Prevalence of subclinical mastitis and associated risk factors in dairy farms in urban and peri-urban areas of Thika Sub County, Kenya

D K Mureithi and M N Njuguna

Department of Animal Health and Production, Mount Kenya University, P O Box 342-01000 Thika, Kenya
dmureithi@mku.ac.ke

Abstract

A cross sectional study was carried out to investigate the prevalence of subclinical mastitis in dairy cattle, determine the most frequent of intramammary infections and evaluate associated risk factors affecting subclinical mastitis in the urban and peri urban areas of the Thika Sub county. 172 lactating cows of different ages, parities and lactation stages on 13 smallholder farms were sampled. Milk samples from 172 animals and 688 udder quarters were tested for subclinical mastitis using a California mastitis test. Milk samples from California mastitis test (CMT) positive cows and quarters were collected for further bacteriological analysis. Risk factors were also recorded during sampling.

The results showed that 110 cows out of 172 representing 64 % were CMT positive for subclinical mastitis in the study area. At the quarter level of 688 active quarters tested for subclinical mastitis, 384 (55.8%) were positive to CMT test. Breed, udder hygiene, stage of lactation, parity and floor type had a significant influence on the prevalence of subclinical mastitis. Among the breed, Ayrshire had a high prevalence 80.6%. Mid stage of lactation and multiparous animals had the highest prevalence of 77.8% and 70.1% respectively. Dirty udder and animals housed in muddy soil floor type had a significantly higher prevalence of subclinical mastitis. The study concludes that there is a high prevalence of subclinical mastitis in smallholder dairy farms in urban and peri-urban regions of the Thika sub - county. The study recommends that in order to reduce high prevalence of subclinical mastitis, smallholder farmers require to keep the udder clean, mostly in the wet season, improve floor conditions through regular cleaning of the floor or upgrade to the concrete floor.

Key words: California mastitis test, floor type, lactating dairy cows, Staphylococcus aureus

Introduction

The dairy industry from a global perspective is massive and of major importance in economic growth. Today approximately over 150 million households around the globe are engaged in milk production. In East Africa, Kenya is the leading producer, producing an estimated 3.2 billion litres per year by approximately 600,000 smallholder farmers (FAO 2011). The performance of dairy industry is driven by rising human population, ease of access to technology input, increased demand for products from animal and better buying power in urban center. Despite the rapid expansion of dairy sector, milk production often does not meet the country's milk requirements due to a horde of associated constraints such as poor animal genetic, animals’ diseases, small size of dairy enterprises, poor quality feed in the market and fluctuating seasonal forage availability because of high dependence on rain fed agriculture (FAO 2011). Among these factors, production disease particularly mastitis, is a multifaceted and expensive disease of dairy cows, which significantly reduce milk production and performance of dairy sector (Katsande et al 2014). Many studies have clearly shown that subclinical mastitis (SCM) is more important economically than clinical mastitis (Mdegela et al 2009). This is because SCM is more difficult to detect making it persists longer in the herds and eventually causing more production losses. It results in reduced milk yield, unwanted changes in the milk’s composition, increased cost of veterinary services and medicine (Ogola et al 2007; Abrahmsén et al 2014; Ayano et al 2013).

Infectious agents commonly associated with mastitis in cattle are Streptococcus agalactiae and S. aureus (Hawari and Dabbas 2008), whereas Coliforms and environmental Streptococci that are commonly found in the cows' environment are linked to environmental mastitis (Gitau et al 2014).

The Modified White Side test, catalase test, California mastitis test (CMT), pH and Somatic cell count tests are some of the diagnostic methods that can be used to indirectly diagnose subclinical mastitis. They are preferred for screening test for subclinical mastitis due to their ease of use and ability to yield rapid and satisfactory results (Alebachew and Alemu 2015).

