Influence of Disease Control Practices on Occurrence of Antibiotic-Resistant Bacteria and Antibiotic Residues in Milk from Kilosa and Morogoro Municipality ()
1. Introduction
Antibiotic resistance poses a major threat to global health, food security, and development, and can impact anyone, regardless of age or location [1]. Resistant microorganisms can survive the effects of antibiotics, rendering standard treatments ineffective and increasing the risk of infection spread to others. Misuse of antibiotics, such as excessive dependence, arbitrary drug combinations, incorrect dosage, and failure to observe withdrawal periods, have contributed to the development of organisms that are resistant to commonly used antibiotics [2]. For instance, inappropriate use of antibacterial drugs in treating food-producing animals has been associated with the emergence of bacteria species that can withstand attack by these antibiotics to the extent that standard treatments become ineffective and infections persist [3]. The emergence of antibiotic resistance is a gradual process that results from repeated exposure of bacteria in humans and animals to different types, strengths, and frequencies of antimicrobial drugs. As a result, certain bacterial strains with unique resistance patterns are favored due to selective pressure [4]. Moreover, resistance traits can be transferred from one bacterium to another through horizontal gene transfer [5]. Recent cases of multidrug-resistant tuberculosis (MDR-TB) have been identified in 100 countries; these cases lead to treatment courses that are much longer and less effective than those for non-resistant TB [6]. A high percentage (over 90%) of S. aureus are resistant to penicillin and oxacillin, leading to the common prescription of Vancomycin to treat infections caused by multiply-resistant S. aureus [6]. Studies in Tanzania have reported several bacteria resistant to commonly used antibiotics in livestock production [7]. The presence of antibiotic-resistant pathogens has an important public health implication, especially in developing countries like Tanzania where there is a widespread and uncontrolled use of antibiotics among livestock keepers [8]. Excessive use of antibiotics can lead to the buildup of antibiotic residues in animal food sources [1]. This occurs when an animal ingests tainted grasses, water, or any food contaminated with antibiotics from the feces of another animal that had been previously treated with antibiotics [9]. Their presence in human foods is associated with several adverse public health effects, including hypersensitivity, gastrointestinal disturbance, and neurological disorders [10]. It is important to acknow-ledge that the presence of antibiotic residues in milk can hinder the fermentation process involved in the production of some essential food items like yogurt and cheese [1]. The use of antibiotics that may result in the deposition of residues in meat, milk, and eggs should not be allowed in food meant for human consumption unless it is necessary for the prevention and treatment of animal diseases. In that case, a withholding period must be observed until the residues are negligible or no longer detected [11]. The present study is aimed at investigating the influence of disease control practices on the development of antibiotic-resistant bacteria and antibiotic residues in milk collected from the two farming systems (intensive and semi-intensive).
2. Methodology
The present study involved the selection of two districts in the Morogoro region, namely Morogoro Municipal and Kilosa District. The choice of Morogoro Municipal was based on its high concentration of livestock keepers. Specifically, it was observed that roughly 33% of the region’s population is engaged in subsistence farming and livestock keeping [12].
2.1. Experimental Design
A cross-sectional study was conducted using a random selection of 8 Wards from each district as sampling areas. The study aimed to compare sociological data obtained from questionnaires and laboratory results to find any scientific correlation. The chi-squared test was used to compare questionnaire responses, proportion of isolates, prevalence rates, and antibiotic resistance patterns of S. aureus isolates between the two groups. The sample size for the study was calculated using a confidence level (Zα) of 95%, a prevalence rate of 7.6%, and a maximum error (e) of 5%. The formula used to calculate the sample size was [13]
n = Zα2*P(−)e2
n = 1.962 × 0.076 (1 − 0.052)
n = 107.909
2.2. Questionnaire Survey
The questionnaire included questions in both open and closed-ended formats to allow respondents to express themselves freely. This approach ensured that a range of information was obtained, including knowledge on key topics such as the withdrawal period, availability of veterinary services, drug administration, and consumption of milk from an animal under treatment without observing the withdrawal period.
2.3. Sampling
To gather data, questionnaires were completed by willing livestock keepers and milk samples were obtained. From the pooling containers used by households, 25 ml of milk was directly collected. The samples were then transferred into sterile screw-capped falcon tubes and kept cool before being frozen within 8 hours. Each district provided 108 milk samples, with an average of 12 samples per ward.
