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This will help share UK technical expertise, building capability in developing countries in designing and implementing waste management activities. CLiP works with partners across the Commonwealth to share expertise and find solutions to the environmental and socio-economic problems caused by litter in the marine environment. Travel and subsistence through ODA will directly act upon the mandate in the 25 Year Environment Plan to support developing nations to tackle plastic pollution. This in turn will help drive direct action towards the Sustainable Development Goals (SDGs) - in particular SDG14 Life Below Water - as well as elements of SDG 3 (good health and well-being for people), SDG 11 (sustainable cities and communities) and SDG 12 (responsible consumption and production). This funding will cover the travel and subsistence for additional participants from the other regions to take part in the regional conferences. The funding will be focused on those ODA-eligible countries that need it the most. Funding travel and subsistence for increased regional participation is a cost-effective way of maximising impact and reach of the regional conference on marine litter, which will support cooperation, information-sharing and solutions on one of the most widespread and critical problems facing our ocean today."], "participating_org_ref":["GB-GOV-7","GB-GOV-7"], "participating_org_type":["10","10","10"], "participating_org_role":["2","1","4"], "participating_org_narrative":["Department for Environment, Food, and Rural Affairs","Department for Environment, Food, and Rural Affairs","Cefas"], "activity_status_code":"4", "activity_date_type":["1","3","2","4"], "activity_date_iso_date":["2018-04-01T00:00:00Z","2020-03-31T00:00:00Z","2018-04-01T00:00:00Z","2020-03-31T00:00:00Z"], "contact_info_organisation_narrative":["Department for Environment, Food, and Rural Affairs"], "contact_info_department_narrative":["The Department for Environment, Food and Rural Affairs is the government department 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cardiovascular disease and cancer are responsible for the vast majority of deaths in all but the poorest low and middle income countries (LMICs). They are particularly rising in LMICs and are higher in many LMICs than in high income countries. A key driver of this health burden is poor quality nutrition, including diets high in energy dense and highly processed foods and low in fruit, vegetables and fibre. There are several factors that may contribute to poor diets, including poor conditions for growing, storing and transporting fruit and vegetables, and a reliance on relatively expensive food imports. In small island developing states (SIDS) the relationship between a reliance on food imports, poor nutrition and a high burden of chronic diseases is particularly apparent. Community-based agricultural food production initiatives are one possible approach to improving food and nutritional security and to reducing the risk of chronic diseases. They can also help to improve 'food sovereignty' by increasing the ability of populations to influence their own food systems in ways that are sustainable and promote health. Such initiatives may take several forms, but are owned, organised and managed locally, and produce either fresh or minimally processed food for local consumption. While the potential contribution of such initiatives is recognised, there is very little evidence available on what their impacts actually are in terms of health, social well-being, economics or the environment. There is an urgent need for improved evidence on their impacts, and this proposal is concerned with developing and testing methods to contribute towards filling this evidence gap. The proposal is designed to help establish a transdisciplinary research programme with the conceptual and methodological skills necessary to undertake robust evaluations of community-based food production initiatives in LMICs. The evaluation of the initiatives will include their contribution to promoting health and social wellbeing, their economic and environmental impacts, and their sustainability. The development work proposed here will be undertaken in two contrasting middle income SIDS, St Vincent and the Grenadines and Fiji. Both are actively engaged in promoting local food production for local consumption, and their well-defined geographical boundaries and relatively small size provide ideal settings to undertake development work. However, the overall goal is to develop a framework and methods that are readily adaptable and applicable to other LMIC settings in which nutritional insecurity is a major contributor to the risk of chronic diseases, including many settings in sub-Saharan African, where levels obesity and diabetes are already high and increasing. In this project we will update and expand existing evidence reviews on community-based food initiatives in LMICs. In the two chosen settings, we will develop and test research methods to investigate the current nutritional adequacy of local diets