In urban and peri-urban parts of Kenya, subclinical mastitis is not adequately investigated and data relating to its scale, risk factors and distribution is scarce. The information is essential when planning suitable mitigation that would help decrease its prevalence and effects. To bridge the identified gaps, the study investigated the prevalence of SCM in lactating dairy cows, determined the most frequency of intramammary infections and evaluated associated risk factors affecting SCM in the urban and peri urban areas of Thika Sub County.

Materials and Methods

Study area

Data for this study was collected in the Thika Sub County during the wettest month of April 2014. Thika Sub County is located in Kiambu County, 40 km from the Nairobi capital city of Kenya. Its elevation is approximately 5,351 ft. above sea level. It covers an area of about 217.60 km² and is situated between Latitude 1°1'S, and longitudes 37°5'E. The area experience bimodal rains with long rains being experienced between March and May and the short rains coming between September and November. The average annual rainfall in Thika and its environs ranges between 900 mm and 1,250 mm per annum. The average annual temperature is 19.8 °C in Thika. A cold spell is experienced during the month of July- August. Dairy farming form bulk of the main economic activities in the peri urban areas of Thika Sub County.

Study animals and sample size determination

A list of all small holder dairy farms (herd size ranging from 1 to 46 cows) in Thika Sub County was compiled with the assistance of the area animal health assistant. Using a random number table 13 dairy farms were selected. 172 lactating dairy cows of different ages, parities and lactation stages were purposively sampled proportion to the size of the dairy farms on the 13 small holder farms. The dairy cows were distributed according to breed (90 Friesian breed, 18 Jersey, 28 Guernsey and 36 Ayrshire), age (116 cows aged less than 6 years young and 56 cow aged greater than 6 years old). All dairy cows had no clinical symptoms. The animals lived under close similar condition of breeding habitat and feeding system. Clinical and physical examination were carried out in all animals with major focus on the cow’s udder. At the same time data on the age of the cow, udder hygiene (good/poor i.e. good udder hygiene was considered as physically clean udder on observation, teat dipping after milking, milking mastitis cow last, using warm water to clean the udder, washing hand before and after milking each cow, using different towels to wipe dry the udder for different animal), breed of the cow, the stage of lactation, milk production, parity, floor type and the respective farm names were also recorded.

California mastitis test (CMT)

The California Mastitis Test (CMT) was done at the farm following the guidelines of the National Mastitis Council, 1999. A small sample of milk, about 2 ml was collected from each quarter into a plastic paddle that had 4 shallow cups corresponding to the 4 udder quarters.The CMT reagent of an equal amount was added to the milk and the paddle rotated to form a CMT reagent-milk mixture. After approximately 10 seconds, the score was read while continuing to rotate the paddle. Results were recorded as 0 (negative/trace), +1 (weak positive), +2 (distinct positive), and +3 (strong positive) basing on the thickness of the gel formed by CMT reagent-milk mixture. Cows with at least one CMT-positive quarter were defined as CMT-positive

Milk sample collection, handling and transportation

Following Ayano et al (2013), the study applied aseptic procedures for collecting a composite of all quarter milk samples. Milk samples were collected before milking was done. Just before sample collection udders and especially teats were cleaned and dried. The first 3-milking streams were discarded and thereafter approximately 10 ml of milk collected in to a sterile test tube. After collection, the sample was placed in an icebox transported to the laboratory and stored at refrigerated temperature of 4⁰C for a maximum of 24 hours until inoculated on a standard bacteriological media.

