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. 2023 Aug 17;9(5):2376–2385. doi: 10.1002/vms3.1234

Mastitis on selected farms in Wakiso district, Uganda: Burden, pathogens and predictors of infectivity of antimicrobial resistant bacteria in dairy herds

Steven Kakooza 1,2, Francis Mutebi 1,3, Paul Ssajjakambwe 3, Eddie Wampande 1,4, Esther Nabatta 1,4, Collins Atuheire 3, Sayaka Tsuchida 5, Torahiko Okubo 6, Kazunari Ushida 5, John Baligwamunsi Kaneene 7,✉
PMCID: PMC10508481  PMID: 37592441

Abstract

Background

Mastitis and associated antimicrobial resistance (AMR) are major challenges to the dairy industry worldwide.

Objective

This study aimed to expose the mastitis burden, causative bacteria and drivers for mastitis‐causing multi‐drug‐resistant (MDR) Staphylococci infectivity in cows on dairy farms in Wakiso district, Uganda.

Methods

On 22 farms, practices were documented using questionnaires, and 175 cows were screened by the California mastitis test. Composite milk samples from the positive reactors were submitted to the laboratory for bacterial culture testing. Antimicrobial sensitivity testing by the Kirby Bauer disc diffusion method was done only on Staphylococci with a panel of 10 antimicrobials of clinical relevance.

Results

Mastitis was detected in 80.6% (n = 141) of the 175 sampled cows, of which sub‐clinical mastitis (76.0%: n = 133) was predominant. The Chi‐squared analysis hypothesized that cow age (p = 0.017), sub‐county (p = 0.013), parity (p < 0.0001), sex of farm owner (p = 0.003), farm duration in dairy production (p = 0.048) and the use of milking salve (p = 0.006) were associated with mastitis. Coagulase‐negative Staphylococci were the most prevalent (71.4%; n = 95), followed by Staphylococcus aureus (30.1%, n = 40). Staphylococci (76.3%; n = 135) were majorly resistant to penicillin and tetracycline. Only one isolate was phenotyped as a methicillin‐resistant Staphylococcus specie (MRSS). The prevalences of MDR strains at cow and isolate level were 6.3% and 8.3%. The major MDR phenotype identified was penicillin–tetracycline–trimethoprim‐sulphamethoxazole. The isolate detected as an MRSS exhibited the broadest MDR pattern. Cow parity was identified as a predictor of infectivity of mastitis‐causing MDR Staphylococci in dairy herds.

Conclusion

The high prevalence of mastitis and associated pathogen AMR found exposes possibilities of economic losses for the dairy sector warranting the need for farmer sensitization on the institution of proper mastitis prevention and control programs, with emphasis on milking hygiene practices and routine disease monitoring.

Keywords: antimicrobial resistance, mastitis, Uganda

On dairy farms in Wakiso district, Uganda, mastitis was detected in 80.6% of the 175 sampled cows, which sub‐clinical mastitis was predominant. This exposes possible economic losses for the dairy sector warranting the need for mastitis prevention and control programmes with emphasis on milking hygiene practices and routine disease monitoring.

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1. INTRODUCTION

The development of the dairy industry in Uganda has been slowed down by many factors among which are diseases (Ekou, 2014). Mastitis remains a frequent (Ruegg, 2017) and economically important disease of dairy cattle, characterized by udder inflammation with cases being accompanied by either physical, chemical or bacteriological changes in milk (Hamadani et al., 2013). It is the costliest disease of dairy cattle (Liang et al., 2017) causing reduced milk yield, increased health management costs and making milk less suitable for consumption and processing (Cengiz et al., 2014). In addition, it is viewed as the main cause of antibiotic use in adult dairy cows, a key driver of antimicrobial resistance (AMR).

Previous studies on sub‐clinical mastitis (SCM) in Uganda reported prevalences ranging from 61.3% to 87.9% (Abrahmsén et al., 2014; Kasozi et al., 2014; Kateete et al., 2013). This was mainly attributed to poor on‐farm milking hygiene and mastitis control practices.

Various organisms have been implicated as mastitis etiologic agents, and among them are Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Trueperella pyogenes, Mycoplasma spp. and Corynebacterium bovis, Corynebacterium spp., Streptococcus uberis, coliforms (Escherichia coli, Citrobacter, Enterobacter, Klebsiella spp.), Pseudomonas aeruginosa, Bacillus cereus, Bacillus licheniformis, Pasteurella spp., Streptococcus faecalis, and various fungal, and yeast (Zadoks et al., 2011). Globally, Staphylococci are among the main causes of mastitis as they are frequently isolated pathogens in cases of CM and SCM (Martins et al., 2019). Consumption of milk from infected cows should not be mis‐regarded because food‐borne infections by S. aureus, especially due to its heat resistant toxin, are of a public health concern (Kadariya et al., 2014).

