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Grand Challenges is a family of initiatives fostering innovation to solve key global health and development problems. Each initiative is an experiment in the use of challenges to focus innovation on making an impact. Individual challenges address some of the same problems, but from differing perspectives.

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Creating Spirulina Microentrepreneurs to Solve Malnutrition

Sailendra AppanahEnerGaia Bangladesh Ltd.Dhaka, Bangladesh
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Sailendra Appanah of EnerGaia Bangladesh Ltd in Bangladesh will teach low-income women in rural Bangladesh to farm Spirulina, which is an edible protein- and nutrient-rich microalgae, to provide better nutrition and an income for them and their families. They have developed a low-cost Spirulina production system comprising closed tanks with filtered air and water inputs, and a business model that provides the farmers with a lease-to-own financing solution and guaranteed buyers of excess product. They will recruit 30 interested women from Dhaka, Bangladesh, and pay them a small wage to undergo three months of training at their local Spirulina farm. They will then provide them with tanks through the lease-to-own program, help them with installation and operation, and process the fresh spirulina produce for sale or for local consumption. They will evaluate the effect of their approach on income and malnutrition in the community.

Marketing an Iron-Fortified Food to India's Adolescent Girls

Mathew EdmundsonViolet HealthNew York, New York, United States
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Matthew Edmundson of Violet Health in the U.S. will develop iron-rich biscuits and tailor marketing campaigns to combat iron deficiency in adolescent girls in India. Iron deficiency is a global health concern and is particularly dangerous during pregnancy when it can increase the risk of maternal death and health problems for the infant. Nearly half of all adolescent girls in India are iron-deficient, and although iron tablets are available they are not taken properly, partly due to their bad taste and a cultural aversion to tablets. Thus, more culturally acceptable alternatives are needed. To address this, they developed a low-cost, iron-rich biscuit that could overcome anemia and non-compliance to iron tablets in clinical tests with pregnant women in India. They will now focus on helping low-income adolescent girls by adapting the biscuits to their nutritional needs and preferences, which will be determined by interviewing 50 girls from different areas. These insights will also be used for a pilot marketing campaign to generate demand amongst the girls and their families and community members. They will test their approach with 300 girls from rural and urban locations in India to determine the effects of different marketing methods on demand.

Folic Acid and Iron: Next Generation Nutrition in Uganda

Lorraine WeatherspoonMichigan State UniversityEast Lansing, Michigan, United States
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Lorraine Weatherspoon of Michigan State University in the U.S. will develop a blended instant bean sauce in an edible pouch that provides a culturally-acceptable iron and folic acid supplement for low-income pregnant women in Uganda. Iron and folic acid are particularly important during pregnancy as they reduce the risk of low birth weight and neural tube defects amongst many other morbidities and mortalities also for the mothers. Supplements provided as tablets are available, but have not been widely accepted. They are developing a more appealing iron and folic acid supplement by combining it with a commonly used product: a bean and silver fish sauce that can be made with local ingredients. They are using dried namulonge beans as they have high yields and a desirable taste, mixed with roasted, milled silver fish and micronutrients, packaged in an edible film to protect the food during storage and transport. The food is cooked in hot water and eaten with traditional foods such as cooking banana or rice. They will assess the nutritional composite of the product and acceptability by the target group. Their product will then be tested in a randomized controlled trial with teenage women at different stages of pregnancy at an antenatal clinic in Kampala to determine its effect on nutrition during pregnancy and the overall health of the mother and child at birth.

High-Quality Fish-Powder for New Cambodian Ready-To-Use Food

Lyndon PaulVissot Co LtdPhnom Penh, Cambodia
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Lyndon Paul of Vissot Co Ltd in Cambodia will reduce production costs for their nutritional wafer biscuits, which are made from a micronutrient-fortified fish powder, to help treat severe acute malnutrition in children and prevent malnutrition in young children and pregnant women in Cambodia. Acute and chronic malnutrition are a major public health concern in Cambodia. They previously developed a fortified fish powder and showed that it could replace milk in food for infants and was effective at reducing malnutrition. However, unstable supply and variable quality of the inland fish used to make the wafers have led to fluctuating prices. To address this, they will set up an optimized supply chain to reduce production costs by 60%. They will train workers in five communities where the fish are caught to sort, clean and pack the fish for transport to their factory in Phnom Penh. There, the fish will be processed into fish meal with acceptable taste and texture. They will evaluate the supply chain by collecting data from the fishers to the final product and evaluate quality and food safety.