2.4. Laboratory Analysis
The milk samples were transferred to the laboratory for identification and isolation of S. aureus, determination of antibiotic drug resistance and antibiotic residues.
2.5. Isolation and Identification of S. Aureus
The fresh milk samples collected from the households in Kilosa and Morogoro Municipality were immediately cultured on blood agar and MacConkey agar according to the standard methods of the examination. Bacterial culturing was performed by streaking three loopfuls from each milk sample onto labeled media plates. The plates were then incubated at 37˚C for 24 hours before readings were taken and recorded.
2.6. Gram Staining
Two drops of normal saline were added to a sterilized slide using a sterilized wooden stick. A small sample of test colony was transferred to the slide and a form smear, which was dried by gently heating on a gas burner. A few drops of crystal violet were then added and left for about one minute. The slides were washed in a gentle and indirect stream of tap water for 2 seconds and then flooded with mordant iodine and were left to dry for one minute. Thereafter, the slides were washed again in a gentle and indirect stream of tap water for two seconds, followed by washing the slides by using a decolorizing agent (Acetone-alcohol decolorizer) and left for 15 seconds. Finally, slides were washed in a gentle and indirect stream of tap water until no color appeared and then was dried with absorbent paper ready for observation using microscope.
2.7. Catalase Test (Slide Test)
A small amount of bacterial colony was grown on nutrient agar and incubated at 37˚C for 18 - 24 hours, and then transferred to a surface of a clean, dry glass slide using a loop or sterile wooden stick. This was followed by transferring 3 to 4 drops of 3% hydrogen peroxide on the slide and mixed. A positive reaction was indicated by the formation of bubbles from the culture.
2.8. Coagulase Test
Rabbit plasma was diluted in saline (0.85% NaCl) at a ratio of 1:6; 1 ml of the resulting dilution was transferred into small tubes. Several isolated colonies of test organisms were then transferred into the small tubes to give a milky suspension. The suspension containing tubes were incubated at 35˚C in for 4 hours. Examination for clot formation was done by tilting the tube through 90˚; negative tubes were left at room temperature overnight and re-examined.
2.9. Determination of Antibiotic Resistance
Antibiotic resistance test was done by using the agar disk diffusion standard method with Mueller-Hinton agar. The plates were incubated at 37˚C for 24 hours in the incubator. The antibiotics tested included oxacillin (1 mg) (30 mg), cefoxitin (30 mg), amoxicillin (30 mg), Vancomycin (30 mg), ampicillin (10 mg), tetracycline (30 mg) and kanamycin (30 mg). Susceptibility categorization was carried out according to National Committee of Clinical Laboratory Standards (NCCLS) recommendations (Hindler, 2010).
Procedure
Appropriate drug discs were impregnated on the surface of the agar plate using sterile forceps or a needle tip. To ensure complete contact with the agar surface the forceps or needle tip was gently pressed down on each disc. The discs were distributed evenly so that they were no closer than 15 mm from the edge of the plate and no two discs were closer than 24 mm from center to center. The plates were then inverted and placed in a 35˚C - 37˚C incubator for 20 hours. After 20 to 24 hours of incubation each plate was examined, and the diameters of complete inhibition zones were measured using sliding calipers.
Interpretation
Sizes of zones of inhibition were then interpreted by referring to National Committee of Clinical Laboratory Standards (NCCLS) recommendations. A categorization of “s” susceptible implies that an infection due to the strain tested may be expected to respond to the recommended dosage of antibiotic for that type of infection and infecting species. Resistant strains “R” on the other hand are not completely inhibited by concentrations within the therapeutic range. The intermediate “I” is a category including strains which may respond to concentrations attainable by unusually high dosage or in areas. The intermediate category also comprises a “buffer zone,” which should prevent major interpretative discrepancies from small, uncontrolled technical factors.
2.10. Detection of Antibiotic Residues in Milk Samples
Detection of antibiotic residues in milk samples was done by using Delvotest kit (FAO 2014). Delvotest is a broad-spectrum microbial inhibition test used specifically to detect the presence of antibiotic residues in dairy products, especially milk, to enable producers to adhere to MRL as required by FAO. A kit for 100 samples is composed of 100 ampoules each containing Bacillus stearothermophilus var. calidolactis, nutrients for growth and bromocreso purple.