In dairy farming, the emergence of AMR has been attributed to various routine management practices (Acar & Moulin, 2006). Several studies have reported variations in the occurrence of AMR among Staphylococci isolated from mastitic cases (Abdi et al., 2018; Alekish et al., 2013; Beuron et al., 2014; Kalayu et al., 2020; Pourtaghi et al., 2016; Turutoglu et al., 2006). In most studies, the highest AMR prevalence (33.8%–100%) was seen with penicillin but sporadic detection of bacterial intolerance to other antimicrobial classes was evident. Such occurrences complicate the selection of antimicrobial agents for the effective management of mastitis. Hitherto limited studies highlight risk factors for the observed AMR dynamics.

While some studies in Uganda highlighted the occurrence of mastitis and the emergence of AMR among associated pathogens (Byarugaba et al., 2008; Kasozi et al., 2014; Kateete et al., 2013; Ssajjakambwe et al., 2017), the spectrum of antimicrobial classes used was limited. Thus, AMR phenotypic characterization, such as multi‐drug resistance (MDR), extensively drug resistance and pan drug resistance as of mastitis‐associated pathogens, was not extensively studied. This study attempted to establish the mastitis burden and causal pathogens in the herds. The AMR profiles of Staphylococci, one of the prevalent bacteria isolated, were also tested against a panel of antimicrobials with emphasis on those currently in use by the animal health sector in Uganda. Factors associated with the infectivity of MDR Staphylococci in cases of mastitis were ascertained.

2. MATERIALS AND METHODS

2.1. Study area

The study area was in Wakiso district, the coordinates of which are 00°24′ N, 32°29′ E. The district has two counties, Busiro and Kyadondo. Busiro county was sampled as it had many active dairy operations compared to Kyadondo. In Busiro, 3 sub‐counties were selected out of the 10, and these were Wakiso town council, Mende and Wakiso sub‐counties because the farms there were easily accessible.

2.2. Study design

This was a cross‐sectional study, conducted between November 2017 and April 2018 among selected dairy herds of Wakiso district. Before beginning the study, the District Veterinary Offices (DVOs) were visited to obtain information on dairy status, the number of dairy farms and animals in the sampling area. The study involved both field and laboratory‐based methods.

2.3. Sample size and sampling design

The sample size of 246 milking cows was calculated according to Thrusfield (2005) at a 95% confidence interval (CI) and 5% precision with the estimated mastitis prevalence of 20% reported in unpublished district disease surveillance reports. In this study, only 22 farms were visited based on subjects’ willingness to participate in the research, accessibility of the farm and having lactating cows at the time of visit. The 22 farms were selected by simple random sampling from a list of 45 farms, which were in the three selected sub‐counties. A total of 175 milking cows were sampled. The deviation in our desired sample size was majorly influenced by the high number of dried‐off cows at the time of sampling particularly in the small herds, of which they were the majority.

Purposive sampling was used for the selection of milking cows to be sampled on farms with few milking animals, and simple random sampling was used for farms with large milking herds.

Each cow was clinically examined for features of mastitis, such as the presence of any gross abnormalities like fibrosis, inflammatory swellings, pain, visible injury or lesion, atrophy of the udder quarters and teat blindness. Following thorough clinical examination for mastitis, milk samples were aseptically collected.

2.4. Data and sample collection

Pretested data collection forms were used to attain animal biodata, husbandry practices and the herd characteristics. These forms were used with the aim of assessing the cow and herd‐level risk factors associated with mastitis‐causing resistant bacteria infectivity. Information was obtained by interviewing and attending herdsmen and/or farmers, recording inspections and onsite observations. The list of variables were cow demographics (age, sex, parity, past history of mastitis), farm ownership data (sub‐county, owner's age, sex, duration in production, land size) and herd management data (manager level of education, use of antibiotic feed supplements, source of labour, animal drinking water sources, record keeping, teat washing, use of a single towel per cow, milking technique, teat dipping, use of disinfectants, calf suckling, milking order, mastitis herd health checks, lab testing and treatment of sick animals).

2.5. Milk sampling, gross evaluation and transportation

Following the completion of data collection forms, composite milk samples (a pooled milk specimen from a single cow's four mammary quarters) were collected, transported and stored aseptically according to procedures as described previously (Oliver et al., 2004). Briefly, teats were cleaned and dried before milk sample collection. Then teat orifices were cleaned again with cotton soaked in 70% alcohol to prevent contamination of teats. About 2 mL of milk were stripped using clean gloved hands into a sterile sample tube from the quarter(s). Each sample was labelled with the farmer's identification system, such as cow name or ear tag. The samples were immediately transferred into a cool box maintained at 4°C with ice packs and then taken to a laboratory for bacterial analysis.

Each collected milk sample was observed for any abnormalities in colour, odour and consistency. The presence of clots, flakes, blood and other consistency changes was part of the indicators for CM, along with udder and teat morphological changes. The findings were recorded in an Excel designed data collection tool.

