Introduction
Africa hosts about 87% of the world’s camel population (38 m), which is estimated at 32 million. About 60% of this population is found in the Horns of Africa. It has been estimated that the global camel population has been growing annually at about 3.4% for the last five decades [1]. Camels have adaptive features for harsh climatic conditions, which therefore make them a valued stable source of livelihood in arid lands [2]. The camel (Camelus dromedarius) is an important source of livelihood to the local populations in arid, semiarid, and desert areas where it provides milk, meat, hides, and transport [3]. Other benefits that are provided by the camel include racing, tourism, and hair products [3]. Kenyan camel milk production has significantly increased following the emergence of new camel keepers in arid and semi-arid lands (ASALs) [4].
The majority of the pastoral communities consume camel milk raw for traditional and cultural reasons as they believe that boiling the milk will result in spoilage and cause damage to vital elements though it may pose serious health risks to humans [5]. A recent study from three camel value chains showed that the Isiolo value chain accounted for 89% of milk brought to Nairobi City with an estimated daily supply of 3,000 L [6]. Despite the evident growth pattern, the subsector has largely remained informal, with minimal regulation and investments from relevant authorities. As a result, access to markets has been challenging, with only 12% of the total milk produced marketed: 10% sold to rural consumers and only 2% gets to urban markets. The remaining 88% is consumed in local households, with a significant proportion going to waste due to post harvest losses [7]. The pastoralists tend to favor camel milk over other types of milk from the other livestock species due to reasons such as being highly nutritious, and easily digestible among others [8].
There is no known unified common standard for camel milk in Africa, which increases the tendency to use the standard of the widely consumed cow milk. However, countries such as Kenya have developed their own standards [9]. Most of the camel milk produced is consumed locally (88%) and does not reach the urban markets. They are kept for subsistence use by pastoral communities within the area of production. It has been estimated that about 38% of this milk is consumed, whereas 50% gets spoiled due to the absence of appropriate preservation technologies or storage facilities [10].
National and global regulations have provided hygiene standards for raw milk from cows and other dairy animals [9]. Furthermore, the most commonly used methods for determining the hygiene of raw milk are the bacterial count and somatic cell count (SCC), which have been defined by the European Union (The Kenya Dairy Board, 2021). For example, the bacterial count and SCC in raw cow milk should not exceed 100,000 and 400,000/ml, respectively. The two measures reflect the levels of milk contamination and udder health, respectively.
Camel milk handling at the value chain that include, household, transportation, bulking, and retails sale can be an important source of microbial contamination, a potential risk to human health [5,6]. The source of microbial contamination is associated with unhygienic milking and handling, use of dirty water, poorly washed utensils, and unhygienic retail facilities [11]. When the milk hygiene standards are very low, this creates a potential hazard for consumers, as high microbial contamination in raw milk may be a source of pathogenic microorganisms that cause human and milk-borne diseases [12]. The latter would also result in milk spoilage before reaching the end consumer translating to economic loss. The occurrence of milk-borne diseases is significantly reported in communities consuming raw milk compared with those consuming boiled or pasteurized milk [13].
In Ethiopia, a study by [14] reported that 85.7% of raw camel milk samples demonstrated bacterial contamination with an overall mean TBC and coliform count (CC) estimated at 4.75 ± 0.17 and 4.03 ± 0.26 log Colony forming unit (CFU)/ml, respectively. The study further showed that the TBC increased from udder to market level while 38.9% of TBCs and 88.2% CCs in the contaminated raw camel milk samples were in the range considered unsafe for human utility [14]. Microbial analysis of raw camel milk in Morocco showed high contamination levels with total aerobic flora ranging from 5.6 × 103 to 1.8 × 109 CFU ml−1, total coliforms, and fecal coliforms with average counts of 1.82 × 107 and 3.25 × 106 CFU ml−1, respectively [15]. Another study carried out in Isiolo County [16] along the camel milk value chain, showed that microbial counts in milk increased significantly from log10 4.91 ± 1.04 CFU/ml at production to log10 7.52 ± 1.32 CFU/ml at the Nairobi market for TVCs and log10 3.68 ± 1.28 CFU/ml at production to log10 6.42 ± 1.13 CFU/ml at the Nairobi market for coliform counts. Another more recent study in Isiolo County on camel milk contamination with coliform bacteria and coliform counts showed a high level of contamination along the camel milk value chain [5]. The study further showed that the factors associated with milk contamination were gender and the practice of smoking [5]. Women handling milk was associated with high counts while smoking was associated with lower counts [5]. It was shown that women’s engagement in more household chores gave them less time to clean the milking equipment thoroughly while smoking milking containers tended to suppress bacterial growth.
