Brucellosis, caused by several species of the genus Brucella, is a zoonotic disease that affects humans and animal species worldwide. Information on the Brucella species circulating in different hosts in Kenya is largely unknown, thus limiting the adoption of targeted control strategies. This study was conducted in multi-host livestock populations in Kenya to detect the circulating Brucella species and assess evidence of host–pathogen associations. Serum samples were collected from 228 cattle, 162 goats, 158 sheep, 49 camels, and 257 humans from Narok and Marsabit counties in Kenya. Information on age, location and history of abortion or retained placenta were obtained for sampled livestock. Data on age, gender and location of residence were also collected for human participants. All samples were tested using genus level real-time PCR assays with primers specific for IS711 and bcsp31 targets for the detection of Brucella. All genus positive samples (positive for both targets) were further tested with a speciation assay for AlkB and BMEI1162 targets, specific for B. abortus and B. melitensis, respectively. Samples with adequate quantities aggregating to 577 were also tested with the Rose Bengal Test (RBT). A total of 199 (33.3%) livestock and 99 (38.5%) human samples tested positive for genus Brucella. Animal Brucella PCR positive status was positively predicted by RBT positive results (OR = 8.3, 95% CI 4.0–17.1). Humans aged 21–40 years had higher odds (OR = 2.8, 95% CI 1.2–6.6) of being Brucella PCR positive compared to the other age categories. The data on detection of different Brucella species indicates that B. abortus was detected more often in cattle (OR = 2.3, 95% CI 1.1–4.6) and camels (OR = 2.9, 95% CI 1.3–6.3), while B. melitensis was detected more in sheep (OR = 3.6, 95% CI 2.0–6.7) and goats (OR = 1.7, 95% CI 1.0–3.1). Both B. abortus and B. melitensis DNA were detected in humans and in multiple livestock host species, suggesting cross-transmission of these species among the different hosts. The detection of these two zoonotic Brucella species in humans further underpins the importance of One Health prevention strategies that target multiple host species, especially in the multi-host livestock populations.

Poultry production is an important way of enhancing the livelihoods of rural populations, especially in low- and middle-income countries (LMICs). As poultry production in LMICs remains dominated by backyard systems with low inputs and low outputs, considerable yield gaps exist. Intensification can increase poultry productivity, production and income. This process is relatively recent in LMICs compared to high-income countries. The management practices and the constraints faced by smallholders trying to scale-up their production, in the early stages of intensification, are poorly understood and described. We thus investigated the features of the small-scale commercial chicken sector in a rural area distant from major production centres. We surveyed 111 commercial chicken farms in Kenya in 2016. We targeted farms that sell the majority of their production, owning at least 50 chickens, partly or wholly confined and provided with feeds. We developed a typology of semi-intensive farms. Farms were found mainly to raise dual-purpose chickens of local and improved breeds, in association with crops and were not specialized in any single product or market. We identified four types of semi-intensive farms that were characterized based on two groups of variables related to intensification and accessibility: (i) remote, small-scale old farms, with small flocks, growing a lot of their own feed; (ii) medium-scale, old farms with a larger flock and well located in relation to markets and (iii) large-scale recently established farms, with large flocks, (iii-a) well located and buying chicks from third-party providers and (iii-b) remotely located and hatching their own chicks. The semi-intensive farms we surveyed were highly heterogeneous in terms of size, age, accessibility, management, opportunities and challenges. Farm location affects market access and influences the opportunities available to farmers, resulting in further diversity in farm profiles. The future of these semi-intensive farms could be compromised by several factors, including the competition with large-scale intensive farmers and with importations. Our study suggests that intensification trajectories in rural areas of LMICs are potentially complex, diverse and non-linear. A better understanding of intensification trajectories should, however, be based on longitudinal data. This could, in turn, help designing interventions to support small-scale farmers.