2.6. Mastitis screening using California mastitis test (CMT)

The California mastitis test (CMT) was used as a screening test for SCM, and it was carried out according to the procedure described by Schalm and Noorlander (1957). About 2 mL of milk from each quarter was placed in each of four shallow cups of the CMT paddle. An equal amount of the commercial CMT reagent (Bovi‐Vet CMT Kruuse, Germany) was added to each cup. A gentle circular motion was applied to the mixtures in a horizontal plane for 15 s. The CMT results were scored as 0 (negative), trace, 1 (weak positive), 2 (distinct positive) and 3 (strong positive) based on gel formation. All CMT scores of 0 and trace were considered negative, whereas CMT scores of 1–3 were considered indicators of SCM (Dingwell et al., 2003). Positive cows were defined as those having at least one quarter with a CMT score of 1 and/or above.

2.7. Bacteriological examination of milk samples

Bacteriological analysis of milk samples was carried out from the Central Diagnostic Laboratory (CDL), College of Veterinary Medicine, Animal Resources and Biosecurity (CoVAB), Makerere University. Analysis was done by spreading 50 μL of the milk sample on the surface of 5% sheep blood agar (Merck) in a Petri dish. The plates were incubated aerobically at 37°C for 24 h before an evaluation for gross colony morphology, pigmentation and haemolytic characteristics.

Colonies were selected and sub‐cultured on nutrient agar (Mast group) and incubated aerobically at 37°C for 24 h. Bacteria were then identified according to their gram reaction, morphology and biochemical tests (organism; genus‐ and species‐specific). Staphylococcus aureus was identified by the gram reaction (Gram‐positive cocci in clusters), tube coagulase test (positive), double haemolysis (alpha and beta) and mannitol fermentation (positive). Coagulase‐negative Staphylococcus spp. (CNS) were identified by the gram reaction (Gram‐positive cocci in clusters) tube coagulase test (negative) and haemolysis (alpha or beta). Streptococcus agalactiae was identified by the gram reaction (Gram‐positive cocci in chains), haemolysis (beta), catalase (negative) and confirmed by Christie–Atkins–Munch–Peterson (CAMP) test (positive). Other Streptococcus spp. were identified by the gram reaction (Gram‐positive cocci in chains), haemolysis (beta), catalase (negative) and CAMP (negative).

Coliforms were identified by the gram reaction (Gram‐positive rods), haemolysis (alpha or beta), growth on Mac Conkey (positive) and lactose fermentation (positive). Samples were considered positive for an S. aureus when at least one colony‐forming unit (CFU) was identified from the sample, whereas for other, bacterial growth was taken to be significant if more than 6 CFUs grew on the plate (Abrahmsén et al., 2014; Duse et al., 2021).

2.8. Detection and definition of AMR

2.8.1. Antimicrobial susceptibility testing using disc diffusion method

Antimicrobial susceptibility testing was done by Kirby Bauer's disc diffusion technique (Hudzicki, 2009) on Müller Hinton agar (Merck). All confirmed Staphylococci isolates were tested with 10 antimicrobial drugs; penicillin (PC) (10 U) (penicillin), tetracycline (TE) (30 μg) (tetracyclines), erythromycin (EM) (15 μg) (macrolide), ciprofloxacin (CIP) (5 μg) (fluoroquinolone), vancomycin (VM) (30 μg) (glycopeptide), gentamicin (GM) (10 μg) (aminoglycoside), cloxacillin (CX) (5 μg) and oxacillin (OX) (1 μg) (modified penicillins) and sulphamethoxazole trimethoprim (SXT) (25 μg) (potentiated sulphonamide). The antimicrobials used in this study were selected from the essential veterinary drug list for Uganda (EVDLU) being used for the treatment of mastitis and other animal bacterial diseases. The zones of inhibition were measured around disk and interpreted according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Reference strains of E. coli ATCC 25922 and S. aureus ATCC 25923 were used for quality control for antimicrobial susceptibility tests. The sensitivity patterns were categorized as susceptible, intermediate or resistant. Phenotypic expression of mecA gene was determined using previously described methods (Saba et al., 2017) where cefoxitin disks (30 μg) were used to test only those isolates resistant to oxacillin. Methicillin‐resistant Staphylococcus strains were classified as those isolates resistant to cefoxitin and oxacillin.

2.9. Defining of AMR

The criteria by Magiorakos et al. (2012) were used in the characterization of resistant Staphylococci as MDR, extensively drug resistant and pan drug resistant. For the case of S. aureus, one or more of these considerations were followed: An MRSA was considered MDR by the virtue of being an MRSA and a strain that was non‐susceptible to ≥1 agent in three and above antimicrobial categories.