Despite the growing significance of camel milk as a nutritional and economic resource in pastoralist communities, limited studies have explored the microbiological quality of camel milk along the entire value chain. Addressing this knowledge gap is critical, as the quality of camel milk can be significantly influenced by hygiene practices, container types, and storage conditions across the production and supply chain. This study provides valuable insights into potential contamination points and the roles of different stakeholders, thus contributing to enhanced milk safety practices. By identifying specific risk factors, this research offers practical recommendations to improve the safety of camel milk, which is vital for public health and the livelihoods of pastoral communities. This study was conducted to estimate the TVCs and CCs and their associated factors in raw camel milk from the pastoral camel keepers and the entire milk value chain in Isiolo County and Nairobi, Kenya.
Materials and Methods
Study period and area
The study was conducted in February 2024. Milk samples were mainly collected in Isiolo County and a few samples from traders in the retail end market of Nairobi County. In general, Isiolo County is a typical ASAL area located in the lower northeastern region of Kenya. The county covers an area of about 25,382 km2 with a total human population of 268,000 individuals [4]. The county has 10 assembly wards distributed in three sub-counties, namely, Isiolo township, Merti, and Garbatulla, while the administrative headquarters is in Isiolo town. Geographically, Isiolo County lies between 0° 21’ South and 37° 35’ East, and the altitude is between 170 and 1,100 m. The rainfall pattern is bimodal, unpredictable, and erratic in distribution. Long rains occur from late March to May, while short rains occur from November to December. The annual average rainfall range is between 350 and 600 mm while the mean range of annual temperature is between 24°C and 30°C. Livestock keeping is the major economic activity for the population of the people in the County and is a key source of livelihood. The main livestock species found in Isiolo County include camel, goats, sheep, cattle, donkeys, and poultry. The camel has recently gained popularity and the shift has been occasioned by the resilience of the camel, the increasingly frequent and severe droughts resulting in limited pasture and water resources, and new economic opportunities especially increased demand for camel meat and milk. The estimated camel population in Isiolo County is about 148,000 [4].
Study design and data collection
This was a cross-sectional study where camel milk samples were collected at critical points along the value chain using purposive and convenience sampling. Four critical points that included the producers, transporters, two bulkers, and traders (in Isiolo town and in Nairobi) were identified and milk samples were then collected. Farmers who had lactating camels and were selling milk were eligible for selection. The details of the eligible farmers were provided by the County Veterinary extension workers. Due to logistical reasons and the sparse population in the arid area, farmers who were located along the main highway were conveniently selected for the study. All the transporters in each region were selected as they were few. The only two bulkers in Isiolo Town were also selected. Urban sampling was mainly done in Isiolo town and Nairobi City, all the retail traders who were located along only camel milk centers and were willing to participate were selected. All the other sampling points including within the pastoral communities bomas and transporters were considered rural.
In addition to collecting milk samples, data related to factors that predispose camel milk to microbial contamination along the market chain were collected. This was achieved by administering a closed ended questionnaire to the respondents at each of the four identified critical points. These data included milking procedures, types of milk containers used for storing and carrying milk, the method of cleaning milk containers, source of water for cleaning water containers, and methods of milk preservation, among others.
The study employed purposive sampling to target camel milk handlers within the study area, ensuring the inclusion of participants relevant to the research objectives. A sample size range of 100–200 samples was set as a practical goal to gather sufficient data distributed across the entire camel milk value chain for analysis, without formal sample size calculation. This approach is consistent with methodologies used in public health studies targeting specific subpopulations, where purposive sampling ensures the representation of hard-to-reach groups [17].
