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      "description_narrative":["For the majority of cancers, early detection results in better survival. Oral cancer is one of the few cancers that is visible and many of these cancers are preceded by a potentially malignant lesion where medical intervention can prevent the development of cancer. Taken together, oral cancer presents an opportunity for early detection. However, identifying which oral lesion has a propensity to become oral cancer is not straightforward without specialised training and this problem is confounded by the lack of specialists who are trained in this expertise particularly in low- and middle-income countries, where the majority of oral cancers are diagnosed. One innovative approach to overcome this is to develop an artificial intelligence algorithm to classify oral lesions into those that are benign and those that are potentially malignant or are occult cancer so that patients can be triaged accordingly to receive appropriate clinical management. In this project, we propose to work within a multi-disciplinary, international team to collate a library of images from existing and prospective collections that will facilitate the development of an artificial intelligence algorithm that will be tested and validated. The outcome of this project will pave the way for further rigorous testing, development of an App incorporating this automated tool and clinical validation for the early detection of oral cancer. The development of an automated tool for the classification of oral lesions will facilitate the identification of patients most at risk to develop oral cancer so that these individuals can be managed appropriately. This project is particularly impactful in the low- and middle-income countries as the majority of the global burden of oral cancer is found in these countries.","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. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
      "participating_org_ref":["GB-GOV-13","GB-COH-RC000346","GB-COH-RC000346"],
      "participating_org_role":["1","2","3"],
      "participating_org_type":["10","15","15"],
      "participating_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY","MEDICAL RESEARCH COUNCIL","MEDICAL RESEARCH COUNCIL"],
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      "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"],
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      "reporting_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY"],
      "title_narrative":["Surveys for Urban Equity: getting, and using, the data needed to respond to neglected non-communicable diseases in urban areas in LMICs"],
      "description_narrative":["Non-communicable diseases (NCD) are a major public health issue in South Asia (S Asia), accounting for 60% of deaths. Urbanisation is a key driver, increasing mental stress and injuries and risk factors such as tobacco use, poor diet and inadequate physical activity. Public health decision-makers in LMICs need unbiased, precise and accessibly-presented data to inform equitable urban development. Nationally representative surveys are the main data source used to inform decision-making in LMICs, e.g. Demographic and Health Surveys (DHS) and STEPS NCD Risk Factor Surveillance are used in over 90 LMICs. This approach has many problems: it excludes unofficial poor settlements and peri-urban areas beyond administrative boundaries; definitions of a 'household' overlook multiple occupancy by poor urbanites; current methods for ranking wealth are not sensitive to urban poverty; and NCDs currently assessed in these surveys do not include injuries and mental ill-health, conditions that disproportionately affect the urban poor. These methodological constraints leave policy makers with no way of understanding or responding to the NCD burden and inequities found within urban areas in LMICs. Furthermore, the way data is currently presented - in long wordy reports - undermines decision-makers' ability to find and interpret data for planning and managing health programmes. We will capitalise on existing partnerships and develop new ones, to i) identify and test questions on mental health and injuries, ii) test cheap and efficient novel methods to reduce bias in urban surveys iii) explore alternative approaches to defining households, measuring and ranking wealth iv) develop data visualisation tools to support decision-makers' use of survey data. We will conduct this foundation work in Nepal, Bangladesh and Vietnam as their different urban characteristics increase our works applicability to other LMICs and we have existing strong partnerships. We will hold two meetings and facilitate ongoing interaction with international and national bodies to share expertise and build capabilities on the novel survey methods, measures of wealth and NCDs, data visualisation and use of data to address urban inequities.  We will conduct a systematic search of questionnaires and draw on our own work assessing injuries and mental health to identify the best questions for LMIC urban areas. We will finalise the questionnaire in collaboration with government stakeholders after checking its comprehensibility in urban slums. We will pilot our novel survey sampling and mapping methods in Kathmandu, where our initial pilot of these methods was curtailed by the 2015 earthquake. Our novel methods use satellite imagery, mobile phone and census data, to identify the entire urban population including those not captured by the census. Once sampled, we will use a web-based app to accurately map communities. Smaller feasibility studies of the methods and developed questionnaire will be conducted in Hanoi and Dhaka. We will explore household types and identify wealth indicators in urban slums. Using our pilot data, we will explore associations between household consumption, assets and income to develop an appropriate measure of urban wealth. In each country, we will assess the extent to which data is used in urban planning and management through interviews with decision-makers. Through the establishment of communities of practice within municipalities, we will co-produce appropriate data visualisation tools to support planning and management. This foundation grant has the potential to i) transform survey methods used in all LMICs, enabling more accurate assessment of health inequities in urban areas ii) provide questions on mental health and injuries for use in other surveys in LMICs, and iii) ensure data informs the health-sector response to NCDs in LMICs.","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. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
