Urban Livestock Keeping in the City of Nairobi: Diversity of Production Systems, Supply Chains, and Their Disease Management and Risks

Urban livestock keeping in developing cities have an important role in food security and livelihoods but can also pose a significant threat to the environment and health of urban dwellers. The aim of this study was to identify the different livestock systems in Nairobi, their supply chains, and their management and food safety risks. Seven focus group discussions with livestock production officers in charge of each major Nairobi sub-county were conducted. Data were collected on the type of systems existing for each livestock species and their supply chains, disease management, food safety risks, and general husbandry and gender factors. Supply chain flow diagrams and thematic analysis of the data was done. Results of the study show a large variability of livestock keeping in Nairobi. The majority were small scale with: <5 dairy cows, 1-6 dairy goats, <10 small ruminants, <20 pigs, 200-500 broilers, 300-500 layers, <10 indigenous chickens, or <20 rabbits. Beef keeping was mainly described as a "by the way" system or done by traders to fatten animals for 3 month. Supply chain analysis indicated that most dairy farmers sold milk directly to consumers due to "lack of trust" of these in traders. Broiler and pig farmers sold mainly to traders but are dependent on few large dominating companies for their replacement or distribution of products. Selling directly to retailers or consumers (including own consumption), with backyard slaughtering, were important chains for small-scale pig, sheep and goat, and indigenous chicken keepers. Important disease risk practices identified were associated with consumption of dead and sick animals, with underground network of brokers operating for ruminant products. Qualified trained health managers were used mainly by dairy farmers, and large commercial poultry and pig farmers, while use of unqualified health managers or no treatment were common in small-scale farming. Control of urban livestock keepers was reported difficult due to their "feeling of being outlaws," "lack of trust" in government, "inaccessibility" in informal settlements, "lack of government funding," or "understaffing." Findings are useful for designing policies to help to control urban livestock production and minimize its associated health and environment risks

Establishing a One Health office in Kenya

A One Health (OH) approach that integrates human,animal and environmental approaches to management of zoonotic diseases has gained momentum in the last decadeas part of a strategy to prevent and control emerging infectious diseases. However, there are few examples of howan OH approach can be established in a country. Kenya establishment of an OH office, referred to asthe Zoonotic Disease Unit (ZDU) in 2011. The ZDU bridges theanimal and human health sectors with a senior epidemiologist deployed from each ministry; and agoal of maintaining collaboration at the animal and human health interface towards better prevention and control of zoonoses.The country is adding an ecologist to the ZDU to ensure that environmental risks are adequately addressed in emerging disease control

Investigation of the governance structure of Nairobi dairy value chain and its influence on food safety

The dairy value chain of Nairobi is comprised, in its majority, of small-scale independent enterprises that operate within a complex interlinked system. In this complexity, the coordination and power structures of the system may have major influences on the management of dairy food safety. Therefore, the aim of this study was to investigate the governance and challenges issues faced by stakeholders throughout the Nairobi dairy value chain and assess their potential implications on food safety. Qualitative data was collected through focus group discussions and key informant interviews based on a dairy value chain mapping framework previously developed. Thematic analysis enabled identification of governance themes, key challenges and their implication on food safety. Themes were organized depending on their association with farmers (informal settlement or peri-urban), dairy cooperatives, dairy traders, processing companies, retailers or government officers. The identified governance themes included: i) weak linkage between government and farmers, ii) inadequate compliance with government regulations by traders and retailers, iii) emphasis on business licenses and permits for revenue rather than for food safety, iv) multiple licensing resulting in high business cost and lack of compliance, v) fragmented regulation, vi) unfair competition and vii) sanctions that do not always result in compliance. The key challenges identified included, amongst others: i) inadequate farmer support, ii) harassment of traders and retailers and iii) high business costs by traders, retailers, dairy cooperatives and large processors. The implication of governance and challenges of food safety were, amongst others: i) inadequate extension services, ii) insufficient cold chain, iii) delivery of adulterated and low milk quality to bulking centres, iv) inadequate food safety training and v) lack of policies for management of waste milk. The range of issues highlighted are based on stakeholders’ perceptions and reflects the complexity of the relationships between them. Many of the governance themes demonstrate the linkages that are both beneficial or confrontational between the formal and informal sectors, and between industry and regulatory authorities, with possible direct food safety consequences. Findings obtained provide indications to decision-makers of potential governance areas that could help improve efficiency and food safety along the dairy value chain

