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      "description_narrative":["Tuberculosis (TB) is a major cause of disease and death globally. 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. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world."],
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      "title_narrative":["The CRASH-3 Trial: Tranexamic acid for the treatment of significant traumatic brain injury."],
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      "title_narrative":["MICA: Performance evaluation of a point-of-care whole blood viral load test (SAMBA) to optimize HIV treatment in resource-limited settings"],
      "description_narrative":["As of 2012, 9.7 million individuals were receiving antiretroviral therapy (ART) for treatment of HIV-1 infection in low- and middle-income countries. However, among patients receiving first-line ART, 20-30% will have a detectable viral load after 12 months. The long-term success of ART programmes is heavily dependent on accurate, available and timely viral load monitoring to document viral suppression or indicate the need for second line ART switch.    Existing HIV viral load assays require significant infrastructure and highly trained personnel to perform, thus only a few centralised laboratories are capable of viral load testing in most developing countries. Centralised testing leads to poor access to those in need, long turn-around times, delay of results and subsequent loss of patients, all of which lead to sub-optimal ART treatment outcomes, which can cause significant morbidity and mortality.  The University of Cambridge, in partnership with Diagnostics for the Real World, has developed an innovative point-of-care nucleic acid amplification test for the diagnosis monitoring the efficacy of HIV treatment by determining of the amount of circulating virus  is above or below the threshold for treatment failure. The SAMBA HIV-1 Semi-Q Test allows the patient to be tested and treated in the same visit, thus improving access and treatment outcomes. The plasma-based semi-automated (SAMBA I) assay has received product approval in Malawi, Kenya, Zimbabwe and Uganda and has been used for testing of over 35,500 patients at Médecins sans Frontières (MSF) sites in Malawi and Uganda to date.   The SAMBA HIV-1 Semi-Q Test has recently been improved to enable the use of small volume whole blood, using a patented method of filtration. This removes the need for plasma separation, thus increasing utility at lower cadre health clinics and reduces the time to result. In addition a fully automated SAMBA instrument system has been developed, called SAMBA II. The key aims of this proposal are: 1) integrate the whole blood SAMBA HIV-1 Semi-Q Test onto the fully automated SAMBA II instrument, 2) perform an evaluation in house, in Africa and in Europe to evaluate its perforce compared to another  CE-marked test and 3) submit for CE-mark. Although the SAMBA test will most likely be used in Africa, a CE-mark is required to allow it to be procured by NGO's.","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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      "description_narrative":["GCRF Foundation Infections 2016 to identify and validate biomarkers in urine from participants in Cameroon. That could indicate the presence of a viable, adult female Onchocerca volvulus worm in a patient suffering from onchocerciasis (river blindness).\n","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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      "reporting_org_narrative":["DEPARTMENT FOR BUSINESS, ENERGY & INDUSTRIAL STRATEGY"],
      "title_narrative":["Human Decoy Trap; operational and social acceptability of novel tool to improve surveillance and control of mosquitoes and other disease vectors"],
      "description_narrative":["Malaria infects over 200 million people every, mostly in sub-Saharan Africa. Nearly half a million people died from the disease in 2015, the majority of deaths being in children under the age of five. The malaria parasite is spread by infected mosquitoes and the most effective way to monitor the disease is to monitor populations of these mosquitoes. However, current tools for sampling malarial mosquitoes are time-consuming and labour intensive, making them expensive and difficult to standardize. Accordingly, data between countries and regions cannot be reliably compared. To solve this problem, we have developed a mosquito trap that exploits the blood-seeking behaviour of mosquitoes by mimicking the sensory stimuli that a mosquito follows when searching for a person to bite. These include the look, smell and temperature of warm-blooded hosts. We have incorporated these stimuli into a trap that lures mosquitoes towards it and then captures them when they land. Our project will test this \"Human Decoy\" Trap against current methods used in mosquito monitoring to determine whether the Human Decoy Trap can overcome the limitations of existing tools. We will evaluate if Human Decoy Trap catches are suitably similar to those of current traps in terms of numbers of mosquitoes and other important data related to malaria that can be extracted from mosquitoes caught by traps, such as the proportion of caught mosquitoes infected with malaria parasites. Over 90 countries, mostly low and middle income, are malaria-endemic. We will work in Burkina Faso, Benin and Cameroon, three West African countries where malaria causes thousands of deaths every year, but differing in intensity and seasonality of transmission and with different mosquito species involved. This will help us to understand whether there are differences in trap performance in a wide range of malaria settings. In addition, we will work with end-users of the trap, namely local communities, public health operatives and field technicians, to better understand their perspectives and needs regarding mosquito sampling and control. During the course of the project, we will use data we collect to optimize and improve the trap's performance and design. This will help us to develop a commercial prototype that is effective and acceptable to end-users, maximising the likelihood the trap will be adopted into the communities and sectors that need it the most. Longer-term, we envision a version of the Human Decoy Trap that can be deployed as a mosquito control tool. The most effective way of controlling malaria is to reduce the number of infective mosquito bites a person receives. This is currently achieved by providing people with insecticide-treated bed nets to protect them from bites whilst they sleep and spraying the walls inside houses thus killing mosquitoes that rest there. However, neither of these options protects people from mosquitoes that may bite them outdoors during the day or just before they go to bed at night. Data from this current project will be used to provide preliminary evidence for the suitability of the Human Decoy Trap as a control tool that is specifically targeted at malaria mosquitoes biting outdoors, which may also be effective against other species of mosquitoes that can carry other infectious diseases, such as dengue fever, chikungunya and Zika viruses. Such an improved sampling method would enhance the quality of data necessary for efficient targeting and evaluation of malaria control intervention activities and reduce the cost of collecting it. A successful outdoor mosquito control device would help to reduce the population of infected mosquitoes that cause malaria. Ultimately, the combined effect of these tools would be a reduction in the human suffering and death caused by malaria to millions of people every year and an improvement in the social and economic prospects of the 3.2 billion people living at risk of malaria.","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 GREENWICH"],
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      "title_narrative":["OODA GCRF and Newton Consolidation Accounts University of Exeter"],
      "description_narrative":["The GNCAs represent an additional allocation from BEIS designed to reinvest in excellent UKRI Global Challenges Research Fund (GCRF) and Newton Fund programmes and enable them to maximise development impact. This involves instances where funding can be utilized to 9 original grant objectives affected by the ODA review, or opportunities for new follow-on, knowledge exchange or impact activities. In either case, the funding is targeted to support research along the route to achieving economic or social impact in countries on the OECD DAC list.","Research and development activity contributing to the UK’s strategy to address key development challenges."],
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