2.10. Statistical analyses

Statistical analyses were conducted using SPSS Version 24.0 (IBM Corporation) and Stata version 14.0 (Stata corp) programmes with a 95% CI and 5% significance level. The corresponding prevalence CIs were computed as exact binomial 95% CIs. The prevalence of CM and SCM was obtained by determining the proportion of studied milking animals with positive CMT results, which included cows that had clinical signs and those that did not show clinical signs of mastitis. Logistic regression was used to ascertain the predictors of mastitis and mastitis causing MDR‐resistant Staphylococci infectivity. Other potential management‐based predictors, such as use of antibiotic feed supplements, use of proper hand milking technique, drying of cow teats before milking, dipping teats in germicidal solution using a non‐return dipper, milking mastitic cows last, culling of chronic cases, doing CMT on farm and submitting samples from suspected cases for bacterial culture and sensitivity testing, were not analysed because they were either practiced or not practiced in all farms. Variables with p‐values of less than 0.05 in the univariate analysis done using the Chi‐squared (χ2) test were further analysed by multivariable logistic regression (with a stepwise selection) and Akaike information criteria. Before inclusion in the multivariable model, the multicollinearity of variables was also checked using a variance inflation factor (VIF). Variables with VIF values above 5.0 were eliminated from the model (in our case none). For predictors of mastitis‐causing MDR Staphylococci, regression modelling was done for only one variable (parity) as the rest had p‐values of more than 0.05 in the univariate analysis by χ2 test. Model goodness‐of‐fit tests were also performed using the Hosmer–Lemeshow test.

3. RESULTS

3.1. Descriptive epidemiology

3.1.1. Cow variables

The demographic characteristics of the 175 studied cows are presented in Table 1. The number sampled never varied much among the sub‐counties. Moreover, the majority of cows were 3–8 years (>80%) and had more than one calving (76%).

TABLE 1.

Characteristics of cows included in the study.

Characteristic Frequency Proportion (%) 95% CI
Sub‐county
Wakiso 70 40.0 0.33–0.48
Wakiso town council 54 30.9 0.24–0.38
Mende 51 29.1 0.23–0.36
Age (years)
3–5 101 57.7 0.50–0.65
6–8 54 30.9 0.24–0.38
>8 20 11.4 0.07–0.17
Animal breed
Guernsey 6 3.4 0.02–0.07
Friesian cross 44 25.1 0.19–0.32
Friesian 119 68.0 0.61–0.75
Arshire cross 1 0.6 0.00–0.03
Local 3 1.7 0.00–0.05
Guernsey cross 2 1.1 0.00–0.04
Parity
Primiparous 42 24.0 0.18–0.31
Multiparous 133 76.0 0.69–0.82
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Abbreviation: CI, confidence interval.

3.1.2. Farm ownership, herd management and milking hygiene practices

The visited farms were located within the sub‐counties of Wakiso (n = 6), Wakiso town council (n = 4) and Mende (n = 12). On the 22 farms, the personnel that milked animals were all men, and the employee types were majorly hired employees (18/22; 81.8%) and family members (4/22; 18.2%). The mean, range, median of farm owners’ ages, herd sizes, durations in production and land sizes were 57.9 (n = 22), 62.0, 36.0–90.0; 32 (n = 19), 24.0, 5.0–102.0, 27.0 (n = 22), 20.5, 10.0–75.0; 69.1 (n = 20), 25.5, 1.0–500.0, respectively.

Approximately 86.4% (n = 19, CI: 0.63–0.96) of the farmers kept farm records, 68.2% (n = 15, CI: 0.45–0.85) practiced the division of labour and 72.7% (n = 16, CI: 0.49–0.88) kept other livestock (for instance goats, sheep, chickens) on the farms. On all farms, an underground water source and improper hand milking techniques (precisely finger milking) were evident. At milking time, the use of water mixed with recommended disinfectant solution (such as sodium hypochlorite) for washing milkers’ hands and cow teats was done by only one farm (4.5%, CI: 0.01–0.30). The latter farm also uniquely used a single towel for each cow when washing teats and had its milkers washing their hands before milking. Calf suckling before milking was done on seven farms (31.8%; CI: 0.15–0.55). There were no farmers who added antibiotic supplements in dairy meals, encouraged milkers to dry their hands and cows’ teats before milking and used known germicidal solutions (such as povidone iodine) in a non‐return dipper for teat dipping after milking. Overall, 36.4% (n = 8; CI: 0.18–0.59) of the farms practiced dry cow therapy, 54.5% (n = 12, CI: 0.33–0.75) periodically did herd health mastitis check by strip cup method and 72.7% (n = 16; CI: 0.49–0.88) used milking salve when milking. Moreover, no farm milked mastitic cows last, culled chronic mastitis cases, did CMT on the farm and submitted samples for the laboratory diagnosis of mastitis causing agents and their antimicrobial susceptibility testing before treatment.

