Jean Pierre Mpatswenumugabo

A cross-sectional study on 156 smallholder dairy farms in Rwanda was carried out to assess the association between farm management practices and milk yield and quality. A pre-tested questionnaire was used to collect data on cow characteristics and farm management practices. Milk yield was recorded at household level, milk composition was monitored using a Lactoscan device (Milk Analyzer). Somatic cell count (SCC) was determined using a DeLaval cell counter (DCC). A Delvotest SP-NT kit was used to determine antibiotic residues in raw milk. Most dairy cows were kept in zero-grazing system (84.6%) and most farmers had less experience of dairy production (78.2%). Mean daily milk yield was 3.9 L/cow and was associated with type of breed, milking frequency, stage of lactation, and parity. Mean milk content of protein, fat, lactose and solid non-fat, and density were normal and showed no association with different management practices. Based on SCC analyses, 65.8% of the milk samples with less than 300,000 cells/mL were graded as acceptable for delivery to a milk collection centre (MCC) and 12.9% of the samples tested positive for antibiotic residues. These findings suggest low milk yields on smallholder farms in Rwanda that are attributable to type of breed and prevalent high level mastitis, among other factors. The results also indicate possible non-compliance with withdrawal periods, resulting in antibiotic residues in milk, which has public health implications for consumers. Routine testing at MCC for both SCC and antibiotic residues is important for quality control.

A cross-sectional study on 156 smallholder dairy farms in Rwanda was carried out to assess the association between farm management practices and milk yield and quality. A pre-tested questionnaire was used to collect data on cow characteristics and farm management practices. Milk yield was recorded at household level, milk composition was monitored using a Lactoscan device (Milk Analyzer). Somatic cell count (SCC) was determined using a DeLaval cell counter (DCC). A Delvotest SP-NT kit was used to determine antibiotic residues in raw milk. Most dairy cows were kept in zero-grazing system (84.6%) and most farmers had no experience of dairy production (78.2%). Mean daily milk yield was 3.9 L/cow and was associated with type of breed, milking frequency, stage of lactation and parity. Mean milk content of protein, fat, lactose and solid non-fat, and density were normal and showed no association with different management practices. Based on SCC analyses, 65.8% of the milk samples were graded as acceptable for delivery to a milk collection centre (MCC) and 12.9% of the samples tested positive for antibiotic residues. These findings suggest low milk yields on smallholder farms in Rwanda that are attributable to breed and mastitis, among other factors. The results also indicate possible non-compliance with withdrawal periods, resulting in antibiotic residues in milk, which has public health implications for consumers. Routine testing at MCC for both SCC and antibiotic residues is important for quality control.

Animal-source foods like milk are important for the growth and development of young children, especially in developing countries. However, Rwanda faces challenges related to low milk yield and quality, impacting both dairy production and public health. This thesis investigated the factors affecting milk production and quality on smallholder dairy farms in Rwanda’s Northern Province, aiming to improve food security, nutrition, and livelihoods of poor households. The field research involved collecting cow’s milk and children’s faecal samples from 156 households with lactating cows for laboratory analysis. The results showed that 12.9% of milk samples contained antibiotic residues, and 34.2% had somatic cell counts exceeding 300,000 cells/ml, a marker of poor milk quality. Salmonella spp. was found in 25.6% of milk samples, while E. coli strains were most prevalent in children's faecal samples. No identical pathogens were found in both milk and faecal samples from the same households. Factors influencing milk yield included feeding practices, cattle breeds, milking frequency, body condition, and parity. Interestingly, farm management practices did not significantly affect the presence of pathogens in milk samples, though household hygiene practices were associated with pathogens in children’s faecal samples. Anthropometric measurements of 601 children showed that 27% were stunted, with a higher prevalence among boys (33.8%) than girls (20.9%). Statistical analysis identified several factors contributing to stunting, including livestock ownership and household income. These findings emphasize the need for a multidisciplinary approach to improve milk production and quality. Such interventions could help address child malnutrition and enhance food security, nutrition, and livelihoods in Rwanda's rural areas.

