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Urbanization is predicted to be a key driver of disease emergence through human exposure to novel, animal-borne pathogens. However, while we suspect that urban landscapes are primed to expose people to novel animal-borne diseases, evidence for the mechanisms by which this occurs is lacking. To address this, we studied how bacterial genes are shared between wild animals, livestock, and humans (n = 1,428) across Nairobi, Kenya-one of the world's most rapidly developing cities. Applying a multilayer network framework, we show that low biodiversity (of both natural habitat and vertebrate wildlife communities), coupled with livestock management practices and more densely populated urban environments, promotes sharing of Escherichia coli-borne bacterial mobile genetic elements between animals and humans. These results provide empirical support for hypotheses linking resource provision, the biological simplification of urban landscapes, and human and livestock demography to urban dynamics of cross-species pathogen transmission at a landscape scale. Urban areas where high densities of people and livestock live in close association with synanthropes (species such as rodents that are more competent reservoirs for zoonotic pathogens) should be prioritized for disease surveillance and control.
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Doenças dos Animais , Animais Selvagens , Animais , Humanos , Quênia/epidemiologia , Animais Selvagens/microbiologia , Ecossistema , Biodiversidade , Cidades , Urbanização , Gado/microbiologiaRESUMO
BACKGROUND: Livestock systems have been proposed as a reservoir for antimicrobial-resistant (AMR) bacteria and AMR genetic determinants that may infect or colonise humans, yet quantitative evidence regarding their epidemiological role remains lacking. Here, we used a combination of genomics, epidemiology and ecology to investigate patterns of AMR gene carriage in Escherichia coli, regarded as a sentinel organism. METHODS: We conducted a structured epidemiological survey of 99 households across Nairobi, Kenya, and whole genome sequenced E. coli isolates from 311 human, 606 livestock and 399 wildlife faecal samples. We used statistical models to investigate the prevalence of AMR carriage and characterise AMR gene diversity and structure of AMR genes in different host populations across the city. We also investigated household-level risk factors for the exchange of AMR genes between sympatric humans and livestock. RESULTS: We detected 56 unique acquired genes along with 13 point mutations present in variable proportions in human and animal isolates, known to confer resistance to nine antibiotic classes. We find that AMR gene community composition is not associated with host species, but AMR genes were frequently co-located, potentially enabling the acquisition and dispersal of multi-drug resistance in a single step. We find that whilst keeping livestock had no influence on human AMR gene carriage, the potential for AMR transmission across human-livestock interfaces is greatest when manure is poorly disposed of and in larger households. CONCLUSIONS: Findings of widespread carriage of AMR bacteria in human and animal populations, including in long-distance wildlife species, in community settings highlight the value of evidence-based surveillance to address antimicrobial resistance on a global scale. Our genomic analysis provided an in-depth understanding of AMR determinants at the interfaces of One Health sectors that will inform AMR prevention and control.
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Gado , Saúde Única , Humanos , Animais , Escherichia coli/genética , Antibacterianos/farmacologia , Quênia/epidemiologia , Farmacorresistência Bacteriana/genéticaRESUMO
BACKGROUND: We implemented a longitudinal study to determine the incidence of Brucella infection in cattle, camels, sheep and goats that were being raised in a pastoral area in Isiolo County, Kenya. An initial cross-sectional survey was implemented to identify unexposed animals for follow up; that survey used 141 camels, 216 cattle, 208 sheep and 161 goats. Sera from these animals were screened for Brucella spp. using the Rose Bengal Plate test (RBPT), a modified RBPT, and an indirect multispecies Enzyme Linked Immunosorbent Assay (iELISA). Results of RBPT and iELISA were interpreted in parallel to determine seroprevalence. A total of 30 camels, 31 cattle, 22 sheep and 32 goats that were seronegative by all the above tests were recruited in a subsequent longitudinal study for follow up. These animals were followed for 12 months and tested for anti-Brucella antibodies using iELISA. Seroconversion among these animals was defined by a positive iELISA test following a negative iELISA result in the previous sampling period. All seropositive samples were further tested using real-time PCR-based assays to identify Brucella species. These analyses targeted the alkB and BMEI1162 genes for B. abortus, and B. melitensis, respectively. Data from the longitudinal study were analysed using Cox proportional hazards model that accounted for within-herds clustering of Brucella infections. RESULTS: The overall incidence rate of Brucella infection was 0.024 (95% confidence interval [CI]: 0.014-0.037) cases per animal-months at risk. Brucella infection incidence in camels, cattle, goats and sheep were 0.053 (0.022-0.104), 0.028 (0.010-0.061), 0.013 (0.003-0.036) and 0.006 (0.0002-0.034) cases per animal-month at risk, respectively. The incidence rate of Brucella infection among females and males were 0.020 (0.009-0.036) and 0.016 (0.004-0.091), respectively. Real-time PCR analyses showed that B. abortus was more prevalent than B. melitensis in the area. Results of multivariable Cox regression analysis identified species (camels and cattle) as an important predictor of Brucella spp. exposure in animals. CONCLUSIONS: This study estimated an overall brucellosis incidence of 0.024 cases per animal-months at risk with camels and cattle having higher incidence than sheep and goats. These results will inform surveillance studies in the area.