Milk sampling
Eight camel herds from different wards of Isiolo County were purposively selected and used for sample collection. The number selected was based on logistical reasons such as the ability to reach the households between 5.00 and 8.00 am before the milk was collected. Due to the long distances between households, that was the most logical number that could be reached within the data collection period given the available budget as the milk was being transported to the laboratory the same day before fresh samples were collected the following day. The milk collection was done using sterile syringes and transferred to sterile containers to ensure the aseptic procedure. Milk was sampled between 5:00 and 8:00 am from milking containers (10 ml each) at the household level, and from all the pooled containers available and used to carry milk by the transporters from the herd to the bulkers in Isiolo town. The milk was finally collected from the two main camel milk bulkers in Isiolo town. Specifically, samples were collected from the pooling tank, the residual tank, and the tap from the pooling and residual tanks. For the traders in Isiolo town, milk was collected from retailers who received milk directly from the producers and sold to the consumers by the roadside. The final collection point was from retailers in Eastleigh Street market, Nairobi County, who received milk directly from the bulkers in Isiolo town and sold the same to the final consumers in Nairobi City. At each sampling point, 20 ml of milk sample was collected using sterilized milk containers, labeled, and immediately kept in cool boxes packed with frozen icepacks at about 5°C–10°C, where it awaited transportation to the laboratory for microbiological analysis within 30 minutes to 2 hours.
Microbiological analysis
Milk samples were assessed for total viable microbial counts and coliform counts (CCs) according to the Kenya Standard (KS2061:2016). For enumeration, the appropriate dilutions. Dilutions were selected to ensure that the total number of colonies on a plate fell between 30 and 300 CFU for TVC and between 15 and 150 CFU for CC [12].
Total viable microbial counts
The camel milk sample was serially diluted by adding 1 into 9 ml of phosphate-buffered saline, pH 6.9 until a solution expected to give a plate count of 30–300 CFU was obtained. One milliliter of the sample from a chosen dilution was then placed on the Petri dish and 10–15 ml of molten plate count agar, and added aseptically, this was evenly mixed by slowly rotating the plate on a flat surface, which was further allowed to solidify for 15 minutes. Thereafter, the plate was incubated for 48 hours at 32°C after which colonies were enumerated using a colony counter. TVC was then computed by multiplying the count on the plate by 10n, in which n stands for the number of consecutive dilutions of the original sample [18].
Coliform counts
About 1 ml of milk sample serially diluted from a master dilution of 1:10 was transferred into sterile well-labeled culture plates. Next, 15 ml of molten violet red bile agar (VRBA) at a temperature of 50°C was added to the milk sample, mixed evenly, and allowed to solidify for 5–10 minutes. The mixture was then overlaid with plating agar to inhibit surface colony formation and then incubated at 37°C for 24 hours. Bacterial colonies were then enumerated using a colony counter [18].
Data management and analysis
Data from the questionnaires and laboratory results were entered into Microsoft Excel 2010, from where they were imported into Stata 18.0 software (Stata Corp. LLC, USA) after verifying and cleaning for any entry errors. A descriptive analysis was first carried out on the data, including the computing for proportions for categorical variables and the mean, median, SD, and range for the continuous variables.
Both linear and logistic regressions were used to help identify the risk factors and the strength of the associations between milk TVC and CC and the predictor factors. The models also explored the potential interaction factors and confounders. A multilevel mixed-effects logistic regression (for the dichotomized total CC; cut off of 100,000 CFU/ml) and multilevel mixed-effects linear regression (for the natural logarithm of TVC) analyses were performed to identify risk factors associated with microbial contamination of milk. In the first step, univariable regression analysis for the predictor variables was fitted into separate models to determine their unconditional associations with the natural logarithm of TVC and CC. In the second step, multivariable logistic and linear regression analyses were fitted for the univariable associations with p ≤ 0.3. Earlier, correlations between predictor variables were evaluated using pair-wise correlation. The final models for both natural logarithms of total viable bacterial and CC were fitted manually through backward stepwise removal of variables with the least statistical significance while retaining variables with p ≤ 0.05. Plausible biological interactions between significant explanatory variables in the final model were also tested [19]. Finally, the area under the receiver operating characteristic curve and PRESS statistics were used to evaluate the overall performance of the models.