3.2. Prevalence and risk factors of mastitis among sampled cows

The overall prevalence of mastitis was 80.6% (n = 141), where 76.0% (n = 133) of the animals had SCM, and 4.6% (n = 8) were clinical cases. Clinical mastitis presented with pus in milk (50%; n = 4), swollen udder (25%; n = 2) and unfunctional teats (25%; n = 2). Of the total number of milk samples examined, 34.9% (n = 61) of the cows had a CMT score of 3 (tentative somatic cell counts [SCC] over 5000,000), 25.7% (n = 45) had a score of 2 (estimated SCC range of 1200,000–5000,000) and 19.4% (n = 34) had a score of 1 (estimated SCC range of 400,000–1200,000). Moreover, 15 samples (8.6%) and 20 samples (11.4%) were considered trace (estimated SCC range of 200,000–400,000) and negative (estimated SCC range less than 200,000), respectively.

The following variables were hypothesized to be associated with mastitis (p < 0.05) at univariable screening using the Chi‐squared (χ2) test; cow age (χ2 = 8.15, df = 2, p = 0.017), sub‐county (χ2 = 8.72, df = 2, p = 0.013), parity (χ2 = 12.30, df = 1, p < 0.0001), sex of the farm owner (χ2 = 8.86, df = 1, p = 0.003), farm duration in dairy production (χ2 = 6.09, df = 2, p = 0.048) and the use of milking salve (χ2 = 7.42, df = 1, p = 0.006). The multivariable regression modelling showed that the likelihood of mastitis occurrence increased with cows from Wakiso town council, multiparous cows, cows milked using milking salve and cows on farms owned by men (p < 0.05). The Hosmer–Lemeshow goodness‐of‐fit test suggested that the model fit the data (χ2 =  3.38; p  =  0.908) (Table 2).

TABLE 2.

Multivariable logistic regression analysis of risk factors associated with mastitis.

Variable Number of animals Mastitis positivity Odds ratio 95% CI p‐Value
Sub‐county
Wakiso a 70 50 (71.4) 1.0 – –
Wakiso town council 54 50 (92.6) 13.9 1.4–142.6 0.027
Mende 51 41 (80.4) 2.6 0.30–5.02 0.479
Parity
Primiparous a 42 26 (61.9) 1.0 – –
Multiparous 133 115 (86.5) 3.1 1.1–9.0 0.036
Cow age (years)
3–5 a 101 74 (73.3) 1.0 – –
6–8 54 49 (90.7) 5.2 0.8–29.8 0.069
>8 20 18 (90.0) 1.3 0.2–8.3 0.795
Owner's sex
Male 169 139 (82.2) 12.8 1.1–149.9 0.043
Female a 6 2 (33.3) 1.0 0.04–4.28 –
Use of milking salve
Yes 153 128 (83.7) 15.7 1.4–171.7 0.024
No a 22 13 (59.1) 1.0 – –
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Note: Significant p‐values in bold.

Abbreviation: CI, confidence interval.

a

Reference.

3.3. Etiologic agents of mastitis among sampled cows

All the 141 diagnosed cases of mastitis were subjected to aerobic culture of bacteria to establish the infectious causes of mastitis in the dairy herds. Among these, 94.3% (n = 133) of samples had significant growth. The proportions of isolation from milk of clinically and sub‐clinically affected cows were 75% (6/8) and 95.5% (127/133), respectively.

The occurrence of pathogens from milk samples was not mutually exclusive. The bacteria that were isolated from the CMT positive samples were S. aureus (30.1%, n = 40), CNS (71.4%; n = 95), other Streptococcus spp. (6.0%, n = 8), S. agalactiae (13.5%, n = 18) and coliforms (3.8%, n = 5) (Table 3).

TABLE 3.

Bacteria isolate frequency and their occurrence in California mastitis test (CMT) positive samples.

Bacteria Number of isolates (%), N = 177 Occurrence in CMT positive samples (%), N = 133
Yes, N 1 (%) No, N 2 (%)
Staphylococcus aureus 40 (22.6) 40 (30.1) 93 (69.9)
CNS 106 (59.9) 95 (71.4) 38 (28.6)
Streptococcus spp. 8 (4.5) 8 (6.0) 125 (94.0)
Streptococcus agalactiae 18 (10.2) 18 (13.5) 115 (86.5)
Coliforms 5 (2.8) 5 (3.8) 128 (96.2)
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Abbreviation: CNS, coagulase‐negative Staphylococcus spp.

3.4. Bacterial antimicrobial resistance testing

Only the Staphylococci isolates (which were the majority) were tested for their susceptibility to a panel of drugs. The highest resistance was in penicillin (77.8%) followed by tetracycline (53.3%) and trimethoprim sulphamethoxazole (11.1%). The resistance patterns are in Table 4 .

TABLE 4.

Antimicrobial sensitivity patterns of mastitis‐associated Staphylococci (N = 135).