Food-Derived Nutraceutical Encapsulation System for Food Fortification

Joachim LooNanyang Technological UniversitySingapore, Singapore
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Joachim Loo of Nanyang Technical University in Singapore will develop techniques to encapsulate micronutrients such as iron for food fortification using okara, which is a nutritionally-rich pulp that is made as a wasted by-product during the production of soybean products. Micronutrient malnutrition affects two billion people globally. Providing micronutrients in the diet is difficult because they are unstable by themselves, and so need some form of protection, for example by encapsulating them in a stable, digestible material. Okara is produced in large quantities during the production of soybean products like tofu and soya milk, leading to high environmental and economic costs for disposal. They will determine whether okara can be repurposed as an encapsulation material for micronutrients by developing and testing drying and sterilization methods and designing protocols to encapsulate vitamin A and iron. They will then evaluate the ability of the okara microcapsules to release bioactive micronutrients when exposed to artificial gastric and intestinal fluids.

Edible Micro-Balloons for Nutrition Enhancement

Muthupandian AshokkumarUniversity of MelbourneMelbourne, Victoria, Australia
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Muthupandian Ashokkumar at the University of Melbourne in Australia, along with Francesca Cavalieri, Meifang Zhou, and Srinvas Mettu, will produce edible microballoons made from protein that contain essential nutrients for adding to common foods to combat malnutrition in mothers and infants. Encapsulating the nutrients, rather than adding them directly to food, helps keep them stable and promotes their absorption in the body. It can also mask unpleasant tastes, and control the timing and location of nutrient release, which can increase their performance. They have developed a method that uses ultrasound waves to encapsulate oil- and water-soluble vitamins and minerals within edible shells made from a range of proteins including milk and pea proteins. They will analyze the stability and strength of microballoons made from different materials that contain the recommended daily doses of nutrients for mothers and infants. They will also develop methods to encapsulate water, which could be used to reduce the fat content of fat-rich products.

Creating a Market Solution to Treat Moderate Acute Malnutrition (MAM) in Rural Nigeria

Owens WiwaClinton Health Access InitiativeBoston, Massachusetts, United States
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Owens Wiwa of the Clinton Health Access Initiative in the U.S. will determine whether providing free vouchers for mothers to receive a nutrient-dense food can help infants with moderate acute malnutrition in Nigeria. By linking the vouchers to attendance at immunization clinics, they also hope to boost immunization coverage. Malnutrition is a major public health concern in Nigeria, where almost one third of children are underweight, and ten percent are wasted. However, improving nutrition in poor and rural households is difficult because of a lack of education and limited access to nutritional foods. They will pilot test their approach in a randomized controlled trial at two locations by training healthcare workers at immunization centers to council mothers on feeding practices and to monitor infant growth to identify malnutrition. The mothers of malnourished infants between six and 23 months old will be provided with vouchers to receive three months' worth of an existing fortified food, which will be provided at a local health facility. They will evaluate the effect of their approach on the infants' nutritional status and immunization coverage.

Hybrid Value Chain for Vulnerable Populations

Gloraia PenaCooperativa Multiactiva De Madres Del Valle CoomacCali, Colombia
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Gloraia Pena of Cooperativa Multiactiva De Madres Del Valle Coomac in Colombia will implement a hybrid value chain business model to leverage collective purchasing power in a community of low-income families in Colombia to reduce the price of nutritious local foods. Current food prices are relatively high for low-income families because they buy in small volumes. They will combine collective purchasing power with a hybrid value chain model, which incorporates the needs and roles of the public and private sectors, to increase access to nutritional foods. They will collect social and economic data from an existing group of 9,000 families in a poor neighbourhood in Colombia to understand how their approach should be implemented. This will include the numbers of participants needed to reduce the cost sufficiently to encourage people to buy the healthier foods and ultimately produce a positive long-term impact.