Mapping potential amplification and transmission hotspots for MERS-CoV, Kenya

Dromedary camels have been implicated consistently as the source of Middle East respiratory syndrome coronavirus (MERS-CoV) human infections and attention to prevent and control it has focused on camels. To understanding the epidemiological role of camels in the transmission of MERS-CoV, we utilized an iterative empirical process in Geographic Information System (GIS) to identify and qualify potential hotspots for maintenance and circulation of MERS-CoV, and produced risk-based surveillance sites in Kenya. Data on camel population and distribution were used to develop camel density map, while camel farming system was defined using multi-factorial criteria including the agro-ecological zones (AEZs), production and marketing practices. Primary and secondary MERS-CoV seroprevalence data from specific sites were analyzed, and location-based prevalence matching with camel densities was conducted. High-risk convergence points (migration zones, trade routes, camel markets, slaughter slabs) were profiled and frequent cross-border camel movement mapped. Results showed that high camel-dense areas and interaction (markets and migration zones) were potential hotspot for transmission and spread. Cross-border contacts occurred with in-migrated herds at hotspot locations. AEZ differential did not influence risk distribution and plausible risk factors for spatial MERS-CoV hotspots were camel densities, previous cases of MERS-CoV, high seroprevalence and points of camel convergences. Although Kenyan camels are predisposed to MERS-CoV, no shedding is documented to date. These potential hotspots, determined using anthropogenic, system and trade characterizations should guide selection of sampling/surveillance sites, high-risk locations, critical areas for interventions and policy development in Kenya, as well as instigate further virological examination of camels.The United States Agency for International Development through the MERS-CoV applied research activities in Middle East and North East Africa under the USAID’s Emerging Pandemic Threats Program (OSRO/GLO/505/USA).http://link.springer.com/journal/103932019-06-01hj2018Veterinary Tropical Disease

A hundred years of rabies in Kenya and the strategy for eliminating dog-mediated rabies by 2030

Background: Rabies causes an estimated 59,000 human deaths annually. In Kenya, rabies was first reported in a dog in 1912, with the first human case reported in 1928. Here we examine retrospective rabies data in Kenya for the period 1912 – 2017 and describe the spatial and temporal patterns of rabies occurrence in the country. Additionally, we detail Kenya’s strategy for the elimination of dog-mediated human rabies by 2030. Methods: Data on submitted samples and confirmed cases in humans, domestic animals and wildlife were obtained from Kenya’s Directorate of Veterinary Services. These data were associated with the geographical regions where the samples originated, and temporal and spatial trends examined. Results: Between 1912 and the mid 1970’s, rabies spread across Kenya gradually, with fewer than 50 cases reported per year and less than half of the 47 counties affected. Following an outbreak in the mid 1970’s, rabies spread rapidly to more than 85% of counties, with a 4 fold increase in the percent positivity of samples submitted and number of confirmed rabies cases. Since 1958, 7,584 samples from domestic animals (93%), wildlife (5%), and humans (2%) were tested. Over two-thirds of all rabies cases came from six counties, all in close proximity to veterinary diagnostic laboratories, highlighting a limitation of passive surveillance. Conclusions: Compulsory annual dog vaccinations between 1950’s and the early 1970’s slowed rabies spread. The rapid spread with peak rabies cases in the 1980’s coincided with implementation of structural adjustment programs privatizing the veterinary sector leading to breakdown of rabies control programs. To eliminate human deaths from rabies by 2030, Kenya is implementing a 15-year step-wise strategy based on three pillars: a) mass dog vaccination, b) provision of post-exposure prophylaxis and public awareness and c) improved surveillance for rabies in dogs and humans with prompt responses to rabies outbreaks

Mapping of beef, sheep and goat food systems in Nairobi — A framework for policy making and the identification of structural vulnerabilities and deficiencies