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Brucella/imunologia , Brucelose/veterinária , Camelus/microbiologia , Doenças dos Bovinos/epidemiologia , Doenças das Cabras/epidemiologia , Doenças dos Ovinos/epidemiologia , Animais , Brucelose/epidemiologia , Brucelose/microbiologia , Bovinos , Doenças dos Bovinos/microbiologia , Estudos Transversais , Ensaio de Imunoadsorção Enzimática/veterinária , Feminino , Doenças das Cabras/microbiologia , Cabras , Incidência , Quênia/epidemiologia , Gado , Estudos Longitudinais , Masculino , Fatores de Risco , Estudos Soroepidemiológicos , Ovinos , Doenças dos Ovinos/microbiologiaRESUMO
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 detect Brucella infection 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 against Brucella spp. All sera positive by RBT and 16 randomly selected negative samples were further tested using conventional PCR targeting bcsp31 gene and real-time PCR (RT-PCR) assays targeting IS711 and bcsp31 genes. 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 abortus was detected in four out of the six PCR positive samples through a real-time multiplex PCR. CONCLUSION: The detection of antibodies against Brucella spp. and DNA in serum from slaughterhouse pigs confirm the presence of Brucella in 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. of Brucella in pigs.
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Brucella/isolamento & purificação , Brucelose/veterinária , Doenças dos Suínos/epidemiologia , Matadouros , Animais , Anticorpos Antibacterianos , Brucelose/sangue , Brucelose/epidemiologia , Brucelose/microbiologia , DNA Bacteriano , Ensaio de Imunoadsorção Enzimática/veterinária , Quênia/epidemiologia , Reação em Cadeia da Polimerase/veterinária , Testes Sorológicos/veterinária , Suínos , Doenças dos Suínos/microbiologiaRESUMO
Commercial layer and indigenous chicken farming in Nairobi and associated activities in the egg value chains are a source of livelihood for urban families. A value chain mapping framework was used to describe types of inputs and outputs from chicken farms, challenges faced by producers and their disease control strategies. Commercial layer farms were defined as farms keeping exotic breeds of chicken, whereas indigenous chicken farms kept different cross breeds of indigenous chicken. Four focus group discussions were held with producers of these chickens in peri-urban area: Dagoretti, and one informal settlement: Kibera. Qualitative data were collected on interactions between farmers, sources of farm inputs and buyers of poultry products, simple ranking of production challenges, farmers' perception on diseases affecting chicken and strategies for management of sick chicken and waste products. Value chain profiles were drawn showing sources of inputs and channels for distribution of chicken products. Production challenges and chicken disease management strategies were presented as qualitative summaries. Commercial layer farms in Dagoretti kept an average of 250 chickens (range 50-500); while flock sizes in Kibera were 12 chickens (range 5-20). Farms keeping indigenous chicken had an average of 23 chickens (range 8-40) in Dagoretti, and 10 chickens (range 5-16) in Kibera. Commercial layer farms in Dagoretti obtained chicks from distributors of commercial hatcheries, but farms in Kibera obtained chicks from hawkers who in turn sourced them from distributors of commercial hatcheries. Indigenous chicken farms from Dagoretti relied on natural hatching of fertilised eggs, but indigenous chicken farms in Kibera obtained chicks from their social connection with communities living in rural areas. Outlets for eggs from commercial layer farms included local shops, brokers, restaurants and hawkers, while eggs from indigenous chicken farms were sold to neighbours and restaurants. Sieved chicken manure from Dagoretti area was fed to dairy cattle; whereas non-sieved manure was used as fertilizer on crops. Production challenges included poor feed quality, lack of space for expansion, insecurity, occurrence of diseases and lack of sources of information on chicken management. In Kibera, sick and dead chickens were slaughtered and consumed by households; this practice was not reported in Dagoretti. The chicken layer systems contribute to food security of urban households, yet they have vulnerabilities and deficiencies with regard to disease management and food safety that need to be addressed with support on research and extension.