Results
The study involved a total of 181 sampling units including pastoral households/producers, transporters, traders, and two bulking plants giving a total of 191 samples. The sampling was done across these levels of a supply chain, in Isiolo County and Eastleigh, Nairobi County. These results present a summary of the microbiological TVC and CCs testing which is crucial for assessing the hygiene and safety of camel milk, ensuring it meets quality standards and is free from harmful microbial contamination. Out of 191 samples, 42.93% were from producers, 24.08% were from traders, 19.9% were from bulkers, and 13.09% were from transporters (Table 1).
Respondents demographics
From both Isiolo County and Eastleigh market of Nairobi County, the mean age of the 165 respondents who agreed to provide their age was 41.7 years, with an age range from 14 to 85 years.
Out of the 191 milk samples collected in this study, 53.9% were from female respondents while 39.8% were from male respondents. The remaining 6.3% of the samples were sourced from bulking plants. About the level of education, 179 respondents, 64.8% had no formal education, 22.9% had primary education, 9.5% had secondary education, while the remaining 2.8% had tertiary education. With regards to hygiene awareness, 35.8% of the 179 respondents had received training on milk hygiene, while 64.2% had never received any training (Table 1).
Table 1.
Characteristic of respondents from camel milk value chain in Isiolo and Nairobi Counties, March 2024.
| Category | Respondents sub-category | Number | Percentage |
| Gender of respondents (n=179) | |||
| Female | 103 | 57.4% | |
| Male | 76 | 42.4% | |
| Education level (n=179) | |||
| None | 116 | 64.8% | |
| Primary | 41 | 22.9% | |
| Secondary | 17 | 9.5% | |
| Tertiary | 5 | 2.8% | |
| Milk value chain level (n=191) | |||
| Bulker | 38 | 19.9% | |
| Producer | 82 | 42.93% | |
| Trader | 46 | 24.08% | |
| Transporter | 25 | 13.09% | |
| Milk hygiene training (n=179) | |||
| Trained | 64 | 35.8% | |
| Never trained | 115 | 64.2% |
Practices and milk handling material
With regards to hygiene for the 191 samples in this study, there was a fair reported adherence to hygiene practices recommended for milk handling. The majority of respondents, (92.15%), were observed to be appearing clean, 85.86% were operating in an environment that looked clean. Many respondents (87.96%) practiced smoking of the milk containers as a form of cleaning/disinfection, and 62.83% used conventional disinfectants like soap for cleaning the milk containers. The use of hot water to clean milk containers was practiced by few respondents (46.60%) with the rest using cold or warm water. The estimated temperature range description by farmers is 35°C–45°C for warm and 50°C–70°C for hot [20]. The majority of the respondents (38.22%) used tap water, while the others used underground water (well/borehole) or water from dams to clean milk handling containers. This distribution highlights a diverse means of access to water sourcing in camel milk production (Table 2).
Out of the 191 containers from which samples were obtained, the majority (79.58%) were plastic, 12.57% were either calabash or made of wood, and 7.85% were made from stainless steel. Excluding the bulking plant sampled containers, the other 179 container sizes ranged from 0.5 to 200 L, with an average size of 14.23 L. Twelve milk samples were collected from the big bulking plants which used stainless steel containers with sizes ranging from 300 to 3,500 L. The mean container size in these bulking plants was 1,100 L, indicating the fairly larger-scale nature of milk storage capacity at this level (Table 3).
Microbiological counts from milk samples
VRBA and TVCs results
According to Kenya Standard on raw whole camel milk specification (KS 2016:2017), the results from the coliform counts (CCs) on VRBA, showed that 102 (53.69%) were between zero and 1,000 CFU/ml, thus graded as I, 45 (23.69%) grade II, with counts >1,000–50,000 CFU/ml while those in grade III were 43 (22.63%) with counts >50,000–100,000 CFU/ml. About 46.60% of the milk samples had a colony count of over 1,000, (the indication of significant bacterial contamination), while 29.84% showed no bacterial growth. The coliform counts binary classification for the purpose of logistic regression modeling was done at 500 CFU/ml with those having a result equal, or greater than this threshold considered to be of poor quality.
