49 research outputs found

    Enabling modernisation, marginalising alternatives? Kenya's agricultural policy and smallholders

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    To address intensifying social and environmental challenges, development policy must learn from inclusions and exclusions of past discourses. We analyse Kenya's post-colonial agricultural policy discourse. Our analysis reveals a near-exclusive focus on the promotion of agricultural modernisation based on industrial farm inputs, a bureaucratic state and/or ‘the liberalised market’. It was with this thrust to modernise that smallholders (and other farmers) were generally seen as aligning. Smallholders' agency to diverge from modernisation was thus marginalised in the policy discourse. Overall then, the promotion of diverse agroecological and other farmer-led directions of development was largely missing from Kenya's policy landscape

    Pan-resistome characterization of uropathogenic Escherichia coli and Klebsiella pneumoniae strains circulating in Uganda and Kenya, isolated from 2017-2018

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    Funding: The Holistic Approach to Unravel Antibacterial Resistance in East Africa is a 3-year Global Context Consortia Award (MR/S004785/1) funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care. The award is also part of the EDCTP2 program supported by the European Union.Urinary tract infection (UTI) develops after a pathogen adheres to the inner lining of the urinary tract. Cases of UTIs are predominantly caused by several Gram-negative bacteria and account for high morbidity in the clinical and community settings. Of greater concern are the strains carrying antimicrobial resistance (AMR)-conferring genes. The gravity of a UTI is also determined by a spectrum of other virulence factors. This study represents a pilot project to investigate the burden of AMR among uropathogens in East Africa. We examined bacterial samples isolated in 2017–2018 from in- and out-patients in Kenya (KY) and Uganda (UG) that presented with clinical symptoms of UTI. We reconstructed the evolutionary history of the strains, investigated their population structure, and performed comparative analysis their pangenome contents. We found 55 Escherichia coli and 19 Klebsiella pneumoniae strains confirmed uropathogenic following screening for the prevalence of UTI virulence genes including fimH, iutA, feoA/B/C, mrkD, and foc. We identified 18 different sequence types in E. coli population while all K. pneumoniae strains belong to ST11. The most prevalent E. coli sequence types were ST131 (26%), ST335/1193 (10%), and ST10 (6%). Diverse plasmid types were observed in both collections such as Incompatibility (IncF/IncH/IncQ1/IncX4) and Col groups. Pangenome analysis of each set revealed a total of 2862 and 3464 genes comprised the core genome of E. coli and K. pneumoniae population, respectively. Among these are acquired AMR determinants including fluoroquinolone resistance-conferring genes aac(3)-Ib-cr and other significant genes: aad, tet, sul1, sul2, and cat, which are associated with aminoglycoside, tetracycline, sulfonamide, and chloramphenicol resistance, respectively. Accessory genomes of both species collections were detected several β-lactamase genes, blaCTX-M, blaTEM and blaOXA, or blaNDM. Overall, 93% are multi-drug resistant in the E. coli collection while 100% of the K. pneumoniae strains contained genes that are associated with resistance to three or more antibiotic classes. Our findings illustrate the abundant acquired resistome and virulome repertoire in uropathogenic E. coli and K. pneumoniae, which are mainly disseminated via clonal and horizontal transfer, circulating in the East African region. We further demonstrate here that routine genomic surveillance is necessary for high-resolution bacterial epidemiology of these important AMR pathogens.Publisher PDFPeer reviewe

    Epidemiology of Microbial Keratitis in Uganda: A Cohort Study.

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    Purpose: To describe the epidemiology of Microbial Keratitis (MK) in Uganda.Methods: We prospectively recruited patients presenting with MK at two main eye units in Southern Uganda between December 2016 and March 2018. We collected information on clinical history and presentation, microbiology and 3-month outcomes. Poor vision was defined as vision < 6/60).Results: 313 individuals were enrolled. Median age was 47 years (range 18-96) and 174 (56%) were male. Median presentation time was 17 days from onset (IQR 8-32). Trauma was reported by 29% and use of Traditional Eye Medicine by 60%. Majority presented with severe infections (median infiltrate size 5.2 mm); 47% were blind in the affected eye (vision < 3/60). Microbiology was available from 270 cases: 62% were fungal, 7% mixed (bacterial and fungal), 7% bacterial and 24% no organism detected. At 3 months, 30% of the participants were blind in the affected eye, while 9% had lost their eye from the infection. Delayed presentation (overall p = .007) and prior use of Traditional Eye Medicine (aOR 1.58 [95% CI 1.04-2.42], p = .033) were responsible for poor presentation. Predictors of poor vision at 3 months were: baseline vision (aOR 2.98 [95%CI 2.12-4.19], p < .0001), infiltrate size (aOR 1.19 [95%CI 1.03-1.36], p < .020) and perforation at presentation (aOR 9.93 [95% CI 3.70-26.6], p < .0001).Conclusion: The most important outcome predictor was the state of the eye at presentation, facilitated by prior use of Traditional Eye Medicine and delayed presentation. In order to improve outcomes, we need effective early interventions