and the contribution of community-based food production, and find out who is involved in and supports local food production. We also aim to develop methods to estimate the environmental impacts such as on local water use and carbon emissions. Finally, we aim to determine the major challenges and successes in establishing and sustaining selected initiatives, and how barriers to success might be overcome. The findings will enable us to develop an evaluation framework and refine methods to design a programme of work to robustly evaluate and compare community-based food production initiatives in Africa, the Caribbean and Pacific from the perspective of their impacts on chronic disease risk, social and economic well-being and the environment.","The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. 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Such\nchanges in the climate system have direct effects on\nthe livelihoods, the economy, overall development\nand the very existence of many small island nations.\nUrgent action to build capacity for climate resilience is\ntherefore required.\nThe overall aim of CommonSensing is to use\nsatellite remote sensing applications to support three\nCommonwealth countries: Fiji, the Solomon Islands\nand Vanuatu achieve their goal of improved national\nresilience to climate change. The project’s main output\nis to provide evidence and data needed for these\nisland states to be able to apply to climate funding\nin collaboration with the Commonwealth Climate\nFinance Access hub with a much higher degree of\nsuccess than presently. This will allow these island\nstates to obtain the funding they need to protect\ncritical infrastructure and build resilience into their\neconomy to combat the growing effects of climate\nchange.\nCommonSensing will deliver impact in two main\nareas:\n• In terms of Earth Observation (EO) derived\nservices, CommonSensing will use EO data to\nprovide partners with access to vital information\nregarding disaster and climate risks to inform\nplanning, food security needs and impact on\nthe environment. This information will be readily\navailable to users through easily accessible\nservices.\n• In terms of sustainability and capacity\ndevelopment, partners aim to contribute to\nnational and regional technical capabilities to\ninform policy and secure funding for climate\nchange resilience programmes beyond the\nthree-year project. In addition, CommonSensing\nconsortium partners are committed to supporting\nthe long-term sustainability of the information\nservices they develop with the three partner\ncountries.","The overall aim of CommonSensing is to improve resilience towards climate change, including disaster risk reduction, and contribute to sustainable development in three selected Commonwealth Small Island Developing States (SIDS): Fiji, the Solomon Islands and Vanuatu. The project will combine earth observation data to provide stakeholders with access to important information regarding disaster risks (including disaster risk planning, food security, climate risk and other environmental concerns). This information will be accessible to beneficiaries through a web portal and mobile applications."], "participating_org_ref":["GB-GOV-13","GB-GOV-13","GB-GOV-EA31"], "participating_org_role":["1","2","3","4"], "participating_org_type":["10","10","10","71"], "participating_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY","DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY","UK SPACE AGENCY","SATELLITE APPLICATIONS CATAPULT"], "other_identifier_ref":["GB-GOV-13-GCRF-UKSA_FJ_SB_VU_UKSA-43"], "activity_status_code":"4", "activity_date_iso_date":["2018-01-02T00:00:00Z","2018-01-02T00:00:00Z","2020-12-31T00:00:00Z","2021-03-31T00:00:00Z"], "activity_date_type":["1","2","3","4"], "contact_info_organisation_narrative":["Department of Business Energy and Industrial Strategy"], "contact_info_department_narrative":["General enquiries"], "contact_info_email":["enquiries@odamanagement.org"], "contact_info_website":["https://www.gov.uk/government/publications/beis-official-development-assistance-research-and-innovation"], "contact_info_mailing_address_narrative":["Department of Business, Energy and Industrial Strategy, 4th Floor, 1 Victoria Street, SW1H 0ET"], "recipient_country_code":["SB","VU","FJ"], "recipient_country_percentage":[33.333333333333336,33.333333333333336,33.333333333333336], "sector_code":["43082"], "sector_vocabulary":["1"], "policy_marker_code":["1","5","6","7","8","10","11","12"], "policy_marker_significance":["0","1","0","2","0","2","0","0"], "policy_marker_vocabulary":["1","1","1","1","1","1","1","1"], "collaboration_type_code":"1", "default_flow_type_code":"10", "default_finance_type_code":"110", "default_aid_type_code":["C01"], "default_tied_status_code":"5", "budget_status":["1","1","1","1"], "budget_type":["1","1","1","1"], "budget_period_start_iso_date":["2018-04-01T00:00:00Z","2019-04-01T00:00:00Z","2020-04-01T00:00:00Z","2021-04-01T00:00:00Z"], "budget_period_end_iso_date":["2019-03-31T00:00:00Z","2020-03-31T00:00:00Z","2021-03-31T00:00:00Z","2022-03-31T