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Demand for dairy products in sub-Saharan Africa, is expected to triple by 2050, while limited increase in supply is predicted. This poses significant food security risk to low income households. Understanding how the dairy food system operates is essential to identify mitigation measures to food insecurity impact. This study aims to determine the structure and functionality of Nairobi's dairy system using a value chain mapping approach. Primary data were gathered through focus group discussions and key informant interviews with dairy value chain stakeholders in Nairobi to obtain qualitative information on people and products in the chains while describing their interactions and flows. Qualitative thematic analysis combined with flowcharts created by participants enabled identification of key food system segments and the development of chain profiles (or flow-diagrams) which together form Nairobi's dairy system. Seven chain profiles forming Nairobi's dairy value chain were identified. These were found to be dominated by small-scale individuals who operate largely independently. Our profiles for the urban and peri-urban farming systems were structurally similar in their downstream networks, obtaining inputs from similar sources. Upstream, the urban systems were shorter, supplying mostly to immediate neighbours or based on own consumption, while the peri urban systems supplied to a wider network and showed some affiliations to producers' associations. Two distinct profiles characterize the milk flow from traders belonging either to a Dairy Traders Association (DTA) or those not belonging to this association (non-DTA). DTA traders sell mainly to fixed retailers and non-DTA traders to mobile retailers (hawkers or roadside vendors). Profiles associated with medium and large cooperatives were driven by networks of collection centres, but with medium-sized cooperatives selling half of their production to large processing companies, and large cooperatives only to fixed retailers. Large processing companies' profiles indicated distribution of high volumes and value addition processing. They reported strategic milk collection arrangements with suppliers on long, medium - or short - term contracts and with well-established product distribution channels. We have identified numerous inter-linkages across dairy chain profiles in Nairobi's complex system, demonstrating significant interdependency among the stakeholders. Therefore, enhancing the system's efficiency requires a holistic, system-wide approach and any policy interventions should consider every segment of the value chain. This study provides a methodological approach for organizations and policy makers to understand and address structural and functional vulnerabilities within food systems more broadly. The insights from this study are relevant to other rapidly growing cities in the region.
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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.
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Introduction: Understanding multi-pathogen infections/exposures in livestock is critical to inform prevention and control measures against infectious diseases. We investigated the co-exposure of foot-and-mouth disease virus (FMDV), Brucella spp., Leptospira spp., and Coxiella burnetii in cattle in three zones stratified by land use change and with different wildlife-livestock interactions in Narok county, Kenya. We also assessed potential risk factors associated with the transmission of these pathogens in cattle. Methods: We identified five villages purposively, two each for areas with intensive (zone 1) and moderate wildlife-livestock interactions (zone 2) and one for locations with low wildlife-livestock interactions (zone 3). We sampled 1,170 cattle from 390 herds through a cross-sectional study and tested the serum samples for antibodies against the focal pathogens using enzyme-linked immunosorbent assay (ELISA) kits. A questionnaire was administered to gather epidemiological data on the putative risk factors associated with cattle's exposure to the investigated pathogens. Data were analyzed using the Bayesian hierarchical models with herd number as a random effect to adjust for the within-herd clustering of the various co-exposures among cattle. Results: Overall, 88.0% (95% CI: 85.0-90.5) of the cattle tested positive for at least one of the targeted pathogens, while 41.7% (95% CI: 37.7-45.8) were seropositive to at least two pathogens. FMDV and Brucella spp. had the highest co-exposure at 33.7% (95% CI: 30.9-36.5), followed by FMDV and Leptospira spp. (21.8%, 95% CI: 19.5-24.4), Leptospira spp. and Brucella spp. (8.8%, 95% CI: 7.2-10.6), FMDV and C. burnetii (1.5%, 95% CI: 0.7-2.8), Brucella spp. and C. burnetii (1.0%, 95% CI: 0.3-2.2), and lowest for Leptospira spp. and C. burnetii (0.3%, 95% CI: 0.0-1.2). Cattle with FMDV and Brucella spp., and Brucella spp. and Leptospira spp. co-exposures and those simultaneously exposed to FMDV, Brucella spp. and Leptospira spp. were significantly higher in zone 1 than in zones 2 and 3. However, FMDV and Leptospira spp. co-exposure was higher in zones 1 and 2 than zone 3. Discussion/conclusion: We recommend the establishment of a One Health surveillance system in the study area to reduce the morbidity of the targeted zoonotic pathogens in cattle and the risks of transmission to humans.