Developing Spent-Grain Food Supplements in Ethiopia

Tsegaye NegaCarleton CollegeNorthfield, Minnesota, United States
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Tsegaye Nega of Carleton College in the U.S. will develop methods to produce and distribute affordable nutritional food supplements made from excess, dried spent grains from the brewery process. Beer production has grown recently in Ethiopia, and a by-product, brewer's spent grain, is rich in fiber and protein and can be easily added to bread to boost its nutritional content. They will perform a pilot study in Addis Ababa and Dukem, Ethiopia, where they will partner with a major brewing company to access the starting materials, and determine the standards needed for this human-grade food and the production and distribution setups required. They will also further develop nutritional product marketing and testing. Their approach is a low-cost, sustainable solution to combat malnutrition in Ethiopia.

Development of Low-Cost Clean-Tasting Protein Isolates Using Upcycled Agricultural By-Products

Amanda StilesRipple Foods, PBCBerkeley, California, United States
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Amanda Stiles of Ripple Foods, PBC, in the U.S. will produce a low-cost protein isolate upcycled from locally-sourced agricultural by-products that can be used as a nutritious food additive or standalone high-protein broth. Protein malnutrition is a major health concern in southern Asia and sub-Saharan Africa. However, protein is expensive to produce and often has a bad taste. They have developed an automated approach to identify low-cost, efficient methods to isolate plant proteins from agricultural by-products in the U.S. They will apply their approach to by-products from low-resource settings, such as wheat bran, and perform a high-throughput protein isolation screen to identify optimal extraction and purification protocols for yield and purity. The final products will be taste-tested to ensure they have a limited impact on flavor when used as food additives.

Improving Process Efficiencies: Assessing and Improving Immunization Clinic Workflows Using an Electronic Immunization Registry

Samantha DolanUniversity of WashingtonSeattle, Washington, United States
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Samantha Dolan and Peter Rabinowitz of the University of Washington in the U.S., and Ian Njeru of I-TECH Kenya, will improve digital data collection and monitoring of childhood immunizations at Kenyan health facilities by optimizing workflows. Using electronic tools to track immunizations has the potential to improve the accuracy of data collection and reporting, identify children who have not been vaccinated, and free up time for health care workers. To fully realize this potential, workflow patterns need optimizing for different types of health facilities. They will use an iterative approach with so-called Lean methods to maximise value while reducing waste, and time-motion study techniques to evaluate current workflows and identify bottlenecks that reduce efficiency. These workflows will then be redesigned and tested across different sizes and types of facilities in Kenya. They will also compare the efficiency and performance of electronic registries with paper-based registries.

Obtaining Accurate Estimates of Subnational Vaccine Coverage

Joshua WarrenYale UniversityNew Haven, Connecticut, United States
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Joshua Warren and Daniel Weinberger of Yale University in the U.S. will develop an analytical framework to improve local estimates of vaccine coverage in low- to middle-income countries. Current estimates can be unreliable, due to errors and biases in record-keeping and difficulties in estimating local population sizes, and are further complicated when children are vaccinated outside of their home administrative district. They will develop advanced spatial analytical methods including bias adjustments that take these issues into account and can generate more reliable local estimates also from poor quality data. They will collect higher quality survey data on vaccine coverage and population sizes from selected locations to calibrate and ultimately validate the estimates. Their approach can be used in other low-income settings to improve vaccine coverage.

True Cover: Localized, Accurate Immunization Coverage

Matt BergOnaNairobi, Kenya
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Matt Berg of Ona in the U.S. will combine high-resolution satellite images, spatial sampling statistics, and mobile data collection to better calculate local immunization coverage in Bangladesh. Current approaches often vastly overestimate coverage because of the difficulty in calculating actual population sizes from nationwide data and birth registries. As a more effective approach, they will use satellite imagery to detect liveable structures within a set area, and software that selects possible households that require verification by community surveillance teams. These teams will be supplied with offline maps and a mobile application to note actual households and record the immunization status of any children under five. These data will then be used to generate maps to visualize actual coverage and identify areas with the greatest immunization needs. They will develop tools for automation, coverage calculations, and map visualizations to supplement their existing mapping and mobile data collection tools and test their approach in a research site in Bangladesh.

