50.75 Marital status Single 10 14.93 Married 57 85.07 Table 1: Attributes of cattle farmers in Nakisunga Sub County, Mukono

16. RESULTS CONT’ majority (70.15%) of the cattle farms kept record 46.27% had concrete/cemented floors most (61.19%) practiced zero-grazing majority (98.51%) employed stripping as the milking method Variable (n = 67) Frequency (n) Percent (%) Dairy Farm characteristics Keeps records Yes 47 70.15 No 20 29.85 Housing floor type Earth 28 41.79 Block slate 8 11.94 Concrete/cement 31 46.27 Management system Zero-grazing 41 61.19 Semi-intensive 7 10.45 Extensive 6 8.96 Tethering 13 19.4 Milking method Stripping 66 98.51 Machine milking 1 1.49 Table 2: Attributes of cattle farms in Nakisunga Sub County, Mukono

17. RESULTS CONT’ Type of mastitis (n = 162) Prevalence, n (%) 95%CI P-value Clinical 8 (4.94) a 2.47 – 9.63 0.0001 ab Sub clinical 115 (70.99) b 63.46 – 77.52   Combined (Mastitis) 123 (75.95) 68.59 – 82.29   TYPE OF MASTITIS Prevalence, n (%) Of the 163 cows screened for mastitis , 4.94%(8/163) were positive for CM 70.99%(115/163) tested positive to SCM Table 3: Prevalence of mastitis among cattle in Nakisunga Sub County, Mukono Figure 1: Prevalence of mastitis among cattle in Nakisunga Sub County, Mukono

18. RESULTS CONT’ Prevalence of clinical and subclinical mastitis by Parish SCM in cattle was highest in Banda parish (100.0%) followed by that in Nakisunga (88.9%) , Namayiba (86.7%) Kiyola parish had the lowest(40.0%) The prevalence of CM among cattle was highest (20.0%) in Wankoba parish followed by 16.7% in Kyabalongo 10.5% in Seeta-Nazigo parish as presented

19. RESULTS Quarters (n = 648) SCM, n (%) Positive Negative Left fore 90 (55.56) 72 (44.44) Right fore 85 (52.47) 77 (47.53) Left hind 92 (56.79) 70 (43.21) Right hind 103 (63.58) 59 (36.42) Overall 370 (57.10) 278 (42.90) 63.58 % 55.56 % 52.47% 56.79 % Out of , 648 udder quarters screened for SCM, 57.10% (370/648) tested positive for SCM Table 4: Quarter prevalence of SCM among the screened cows Figure 2 : Quarter prevalence of SCM among the screened cows

20. Table 5 : Bivariable and multivariable analysis for predisposing factors of SCM Variable n Prevalence of SCM, n (%) cOR(95%CI), P-value aOR(95%CI), P-value Management factors Management system Zero grazing 111 81 (72.97) 1 1 Semi intensive 19 16 (84.21) 1.97(0.5-7.3), 0.306 2.52(0.5-12.7), 0.262 Extensive 12 6 (50.0) 0.37(0.1-1.2), 0.107 0.49(0.1-2.6), 0.402 Tethering 20 12 (60.0) 0.56 (0.2-1.5), 0.244 0.46(0.1-1.7), 0.255 Bedding         Housing without beddings 105 71 (67.62) 1 1 ­­Housing with beddings 57 44 (77.19) 1.62(0.8-3.4), 0.202 1.3(0.5-3.5), 0.606 Udder injuries Absent 143 101 (70.63) 1 - Present 19 14 (73.68) 1.16(0.4-3.4), 0.783 - Dirtiness level         Slightly dirty 53 39 (73.58) 1 - Moderately dirty 70 51 (72.86) 0.96(0.4-2.2), 0.928 - Very dirty 39 25 (64.10) 0.64(0.3-1.6), 0.330 - Suckling         None suckled cows 123 92 (74.80) 1 1 Suckled cows 39 23 (58.97) 0.48(0.2-1.03), 0.060 1.03(0.4-3.0), 0.960

21. Table 6: Bivariable and multivariable analysis for predisposing factors of SCM Animal factors Breed         Friesian crosses 146 104 (71.23) 1 - Jersey 3 3 (100.0) - - Guernsey 9 5 (55.56) 0.5(0.1-2.0), 0.326 - Aryshire 4 3 (75.0) 1.2 (0.1-11.9), 0.870 - Lactation stage Early 58 27 (46.55) 1 1 Mid 36 32 (88.89) 9.2(2.9-29.3), < 0.001 8.1(2.3-28.7), 0.001 Late 67 55 (82.09) 5.3(2.3-11.8), < 0.001 6.4(2.3-17.6), < 0.001 Body condition score 2 – 3 98 71 (72.45) 1 - 3.5 – 4.5 64 44 (68.75) 0.84(0.4-1.7), 0.612 - Teat size         Small 60 38 (63.33) 1 1 Medium 79 57 (72.15) 1.5(0.7-3.1), 0.269 1.5(0.6-3.6), 0.420 Large 23 20 (86.96) 3.9(1.02-14.5), 0.045 4.4(0.99-20.0), 0.052 Teat end shape         Flat 98 68 (69.39) 1 - Rounded 47 35 (74.47) 1.29(0.6-2.8), 0.528 - Pointed 17 12 (70.59) 1.06(0.3-3.3), 0.921 -