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BACKGROUND: Brucellosis is a neglected zoonotic disease that affects both animals and humans, causing debilitating illness in humans and socio-economic losses in livestock-keeping households globally. The disease is endemic in many developing countries, including Kenya, but measures to prevent and control the disease are often inadequate among high-risk populations. This study aimed to investigate the human and livestock seroprevalence of brucellosis and associated risk factors of Brucella spp. in a pastoralist region of northern Kenya. METHODS: A cross-sectional survey was conducted using a two-stage cluster sampling method to select households, livestock, and humans for sampling. Blood samples were collected from 683 humans and 2157 animals, and Brucella immunoglobulin G (IgG) antibodies were detected using enzyme-linked immunosorbent assays. A structured questionnaire was used to collect data on potential risk factors associated with human and animal exposures. Risk factors associated with Brucella spp. exposures in humans and livestock were identified using Multivariate logistic regression. RESULTS: The results indicated an overall livestock Brucella spp. seroprevalence of 10.4% (95% Confidence Interval (CI): 9.2-11.7). Camels had the highest exposure rates at 19.6% (95% CI: 12.4-27.3), followed by goats at 13.2% (95% CI: 9.3-17.1), cattle at 13.1% (95% CI: 11.1-15.3) and sheep at 5.4% (95% CI: 4.0-6.9). The herd-level seroprevalence was 51.7% (95% CI: 47.9-55.7). Adult animals (Adjusted Odds Ratio (aOR) = 2.3, CI: 1.3-4.0), female animals (aOR = 1.7, CI: 1.1-2.6), and large herd sizes (aOR = 2.3, CI: 1.3-4.0) were significantly associated with anti-brucella antibody detection while sheep had significantly lower odds of Brucella spp. exposure compared to cattle (aOR = 1.3, CI: 0.8-2.1) and camels (aOR = 2.4, CI: 1.2-4.8). Human individual and household seroprevalences were 54.0% (95% CI: 50.2-58.0) and 86.4% (95% CI: 84.0-89.0), respectively. Significant risk factors associated with human seropositivity included being male (aOR = 2.1, CI:1.3-3.2), residing in Sericho ward (aOR = 1.6, CI:1.1-2.5) and having no formal education (aOR = 3.0, CI:1.5-5.9). There was a strong correlation between human seropositivity and herd exposure (aOR = 1.6, CI:1.2-2.3). CONCLUSIONS: The study provides evidence of high human and livestock exposures to Brucella spp. and identifies important risk factors associated with disease spread. These findings emphasize the need for targeted prevention and control measures to curb the spread of brucellosis and implement a One Health surveillance to ensure early detection of the disease in Isiolo County, Northern Kenya.
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Brucella , Brucelose , Adulto , Bovinos , Humanos , Animais , Masculino , Feminino , Ovinos , Gado , Estudos Soroepidemiológicos , Quênia/epidemiologia , Estudos Transversais , Camelus , Brucelose/epidemiologia , Brucelose/veterinária , Fatores de Risco , Anticorpos Antibacterianos , CabrasRESUMO
The human population is growing and urbanising. These factors are driving the demand for animal-sourced proteins. The rising demand is favouring livestock intensification, a process that frequently relies on antibiotics for growth promotion, treatment and prevention of diseases. Antibiotic use in livestock production requires strict adherence to the recommended withdrawal periods. In Kenya, the risk of residues in meat is particularly high due to lack of legislation requiring testing for antibiotic residues in meat destined for the local market. We examined pig carcasses for gross pathological lesions and collected pork samples for antibiotic residue testing. Our aim was to determine if a risk-based approach to residue surveillance may be adopted by looking for an association between lesions and presence of residues. In total, 387 pork samples were tested for antibiotic residues using the Premi®Test micro-inhibition kit. The prevalence of antibiotic residues was 41.26% (95% CI, 34.53-48.45%). A logistic regression model found no significant associations between gross pathological lesions and the presence of antibiotic residues. We recommend that the regulating authorities strongly consider routine testing of carcasses for antibiotic residues to protect meat consumers. Future studies should research on farming practices contributing to the high prevalence of residues.