Briefly, 0.1 ml of a well-homogenized milk sample was added to each ampoule and covered by adhesive foil before being incubated for at least three hours. Color changes were examined/observed from the underneath of a slantly held ampoule and were interpreted as follows:
Yellow color indicated negative test/results, meaning that the milk does not contain any antibiotics, or the antibiotic concentration is below the detection sensitivity of the test.
Purple color indicated positive test/results, meaning that the milk sample contains antibiotics equal and above the detection limit.
3. Results
3.1. Questionnaire Survey
Results showed that all livestock keepers use drugs (antibiotics) to treat animals in case of sickness in both study areas (Kilosa and Morogoro Municipality). 27% of the livestock keepers in Kilosa required veterinary personnel to administer drugs, whereas 83% of the farmers in Morogoro Municipality relied on veterinary personnel in administering drugs. Assessment of farmers’ knowledge about withdrawal periods showed that only 14.8% of farmers in Kilosa were aware, compared to 89.8% in Morogoro. Milking practices during and after treatment varied markedly between the two areas. In Kilosa, 44% of respondents reported using the milk for household consumption, 38.9% fed it to calves, 2.8% sold it, 13% discarded it, and 1.9% refrained from milking altogether. In Morogoro, 43.3% of respondents fed the milk to calves, 1.9% sold it, and 63.9% discarded it. Importantly, none of the respondents in Morogoro Municipality reported consuming milk from animals undergoing or immediately after treatment. Availability of veterinary services was low in Kilosa compared to Morogoro Municipality; it was 17% and 77% for Kilosa and Morogoro, respectively, as indicated in Table 1.
Table 1. Questionnaire results from the study area.
Category |
Code |
Morogoro Municipality |
Kilosa |
Number of respondents |
Percent (%) |
Number of respondents |
Percent (%) |
Drugs administration |
Vet personnel |
90 |
83.3 |
29 |
26.9 |
Livestock keepers |
6 |
5.6 |
71 |
65.7 |
Animal attendants |
12 |
11.1 |
8 |
7.4 |
Knowledge about the withdrawal period |
Yes |
97 |
89.8 |
16 |
14.8 |
No |
11 |
10.2 |
96 |
85.2 |
Milk during and after treatment |
Do not milk |
0 |
0 |
1 |
1.9 |
Sell the milk |
2 |
1.9. |
3 |
2.8 |
Milk and discard |
69 |
63.9 |
14 |
13 |
Consume in family |
0 |
0 |
48 |
44.4 |
Used by calves |
37 |
43.3 |
42 |
38.9 |
Availability of veterinary services |
No |
25 |
23.1 |
90 |
83.3 |
Yes |
83 |
76.9 |
18 |
16.7 |
Education Level |
No school |
2 |
1.9 |
62 |
57.4 |
Primary education |
29 |
26.9 |
38 |
35.2 |
Secondary education |
49 |
45.4 |
6 |
5.6 |
High education |
28 |
25.9 |
2 |
1.9 |
3.2. Prevalence of Staphylococcus aureus
About 25% of all milk samples collected from Kilosa were contaminated by Staphylococcus aureus isolates, compared to only 13% of the milk samples collected in Morogoro (Table 2).
Antibiotic resistance profile of Staphylococcus aureus
Determination of the Antibiotic resistance profile was conducted as shown in Figure 1.
All Staphylococcus aureus isolated from both study areas were entirely resistant to ampicillin, amoxicillin and oxacillin. Furthermore, 82% of Staphylococcus aureus isolates from Kilosa were resistant to cefoxitin, 56% were resistant to vancomycin, and only 26% resistant to Kanamycin. Likewise, in Morogoro Municipality 86% of Staphylococcus aureus isolates were resistant to cefoxitin, followed by vancomycin (57.1%) and 21.4% were resistant to kanamycin (Table 3). Multi-drug resistance (MDR) isolates of Staphylococcus aureus were observed in milk from Kilosa whereby (75.2%) of Staphylococcus aureus were resistant to more than two antibiotics, where samples from Morogoro had (79.1%) which were resistant to more than two drugs as indicated in Table 4.
Figure 1. Inhibition zones of S. aureus around different antibiotic discs.
Table 2. S. aureus isolates from milk samples.