00:00:00Z"], "budget_value":[747337.09,3750514.12,3439729.3,1710500.2], "budget_value_currency":["GBP","GBP","GBP","GBP"], "planned_disbursement_type":["1","1","2","1","2","2","1","1","1"], "planned_disbursement_period_start_iso_date":["2019-06-30T00:00:00Z","2020-10-01T00:00:00Z","2021-04-01T00:00:00Z","2021-07-01T00:00:00Z","2021-10-01T00:00:00Z","2022-01-01T00:00:00Z","2022-04-01T00:00:00Z","2022-07-01T00:00:00Z","2022-10-01T00:00:00Z"], "planned_disbursement_period_end_iso_date":["2021-03-31T00:00:00Z","2020-12-31T00:00:00Z","2021-06-30T00:00:00Z","2021-09-30T00:00:00Z","2021-12-31T00:00:00Z","2022-03-31T00:00:00Z","2022-06-30T00:00:00Z","2022-09-30T00:00:00Z","2022-12-31T00:00:00Z"], "planned_disbursement_value":[7484727.38,1563406.0,727380.2,489022.0,617481.27,900937.07,245275.78,245368.78,160000.0], "planned_disbursement_provider_org_ref":["GB-GOV-13","GB-GOV-13","GB-GOV-13","GB-GOV-13","GB-GOV-13","GB-GOV-13","GB-GOV-13","GB-GOV-13","GB-GOV-13"], "planned_disbursement_provider_org_type":["10","10","10","10","10","10","10","10","10"], "planned_disbursement_provider_org_narrative":["UK - 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In 2015, WHO estimated there were 9.6 million TB cases and 1.5 TB deaths. Nearly 500,000 of these cases were resistant to two or more of the main drugs used to treat TB. New drugs, and combinations of drugs, are being developed to treat tuberculosis, as are new vaccines that may protect against disease in adults. Quantifying the burden of TB is fundamental to understanding its global epidemiology and for making appropriate resource allocation decisions. Most estimates of new TB case numbers each year rely strongly on the number of cases reported by countries in that year to WHO. Unfortunately, one in three TB cases are thought to go either undetected or unreported, so the number of cases reported underestimates the number of new cases. While one can correct for this, it is hard to know exactly how much to adjust the reported numbers. Some countries have good systems for recording causes of deaths, which can be used to estimate the number of deaths caused by TB. Increasingly, large and expensive prevalence surveys are being used to estimate the number of people with active disease in a population. These estimates are less subject to bias, but measure a different quantity. Little work has explored the best way of combining these three data sources. A major goal of this work is to use mathematical transmission models for burden estimation and provide a unified framework for all data. These models yield the number of new cases, deaths, and also the prevalence of disease. They explicitly represent disease transmission and so introduce a dependence between the number of new cases in different years. These models involve parameters evidenced from previous epidemiological work, but must be calibrated to learn from data on TB reports, deaths and prevalence. Calibration means adjusting imperfectly known model parameters in order to match observed model outputs to the data. This process provides a model that may be used to make predictions about burden, but may also teach us something about the underlying processes. Many of the parameters concerning the epidemiology and disease course of TB are quite uncertain, and this uncertainty is rarely represented fully in models needing calibration, but will be done in this project using statistical techniques that also allow comparison of different models' performance. TB burden estimation and calibration of transmission models are almost always carried out on a country-by-country basis. Many parameters describing disease progression are likely to be similar in different countries, even if their exact values differ for unknown reasons. Hierarchical modelling techniques allow such parameters to be correlated between countries. This can improve precision, particularly for countries with little data, as estimates can be informed by data from neighbouring countries. I will explore these techniques for the transmission model, and also in statistical modelling aiming to account for the observed patterns of drug-resistance. The transmission model will ultimately be extended to include different types of drug resistance. As new treatments and vaccines emerge, those with responsibility for public health will want to understand the potential impact these new technologies can have in terms of gains in health, and changes in spending. Producing cost-effectiveness and budget impact evidence requires a model that includes transmission, in order to account for indirect benefits accrued by avoiding secondary cases. We will use our model to provide guidance to decision-makers seeking to maximise health gain with limited resources. We will also analyse sources of uncertainty in the model to identify future research that would have most value in increasing the precision of burden estimates and in reducing decision uncertainty around the introduction of new interventions.","The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. 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