    The Livestock Sub-sector in Kenya’s NDC: A scoping of gaps and priorities

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    Under the Paris Agreement, countries should update their Nationally Determined Contribution (NDC) every five years, with progressive ambition in each new submission. Kenya plans to review and revise its NDC in June 2020. The State Department for Livestock has undertaken a stock-taking exercise with support from UNIQUE forestry and land use, CCAFS and GRA. This report summarizes the main findings and recommendations for the livestock sub-sector contribution to enhanced climate change ambition. The livestock sub-sector is well aligned with Kenya‘s comprehensive policy framework: The livestock sub-sector is critical to achieving Kenya’s development objectives, including the Big Four Agenda and the Agriculture Sector Growth and Transformation Strategy (ASGTS, 2019-2029). The prioritization exercise that informed the ASGTS highlighted dairy, beef, sheep/goat, poultry and camel as being among Kenya’s 13 value chains with high potential for agricultural transformation and are central to achieving the objectives of the three ASGTS anchors. The Kenya Climate-Smart Agriculture Strategy and Implementation Framework (KCSAIF) sets out clear actions that are in line with livestock sub-sector priorities. With the exception of the dairy industry where some progress has been made, implementation of the KCSAIF in different live-stock industries (e.g., beef, sheep, goats, poultry) is in its early stages. The livestock sub-sector is central to Kenya’s climate change ambitions: Livestock is the largest source of GHG emissions in the agricultural sector, accounting for over 50% of GHG emissions in the Second National Communication, mainly due to enteric fermentation. Trends in livestock GHG emissions are also key drivers of the business as usual (BAU) scenario in Kenya’s first NDC. The projections underlying the BAU scenario in the first NDC assumed 1% annual average growth in enteric fermentation emissions from 2010 to 2030. Official livestock population data combined with IPCC 2006 Tier 1 emission factors show that from 2000 to 2018, enteric fermentation emissions in fact increased by 8.5% per year, and have exceeded the BAU projections in every year since 2007. Assuming annual growth of 3.34%, livestock enteric fermentation emissions in 2030 could exceed 33 Mt CO2e, which is more than double the estimated emissions in 2010. Increasing livestock GHG emissions are mainly driven by rising demand for meat and milk due to increasing population, urbanization and rising incomes. As other sectors decarbonize, agricultural emissions – led by livestock emissions – will become more important. Livestock can also contribute to GHG mitigation. A Dairy NAMA has been proposed, with an estimated mitigation potential of 8.8 Mt CO2e over a 10-year period. The Dairy NAMA has not yet been implemented due to lack of financial support. Other livestock industries also have mitigation potential and there are strong synergies with adaptation. However, the technical feasibility, costs and benefits have not yet been assessed in detail. The majority of non-dairy cattle and small ruminants are raised in the arid and semi-arid areas, where adaptation to climate change and food security are national priorities. Livestock sub-sector contributions to enhanced NDC: NDCs can be enhanced on the basis of a stocking taking of trends, policies and measures, and actions of sub-national and non-state actors in the sector; by updating assumptions and analysis; by ensuring alignment of the NDC with sector development objectives; by ensuring complete coverage of sectors and sub-sectors; and by ensuring that adaptation priorities, policies and plans are appropriately reflected. Based on a stock-taking, the following pathways to NDC enhancement have been identified in the livestock sector. In addition to pursuing financing of the Dairy NAMA, in line with the recommendation in the Mitigation Technical Analysis Report, during the 2018-2022 National Climate Change Action Plan implementation period the livestock sub-sector should build expertise and improve data for mitigation action, while focusing climate change efforts on adaptation. In particular, actions to enhance mitigation ambition and promote adaptation actions are proposed in the following four areas. (1) In-depth assessment and identification of adaptation and mitigation options. This will contribute to identification of feasible livestock sub-sector climate actions for inclusion in the third NDC. •Documentation of vulnerability to climate change and extreme events by livestock in different production systems and in grasslands, for evidenced based development of policies and measures in the livestock sub-sector. •In-depth feasibility assessment in each production system for each livestock species for upscaled implementation of key adaptation and mitigation strategies. •Inventory of domestic (national and county government, non-government, private sector) and internationally-supported initiatives that promote key adaptation and mitigation strategies. •Stakeholder-led identification of adaptation and mitigation initiatives for upscaling. (2) Develop a Livestock Sub-Sector Climate Change Action Plan.T his will support coordination in the sub-sector and assist in resource mobilization for enhanced climate action. •Engage stakeholders and key supporting institutions in the main initiatives in each production system for each species to identify actions to support upscaled implementation of key adaptation and mitigation actions in the livestock sub-sector and ensure coordination with stakeholders. •Develop strategies for the national government to promote climate-smart agriculture (CSA) in the livestock sub-sector, including: -strategies to ensure that these actions are mainstreamed in the workplans of state department for livestock divisions and units and related semi-autonomous government agencies; -strategies to ensure that these actions are mainstreamed in the work of other relevant MDAs and county governments; -strategies to support non-government and private sector actors to address sector support needs; -coordination mechanisms to engage the key stakeholders in each strategy. (3) Improve monitoring and evaluation of livestock sub-sector climate actions. This will support sector coordination, enable tracking of non-state climate actions and support UNFCCC reporting•Design livestock CSA monitoring & evaluation (M&E) system to provide and track information on: -Progress in implementing Livestock Sub-sector Climate Change Action Plan; -KCSAIF M&E framework indicators; -Information required by sub-sector stakeholders; -Other indicators as required by national measurement, reporting and verification (MRV) systems (e.g. adaptation and mitigation action registry). (4) Improve MRV of livestock GHG emissions. This will improve national capacities for MRV to support implementation and tracking of climate actions. •GHG inventory compilation: -Continue to compile and submit the Tier 2 dairy cattle GHG inventory on an annual basis; -Expand application of Tier 2 method to the other livestock species; -Continue to build state department for livestock capacity for GHG inventory compilation. •GHG inventory improvement: -Collaborate with national and county stakeholders to improve livestock administrative statistics in line with GHG inventory data needs; -Strengthen county capacities for improved livestock data collection. •MRV system improvement: -Revise NDC GHG BAU projections for livestock GHG emissions based on Tier 2 emission factors and revised livestock population time series in view of the 2019 livestock census results; -Develop models for tracking change in emission intensity of livestock production in line with key adaptation and mitigation strategies. This report summarizes the state of knowledge and action in the livestock sub-sector regarding adaptation and mitigation, highlighting gaps and priorities for future policy developments. The first chapter provides a general overview of the sector’s position in relation to climate change in Kenya. The following four chapters review priorities for adaptation and mitigation for each of the main livestock species (dairy cattle, non-dairy cattle, small ruminants and poultry). The final chapter assesses policy and institutional issues, and provides recommendations for the State Department for Livestock, with a focus on near-term actions to increase the livestock sector’s support to enhanced climate change ambitions