Sensitivity patterns
Antimicrobial agent Disc potency (μg) Resistant (R), n 1 (%) Intermediate (I), n 2 (%) Susceptible (S), n 3 (%)
Penicillin (PC) 10 U 105 (77.8) 0 (0.0) 30 (22.2)
Oxacillin (OX) 1 1 (0.7) 0 (0.0) 134 (99.3)
Cloxacillin (CX) 5 2 (1.5) 0 (0.0) 133 (98.5)
Gentamicin (GM) 10 2 (1.5) 1 (0.7) 132 (97.8)
Tetracycline (TE) 30 72 (53.3) 9 (6.7) 54 (40.0)
Erythromycin (EM) 15 2 (1.5) 4 (3.0) 129 (95.6)
Ciprofloxacin (CIP) 5 2 (1.5) 2 (1.5) 131 (97.0)
Vancomycin (VM) 30 4 (3.0) 0 (0.0) 131 (97.0)
Trimethoprim sulphamethoxazole (SXT) 23.75 15 (11.1) 2 (1.5) 118 (87.4)
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3.5. The magnitude of mastitis‐associated MDR Staphylococci

The prevalence of antimicrobial resistant Staphylococci at cow level was 6.3% (n = 11) for MDR Staphylococci. At isolate level, 8.3% (n = 11) of the isolates were MDR.

The predominant MDR phenotype for Staphylococci isolates from mastitis was PC–TE–ST (54.5%; n = 6) (Figure 1). However, the isolate phenotypically detected to be a methicillin‐resistant Staphylococcus specie (MRSS) exhibited the broadest resistance pattern (PC–OX–CX–TE–VM).

FIGURE 1.

FIGURE 1

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Characterization of antimicrobial resistance (AMR) patterns among multi‐drug‐resistant (MDR) Staphylococci. ‘*’ signifies isolate that exhibited the broadest spectrum of MDR. CIP, ciprofloxacin (flouroquinolone); CX, cloxacillin (modified penicillin); EM, erythromycin (macrolide); GM, gentamicin (aminoglycoside); OX, oxacillin (modified penicilin); PC, penicillin (penicillin); ST, trimethoprim sulphamethoxazole (potentiated sulphonamide); TE, tetracycline (tetracycline); VCM, vancomycin (glycopeptide).

3.6. Potential risk factors associated with infectivity of mastitis‐associated MDR Staphylococci

Many cow‐level and management‐based factors associated with the infectivity of MDR Staphylococci in mastitic cases were considered. At univariable analysis, parity was significantly associated with the infectivity of MDR Staphylococci (χ2 = 6.00, df = 1, p = 0.014).

The regression analysis model revealed that keeping primiparous cows was a significant positive predictor of infectivity of MDR Staphylococci in cases of mastitis (OR = 4.3, CI = 1.2–14.8, p = 0.022).

4. DISCUSSION

This study investigated the prevalence and drivers of mastitis, occurrence of infectious causes of mastitis and risk factors associated with MDR Staphylococci in cases of mastitis. An overall prevalence of mastitis (clinical and sub‐clinical cases) of 80.6% was higher than that reported before in Uganda (76.1%) (Ssajjakambwe et al., 2017) and in Ethiopia (50.7%) (Asmare & Kassa, 2017). The high prevalence of SCM found in Wakiso could be associated with the adoption of ineffective or lack of crucial mastitis prevention and control practices on a majority of farms. Farmers usually do not have sufficient knowledge on SCM; thus, their efforts are always centred on CM. Consequently, SCM is generally given little attention by farmers in terms of treatment and control when compared to the noticeable CM (Karimuribo et al., 2006). In addition, CMT (an on‐farm mastitis screening examination) was not popular on visited farms (personal observation) as this can be adopted to serve as a first line method in detection of SCM or herd health check for mastitis. This may explain the high prevalence of SCM detected by this study. Similar to other studies (Byarugaba et al., 2008; Ssajjakambwe et al., 2017), the present study revealed fewer cases of CM and more of SCM cases. Findings evidently demonstrate a notable high prevalence of mastitis in the studied area among the sampled cows. The occurrence of disease directly exposes animals to AMR organisms; thus, the institution of good milking hygiene practices will not only prevent emergence of new mastitis cases but also reduce the burden of AMR bacteria. Based on personal observation, animals were predisposed to mastitis causing pathogens as a result of already earmarked risky practices done at milking time and after milking by some previous studies (Abebe et al., 2016; Silva et al., 2021). Most of the farmers washed all individual cows’ teats with a single towel, had no milking in order to segregate sick and non‐sick cows, and milkers used dirty hands and finger milking. Culling of chronic mastitic cows and teat dipping after milking with disinfectants, such as iodine, was not done. It was also hard for farmers to control mastitis and treat cases effectively because field and laboratory tests, such as CMT, bacterial culture and sensitivity, were not done. When controlling mastitis, blind treatment should be discouraged because it commonly causes selective pressure of the microbes to different antimicrobials being tried out by farmers. The use of milking salve and keeping of multiparous animals were significantly associated with mastitis; thus, farmers need guidance on these aspects.