The TVC results based on the Kenya Standard on raw whole camel milk specification (KS 2016:2017) revealed the following distribution: 47.12% of the samples fell within grade I with counts between 0 and 200,000 CFU/ml; 29.84% were categorized as graded as II, with counts ranging from 200,000 to 1,000,000 CFU/ml; and 23.03% classified as grade III with counts between 1,000,000 and 2,000,000 CFU/ml. For the TVC, a substantial portion of the samples (34.55%) had colony counts between 10³ and 10⁵, suggesting moderate contamination. However, 23.04% of the samples had counts exceeding 10⁶, an indication of severe contamination. The TVC results binary classification for the purpose of logistic regression modeling was done at 10⁵ CFU/ml with those having a result equal, or greater than this threshold considered to be of poor quality (Table 4).
Table 2.
Hygiene practices and water source by producers/bulkers/traders in Isiolo and Nairobi Counties, March 2024.
| Category | Number (n=191) | Percentage |
| Hygiene practices | ||
| Smoking milk containers | 168 | 87.96% |
| Use of disinfectant for containers | 120 | 62.83% |
| Clean environment during sampling | 164 | 85.86% |
| Clean respondent during sampling | 176 | 92.15% |
| Use warm water for cleaning containers | 89 | 46.60% |
| Use hot water for cleaning containers | 72 | 37.70% |
| Water source | ||
| Underground water (borehole) | 66 | 34.55% |
| From dams | 52 | 27.23% |
| Tap (piped water) | 73 | 38.22% |
Table 3.
Container material and size from camel milk value chain in Isiolo County, March 2024.
| Category | Sub-category | Number | Percentage |
| Container materials sampled from (n=191) | Calabash and wooden | 24 | 12.57% |
| Plastic | 152 | 79.58% | |
| Stainless steel | 15 | 7.85% | |
| Size of containers sampled (n=191) | Non plant sampling (179) | ||
| Container size range (liters) | 0.5–200 | ||
| Mean container size (liters) | 14.23 | ||
| Big bulking plant sampling (12) | |||
| Container size range (liters) | 300–3,500 | ||
| Mean container size (liters) | 1,100 |
Comparing colony counts and TVCs
The results from the CC (VRBA) showed that 29.84% of the samples had no bacterial growth whereas from the TVC, the lowest category (below 10³) only represented 12.57% of the samples. For low CC contamination levels (VRBA between 1 and 100), only 4.19% of samples fell into this category. In comparison, 12.57% of TVC samples had counts below 1,000, which suggests a higher proportion of TVC results had very low bacterial counts compared to VRBA (Table 4).
There was moderate VRBA (100–500) contamination of 9.95% for the milk samples, whereas 34.55% of TVC samples had counts between 10³ and 10⁵. The results showed that while a small proportion of samples had moderate VRBA counts, a larger proportion had moderate TVC counts. High contamination levels (VRBA between 500 and 1,000) accounted for 9.42% of the samples, whereas TVC showed that 29.84% of samples with counts between 10⁵ and 10⁶, and 23.04% had counts over 10⁶. The VRBA cultures reported a smaller proportion of high coliform contamination, while severe contamination in VRBA (over 1,000) was found in 46.60% of samples, a significantly higher proportion compared to the 23.04% of TVC samples with counts over 10⁶ (Table 4).
Statistically comparing the two camel milk quality tests used in the study, using the Spearman’s rank correlation for the categories in Tables 4 and 5 there was a high correlation. There was a coefficient of 0.6465 between the categories of VRBA and TVC indicate a strong positive association between the two indicators of contamination. This significant correlation, with a p-value of <0.001, suggests that as the levels of VRBA contamination categories increase, the TVC contamination categories also tend to increase.
Factors associated with microbiological culture quality
Univariable logistic regression association for TVC (100,000 CFU) and VRBA (1,000 CFU)
The univariable logistic regression analysis identified several significant factors associated with camel milk contamination threshold of 100,000 CFU/ml for grade I milk, at a p-value ≤ 0.1. Female respondents had a significantly higher likelihood of being associated with contaminated milk compared to male respondents (OR=4.79, p < 0.001). In urban areas of Isiolo town and Eastleigh, the odds of milk contamination were much higher (OR=13.62, p < 0.001) than in rural settings. The use of disinfectants or soap in cleaning camel milk containers was significantly associated with increased milk contamination (OR=4.57, p < 0.001). The respondents who looked cleaner had a lower likelihood of being associated with milk contamination (0.35, p < 0.001) while older respondents and having larger milk container sizes were also associated with slightly higher contamination odds (OR=1.03, p=0.024; OR=1.02, p=0.074, respectively).