Identification of mastitis-causative micro-organisms

Milk samples were examined following the protocol described by Gitau et al (2014). A 10 microliters aliquot of each milk sample was streaked on 5% sheep blood and MacConkey agar plates.This was followed by incubating the plates at 37 °C for 18–24 h in aerobic incubators. The growth of microorganism was examined on the plates after 24 hours and those without growth were further incubated for up to four days before examination. For Staphylococcus aureus and Streptococcus agalactiae, at least one colony-forming unit (CFU) was needed for them to be classified as positive bacterial growth and at least three CFUs for the other genera.The bacterial cultures were gram stained and then examined under a microscope. This was followed by biochemical test to determine the genus and species of the bacterial isolates in the sample. The colonies that were gram-negative rod after staining using their growth morphology on MacConkey agar were classified into lactose and non-lactose fermenters. To differentiate betweenE. coli and Klebsiella, lactose fermenters were further tested by citrate fermentation test with citrate negative classified as E. coli while citrate test positive classified as Klebsiella. Gram-positive cocci with small to medium-sized colonies that were haemolytic or non-haemolytic on 5% sheep blood agar were tested by catalase and coagulase tests. Catalase negative were identified as Streptococci . The catalase positive were examined further with rabbit plasma for coagulase activity. Those with coagulase activity were identified to be S. aureus while those without coagulase activities were identified to be coagulase-negative Staphylococci. Bacitracin was used to test catalase-negative Streptococci and those testing negative classified as S. agalactia.

Statistical analysis

Prevalence of subclinical mastitis was calculated by dividing the total number of samples that were positives by the total number of samples examined and then multiplied by 100. The association of the breed of the cow, age of the cow, udder hygiene (good/poor),the stage of lactation, milk production, parity, and floor type with the CMT positivity was determined by Chi-square test using SPSS statistical package version 20 and 95% was taken as the confidence interval

Results

Prevalence of subclinical mastitis at individual cow and quarter level

Out of 172 lactating cow examined, 110 representing 64% were CMT positive (at least one CMT-positive quarter) for subclinical mastitis in the study area. At the quarter level of 688 active quarters tested for subclinical mastitis, 384 (55.8%) were positive to CMT test as shown in Table 1.

Prevalence of bovine mastitis across different categories of cow

The highest prevalence of subclinical mastitis (at cow level) was observed in Ayrshire breed (80.6 %) followed by Friesian (65.6%), Guernsey (57.1%), and Jersey (33.3%) (Table 2). At the quarter level, Jersey had the highest prevalence of subclinical mastitis of 87.5% while Friesian had the lowest prevalence (Table 3). Analysis of association using chi square showed that breed had significant influence on the prevalence of subclinical mastitis both at the cow and quarter level. Prevalence of subclinical mastitis was shown to increase with age with advancing age (>6 years) showing a higher prevalence (73.2%) than lower age (<6years) which had 59.5%. However, age had no effect on the prevalence of subclinical mastitis.

The prevalence of subclinical mastitis was significantly higher in cows with poor udder hygiene (88.6%) compared to cows with good udder hygiene (Table 2). Cows in mid lactation stage (90-180days) had a significant higher prevalence of subclinical mastitis (77.8%) compared to cows in late lactation (>180 days) and early lactation stage (<90days) (Table 2).Milk production had no significant influence on prevalence of subclinical mastitis. Cow producing more than 15 litres had a higher prevalence compared to cow producing less than 15 litres (Table 2). At the quarter level, cows producing between 7 and 15 litres had a higher prevalence (58.2%) compared to cows producing less than 7 litres and more than 15 litres (Table 3).Primiparous cows had a lower prevalence of SCM than multiparous cows. The prevalence of subclinical mastitis was higher (82.1 %) in lactating cows housed on muddy soil floors compared to the cows that were kept in house with concrete floors and bad concrete floors (Table 2).

Bacterial isolates from milk samples with subclinical mastitis

A summary of the cow-level results of the bacteria isolates from cultured samples in the current study is provided in table 4. Staphylococcus aureas was the highest prevalent organism at 35.5%; followed by Coagulase negative Staphylococus (25.5%), Negative growth (12.7%), Streptococcus agalactiae (11.8%), and Streptococcus spp (11.8%), mixed growth (1.8%) and Escherichia coli (0.91%).