The spectrum of mastitis‐causing pathogens did not differ from what has been reported by previous studies in Uganda (Abrahmsén et al., 2014; Byarugaba et al., 2008) and other countries (Asmare & Kassa, 2017; Bitew et al., 2010). The most prevalent causative pathogens for mastitis were CNS and S. aureus, a finding which is similar to those of other studies (Byarugaba et al., 2008; Ssajjakambwe et al., 2017; Zeryehun & Abera, 2017). Coagulase‐negative Staphylococci, although regarded as a minor pathogen, can easily be introduced into the teat canal because it is easily found on and around the udder skin (Tolone et al., 2016). Thus, poor mastitis control and milking hygiene practices among the study farms could account for its increased chance of entry into the canal thus the high prevalence.

Upon the characterization of S. aureus strains (Sahebekhtiari et al., 2011; Wang et al., 2018), it has been noted that they possess a number of virulence factors enabling their invasion and colonization of the mammary tissues. The major concern is that they are contagious, spread from cow to cow at milking time (Abebe et al., 2016). Unfortunately, many of the farms had predisposing practices, such as use of a single towel for washing all milking animals making it easy for the infection to spread to the majority of the cows (personal observation). The transmission of S. agalactiae is similar to that of S. aureus as both are contagious pathogens. It is plausibly expected to have similar occurrence rates, though they readily respond to treatment which is also noticed in their resistance patterns based on past research (Krömker & Leimbach, 2017). Coliforms, which are common environment contaminants, were the least detected pathogens. This outcome compared to other studies may have been influenced by the time of sampling (dry season) (Alekish et al., 2013). According to Hogan and Smith (2003), when cows are housed in dry lots or pastures, rates of CM are generally decreased during periods of dry weather as circulation and survival of environmental bacteria is lowered.

Anitmicrobial resistance experiments were focused on Staphylococci which included S. aureus and CNS as the most predominant. Resistance to penicillins was reported in the past two decades to occur in Staphylococcus spp. (Ferri et al., 2017). Resistance traits have potential to spread to other classes and patterns but vary between regions and countries. This was also evident in our findings with the highest resistance being recorded mainly against penicillin and tetracycline. This was in agreement with studies done by Byarugaba et al. (2008), Kateete et al. (2013) and Turutoglu et al. (2006) who reported resistance prevalences to penicillins and tetracycline in the range of 52%–86.8% and 33%–76.9%, respectively. Coincidentally, penicillins and tetracycline antibiotics are the most commonly used antimicrobial agents in Uganda (Kakooza et al., 2021). In addition, many Staphylococcus strains possess the ability to resist antibiotic therapy by the production of beta lactamase, an enzyme that inactivates penicillin and closely related antibiotics. Moreover, tetracycline has been used extensively in the management of tick‐borne diseases, such as east coast fever and anaplasmosis by the majority of pastoral communities in Uganda, thus increasing selective pressure against it (Oz et al., 2014).

Minimal AMR against cloxacillin, gentamicin, erythromycin and ciprofloxacin was recorded by the study. This can be attributed to many factors, but most outstanding is that the four antimicrobials are rarely used for treating CM in the study areas and elsewhere in the country. Cloxacillin was only used at the time of dry cow therapy based on interviews pertaining to antimicrobial use on the farms (personal observation). Gentamicin intramammary antibiotics exist on the Ugandan market, but farmers abstain from the use of gentamicin because it is expensive, whereas ciprofloxacin and erythromycin derivatives are scarce on the market.

Vancomycin is a glycopeptide that has been in use for over 50 years and continues to be used as a major antimicrobial in clinical practice for the treatment of infections caused by drug‐resistant Gram‐positive bacteria, such as MRSA (Choo & Chambers, 2016). However, it is rarely used for the treatment of animal infections in Uganda based on the information from the DVO. Nonetheless, it has also been recognized that MRSA isolates that are resistant to beta‐lactam antibiotics may develop induced resistance to vancomycin (Gundogan et al., 2005). This may explain why one Staphylococcus strain that was resistant to methicillin was also resistant to vancomycin and penicillin. The findings of this study add to the available literature on the occurrence of vancomycin‐resistant Staphylococci in mastitis (Abd El‐Aziz et al., 2018), which is scanty. The latter studies (Nigam et al., 2015; Pehlivanoğlu & Yardımcı, 2012) reported quite higher proportions of vancomycin resistance compared to this study.