Consumption of unsafe animal-source foods is the major cause of foodborne disease outbreaks in low-income countries. Despite current knowledge of the threat posed by raw milk consumption to human health, people in many countries in East Africa still consume unboiled milk. This literature review explored the association between milk consumption and the occurrence of five milk-borne bacterial zoonoses: brucellosis, salmonellosis, campylobacteriosis, Escherichia coli infections, and tuberculosis. A search for literature published up to October 1, 2021 was conducted through the Web of Science, PubMed, and Scopus databases, using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The selection process yielded 65 articles describing studies conducted in East Africa 2010–2021, which were carefully scrutinized. The most investigated pathogen was Brucella spp. (54.5%), followed by Escherichia coli (18.2%), Salmonella spp. (12.1%), Mycobacterium spp. (6.1%), and Escherichia coli O157: H7 (6.1%). The most common predisposing factors for potential milk-borne disease outbreaks were consumption of contaminated raw milk, inadequate cold storage along the milk value chain, poor milk handling practices, and lack of awareness of the health risks of consuming unpasteurized milk. Thus a tailor-made training program is needed for all milk value chain actors to enhance the safety of milk sold in informal markets, and a One Health approach should be applied. Future studies should employ more advanced diagnostic techniques and countries in East Africa should invest in modern diagnostic tools and equipment, both in hospitals and in local rural settings where most cases occur.

This study was conducted to assess raw milk bacterial loads and micro-organisms associated with milk handling practices and raw milk chain in the North-western region of Rwanda. A multistage sampling method was used to collect sixty-seven raw milk samples that were analyzed for milk quality at four stages of the raw milk chain: dairy farmers, milk hawkers, milk collection centres (MCC) and milk kiosks. Total bacterial counts (TBC) at different stages of the chain were determined and microorganisms were isolated. A questionnaire was distributed to gather information on factors and milk handling practices that influence milk quality at farm level. The study revealed a TBC mean values of 1.2 × 106 CFU/ml (dairy farmers), 2.6 × 107 CFU/ml (milk hawkers), 1.5 × 106 CFU/ml (MCC) and 6.9 × 106 CFU/ml (kiosks/restaurants). The prevalent micro-organisms were: Escherichia coli (E. coli), 26.9%; Salmonella spp., 16.4%; Streptococcus spp., 16.4%; coagulase- negative staphylococci (CNS), 14.9%. Bacterial load was highly associated with containers used for milk transport, cleaning time of milk containers and source of water used to clean containers. It is, therefore, highly recommended that all concerned parties in the raw milk value chain improve their milk handling and storage practices. Key words: Bacterial contamination, milk handling, milk quality, north-western Rwanda, raw milk.

Wildebeest associated malignant catarrhal fever (WA-MCF) is a fatal disease of cattle. Outbreaks are seasonal and associated with close interaction between cattle and calving wildebeest. In Kenya, WA-MCF has a dramatic effect on cattle-keepers who lose up to 10% of their cattle herds per year. The objective of this study was to report the impact of WA-MCF on a commercial ranch and assess the performance of clinical diagnosis compared to laboratory diagnosis as a disease management tool. A retrospective study of WA-MCF in cattle was conducted from 2014 to 2016 at Kapiti Plains Ranch Ltd., Kenya. During this period, 325 animals showed clinical signs of WA-MCF and of these, 123 were opportunistically sampled. In addition, 51 clinically healthy animals were sampled. Nested polymerase chain reaction (PCR) and indirect enzyme linked immunosorbent assay (ELISA) were used to confirm clinically diagnosed cases of WA-MCF. A latent class model (LCM) was used to evaluate the diagnostic parameters of clinical diagnosis and the tests in the absence of a gold standard. By PCR, 94% (95% C.I. 89–97%) of clinically affected animals were positive to WA-MCF while 63% (95% C.I. 54–71%) were positive by indirect ELISA. The LCM demonstrated the indirect ELISA had poor sensitivity 63.3% (95% PCI 54.4–71.7%) and specificity 62.6% (95% PCI 39.2–84.9%) while the nested PCR performed better with sensitivity 96.1% (95% PCI 90.7–99.7%) and specificity 92.9% (95% PCI 76.1–99.8%). The sensitivity and specificity of clinical diagnosis were 99.1% (95% PCI 96.8–100.0%) and 71.5% (95% PCI 48.0–97.2%) respectively. Clinical diagnosis was demonstrated to be an effective method to identify affected animals although animals may be incorrectly classified resulting in financial loss. The study revealed indirect ELISA as a poor test and nested PCR to be a more appropriate confirmatory test for diagnosing acute WA-MCF. However, the logistics of PCR make it unsuitable for field diagnosis of WA-MCF. The future of WA-MCF diagnosis should be aimed at development of penside techniques, which will allow for fast detection in the field.