For categorical factors, warm and hot water was associated with reduced likelihood of contamination compared to cold (OR=0.197, p=0.001; OR=0.360, p=0.38). The respondents who reported the use of tap and dam water had an increased contamination risk compared to borehole water (OR=15.69, p=0.0001; OR=2.49, p=0.025). The use of plastic containers was associated with less likelihood of contamination compared to the use of wooden or calabash containers (OR 0.307, p=0.014) with the use of stainless steel being not statistically different from the use of wooden and calabash. Looking at the camel milk chain, the contamination likelihood was notably higher at the bulkers and traders compared to producers and traders (OR=9.53, p=0.0001; OR=7.75, p < 0.001).
Table 4.
Microbiological results from camel milk value chain in Isiolo County, March 2024.
| Test type | Count category | Number | Percentage | Binary |
| VRBA | No growth | 57 | 29.84% | Good quality (0) |
| Between 1 and 100 | 8 | 4.19% | ||
| Between 100 and 500 | 19 | 9.95% | ||
| Between 500 and 1,000 | 18 | 9.42% | Poor quality (1) | |
| Over 1,000 | 88 | 46.31% | ||
| TVC | Below 10³ | 24 | 12.57% | Good quality (0) |
| Between 10³ and 10⁵ | 66 | 34.55% | ||
| Between 10⁵ and 10⁶ | 57 | 29.84% | Poor quality (1) | |
| Over 10⁶ | 44 | 23.04% |
Further results on the VRBA univariable logistic regression association, female respondents were also much more likely to be associated with contaminated milk compared to males (OR=3.9, p < 0.001). Samples from urban areas, specifically Isiolo town and Eastleigh, showed a higher odds of contamination compared to samples from rural areas (OR=8.16, p < 0.001). The use of disinfectants for cleaning containers was associated with a higher risk of contamination (OR=3.6, p < 0.001). Having larger milk container sizes were also associated with slightly higher contamination likelihoods (OR=1.02, p=0.077). The source of water was also critical; tap water was significantly associated to increased likelihood of contamination compared to borehole water (OR=11.24, p < 0.001), while dam water showed a moderate increase in risk (OR=3.64, p=0.001). The material of the milk container showed to be associated with milk microbiological quality. Plastic containers showed significantly lower odds of contamination compared to wooden or calabash containers (OR=0.18, p=0.003) with stainless steel being not statistically different from wooden and calabash milk containers. Within the milk supply chain, bulkers (OR=23, p < 0.001) and traders (OR=2.92, p=0.006) are associated with much higher odds of contamination compared to producers.
Multivariable VRBA logistic model
In the multivariable logistic regression analysis of factors associated with contamination in camel milk samples at a 500 CFU level on VRBA culture testing at p-value ≤ 0.05, four risk factors were identified. The multivariable model includes 165 observations excluding the 12 samples from two big bulking plants in Isiolo town and all the respondents who did not provide their age. The age of respondents was inversely related to contamination risk, with each additional year decreasing the odds of contamination by approximately 4% (OR=0.96, p=0.026). Gender showed a strong effect, with females being nearly three times more likely to be associated with higher contamination levels than males (OR=2.95, p=0.010). The use of plastic containers was associated with a markedly reduced likelihood of contamination, suggesting a protective effect (OR=0.0615, p < 0.001). Similarly, respondents in the lower levels of the camel milk chain (Producers and Transporters) were associated with a lower likelihood of contamination (OR=0.08, p < 0.001) (Table 5).