The occurrence of MRSS was rare, a similar finding by Gindonis et al. (2013) and Kateete et al. (2013); though regarded crucial since reports of MRSA/MRSS, a known MDR strain is notably of both veterinary and public health importance. Nevertheless, studies by Fessler et al. (2010) and Vishnupriya et al. (2014) reported higher prevalences of MRSS from mastitis. This could be a result of variations in the methods used by different researchers as more MRSS/MRSA strains are often detected by genotypic methods than by phenotypic assays.

Furthermore, the characterization of AMR patterns among MDR strains revealed that the PC–TE–SXT resistance pattern was the most common. This is supported by the fact that the highest resistances were observed with penicillin, tetracycline and trimethoprim sulphamethoxazole drug classes. The isolate in this study which was phenotyped as MRSS had the widest spectrum of MDR to many antibiotics, including penicillin, oxacillin, cloxacillin, tetracycline and vancomycin.

There still exists a glaring paucity in information regarding risk factors for the occurrence of MDR mastitis‐causing Staphylococci. In this study, cow parity was the only significant predictor for infectivity with MDR Staphylococci. Cows with more calvings (literally more years) had lower chances of being infected with MDR strains. This could be a result of acquired immunity to fight off infections by MDR gained as they mature. Young age has also been studied by van Bijnen et al. (2015) to be associated with higher odds for carriage of a resistant S. aureus, although the study was done in humans.

Due to the scarcity of resources, the required sample size of the farms could not be achieved; thus, the investigation of factors for mastitis and AMR occurrence was limited to cow level neglecting herd level due to few farms. Moreover, we encourage future studies to biotype coliforms and CNS bacteria using accurate real time technology such as matrix‐assisted laser desorption/ionization time of flight mass spectrophotometry. This is because some CNS affect udder health more than others (Supré et al., 2011); thus, it is important to generate such data for control.

5. CONCLUSION

The prevalence of mastitis in the study area of Wakiso district was remarkably high of which SCM was more prevalent than CM. Mastitis prevalence can be reduced through supporting dairy farmer extension campaigns on profitable herd health management practices to include regular testing and treatment protocols, together with the implementation of appropriate infection prevention and control measures. Staphylococci were the most prevalent mastitis causing with AMR phenotyping revealing noxious bugs such as MRSS. This warrants the need for continuous AMR surveillance in consumer milk and milk products for the promotion of public health. The influencers of infectivity of mastitis‐causing drug‐resistant bacteria in herds also need more studying and may be considered in crafting national control strategies.

AUTHOR CONTRIBUTIONS

Conceptualization; data curation; formal analysis; investigation; methodology; writing – original draft; writing – review and editing: Steven Kakooza. Conceptualization; writing – original draft; writing – review and editing; supervision: Francis Mutebi. Conceptualization; data curation; project administration; resources; supervision; validation; writing – original draft; writing – review and editing: Paul Ssajjakambwe. Conceptualization; formal analysis; writing – original draft; writing – review and editing; supervision: Eddie Wampande. Data curation; formal analysis; writing – original draft: Esther Nabatta. Formal analysis; writing – original draft: Collins Atuheire. Formal analysis; writing – original draft; writing – review and editing: Sayaka Tsuchida, Torahiko Okubo and Kazunari Ushida. Conceptualization; formal analysis; resources; supervision; validation; writing – original draft; writing – review and editing: John Baligwamunsi Kaneene.

CONFLICT OF INTEREST STATEMENT

The authors confirm that they have no membership with or participation in any organization or entity with any financial or non‐financial interest in the subject matter discussed in this manuscript.

FUNDING INFORMATION

None.

ETHICS STATEMENT

The study protocol was reviewed by the Research and Ethics Committee of the School of Biosecurity, Biotechnical and Laboratory Sciences (SBLS) at Makerere University (SBLS/REC/17/011). Upon acceptance, the proposal was submitted to the Directorate of Research and Graduate Training School for approval. Farm owners gave written consent to participate in the study and data was done anonymously.

PEER REVIEW

The peer review history for this article is available at https://publons.com/publon/10.1002/vms3.1234.

ACKNOWLEDGEMENTS

This research was, partially, supported by the College of Veterinary Medicine, Animal Resources and Biosecurity (CoVAB) at Makerere University, Michigan State University (MSU), Hokkaido University, Kyoto Prefectural University and Chubu University. The authors are also grateful to the Wakiso district local government veterinarians, Dr. Candia Charles and Dr. Fredrick Kalungi for their assistance in the field sample collection.

Kakooza, S. , Mutebi, F. , Ssajjakambwe, P. , Wampande, E. , Nabatta, E. , Atuheire, C. , Tsuchida, S. , Okubo, T. , Ushida, K. , & Kaneene, J. B. (2023). Mastitis on selected farms in Wakiso district, Uganda: Burden, pathogens and predictors of infectivity of antimicrobial resistant bacteria in dairy herds. Veterinary Medicine and Science, 9, 2376–2385. 10.1002/vms3.1234

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available on request from the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author.

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