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.

Highlights d Isolated Caenorhabditis bovis from ear of a cow at livestock market in rural Kenya d Sequenced genome using the Oxford Nanopore MinION in nearby field laboratory d C. bovis genome is 40% smaller than C. elegans and encodes 7,000 fewer genes d Most closely related to a species isolated from carrion

Surveillance of diseases in Kenya and elsewhere in East Africa is currently carried out by both human and animal health sectors. However, a recent evaluation highlighted the lack of integration between these sectors, leading to disease under-reporting and inefficiencies. This project aimed to develop an integrated and cost-effective surveillance and reporting system for 15 zoonotic diseases piloted in the counties of Bungoma, Busia, and Kakamega in western Kenya. Specifically, in this paper we describe the operational aspects of such a surveillance system. Interviews were carried out with key informants, and this was followed by field visits to identify sentinel sites and liaise with relevant stakeholders. Based on this information, a sampling strategy comprising 12 sentinel sites, 4 in each county, was developed. Each sentinel site comprised of a livestock market, 1–2 neighboring slaughter houses/slabs, and a hospital in the vicinity; each of the 12 sites, comprising 12 × 3 = 36 sampling locations, was visited every 4 weeks for 20 cycles. At each site, animal or patient sampling included a clinical examination and collection of blood, feces, and nasal swabs; in slaughtered animals, mesenteric lymph nodes, hydatid cysts, and flukes were also collected. At the end of each field visit, data on staff involved and challenges encountered were recorded, while biological samples were processed and tested for 15 zoonotic diseases in the field laboratory in Busia, Kenya. Public engagement sessions were held at each sentinel site to share preliminary results and provide feedback to both stakeholders and study participants. A livestock market visit lasted just over 3 h, and the most common challenge was the frequent refusals of animal owners to participate in the study. At the slaughterhouses, visits lasted just under 4 h, and challenges included poorly engaged meat inspectors or slaughter processes that were too quick for sampling. Finally, the hospital visits lasted around 4 h, and the most frequent challenges included low patients turn-out, frequent staff turn-over leading to poor institutional memory, and difficulty in obtaining patient stool samples. Our experiences have highlighted the importance of engaging with local stakeholders in the field, while also providing timely feedback through public engagement sessions, to ensure on-going compliance.

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.

Quantitative evidence for the risk of zoonoses and the spread of antimicrobial resistance remains lacking. Here, as part of the UrbanZoo project, we sampled Escherichia coli from humans, livestock and peri-domestic wildlife in 99 households across Nairobi, Kenya, to investigate its distribution among host species in this rapidly developing urban landscape. We performed whole-genome sequencing of 1,338 E. coli isolates and found that the diversity and sharing patterns of E. coli were heavily structured by household and strongly shaped by host type. We also found evidence for inter-household and inter-host sharing and, importantly, between humans and animals, although this occurs much less frequently. Resistome similarity was differently distributed across host and household, consistent with being driven by shared exposure to antimicrobials. Our results indicate that a large, epidemiologically structured sampling framework combined with WGS is needed to uncover strain-sharing events among different host populations in complex environments and the major contributing pathways that could ultimately drive the emergence of zoonoses and the spread of antimicrobial resistance.