Multivariable TVC logistic model
Table 6 summarizes the findings from a multivariable logistic regression analysis of factors associated with contamination in camel milk samples at a 100,000 CFU level on TVC culture testing at p-value ≤ 0.05. The multivariable model includes 179 observations excluding the 12 samples from 2 big bulking plants in Isiolo town. The analysis revealed that the use of plastic containers by the respondents was associated with a lower likelihood of contamination compared to the use of wooden or calabash and stainless-steel containers (OR=0.12, p-value < 0.001). Being in the two lower levels of camel milk chain (producers and transporters) were associated with a lower risk of contamination compared to traders and bulkers (OR=0.08, p-value < 0.001). On the other hand, the use of cold water to clean milk containers by the respondents was associated with more contamination than those who used warm hot water (odds ratio=4.50, p-value=0.012). The use of disinfectants or soap by the respondents to clean camel milk containers was unusually associated with higher odds of contamination (odds ratio=2.69, p-value=0.022) (Table 6).
Table 5.
Multivariable logistic regression analysis of factors associated with camel milk contamination at a 500 CFU level on VRBA cultures in Isiolo and Nairobi, March 2024.
| Variable | Odds ratio | 95% CI | p-value |
| Age of respondent | 0.96 | 0.93–0.99 | 0.026 |
| Gender of respondent (female) | 2.95 | 1.29–6.75 | 0.010 |
| Plastic containers use | 0.06 | 0.02–0.22 | <0.001 |
| Produce and transporter | 0.08 | 0.03–0.21 | <0.001 |
| Model constant | 2,480.21 | 98.09–62,710.4 | <0.001 |
Discussion
Respondent demographics, hygiene practices, and camel milk hygiene outcome
The mean age of 41 years from the respondents involved in the camel milk value chain in this study was lower than 54 years cited by [21] and 51.4 years [22]. The majority of the respondents lacked formal education and had no prior training in milk hygiene, which may have contributed to the higher contamination rates observed and this agrees with what was observed in Sudan by [22]. Female respondents were particularly associated with increased contamination, which could reflect socio-cultural roles in milk handling and their access to resources for proper hygiene. The findings appear to highlight the importance of formal training on milk hygiene, with only a third of the respondents having received such instruction. The use of container smoking as a traditional method for sterilizing containers was prevalent as evidenced by the black coloration of the milk collected, yet it appears insufficient in controlling bacterial contamination. Moreover, the inconsistent use of disinfectants and variations in water sources between rural and urban areas could further contribute to the overall differences in contamination. Addressing these demographic disparities through tailored educational programs may help improve hygiene practices and reduce contamination risks. The increased bacterial counts and contamination would be associated with higher milk spoilage resulting in financial and economic losses due to milk rejection and increased risk of human infections and higher costs of household healthcare.
Microbiological quality across milk chain levels
The results of this study underscore the varying levels of microbiological contamination across different points in the camel milk supply chain. Producers, transporters, bulkers, and traders exhibited notable differences in contamination levels, suggesting that each stage presents unique challenges in maintaining milk hygiene. It is crucial to consider that the high contamination levels observed, especially in samples from traders and bulkers, may be influenced by factors such as improper handling or lack of hygiene training, as well as time lapsed without proper cold chain since production. These findings emphasize the need for enhanced hygiene practices throughout the milk production and handling process to ensure better quality and safety of camel milk. The CC (VRBA) plates without growth indicated that nearly a third of the samples had no detectable coliforms, whereas a lower percentage of TVC plates had similarly low bacterial counts, which is expected with the two methods. Overall, TVC identified a higher percentage of samples with high and heavy total bacterial count contamination, since the TVC method detects the total viable microbial contamination in the sample, as opposed to the coliform counts. The latter also suggested that urban environments may present unique challenges in maintaining milk quality. This counterintuitive finding suggests that while disinfectants are typically used to improve hygiene, in this context, their use may be linked with improper cleaning practices, such as inadequate rinsing or use of lower than recommended dilutions leading to contamination. The observation further suggests that while both tap and dam water are associated with higher contamination risks, tap water presents a significantly greater concern [11].
Association between TVC and VRBA
A strong positive correlation was observed between the TVC and VRBA results, indicating that bacterial contamination measured by both methods often aligns. The fact that nearly half of the samples exceeded the 1,000 colony threshold for VRBA highlights the severity of bacterial contamination in a significant portion of the milk supply as observed in some past studies [5,6], This finding reinforces the need for regular monitoring using both TVC and VRBA as complementary measures to accurately assess milk quality.
Table 6.