Background: Co-infection, especially with pathogens of dissimilar genetic makeup, may result in a more devastating impact on the host. Investigations on co-infection with neglected zoonotic pathogens in wildlife are necessary to inform appropriate prevention and control strategies to reduce disease burden in wildlife and the potential transmission of these pathogens between wildlife, livestock and humans. This study assessed co-exposure of various Kenyan wildflife species with Brucella spp, Coxiella burnetii and Rift Valley fever virus (RVFV). Methodology: A total of 363 sera from 16 different wildlife species, most of them (92.6%) herbivores, were analysed by Enzyme-linked immunosorbent assay (ELISA) for IgG antibodies against Brucella spp, C. burnetii and RVFV. Further, 280 of these were tested by PCR to identify Brucella species. Results: Of the 16 wildlife species tested, 15 (93.8%) were seropositive for at least one of the pathogens. Mean seropositivities were 18.9% (95% CI: 15.0–23.3) for RVFV, 13.7% (95% CI: 10.3–17.7) for Brucella spp and 9.1% (95% CI: 6.3–12.5) for C. burnetii. Buffaloes (n = 269) had higher seropositivity for Brucella spp. (17.1%, 95% CI: 13.0–21.7%) and RVFV (23.4%, 95% CI: 18.6–28.6%), while giraffes (n = 36) had the highest seropositivity for C. burnetii (44.4%, 95% CI: 27.9–61.9%). Importantly, 23 of the 93 (24.7%) animals positive for at least one pathogen were co-exposed, with 25.4% (18/71) of the positive buffaloes positive for brucellosis and RVFV. On molecular analysis, Brucella DNA was detected in 46 (19.5%, CI: 14.9–24.7) samples, with 4 (8.6%, 95% CI: 2.2–15.8) being identified as B. melitensis. The Fisher’s Exact test indicated that seropositivity varied significantly within the different animal families, with Brucella (p = 0.013), C. burnetii (p = <0.001) and RVFV (p = 0.007). Location was also significantly associated (p = <0.001) with Brucella spp. and C. burnetii seropositivities. Conclusion: Of ~20% of Kenyan wildlife that are seropositive for Brucella spp, C. burnetii and RVFV, almost 25% indicate co-infections with the three pathogens, particularly with Brucella spp and RVFV.

Background: Brucellosis is an emerging yet neglected zoonosis that has been reported in Kenya. Epidemiological data on brucellosis in ruminants is readily accessible; however, reports on brucellosis in pigs remain limited. This study sought to detectBrucellainfection in pig serum by both serological and molecular techniques. Serum from 700 pigs randomly collected at a centralized abattoir in Nairobi region, Kenya were screened in parallel, using both Rose Bengal Test (RBT) and competitive Enzyme-Linked Immuno-sorbent Assay (cELISA) for antibodies againstBrucellaspp. All sera positive by RBT and 16 randomly selected negative samples were further tested using conventional PCR targetingbcsp31gene and real-time PCR (RT-PCR) assays targetingIS711andbcsp31genes.Results: A prevalence of 0.57% (n = 4/700) was estimated using RBT; none of these samples was positive on cELISA. All RBT positive sera were also positive by both PCRs, while two sero-negative samples also tested positive on RT-PCR (n = 6/20).Brucella abortuswas detected in four out of the six PCR positive samples through a real-time multiplex PCR.Conclusion: The detection of antibodies againstBrucellaspp. and DNA in serum from slaughterhouse pigs confirm the presence ofBrucellain pigs. Therefore, investigation of the epidemiology and role of pigs in the transmission of brucellosis in Kenya is needed. Further targeted studies would be useful to systematically quantify and identify the spp. ofBrucellain pigs.

