Covid-19 and urban food security in Ghana during the third wave

While the effects of the COVID-19 pandemic on household food security have been documented, the intensity and forms of food insecurity in urban households in the Global South have not been adequately explored. This is despite the emerging consensus that impacts of the pandemic were more severe in urban than rural Africa. This paper addresses this knowledge gap by examining the relationship between pandemic precarity and food insecurity in Ghana’s urban areas during the COVID-19 pandemic in 2020. This study is based on the World Bank (WB) and Ghana Statistical Service (GSS) COVID-19 High-Frequency Phone Survey. Using a sub-sample of 1423 urban households, the paper evaluates household experiences of the pandemic. Our findings show that household demographic characteristics are not a major predictor of food insecurity. Economic factors, especially the impact of the pandemic on wage income and total household income, were far more important, with those most affected being most food insecure

Quantitative urban classification for malaria epidemiology in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p>Although sub-Saharan Africa (SSA) is rapidly urbanizing, the terms used to classify urban ecotypes are poorly defined in the context of malaria epidemiology. Lack of clear definitions may cause misclassification error, which likely decreases the accuracy of continent-wide estimates of malaria burden, limits the generalizability of urban malaria studies, and makes identification of high-risk areas for targeted interventions within cities more difficult. Accordingly, clustering techniques were applied to a set of urbanization- and malaria-related variables in Kisumu, Kenya, to produce a quantitative classification of the urban environment for malaria research.</p> <p>Methods</p> <p>Seven variables with a known or expected relationship with malaria in the context of urbanization were identified and measured at the census enumeration area (EA) level, using three sources: a) the results of a citywide knowledge, attitudes and practices (KAP) survey; b) a high-resolution multispectral satellite image; and c) national census data. Principal components analysis (PCA) was used to identify three factors explaining higher proportions of the combined variance than the original variables. A k-means clustering algorithm was applied to the EA-level factor scores to assign EAs to one of three categories: "urban," "peri-urban," or "semi-rural." The results were compared with classifications derived from two other approaches: a) administrative designation of urban/rural by the census or b) population density thresholds.</p> <p>Results</p> <p>Urban zones resulting from the clustering algorithm were more geographically coherent than those delineated by population density. Clustering distributed population more evenly among zones than either of the other methods and more accurately predicted variation in other variables related to urbanization, but not used for classification.</p> <p>Conclusion</p> <p>Effective urban malaria epidemiology and control would benefit from quantitative methods to identify and characterize urban areas. Cluster analysis techniques were used to classify Kisumu, Kenya, into levels of urbanization in a repeatable and unbiased manner, an approach that should permit more relevant comparisons among and within urban areas. To the extent that these divisions predict meaningful intra-urban differences in malaria epidemiology, they should inform targeted urban malaria interventions in cities across SSA.</p

A census-weighted, spatially-stratified household sampling strategy for urban malaria epidemiology

<p>Abstract</p> <p>Background</p> <p>Urban malaria is likely to become increasingly important as a consequence of the growing proportion of Africans living in cities. A novel sampling strategy was developed for urban areas to generate a sample simultaneously representative of population and inhabited environments. Such a strategy should facilitate analysis of important epidemiological relationships in this ecological context.</p> <p>Methods</p> <p>Census maps and summary data for Kisumu, Kenya, were used to create a pseudo-sampling frame using the geographic coordinates of census-sampled structures. For every enumeration area (EA) designated as urban by the census (n = 535), a sample of structures equal to one-tenth the number of households was selected. In EAs designated as rural (n = 32), a geographically random sample totalling one-tenth the number of households was selected from a grid of points at 100 m intervals. The selected samples were cross-referenced to a geographic information system, and coordinates transferred to handheld global positioning units. Interviewers found the closest eligible household to the sampling point and interviewed the caregiver of a child aged < 10 years. The demographics of the selected sample were compared with results from the Kenya Demographic and Health Survey to assess sample validity. Results were also compared among urban and rural EAs.</p> <p>Results</p> <p>4,336 interviews were completed in 473 of the 567 study area EAs from June 2002 through February 2003. EAs without completed interviews were randomly distributed, and non-response was approximately 2%. Mean distance from the assigned sampling point to the completed interview was 74.6 m, and was significantly less in urban than rural EAs, even when controlling for number of households. The selected sample had significantly more children and females of childbearing age than the general population, and fewer older individuals.</p> <p>Conclusion</p> <p>This method selected a sample that was simultaneously population-representative and inclusive of important environmental variation. The use of a pseudo-sampling frame and pre-programmed handheld GPS units is more efficient and may yield a more complete sample than traditional methods, and is less expensive than complete population enumeration.</p