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      "participating_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY","MEDICAL RESEARCH COUNCIL","MEDICAL RESEARCH COUNCIL","UNIVERSITY OF LEEDS"],
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      "default_lang":"en",
      "iati_identifier":"GB-GOV-13-GCRF-MR-C-MRFA-NCD2016MR-P025188-1",
      "reporting_org_ref":"GB-GOV-13",
      "reporting_org_type_code":"10",
      "reporting_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY"],
      "title_narrative":["Analysing the policy and governance environment for NCD control, and identifying potential policy options."],
      "description_narrative":["The Non-Communicable Diseases (NCDs) have emerged as the most important global threat to human health and wellbeing. Four major NCDs - heart disease, cancers, diabetes, respiratory diseases - cause the deaths of 38 million people every year, of whom 16 million die prematurely (under the age of 70 years). These diseases cause chronic illness and disability and are a source of suffering and financial hardship for individuals, families, communities and health systems struggling to provide continuous care for people with long-term health problems. The NCDs affect populations across the globe - and they are now the leading cause of death in many low and middle income countries.   Many of these diseases are driven by exposure to commercial products - tobacco, alcohol, highly processed foods (including the so-called 'junk foods') which have high levels of salt, sugar and/or trans-fats. Evidence shows that limiting exposure to these products is likely to bring health benefits, but it is often very difficult for individuals to sustain 'healthy behaviours' over their lifetime. Evidence-informed prevention strategies most likely to bring benefit to the largest numbers of people include: regulating exposure, e.g. taxation on products known to be health-reducing, such as sugary drinks; restricting access, e.g. no sales of tobacco to children, non-smoking zones in public spaces; or reformulating products to make them less likely to cause harm, e.g. lowering the salt content of processed foods. Such strategies, when implemented well, can have a significant impact on improving population health.   However, Governments face many challenges in implementing these policies - for example, there may be resistance from strong and powerful commercial companies that have a vested interest in selling their products. Moreover, in many countries, there is little policy experience in tackling the NCDs.   In this project we propose to undertake detailed policy analyses to identify acceptable and feasible options for Governments in both low- and middle-income countries to tackle the growing burden of NCDs in their countries. Our work will focus on three policy areas - control of sugar, salt and trans-fats in processed foods. We will work with researchers in Afghanistan, Bangladesh, Iran, Nepal, Pakistan, Tunisia and Vietnam to identify how the Government in each country is currently tackling NCDs. We will then map out the influences on policy options operating in each country. Such influences are likely to include the role of powerful stakeholders such as the food producing and selling industries, the media, the medical establishment, the Ministry of trade, etc. We will also identify whether any civil society groups (in some countries this might mean, for example, groups of parents concerned about junk-food marketing to children; in other countries it will include groups of patients suffering from diet-related NCDs such as diabetes) are working on policy issues. We will conduct interviews with key stakeholders to better understand the opportunities for seeing effective policy implemented for controlling sugar, salt and/or trans-fats, as well as identifying the challenges and barriers to putting effective policy options into operation.   This kind of health analysis requires a specific skill set which is not common in many countries. As part of our project we will therefore establish and strengthen the capacity of a network of researchers from all 8 countries (including the UK), who will support each other to carry out the analyses and interpret the findings. We will foster cross-learning of policy successes between different countries. In addition, we will promote engagement and dialogue with a wide variety of stakeholders in each country throughout the lifetime of the project in order to ensure that the findings of the research carry meaning and weight in policy decisions to improve population health both in the 7 research countries and beyond.","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. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
      "participating_org_ref":["GB-GOV-13","GB-COH-RC000346","GB-COH-RC000346"],
      "participating_org_role":["1","2","3"],
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      "participating_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY","MEDICAL RESEARCH COUNCIL","MEDICAL RESEARCH COUNCIL"],
      "activity_status_code":"4",
      "activity_date_iso_date":["2017-03-01T00:00:00Z","2017-07-01T00:00:00Z","2019-02-28T00:00:00Z","2019-12-31T00:00:00Z"],
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      "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"],
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      "default_lang":"en",
      "iati_identifier":"GB-GOV-13-FUND--GCRF-MR_R01910X_1",
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      "reporting_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY"],
      "title_narrative":["A Network for Studying Psychological Resilience in Low and Middle-Income Countries (NESP)"],