In Sub-Saharan Africa (SSA), effective brucellosis control is limited, in part, by the lack of long-term commitments by governments to control the disease and the absence of reliable national human and livestock population-based data to inform policies. Therefore, we conducted a study to establish the national prevalence and develop a risk map for Brucella spp. in cattle to contribute to plans to eliminate the disease in Kenya by the year 2040. We randomly generated 268 geolocations and distributed them across Kenya, proportionate to the area of each of the five agroecological zones and the associated cattle population. Cattle herds closest to each selected geolocation were identified for sampling. Up to 25 cattle were sampled per geolocation and a semi-structured questionnaire was administered to their owners. We tested 6,593 cattle samples for Brucella immunoglobulin G (IgG) antibodies using an Enzyme-linked immunosorbent assay (ELISA). We assessed potential risk factors and performed spatial analyses and prevalence mapping using approximate Bayesian inference implemented via the integrated nested Laplace approximation (INLA) method. The national Brucella spp. prevalence was 6.8% (95% CI: 6.2–7.4%). Exposure levels varied significantly between agro-ecological zones, with a high of 8.5% in the very arid zone with the lowest agricultural potential relative to a low of 0.0% in the agro-alpine zone with the highest agricultural potential. Additionally, seroprevalence increased with herd size, and the odds of seropositivity were significantly higher for females and adult animals than for males or calves. Similarly, animals with a history of abortion, or with multiple reproductive syndromes had higher seropositivity than those without. At the herd level, the risk of Brucella spp. transmission was higher in larger herds, and herds with a history of reproductive problems such as abortion, giving birth to weak calves, or having swollen testes. Geographic localities with high Brucella seroprevalence occurred in northern, eastern, and southern regions of Kenya all primarily characterized by semi-arid or arid agro-ecological zones dominated by livestock pastoralism interspersed with vast areas with mixed livestock-wildlife systems. The large spatial extent of our survey provides compelling evidence for the widespread geographical distribution of brucellosis risk across Kenya in a manner easily understandable for policymakers. Our findings can provide a basis for risk-stratified pilot studies aiming to investigate the cost-effectiveness and efficacy of singular and combined preventive intervention strategies that seek to inform Kenya’s Brucellosis Control Policy.

Background: Brucellosis is a bacterial zoonosis of public health and economic importance worldwide. It affects a number of domestic animals, wild animals and humans. Human brucellosis originates from either livestock or wildlife. The species of Brucella circulating in wild animals in Tanzania is largely unknown due to insufficient surveillance. This study was carried out to identify Brucella species found in selected wildlife hosts in the Serengeti ecosystem. Methodology: The study used a total of 189 archived samples that were obtained from cross-sectional studies previously conducted between 2000 and 2017 in the Serengeti ecosystem in Tanzania. Whole blood, serum and amniotic fluid collected from buffalos, lions, wildebeest, impala, zebra and hyena were available for DNA extraction. Multiplex polymerase chain reaction for B. abortus, B. melitensis, B. ovis and B. suis (AMOS PCR) and quantitative real-time PCR (qPCR) targeting the bcsp31 and IS711 genes for Brucella genus detection and the IS711 targets alkB for B. abortus and BMEI1162 for B. melitensis were used to detect Brucella strains. Results: Out of the 189 samples tested, 12 (6.35 %) and 22 (11.6 %) were positive to AMOS-PCR and qPCR, respectively. Most of the positive samples were from lions (52.6 %) and buffaloes (19.6 %). Other animals that were positive included: wildebeest (13.6 %), impala (13.6 %), zebra (4.5 %) and hyena (4.5 %). Out of 22 positive samples, 16 (66.7 %) were identified as B. abortus and the other six samples did not amplify for neither B. abortus nor B. melitensis. Conclusions: The detection of Brucella DNA in archived wild animal samples shows testing potential of samples collected from this population. The zoonotic species B. abortus and B. melitensis detected in wild animals have previously been reported in livestock and humans in the region. The findings suggest that, due to the contact network, some of the identified wild animal hosts in this study could be reservoirs for infections in domestic animals and humans within the Serengeti ecosystem while others are likely dead-end hosts. One Health control strategies and continuous surveillance programs in other wildlife reserved areas should be implemented to help predicting transmission in livestock and humans in the region.