A cross-sectional study was conducted from May 2016 to January 2017 in Rubavu and Nyabihu districts, Western Rwanda, aiming at estimating the prevalence of subclinical mastitis (SCM) and identifying its causative bacteria. Management practices and milking procedures were recorded through a questionnaire. 123 crossbreed milking cows from 13 dairy farms were randomly selected and screened for SCM using California Mastitis Test (CMT). Composite CMT positive milk samples were processed for bacterial isolation and identification. The overall SCM prevalence at cow level was 50.4%. 68 bacterial isolates were identified by morphological and biochemical characteristics. They included, Coagulase Negative Staphylococci (51.5%),Staphylococcus aureus(20.6%),Streptococcusspecies (10.3%),Bacillusspecies (10.3%),Streptococcus agalactiae(5.8%), andEscherichia coli(1.5%). About 67.1% of the farmers checked for mastitis; of these, 58.9% relied on clinical signs and only 6.8% screened with CMT. Only 5.5% and 2.7% of the farmers tried to control mastitis using dry cow therapy and teat dips, respectively. Thus, to reduce the prevalence of SCM, farmers in the study area need to be trained on good milking practices, including regular use of teat dips, application of dry cow therapy, and SCM screening. This will improve their sales and their financial status.

Four subclinical mastitis diagnostic tests (the UdderCheck® test [a lactate dehydrogenasebased test], the California Mastitis Test [CMT], the Draminski® test [a conductivity-based test] and the PortaSCC® test [a portable somatic cell count-based test]) were compared in a study comprising crossbreed dairy cows (n = 30) during September and October 2015. Sensitivity and specificity of the CMT, Draminski® and UdderCheck® tests were compared with the PortaSCC® as reference. The CMT, Draminski® and UdderCheck® test results were compared with the results of the PortaSCC® test using kappa statistics. Duplicate quarter milk samples (n = 120) were concurrently subjected to the four tests. Sensitivity and specificity were 88.46% and 86.17% (CMT), 78.5% and 81.4% (Draminski®) and 64.00% and 78.95% (UdderCheck®). The CMT showed substantial agreement (k = 0.66), the Draminski® test showed moderate agreement (k = 0.48) and the UdderCheck® test showed fair agreement (k = 0.37) with the PortaSCC® test and positive likelihood ratios were 6.40, 4.15 and 3.04, respectively. The cow-level subclinical mastitis prevalence was 70%, 60%, 60% and 56.7% for PortaSCC®, CMT, Draminski® and UdderCheck® tests, respectively. At udder quarter level, subclinical mastitis prevalence was 20%, 21.67% and 20.83% for PortaSCC®, CMT and UdderCheck®, respectively. A correlation (P 0.05) and moderate strength of association were found between the four tests used. The study showed that compared to the PortaSCC® test, the CMT was the most preferable option, followed by the Draminski® test, while the UdderCheck® test was the least preferable option for subclinical mastitis screening.