    Emerging insights and lessons for the future

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    This concluding chapter summarises the key findings of the ‘Pathways’ transformative knowledge network (TKN), its contributions to the ‘sustainability transformations’ literature and the lessons and implications for internationally networked, transdisciplinary research projects in the future. It revisits the theoretical anchors and methodological anchors introduced in Chapters 2–4, and draws on insights from the TKN from individual hubs in each of these areas, pointing to experiences both during the project and after its formal conclusion. It discusses the approaches used to foster cross-learning and evaluation in the project, and describes the single-, double- and triple-loop learning that this enabled. The chapter provides a deeper understanding of ‘transformative pathways to sustainability’ and the role that science and research can play in fostering them, not only through formal research outputs but also the tacit and experiential knowledge and the relationships that they can foster. The chapter closes by offering lessons and recommendations for researchers, funders, policy-makers, managers and practitioners with an interest in enhancing the contribution of social science and transdisciplinary research to the transformative agenda of the Sustainable Development Goals.Fil: Ely, Adrian. University of Sussex; Reino UnidoFil: Marin, Anabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martin. Escuela de Economia y Negocios. Centro de Investigaciones Para la Transformacion.; ArgentinaFil: Marshall, Fiona. University of Sussex; Reino UnidoFil: Apgar, Marina. No especifíca;Fil: Eakin, Hallie. Arizona State University; Estados UnidosFil: Pereira, Laura. No especifíca;Fil: Charli Joseph, Lakshmi. Universidad Nacional Autónoma de México; MéxicoFil: Siquieros Garcia, Mario. Universidad Nacional Autónoma de México; MéxicoFil: Yang, Lichao. No especifíca;Fil: Chengo, Victoria. No especifíca;Fil: Abrol, Dinesh. No especifíca;Fil: Kushwaha, Pravin. No especifíca;Fil: Hackett, Edward. No especifíca;Fil: Navarrete, David Manuel. No especifíca;Fil: Mehrotra, Ritu Priya. No especifíca;Fil: Atela, Joanes. No especifíca;Fil: Mbeva, Kennedy. No especifíca;Fil: Onyango, Joel. No especifíca;Fil: Olsson, Per. No especifíca

    Microbiome sharing between children, livestock and household surfaces in western Kenya

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    The gut microbiome community structure and development are associated with several health outcomes in young children. To determine the household influences of gut microbiome structure, we assessed microbial sharing within households in western Kenya by sequencing 16S rRNA libraries of fecal samples from children and cattle, cloacal swabs from chickens, and swabs of household surfaces. Among the 156 households studied, children within the same household significantly shared their gut microbiome with each other, although we did not find significant sharing of gut microbiome across host species or household surfaces. Higher gut microbiome diversity among children was associated with lower wealth status and involvement in livestock feeding chores. Although more research is necessary to identify further drivers of microbiota development, these results suggest that the household should be considered as a unit. Livestock activities, health and microbiome perturbations among an individual child may have implications for other children in the household
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