Healthcare-seeking Behaviour for Common Infectious Disease-related Illnesses in Rural Kenya: A Community-based House-to-house Survey

Community surveys of healthcare-use determine the proportion of illness episodes not captured by health facility-based surveillance, the methodology used most commonly to estimate the burden of disease in Africa. A cross-sectional survey of households with children aged less than five years was conducted in 35 of 686 census enumeration areas in rural Bondo district, western Kenya. Healthcare sought for acute episodes of diarrhoea or fever in the past two weeks or pneumonia in the past year was evaluated. Factors associa-ted with healthcare-seeking were analyzed by logistic regression accounting for sample design. In total, 6,223 residents of 981 households were interviewed. Of 1,679 children aged less than five years, 233 (14%) had diarrhoea, and 736 (44%) had fever during the past two weeks; care at health facilities was sought for one-third of these episodes. Pneumonia in the past year was reported for 64 (4%) children aged less than five years; 88% sought healthcare at any health facility and 48% at hospitals. Seeking healthcare at health facilities was more likely for children from households with higher socioeconomic status and with more symptoms of severe illness. Health facility and hospital-based surveillance would underestimate the burden of disease substantially in rural western Kenya. Seeking healthcare at health facilities and hospitals varied by syndrome, severity of illness, and characteristics of the patient

Fermented Food for Life: Stories of Inspiration, Struggle & Success

The Fermented Food for Life” project aims to improve food and nutrition security by increasing local production, distribution and consumption of health-promoting probiotic fermented yoghurt in Kenya, Tanzania, and Uganda, targeting to reach 250,000 consumers in the three countries by its end in June 2018. A pro-poor value chain-based business model was identified as a common approach to achieve project’s main objective. In Uganda, over 100 production units of probiotic yoghurt are up and running across the whole country reaching at least 60,000 regular consumers. The project supported also the establishment of 58 production units in Tanzania and 37 in Kenya, producing in total around 14,000 litres of probiotic yoghurt per week. In Tanzania and Uganda, 56% of production units are owned by women, and 68% of all people involved in probiotic yoghurt production and sales are female. The project has also provided a unique opportunity for employment of rural youth involved in the distribution of yoghurt. Partners in project’s implementation include Heifer International, Jomo Kenyatta University of Agriculture and Technology, University of Western Ontario and Yoba for Life Foundation. The project is undertaken with the financial support of Canada’s International Development Research Centre (IDRC), www.idrc.ca and the Government of Canada, provided through Global Affairs Canada (GAC), www.international.gc.ca Collected here are stories about the Fermented Food for Life project

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

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

Preliminary Ground-Based Observation for the Soil Moisture Measurement Validation of ADEOS II-AMSR/AMSR-E

研究概要:AMSR-E(2002年3月打ち上げ予定)とAMSR (2002年11月打ち上げ予定)の土壌水分測定アルゴリズムの検証のために、モンゴル高原で地上検証用試験地の設定と検証のための準備観測(モニタリングと集中土壌水分・植物水分移動観測)を行った。試験地内の降雨分布および土壌水分と植物水分の分布には地域的な差異があることが分かると共に変化幅も検証に値するものであることが分かった