      "description_narrative":["Vulnerability to or resilience to the commonest mental health disorders (depression, anxiety, drug and alcohol misuse) is related to the combination of genetic susceptibility, early life factors and an individual's current environment. Studies, over 95% of which have been confined to high income countries (HICs), have confirmed the importance of genes, development and adult environment. However, very little is known of these factors in low and middle-income countries (LMICs), where the burden of such common mental health disorders is even more substantial than in HICs.  Here we propose a powerful network of global leaders to analyse the key factors in three contrasting LMIC settings in three regions of the world, Nepal, Malawi and Costa Rica. This will enable us systematically to determine the processes leading to vulnerability or resilience to common disorders of mental health and exploit this knowledge, enabled by globally-leading data sciences and within-country expertise, to develop specific approaches to reinforce resilience and support prevention, diagnosis and treatment.  Our approach is highly multidisciplinary, combining genetic, clinical and social sciences expertise to provide a comprehensive view of an individual's genetics, development and environment. We will combine this expertise with world-leading informatics capacity to create a network for the study of psychological resilience across diverse environments and economies.","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. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
      "participating_org_ref":["GB-GOV-13","GB-COH-RC000346","GB-COH-RC000346"],
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      "contact_info_email":["enquiries@odamanagement.org"],
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      "reporting_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY"],
      "title_narrative":["Identifying Depression Early in Adolescence (IDEA) King's-Brazil-Nepal-Nigeria network"],
      "description_narrative":["Depression is a common mental disorder that will affect up to one out of five people around the world during their lifetimes and tends to start in adolescence. Depression is an especially debilitating mental illness because it often begins early in life and has a chronic course with many depressive episodes occurring throughout one's lifetime. Many people lack access to depression care and this is especially true in the world's poorest countries. Our proposed collaboration aims to bring a high-income country's expertise in research, where most of the scientific knowledge about depression and other mental health problems has been produced, to developing countries, where 9 out of 10 children and adolescents live. This collaboration between King's College London in the UK and researchers from Brazil, Nepal and Nigeria intends to find new ways to identify which adolescents are at risk of depression, what protects young people from developing depression, and are these factors the same or different in these contrasting contexts. Such information is crucial to help us understand how to intervene early in a range of settings to prevent a lifetime of suffering.   In order to achieve this, we propose to do the following: First, we will bring together researchers with different types of expertise from high (UK), middle (Brazil and Nigeria) and low (Nepal) income countries to reach a consensus about how to measure risk and protective factors for depression in comparable ways among adolescents in these different countries. We will then draw upon existing datasets of youth who have participated in research at multiple time points during their childhood and adolescence to run initial tests to see whether similar or different factors predict the development of depression in each country. This collaborative network will then apply for funding to conduct a new research project to assess much larger numbers of adolescents in each country with the consensus measures to identify the biological, social, psychological, and environmental factors that predict which adolescents will develop depression and which will not in each of these settings. Finally, we will scope out potential gaps in equipment, expertise, and policies in each country so that we know what needs to be put in place before such a large-scale research project can be successfully conducted. In order to begin the process of rectifying these gaps, we will deliver online training and offer hands-on apprenticeships to increase the skills of researchers in Brazil, Nepal and Nigeria to enable them to effectively conduct the research themselves.  Ultimately, this research will generate new knowledge on how to identify and prevent depression among youth, which would substantially decrease the personal, social and economic costs associated with the disorder in these countries and around the globe.","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. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
      "participating_org_ref":["GB-GOV-13","GB-COH-RC000346","GB-COH-RC000346"],
      "participating_org_role":["1","2","3"],
      "participating_org_type":["10","15","15"],
      "participating_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY","MEDICAL RESEARCH COUNCIL","MEDICAL RESEARCH COUNCIL"],
      "activity_status_code":"4",
      "activity_date_iso_date":["2018-02-01T00:00:00Z","2018-02-01T00:00:00Z","2019-01-31T00:00:00Z","2019-01-31T00:00:00Z"],
      "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"],
      "activity_scope_code":"3",
      "recipient_country_code":["NP","BR","NG"],
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      "sector_code":["12182"],
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      "policy_marker_code":["1","5","6","7","8","10","11","12"],
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      "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":["D02"],
      "default_tied_status_code":"5",
      "budget_status":["1"],
      "budget_type":["1"],
      "budget_period_start_iso_date":["2018-04-01T00:00:00Z"],
      "budget_period_end_iso_date":["2019-03-31T00:00:00Z"],
      "budget_value":[141314.0],
      "budget_value_currency":["GBP"],
      "capital_spend_percentage":0.0,
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      "transaction_date_iso_date":["2021-09-30T00:00:00Z","2019-03-31T00:00:00Z","2018-02-01T00:00:00Z"],
      "transaction_value":[-1708.4,141314.0,141314.26],
      "transaction_value_currency":["GBP","GBP"],
      "transaction_value_date":["2021-09-30T00:00:00Z","2019-03-31T00:00:00Z","2018-02-01T00:00:00Z"],
      "hierarchy":1,
      "transaction_value_usd":[-2344.7922406041207,186111.25196740677,197408.22173174177]
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}