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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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      "title_narrative":["Development of a new tool for malaria mosquito surveillance to improve vector control"],
      "description_narrative":["Since the year 2000, controlling mosquitoes with insecticide-based interventions has led to a 37% reduction in malaria mortality globally. Nevertheless, malaria still caused 438 000 deaths in 2015, and further progress is being threatened by increasing levels of insecticide resistance in mosquito vectors. The global malaria community urgently needs new tools to monitor mosquito vector populations. Several aspects of mosquito demography and physiology are particularly crucial for planning and assessing vector control strategies.  Prime amongst these are determination of mosquito vector species and age structure.  Accurate species identification is required to confirm what vectors are responsible for transmission.  Mosquito age is a critical determinant of their transmission potential.  This is because the malaria parasite undergo a period of development within the vector before they become transmissible.  Additionally, measurement of insecticide resistance status is essential to assess how effectively vectors could be targeted by current frontline control methods such as Insecticide Treated Nets (ITNs) and spraying. Unfortunately, no methods are currently available  for rapid, large-scale and simultaneous measurement of these crucial mosquito vector demographic and physiological traits. This proposal aims to fill that gap by developing and validating a novel technology for high throughput, high precision surveillance of malaria vector populations in LMICs.   This project aims to develop such a tool for malaria vectors on the basis on strong existing partnerships with leading African malaria researchers, and world-class physical chemists and vector biologists in the UK.   Specifically, the technology is based on the measurement of molecular signature of the mosquito cuticle, which is the outer part of the insects, to predict key traits (species, age and insecticide resistance). Indeed, the composition and structure of the mosquito cuticle, similar to the mammalian skin, changes when the organism ages, it is different in different species, and it is altered in mosquitoes that are resistant to insecticides. Here, we propose to characterize the cuticular changes associated with the traits mentioned above to then make predictions on individual mosquitoes of unknown conditions. The proposed technology is rapid and cost effective as it is based on the measurement of the light absorbed by mosquitoes, a procedure that do not require any sample preparation nor chemical reagents, and it is readily performed in few seconds by a spectrophotometer. The spectra - corresponding to the light absorbed by individual mosquitoes - will be analysed by powerful computational analysis which will enable to estimate the mosquito traits.  We will follow a two-stage process starting with laboratory evaluation of mosquitoes at the University of Glasgow to build on our compelling pilot work on the use of Mid Infrared Spectroscopy (MIRS) coupled with artificial neural network (ANN).  After further optimization and methods development, we will transfer this technology to two of Africa's leading malaria vector research and control institutes where it will undergo further evaluation and application within a diverse range of mosquito vector populations.  We envision this will form the first steps of a pathway along which this technology can be transferred to LMICs for integration into a range of mosquito surveillance applications including programmes to eliminate malaria, and control of other mosquito-borne pathogens such as Zika and Dengue where effective solutions are desperately needed.","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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      "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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      "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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