Multivariable logistic regression analysis of factors associated with camel milk contamination at a 100,000 CFU level on TVC cultures in Isiolo and Nairobi, March 2024.
| Variable | Odds ratio | 95% CI | p-value |
| Use of plastic containers | 0.12 | 0.04–0.36 | <0.001 |
| Being a producer or a Transporter | 0.08 | 0.04–0.20 | <0.001 |
| Use cold water for cleaning containers | 4.50 | 1.40–14.46 | 0.012 |
| Disinfectants or soap to clean containers | 2.69 | 1.16–6.27 | 0.022 |
| Constant | 81.05 | 7.16–916.81 | <0.001 |
Factors associated with increased contamination risk
Logistic regression analysis identified several key factors that significantly influence contamination risks in camel milk. Gender, value chain level, and the use of specific hygiene practices such as disinfectants were among the significant contributors to contamination levels. Female respondents and urban settings were associated with higher contamination, likely due to contextual factors such as resource constraints or the more complex handling processes in urban areas as reported in past studies [10,12,22]. Conversely, the use of plastic containers and cleaning with warm or hot water showed a protective effect, suggesting that these practices should be encouraged to mitigate contamination risks.
Urban areas pose unique challenges for camel milk safety due to environmental pollutants, extended transportation times, and suboptimal hygiene practices. Poorly cleaned containers, shared facilities, and lack of refrigeration during transit increase microbial loads. Additionally, inconsistent hygiene protocols in urban settings have been linked to higher contamination risks. Targeted interventions, such as improved transportation logistics and stricter hygiene standards, are critical for mitigating these risks [23,24].
The unusual significant association in the final model showing more contamination when the participants practice the use of soap and disinfectants for washing milk containers could be explained in two ways. First, it seems to be partly due to the increased use of disinfectants, including soap or detergents, at higher levels of the camel milk chain, such as by traders and bulkers, compared to producers and transporters who often rely on traditional methods like smoking containers. Second, those who practice more rigorous washing may have experienced significant losses from contamination in the past, prompting them to adopt better cleaning practices, even though these practices might not fully eliminate contamination risks due to multiple determinants of contaminations like quality of cold chain and time. Both factors highlight the complex dynamics of hygiene practices and contamination along the camel milk value chain.
Conclusion
The average age of the persons involved in the camel milk value chain was lower than the average reported elsewhere and these persons had a lower level of education. The level of milk contamination at the different levels of the milk value chain was different and the contamination level increased higher in the value chain. The level of milk contamination was agreeably high as detected by both the TVC and VRBA methods. The results further showed that women milk handlers, urban areas, and improper use of disinfectants were associated with higher bacterial contamination in milk. However, the use of plastic containers and the use of hot water to clean the milk containers had a protective effect and was associated with lower bacterial contamination.
Recommendation
There should be sustained efforts to re-train the farmers and other milk handlers along the camel milk chain on the importance of proper personal hygiene and also at the equipment levels. A regular surveillance programme should be put in place to continuously monitor milk contamination levels to enable strategic intervention at the highest points of contamination.
Study Limitations
The study’s reliance on purposive and convenience sampling may introduce bias, as it did not capture all potential contamination points along the camel milk value chain. Logistical constraints limited the sample size, and the study’s single-time point design may not account for seasonal variations in contamination. There could also be recall bias from the use of self-reported questionnaires to collect data. Additionally, the study’s findings may not be fully generalizable to other regions or other livestock species due to the uniqueness of camel milk chain management.
List of abbreviations
ASAL, Arid and semi-arid lands; CC, Coliform counts; CFU, Colony forming unit; OR, Odds ratio; SCC, Somatic cell counts; TBC, total bacterial counts; TVC, Total viable counts; VRBA, violet red bile agar.
Acknowledgment
The authors thank the camel producers, transporters, bulkers, and retailers for participating in the study and providing the milk samples and data required.
Conflict of interests
The authors declare no competing interests regarding the publication of this paper.
Funding
The study was funded by Biovision Foundation, Stiftung für ökologische Entwicklung Heinrichstrasse 147, CH-8005 Zurich, Sweden.
Ethical approval
The study was approved by Biosafety, Animal Use and Ethical Committee, Faculty of Veterinary Medicine, University of Nairobi (Approval no. FVMBAUEC/2021/295).