Nairobi is a large rapidly-growing city whose demand for beef, mutton and goat products is expected to double by 2030. The study aimed to map the Nairobi beef, sheep and goat systems structure and flows to identify deficiencies and vulnerabilities to shocks. Cross-sectional data were collected through focus group discussions and interviews with people operating in Nairobi ruminant livestock and meat markets and in the large processing companies. Qualitative and quantitative data were obtained about the type of people, animals, products and value adding activities in the chains, and their structural, spatial and temporal interactions. Mapping analysis was done in three different dimensions: people and product profiling (interactions of people and products), geographical (routes of animals and products) and temporal mapping (seasonal fluctuations). The results obtained were used to identify structural deficiencies and vulnerability factors in the system. Results for the beef food system showed that 44–55% of the city's beef supply flows through the ‘local terminal markets’, but that 54–64% of total supply is controlled by one ‘meat market’. Numerous informal chains were identified, with independent livestock and meat traders playing a pivotal role in the functionality of these systems, and where most activities are conducted with inefficient quality control and under scarce and inadequate infrastructure and organisation, generating wastage and potential food safety risks in low quality meat products. Geographical and temporal analysis showed the critical areas influencing the different markets, with larger markets increasing their market share in the low season. Large processing companies, partly integrated, operate with high quality infrastructures, but with up to 60% of their beef supply depending on similar routes as the informal markets. Only these companies were involved in value addition activities, reaching high-end markets, but also dominating the distribution of popular products, such as beef sausages, to middle and low-end market. For the small ruminant food system, 73% of the low season supply flows through a single large informal market, Kiamaiko, located in an urban informal settlement. No grading is done for these animals or the meat produced. Large companies were reported to export up to 90% of their products. Lack of traceability and control of animal production was a common feature in all chains. The mapping presented provides a framework for policy makers and institutions to understand and design improvement plans for the Nairobi ruminant food system. The structural deficiencies and vulnerabilities identified here indicate the areas of intervention needed

Risk factors for acute human brucellosis in Ijara, north-eastern Kenya

Brucellosis is an important zoonotic disease globally, with particularly high burdens in pastoral settings. While the zoonotic transmission routes for Brucella spp. are well known, the relative importance of animal contact, food-handling and consumption practices can vary. Understanding the local epidemiology of human brucellosis is important for directing veterinary and public health interventions, as well as for informing clinical diagnostic decision making. We conducted a cross-sectional study in Ijara District Hospital, north-eastern Kenya. A total of 386 individuals seeking care and reporting symptoms of febrile illness were recruited in 2011. Samples were tested for the presence of Brucella spp. using a real-time PCR (RT-PCR) and results compared to those from the test for brucellosis used at Ijara District Hospital, the febrile Brucella plate agglutination test (FBAT). A questionnaire was administered to all participants and risk factors for brucellosis identified using logistic regression with an information theoretic (IT) approach and least absolute shrinkage and selection (LASSO). Sixty individuals were RT-PCR positive, resulting in a prevalence of probable brucellosis of 15.4% (95% CI 12.0–19.5). The IT and LASSO approaches both identified consuming purchased milk as strongly associated with elevated risk and boiling milk before consumption strongly associated with reduced risk. There was no evidence that livestock keepers were at different risk of brucellosis than non-livestock keepers. The FBAT had poor diagnostic performance when compared to RT-PCR, with an estimated sensitivity of 36.6% (95% CI 24.6–50.1) and specificity of 69.3% (95% CI 64.0–74.3). Brucellosis is an important cause of febrile illness in north-eastern Kenya. Promotion of pasteurisation of milk in the marketing chain and health messages encouraging the boiling of raw milk before consumption could be expected to lead to large reductions in the incidence of brucellosis in Ijara. This study supports the growing evidence that the FBAT performs very poorly in the diagnosis of brucellosis

Human brucellosis in Baringo County, Kenya: Evaluating the diagnostic kits used and identifying infecting Brucella species.