Morogoro Municipality |
Kilosa |
Location |
Number of samples |
Number of isolates (%) |
Location |
Number of samples |
Number of isolates (%) |
Kihonda |
13 |
1 (0.93) |
Dumila |
13 |
5 (4.6) |
Kihonda mag |
13 |
2 (1.85) |
Magubike |
14 |
2(1.85) |
Bigwa |
15 |
2 (1.85) |
Magole |
14 |
3 (2.77) |
Kilakala |
13 |
1 (0.93) |
Mabwerebwere |
14 |
2 (1.85) |
Kichangani |
13 |
3 (2.77) |
Kimamba A |
13 |
4 (3.7) |
Msamvu |
13 |
2 (1.85) |
Kimamba B |
14 |
2 (1.85) |
Mazimbu |
15 |
1 (0.93) |
Berega |
13 |
4 (3.7) |
Chamwino |
13 |
2 (1.85) |
Maguha |
13 |
5 (4.6) |
Total |
108 |
14 (13) |
|
108 |
27 (25) |
Table 3. Antibiotic resistance patterns of S. aureus isolates.
Drugs |
Isolates (%) |
Morogoro Municipality |
Kilosa |
K |
3 (21) |
7 (26) |
OX |
14 (100) |
27 (100) |
FOX |
12 (85.7) |
22 (81.5) |
AML |
14 (100) |
27 (100) |
VA |
8 (57) |
15 (55.5) |
AMP |
14 (100) |
27 (100) |
TET |
11 (78.5) |
18 (66.7) |
Key: K: Kanamycin, OX: Oxacillin, FOX: Cefoxitin, AML: Amoxicillin, VA: Vancomycin, AMP: Ampicillin, TET: Tetracycline.
Table 4. Multi-Drug resistance patterns of isolates.
Drugs |
Isolates (%) |
Morogoro Municipality |
Kilosa |
AMP/AML |
14 (100) |
27 (100) |
TET/AMP/AML |
11 (78.6) |
18 (66.7) |
K/AMP/AML |
9 (64) |
7 (26) |
FOX/AMP/AML |
13 (92.8) |
22 (81.5) |
TET/K/AMP/AML |
7 (50) |
4 (14.8) |
K/FOX/AMP/AML |
3 (21.4) |
7 (26) |
TET/OX/FOX/AMP/AML |
3 (21.4) |
19 (59) |
TET/VA/K/FOX/AMP/AML |
6 (42.8) |
4 (14.8) |
TET/VAK/FOX/AMP/AML |
1 (7.1) |
4 (14.8) |
Key: TET: K: Kanamycin, OX: Oxacillin, FOX: Cefoxitin, AML: Amoxicillin, VA: Vancomycin, AMP: Ampicillin, TET: Tetracycline.
3.3. Antibiotic Residues in Milk Samples
About 6% of milk samples from Kilosa contained antibiotic residues, whereas the figure was high up in samples from Morogoro Municipality, as 19% were positive for antibiotic residues, as indicated in Table 5 and Figure 2.
Figure 2. Positive and negative results for antibiotics.
Table 5. Milk samples containing antibiotic residues in each ward.
Morogoro Municipality |
Kilosa |
Location |
Number of sample |
Number (%) of samples with antibiotic residues |
Location |
Number (%) of sample |
Number (%) of samples with antibiotic residues |
Kihonda |
13 |
3 (2.77) |
Dumila |
13 |
1 (0.92) |
Kihonda mag |
13 |
1 (0.92) |
Magubike |
14 |
0 (0) |
Bigwa |
15 |
4 (3.7) |
Magole |
14 |
0 (0) |
Kilakala |
13 |
6 (5.6) |
Mabwerebwere |
14 |
2 (1.85) |
Kichangani |
13 |
0 (0) |
Kimamba A |
13 |
1 (0.92) |
Msamvu |
13 |
1 (0.92) |
Kimamba B |
14 |
0 (0) |
Mazimbu |
15 |
3 (2.77) |
Berega |
13 |
0 (0) |
Chamwino |
13 |
2 (1.85) |
Maguha |
13 |
2 (1.85) |
Total |
108 |
20 (18.5) |
|
108 |
(5.54) |
4. Discussion
The current study has revealed more disease control malpractices, such as the administration of veterinary drugs by unprofessional personnel, including animal attendants, in Kilosa than in Morogoro Municipality. The major reason behind the observed trend is that there are limited and/or expensive veterinary services in most rural areas [14]; this is further compounded by our second finding that livestock keepers in Kilosa had lower levels of formal education than those in Morogoro Municipality. Similar findings were reported by Karimuribo et al. (2020), who also associated disease control malpractices with the poor availability of veterinary services together with the uncontrolled selling of veterinary drugs in livestock markets by unscrupulous businessmen in rural areas. Similarly, the knowledge of the milk withdrawal period and failure to observe the period by livestock keepers in Kilosa is a direct effect of the lack of vet extension services in the area in comparison to the case in Morogoro. Municipality.