Discussion

The overall prevalence of subclinical mastitis was 64% in lactating cows. The finding in this study is greater than that of Gitau et al (2014), who reported subclinical mastitis of 30.5% and 34.3% during the first and second visits in different parts of Kenya. The difference in prevalence could be ascribed to different geographical location and season of sampling. A study by Rahman et al (2009) in Bangladesh has shown that prevalence of mastitis and of mild mastitis is significantly higher in wet than in dry season. However, the prevalence in this study was lower than that reported by Abrahmsén et al (2014) in Uganda of 86.3% of the tested cows. At quarter level, the prevalence of SCM was similar to that reported in Uganda at 55.4 % compared to this study 55.8%.The high prevalence of sub-clinical mastitis in this study could be attributed to poor udder hygiene practices such as lack of post milking teat dipping, lack of washing hand before and after milking each cow, use of same towel to wipe dry the udder for all animals , absence of order in milking of mastitis animals before the healthy ones as well as poor type of floor, all of which might have increased the prevalence.

In this study breed (at cow level) influenced the prevalence of subclinical mastitis with Ayrshire showing the highest prevalence of 80.6%. This study agrees with Alebachew and Alemu (2015) who reported breed had a significant influence on prevalence of mastitis. However the study reported Holstein-Friesian and Jersey with high prevalence of mastitis at 71.7% and 70% respectively as compared to Cross (local X HF) and local which had a prevalence of 48.5% and 66.5% respectively. At the quarter level Jersey had the highest prevalence of SCM of 87.5% which agrees with the finding by (Alebachew and Alemu 2015). In our study age had no significance influence on the prevalence of subclinical mastitis, this disagree with study in Bangladesh by Islam et al (2012) in which advancing age had an influence on prevalence of subclinical mastitis.

Several studies agreed with the present findings of increased subclinical mastitis with the advancing parity (Rahman et al 2009, Mekibib et al 2010, Abrahmsén et al 2014). The prevalence of SCM at quarter level was significantly higher in multiparous animal as compared to primiparous animals. This association was significant at animal level also. In our study lactation stage had an influence on prevalence of mastitis with 90-180 days having the highest prevalence of 77.8%. The animal is at peak production at this stage. Studies have shown that high-yielding dairy cows are, more prone to subclinical mastitis, as the glandular tissues are more susceptible to infection (Radostits et al 2000). However, in the current study milk production was close to significant influence on subclinical mastitis at the cow level. Interestingly, high parity cows are more productive, and are likely to be prone to subclinical mastitis

The prevalence of subclinical mastitis was significantly influenced by floor type and udder hygiene. Muddy soil floor type had a high prevalence of subclinical mastitis compared to good concrete floor. Poor udder hygiene or dirty udder had a higher prevalence of subclinical mastitis as compared to clean udder. The finding agrees with study by Mekibib et al (2010), who also found a high prevalence of subclinical mastitis in soil floor and dirty udder. In the current study the high prevalence can be explained by dirty floor would be a potential source of mastitis organism.

In the present study, bacterial isolates were similar to those found by Gitau et al (2011). The most predominant bacterium isolated (Table 4) was S. aureus (35.5%). This finding was similar to the 36.0% of bacterial isolates found by Haftu et al (2012) in Ethiopia, but lower than the finding by Gitau et al (2014) of 72.9%. Staphylococcus aureus the most prevalent mastitis organism may have been spread by milk man from one animal to other or from the environment to the animal considering the floor type and udder hygiene of the animal.

Conclusions

• There was a high prevalence of subclinical mastitis in smallholder dairy farms in urban and peri-urban regions of Thika sub-county.
  
  
• The findings suggest that in order to reduce high prevalence of subclinical mastitis, smallholder farmers require to keep the udder clean, particularly in the wet season, improve floor conditions through regular cleaning of the floor or upgrade to concrete floor.
  
  
• The risk factors for subclinical mastitis can be addressed by practical management of dairy cows following effective knowledge transfer especially through field days and provision of veterinary extension services.

Acknowledgement

The authors are grateful to the dairy farmers for agreeing to participate in this study. We also appreciate the animal health assistant for assisting in identifying all dairy farmers in the sub county.

References

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Received 9 December 2015; Accepted 15 January 2016; Published 1 February 2016

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