Human brucellosis diagnosis has been a challenge in Brucella-endemic areas. In Kenya, diagnosis is usually carried out using Febrile Brucella Antigen agglutination test (FBAT) whose performance is not well documented. This paper reports on the sensitivity and specificity of the FBAT used for brucellosis diagnosis on blood samples/serum collected in three healthcare facilities in Baringo County, Kenya, and on Brucella species present in the study area. The FBAT test results at the hospitals were used to guide patient management. Patients who visited the hospital's laboratory with a clinician's request for brucellosis testing also filled a questionnaire to assess knowledge and attitudes associated with transmission of the disease in the study area. The remaining serum samples were tested again using FBAT and Rose Bengal Plate Test (RBPT) within a month of blood collection at the University Nairobi Laboratory. The two rapid tests were then compared, with respect to brucellosis diagnostic sensitivity and specificity. To identify infecting Brucella species, a proportion 43% (71/166) of the blood clots were analyzed by multiplex polymerase chain reaction (PCR) using specific primers for B. abortus, B. melitensis, B. ovis and B. suis. Out of 166 serum samples tested, 26.5% (44/166) were positive using FBAT and 10.2% (17/166) positive using RBPT. The sensitivity and specificity of FBAT compared to RBPT was 76.47% and 71.19%, respectively while the positive and negative predictive values were 29.55% and 96.72%, respectively. The FBAT showed higher positivity then RBPT. The difference in sensitivity and specificity of FBAT and RBPTs was relatively low. The high FBAT positivity rate would be indication of misdiagnosis; this would lead to incorrect treatment. Brucella abortus was detected from 9.9% (7/71) of the blood clots tested; no other Brucella species were detected. Thus human brucellosis, in Baringo was mainly caused by B. abortus

Assessment of Milk Quality and Food Safety Challenges in the Complex Nairobi Dairy Value Chain

Food networks present varying food safety concerns because of the complexity of interactions, production, and handling practices. We investigated total bacteria counts (TBCs) and total coliform counts (TCCs) in various nodes of a Nairobi dairy value chain and identified practices that influence food safety. A value chain analysis framework facilitated qualitative data collection through 23 key informant interviews and 20 focus group discussions. Content thematic analysis identified food safety challenges. Cow milk products (N = 290) were collected from farms (N = 63), collection centers (N = 5), shops/kiosks (N = 37), milk bars (N = 17), roadside vendors (N = 14), restaurants (N = 3), milk vending machines (N = 2), mobile traders (N = 2) and a supermarket (N = 1). Mean values of colony-forming units for TBC and TCC were referenced to East African Standards (EAS). Logistic regression analysis assessed differences in milk acceptability based on EAS. The raw milk from farms and collection centers was relatively within acceptable EAS limits in terms of TBC (3.5 × 105 and 1.4 × 106 respectively) but TCC in the milk from farms was 3 times higher than EAS limits (1.5 × 105). Compared to farms, the odds ratio of milk acceptability based on TBC was lower on milk bars (0.02), restaurants (0.02), roadside vendors (0.03), shops/kiosks (0.07), and supermarkets (0.17). For TCC, the odds that milk samples from collection centers, milk bars, restaurants, roadside vendors, and shops/kiosks were acceptable was less than the odds of samples collected from farms (0.18, 0.03, 0.06, 0.02, and 0.12, respectively). Comparison of raw milk across the nodes showed that the odds of milk samples from restaurants, roadside vendors, and shops/kiosks being acceptable were less than the odds of samples collected the farm for TBC (0.03, 0.04, and 0.04, respectively). For TCC, the odds of raw milk from collection centers, restaurants, roadside vendors, milk bars, and shops/kiosks being acceptable were lower than the odds of acceptability for the farm samples (0.18, 0.12, 0.02, 0.04, and 0.05, respectively). Practices with possible influence on milk bacterial quality included muddy cowsheds, unconventional animal feed sources, re-use of spoilt raw milk, milk adulteration, acceptance of low-quality milk for processing, and lack of cold chain. Therefore, milk contamination occurs at various points, and the designing of interventions should focus on every node.</jats:p

Polymerase chain reactions primer sequences.

Polymerase chain reactions primer sequences.</p