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Understanding antibiotic use in livestock systems is key in combating antimicrobial resistance (AMR) and developing effective interventions. Using a standardised questionnaire, we investigated the patterns and drivers of antibiotic use in 165 cattle farms across the three major cattle production systems in Kenya: intensive, extensive, and semi-intensive systems across in three counties: Machakos, Makueni and Narok in Kenya. We used a causal diagram to inform regression models to explore the drivers of antibiotic use in the study farms. Antibiotic use was reported in 92.7% of farms, primarily for prophylactic purposes. Oxytetracycline, penicillin, and streptomycin were the most used antibiotics to treat and control the most reported diseases including mastitis, diarrhoea and East Coast fever (ECF). Regression analysis indicated a positive association between the frequency of antibiotic use at the farm level and both disease incidence and herd size. Conversely, farms that provided cattle with appropriate housing were less likely to use antibiotics, and there was no difference in antibiotic use between those who consulted with veterinarians or sourced antibiotics directly from animal health providers. Our study highlights the complexities around understanding the interplay between practices and drivers of antibiotic use. It also underscores the necessity to enhance education regarding the appropriate usage of antibiotics among cattle farmers, encourage the adoption of proper herd management practices which may reduce disease burden, and reinforce veterinary services and supportive legislation to promote the prudent use of antimicrobials.
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Brucella spp. and Rift Valley fever virus (RVFV) are classified as priority zoonotic agents in Kenya, based on their public health and socioeconomic impact on the country. Data on the pathogen-specific and co-exposure levels is scarce due to limited active surveillance. This study investigated seroprevalence and co-exposure of Brucella spp. and RVFV and associated risk factors among slaughterhouse workers in Isiolo County, northern Kenya. A cross-sectional serosurvey was done in all 19 slaughterhouses in Isiolo County, enrolling 378 participants into the study. The overall seroprevalences for Brucella spp. and RVFV were 40.2% (95% CI: 35.2-45.4) and 18.3% (95% CI: 14.5-22.5), respectively while 10.3% (95% CI 7.4%-13.8%) of individuals were positive for antibodies against both Brucella spp. and RVFV. Virus neutralisation tests (VNT) confirmed anti-RVFV antibodies in 85% of ELISA-positive samples. Our seroprevalence results were comparable to community-level seroprevalences previously reported in the area. Since most of the study participants were not from livestock-keeping households, our findings attribute most of the detected infections to occupational exposure. The high exposure levels indicate slaughterhouse workers are the most at-risk population and there is need for infection, prevention, and control programs among this high-risk group. This is the first VNT confirmation of virus-neutralising antibodies among slaughterhouse workers in Isiolo County and corroborates reports of the area being a high-risk RVFV area as occasioned by previously reported outbreaks. This necessitates sensitization campaigns to enhance awareness of the risks involved and appropriate mitigation measures.
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Brucella , Febre do Vale de Rift , Vírus da Febre do Vale do Rift , Animais , Humanos , Matadouros , Estudos Soroepidemiológicos , Quênia/epidemiologia , Estudos Transversais , Anticorpos AntiviraisRESUMO
Nearly a century after the first reports of Rift Valley fever (RVF) were documented in Kenya, questions on the transmission dynamics of the disease remain. Specifically, data on viral maintenance in the quiescent years between epidemics is limited. We implemented a cross-sectional study in northern Kenya to determine the seroprevalence, risk factors, and ecological predictors of RVF in humans and livestock during an interepidemic period. Six hundred seventy-six human and 1,864 livestock samples were screened for anti-RVF Immunoglobulin G (IgG). Out of the 1,864 livestock samples tested for IgG, a subset of 1,103 samples was randomly selected for additional testing to detect the presence of anti-RVFV Immunoglobulin M (IgM). The anti-RVF virus (RVFV) IgG seropositivity in livestock and humans was 21.7% and 28.4%, respectively. RVFV IgM was detected in 0.4% of the livestock samples. Participation in the slaughter of livestock and age were positively associated with RVFV exposure in humans, while age was a significant factor in livestock. We detected significant interaction between rainfall and elevation's influence on livestock seropositivity, while in humans, elevation was negatively associated with RVF virus exposure. The linear increase of human and livestock exposure with age suggests an endemic transmission cycle, further corroborated by the detection of IgM antibodies in livestock.