Milk collected from Kilosa showed higher percentage of S. aureus compared to that from Morogoro Municipality. The reasons for this disparity in prevalence of S. aureus between the two study areas may be accounted by the differences in milking practices including poor hygiene of the milkers, unhygienic milking equipments, storage containers/utensils, unsuitable storage condition, unclean udder and/or teats, poor quality of water used for cleaning udder [15]. Poor hygiene in rural areas is mainly caused by lack of veterinary services including health workers to educate livestock keepers on maintaining cleanliness [16]. Similar results have showed that 55% of milk samples collected from Hamdallaye village in Nigeria were contaminated with Staphylococcus aureus [17]. Various studies have been conducted in Tanzania including one done by (Mohammed, 2015), which recorded a prevalence of S. aureus in cow’s milk as high as 64%.
Occurrence and spread of bacteria with resistance to one or more antibiotics poses significant public health threat worldwide [18]. In respect to this study, Staphylococcus aureus isolates in both study areas were resistant to ampicillin, amoxicillin and oxacillin; other isolates had multi-drugs (MDR) [19]. High prevalence of antibiotic-resistant S. aureus in the study areas was probably due indiscriminate use of antibiotics by farmers. For instance, penicillin is predominantly used for treatment of mastitis this can lead to development of resistance involving other members of penicillin family such as oxacillin, dicloxacillin, ampicillin, amoxicillin, carbenicillin, ticarcillin, and piperacillin [20]. Indiscriminate use of antibiotics could be linked with lack of knowledge, limited extension services and uncontrolled selling of antibiotics in livestock markets. A study by [21] showed that ampicillin, amoxicillin, oxacillin and tetracycline were among the frequently used antibiotics by majority of farmers. Comparable results have been reported in various countries. A study to investigate antibiotic resistance of S. aureus in Northern Ethiopia, showed resistance of 82%, and 59% to clindamycin and ampicillin, respectively [22]. In Tanzania, a study conducted in Morogoro, showed high resistance of S. aureus to penicillin 72% which was found to be among the most used drug by livestock keepers [12].
Presence of antibiotic residues in food is a serious public health concern because of the harmful effects of these residues on consumer’s health. Antibiotic residues find their way into food chain due to their extensive use and failure in observing withdraw period of these drugs [23]. Results of this study showed that high number of milk samples collected from Morogoro Municipality contained antibiotic residues compared to milk samples from Kilosa. This finding was contrary to questionnaire results, which indicated that livestock keepers in Morogoro had more knowledge on milk withdraw periods suggesting that information gathered from questionnaires is not always a true reflection of the real situation.
5. Conclusion
This study demonstrated that disease control malpractices were more common in Kilosa than in Morogoro Municipality, largely due to limited veterinary services, high costs of professional care, and lower education levels among livestock keepers. Poor milking hygiene and lack of extension services in Kilosa contributed to a higher prevalence of Staphylococcus aureus in milk, while indiscriminate antibiotic use in both areas resulted in the emergence of resistant strains and multidrug resistance. Furthermore, the presence of antibiotic residues in milk, particularly in Morogoro, underscores the risk of drug misuse and the failure to observe withdrawal periods. These findings highlight the urgent need to improve disease control practices in Kilosa and Morogoro. To address the challenges, veterinary services should be strengthened by increasing the number of qualified professionals and making services affordable to livestock keepers. Farmer education and training are equally important to raise awareness on proper drug use, hygiene, and the risks of antibiotic residues. Extension services must be expanded to provide regular guidance, supervision, and monitoring of livestock health. In addition, stricter regulation of veterinary drug sales and use should be enforced to curb indiscriminate antibiotic use. Finally, public health campaigns are necessary to inform communities about the dangers of consuming contaminated milk, thereby promoting safer practices.
Acknowledgements
The authors would like to sincerely thank the Water Institute, Dar es Salaam, for providing logistical and technical support during this study. We are also grateful to the livestock keepers and veterinary personnel in Kilosa and Morogoro Municipalities for their cooperation and valuable information. Special thanks to our colleagues in the Department of Water Resources Management for their assistance and guidance throughout the research process.