Healthcare-seeking Behaviour for Common Infectious Disease-related Illnesses in Rural Kenya: A Community-based House-to-house Survey

Community surveys of healthcare-use determine the proportion of illness episodes not captured by health facility-based surveillance, the methodology used most commonly to estimate the burden of disease in Africa. A cross-sectional survey of households with children aged less than five years was conducted in 35 of 686 census enumeration areas in rural Bondo district, western Kenya. Healthcare sought for acute episodes of diarrhoea or fever in the past two weeks or pneumonia in the past year was evaluated. Factors associated with healthcare-seeking were analyzed by logistic regression accounting for sample design. In total, 6,223 residents of 981 households were interviewed. Of 1,679 children aged less than five years, 233 (14%) had diarrhoea, and 736 (44%) had fever during the past two weeks; care at health facilities was sought for one-third of these episodes. Pneumonia in the past year was reported for 64 (4%) children aged less than five years; 88% sought healthcare at any health facility and 48% at hospitals. Seeking healthcare at health facilities was more likely for children from households with higher socioeconomic status and with more symptoms of severe illness. Health facility and hospital-based surveillance would underestimate the burden of disease substantially in rural western Kenya. Seeking healthcare at health facilities and hospitals varied by syndrome, severity of illness, and characteristics of the patient

Contraceptive method use trajectories among young women in Kenya: A qualitative study

Background Many young women experience important key life transitions during adolescence and early adulthood, such as initiation of sexual activity, first use of contraceptives, marriage, and childbirth. For young women to be able to plan and manage their lives, it is critical to understand how these life events intersect and shape their contraceptive decision-making. This study aims to explore young women's contraceptive method use trajectories, including the factors that influence contraceptive decision-making throughout adolescence and youth. Methodology In 2019, the Full Access, Full Choice project (FAFC), implemented by the University of North Carolina at Chapel Hill and the African Institute for Development Policy, conducted 30 in-depth interviews with young women aged 18–24 years in three counties in Kenya (Nairobi, Mombasa and Migori). Eligible respondents had used two or more modern contraceptive methods. Interview guides utilized a modified life history approach to capture details about respondents' contraceptive use and life experiences from the time they first used contraception until the time of interview.ResultsWe identified five separate contraceptive use trajectories based on the occurrence and timing of marriage, childbirth, and contraceptive method choice as well as various influences on contraceptive decision-making. The majority of respondents began their contraceptive journey by using male condoms or emergency contraception, but subsequent contraceptive decisions were varied across trajectories and influenced by different factors. For many women, the initiation of a non-coitally dependent method occurred after the birth of a child; for some, this was the first method used. Once women transitioned to using a non-coitally dependent method such as injectables or implants, many cycled through different methods to find one that had fewer side effects or provided the desired duration of protection. Discussion This study highlights the nuanced needs of young women throughout their adolescent and youth years in Kenya. This suggests that programs and policies need to encompass young women's diversity of experiences and motivations to best serve them

Detection of Anopheles stephensi mosquitoes by molecular surveillance, Kenya

The Anopheles stephensi mosquito is an invasive malaria vector recently reported in Djibouti, Ethiopia, Sudan, Somalia, Nigeria, and Ghana. The World Health Organization has called on countries in Africa to increase surveillance efforts to detect and report this vector and institute appropriate and effective control mechanisms. In Kenya, the Division of National Malaria Program conducted entomological surveillance in counties at risk for An. stephensi mosquito invasion. In addition, the Kenya Medical Research Institute conducted molecular surveillance of all sampled Anopheles mosquitoes from other studies to identify An. stephensi mosquitoes. We report the detection and confirmation of An. stephensi mosquitoes in Marsabit and Turkana Counties by using endpoint PCR and morphological and sequence identification. We demonstrate the urgent need for intensified entomological surveillance in all areas at risk for An. stephensi mosquito invasion, to clarify its occurrence and distribution and develop tailored approaches to prevent further spread