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Febre do Vale de Rift , Vírus da Febre do Vale do Rift , Animais , Humanos , Gado , Estudos Transversais , Quênia/epidemiologia , Estudos Soroepidemiológicos , Febre do Vale de Rift/epidemiologia , Imunoglobulina G , Imunoglobulina MRESUMO
Rift Valley fever (RVF) is a febrile vector-borne disease endemic in Africa and continues to spread in new territories. It is a climate-sensitive disease mostly triggered by abnormal rainfall patterns. The disease is associated with high mortality and morbidity in both humans and livestock. RVF is caused by the Rift Valley fever virus (RVFV) of the genus Phlebovirus in the family Phenuiviridae. It is a tripartite RNA virus with three genomic segments: small (S), medium (M) and large (L). Pathogen genomic sequencing is becoming a routine procedure and a powerful tool for understanding the evolutionary dynamics of infectious organisms, including viruses. Inspired by the utility of amplicon-based sequencing demonstrated in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Ebola, Zika and West Nile viruses, we report an RVFV sample preparation based on amplicon multiplex polymerase chain reaction (amPCR) for template enrichment and reduction of background host contamination. The technology can be implemented rapidly to characterize and genotype RVFV during outbreaks in a near-real-time manner. To achieve this, we designed 74 multiplex primer sets covering the entire RVFV genome to specifically amplify the nucleic acid of RVFV in clinical samples from an animal tissue. Using this approach, we demonstrate achieving complete RVFV genome coverage even from samples containing a relatively low viral load. We report the first primer scheme approach of generating multiplex primer sets for a tripartite virus which can be replicated for other segmented viruses.
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COVID-19 , Febre do Vale de Rift , Vírus da Febre do Vale do Rift , Infecção por Zika virus , Zika virus , Animais , Humanos , Vírus da Febre do Vale do Rift/genética , Reação em Cadeia da Polimerase Multiplex , SARS-CoV-2/genética , Genômica , Teste para COVID-19RESUMO
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.
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Brucella , Brucelose , Animais , Bovinos , Feminino , Masculino , Gravidez , Criação de Animais Domésticos , Anticorpos Antibacterianos , Teorema de Bayes , Brucelose/epidemiologia , Brucelose/veterinária , Estudos Transversais , Quênia/epidemiologia , Gado , Fatores de Risco , Estudos SoroepidemiológicosRESUMO
Brucellosis is widely distributed in more than 170 countries around the world, where it poses a huge threat to animal husbandry and human health. Brucellosis is a worldwide re-emerging zoonotic disease that poses serious public health problems in many developing countries including Kenya. However, prevalence of brucellosis has not been determined in Baringo County, Kenya, yet there is a continuous movement of cattle resulting from trade and grazing, thus predisposing many herds to brucellosis infection. We investigated the sero-prevalence of brucellosis in humans and domestic ruminants: sheep, goats, cattle and camels among livestock keeping communities in Baringo County, Kenya. In addition, we analyzed the seropositive samples for molecular detection of Brucella species. The study adopted a cross-sectional survey using quantitative data collection methods. The diagnosis was carried out using a competitive enzyme-linked immunosorbent assay (c-ELISA) and the real-time PCR assays. The sero-prevalence of brucellosis among human blood samples was 0.6% (n = 4/640) in Baringo County. About 22.30% (n = 143/640) of animal blood samples examined tested positive for Brucella genus-specific ELISA test. Cattle had a high prevalence of 22.88% (n = 93/322) followed by camels 20.00% (n = 21/105), goats 15.48% (n = 24/155) and subsequently sheep at 8.62% (n = 5/58). Overall, 7.5% (n = 6/80) of the seropositive samples amplified with the genus-specific primers. Brucella melitensis was detected in one out of the six genus positive samples, while none amplified with the B. abortus target. Even though there was high prevalence of brucellosis among livestock in Baringo County, the highest prevalence was invariably noted in cattle, followed by camels, goats and sheep, respectively. Livestock keepers had low prevalence of brucellosis. This implies that there was low risk of transmission of brucellosis between livestock keepers and their livestock.
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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.
Assuntos
Brucella , Coinfecção , Coxiella burnetii , Febre do Vale de Rift , Vírus da Febre do Vale do Rift , Animais , Animais Selvagens , Brucella/genética , Búfalos , Coinfecção/epidemiologia , Coinfecção/veterinária , Coxiella burnetii/genética , Humanos , Quênia/epidemiologia , Vírus da Febre do Vale do Rift/genética , Estudos Soroepidemiológicos , ZoonosesRESUMO
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.