22. Table 7 : Bivariable and multivariable analysis for predisposing factors of SCM Not pendulous 126 87 (69.05) 1 - Pendulous 36 28 (77.78) 0.64(0.3-1.5), 0.311 - Milk yield Low 69 51 (73.91) 1 1 Moderate 55 40 (72.73) 0.94(0.4-2.1), 0.882 1.04(0.4-2.9), 0.931 High 38 24 (63.16) 0.61(0.3-1.4), 0.247 0.9(0.3-2.8), 0.819 Has leaky teats No 123 83 (67.48) 1 1 Yes 39 32 (82.05) 2.2(0.9-5.4), 0.086 1.5(0.5-4.6), 0.438 Lameness         Not lame 150 104 (69.33) 1 1 Lame cow 12 11 (91.67) 4.9(0.6-38.8), 0.135 6.2(0.6-59.4), 0.113 Has history of mastitis No 110 77 (70.0) 1 - Yes 52 38 (73.08) 1.2(0.6-2.4), 0.687 - History of RAB         No 147 106 (72.11) 1 - Yes 15 9 (60.0) 0.58(0.2-1.7), 0.329 -

23. RESULTS - PREDISPOSING FACTORS Significant Predisposing Factors for SCM Lactation Stage and Teat Size were identified as significant predisposing factors for subclinical mastitis Mid-lactation: 8.1 times higher odds of SCM compared to early lactation (aOR = 8.1, 95% CI: 2.3–28.7, P = 0.001) Late-lactation: 6.4 times higher odds of SCM compared to early lactation (aOR = 6.4, 95% CI: 2.3–17.6, P < 0.001) Large teats: 3.9 times higher odds of SCM compared to small teats (cOR: 3.9, 95% CI: 1.02-14.5, P = 0.045) These findings suggest that targeted interventions should focus on cows in mid to late lactation stages and those with larger teats

24. DISCUSSION-HERD LEVEL PREVALENCE The study revealed a high overall mastitis prevalence of 75.95% among cows examined, with subclinical mastitis (SCM) predominating at 70.99% compared to clinical mastitis at 4.94%. This could be attributed to the insidious nature of SCM, which often goes undetected without screening due to the absence of visible clinical signs The prevalence of SCM revealed in this study is comparable to 68.6% reported by (Miyama et al., 2020) in Mbarara district but lower than 87.9% and 86.2% reported by (Abrahmsén et al., 2014; Kasozi et al., 2014) in Kiboga and Kampala respectively. In addition, the prevalence of SCM in cattle revealed by this study is higher than the estimate for African continent (48.2%, 95%CI: 43.6% - 52.8%) reported by ( Khasapane et al., 2023). These discrepancies could be attributed to varying cattle farmer practices from region to region.

25. DISCUSSION The quarter-level analysis showed higher prevalence in hind quarters compare to the fore quarters may be attributed to their increased exposure to environmental pathogens due to their anatomical position, which is closer to the ground and more likely to contact contaminated bedding ,hind limbs or soil. Cows in mid-lactation (88.89% prevalence and late lactation (82.09% prevalence were significantly more likely to have SCM compared to those in early lactation. This indicates that SCM risk increases as lactation progresses due to cumulative exposure to pathogens, prolonged udder stress from milk production, and potential immunosuppression in later stages

26. DISCUSSION Cows with large teats had a significantly higher SCM prevalence (86.96%) compared to those with small teats. Large teats may be more prone to injury or improper milking, facilitating pathogen entry into the udder ( Abd -El- Hady , 2015; Bhutto et al., 2010). Additionally, larger teats may have wider teat canals, increasing susceptibility to bacterial invasion( Stanek et al., 2024)

27. CONCLUSION This study revealed the prevalence of subclinical and clinical mastitis among cows to be 70.99% and 4.94% respectively. The prevalence of SCM was higher in the hind udder quarters compared to fore quarters. Lactation stage and teat size were significant predisposing factors for SCM. Cows in mid-lactation had an SCM prevalence of 88.89% and had 8.1 odds more of having SCM than those in early lactation. Similarly, cows in late lactation had an SCM prevalence of 82.09% and had 6.4 odds more of having SCM compared to early lactation Teat size also showed a significant association with SCM. Cows with large teats had an SCM prevalence of 86.96% (20 of 23 cows) and had 3.9 odds more of having SCM compared to those with small teats ( cOR : 3.9, 95%CI: 1.02-14.5, P = 0.045). The burden of mastitis among cattle revealed by this study underscores the need to devise strategies to reduce the impact of mastitis on profitability of dairy cattle production

28. RECOMMENDATION Recommendation Farmers should take precaution when selecting for cattle for breeding or stalking ,i.e. farmers should avoid cattle with big teats due to their susceptibility to SCM Regular screening of animals mainly those in late and mid lactation should be adopted to tackle the insidious nature of SCM Farmers should adopt good milking practices like post milking disinfection to reduce on chances of udder quarters getting infected For cows with large teats, training on proper milking techniques could reduce SCM risk. The geographic variation in prevalence suggests that extension services should be tailored to specific parishes, with targeted interventions in high-prevalence areas like Banda.

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