Electronic Decision Support System for Accurate Immunization

Ali TurabInteractive Research and Development Global LimitedSingapore, Singapore
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Ali Turab of IRD Global Ltd. in Singapore will develop a decision support tool that can be integrated with digital immunization registries to automatically construct optimal appointment schedules for every child that can adjust for missed immunizations and the introduction of new vaccines. A large majority of children, in both developing and developed countries, are not immunized at the recommended times, which can increase the risk of severe diseases. When a vaccination is missed, it is left to the health care professional to work out the best alternative schedule, which is often inaccurate. To help with this, they will design software that incorporates a child's vaccination history and age to automatically construct a new immunization schedule after every appointment, and that can also identify opportunities to vaccinate children even when they are at a clinic for other reasons. The software will integrate with existing health systems in several developing countries. They will conduct a mixed methods study at the Indus Hospital Korangi Campus in Pakistan to validate their approach for generating optimal schedules and assess usability by health workers.

Accessible Metrics of Access: Novel Tools to Measure Immunization Coverage

Ross BoyceUniversity of North Carolina at Chapel HillChapel Hill, North Carolina, United States
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Ross Boyce at the University of North Carolina in the U.S. will develop an approach that uses new methods of mapping households together with available health data to better identify places that have limited access to healthcare to improve immunization coverage. Many sub-Saharan African countries have very poor rates of childhood vaccination coverage. Improving coverage requires identifying those households and areas with poor access to healthcare, but this is challenging with the limited data available. To more accurately measure healthcare access and thereby immunization coverage, they will perform a six-month study in a rural sub-county of western Uganda. By providing user-friendly tools to health workers and providers, they will generate more accurate household maps and assess three different metrics of healthcare access using freely available software and a Bayesian statistical framework. They will evaluate the accuracy of their approach for predicting coverage by conducting a cross-sectional survey to determine the vaccination status of all children aged between 12 and 23 months in the sub-county.

Using Technology to Deliver Timely Immunization Data to the Doorstep of the Program Staff and Managers for Evidence-Based Decision Making

James NjeruField Epidemiology Society of KenyaNairobi, Kenya
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

James Njeru of the Field Epidemiology Society of Kenya will develop an integrated electronic platform that collects immunization and health data from existing registries and automatically sends regular, user-defined reports via SMS and email to health workers to improve vaccine coverage. Healthcare facilities record their immunization data on District Health Information Systems, but access to the data is limited. To widen access, they will build a platform that analyzes relevant health data from various sources, which will improve data accuracy, displays it on dashboards, registers users, and tracks their activity. They will pilot test their platform over seven months by registering program staff and managers so that they can access the platform and receive reports. The platform will be evaluated for its ability to integrate data and produce reports such as coverage and dropout rates. Feedback from users will also be used to refine the platform.

Improving Immunization Coverage by Scaling-Up a Regional Data Platform

Michael NunanTupaia (Beyond Essential Systems)Thornbury, Victoria, Australia
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Michael Nunan of Beyond Essential Systems in Australia will build on their existing data platform to collect and analyze vaccine data in real-time to provide an early warning of areas or facilities with low immunization coverage. The platform integrates data from various sources, including vaccine supply and healthcare infrastructure such as equipment and staff. They will further develop it to record actual vaccine administrations from health workers entering details on mobile phones, and to produce local estimates of vaccine demand and actual coverage and provide alerts. They will also integrate real-time monitoring of the cold supply chain using sensors. Their system will be evaluated in the Solomon Islands and Vanuatu by comparing it with current methods for estimating vaccine demand and coverage.

DigiMat. Tracking Realtime Immunisation Data (DigiTrack)

Chibuzo OparaDrugStoc E Hub Ltd.Lagos, Nigeria
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Chibuzo Opara of DrugStoc E Hub Ltd. in Nigeria will equip vaccine storage and transport sites with calibrated weighing mats (Digimats) that automatically transmit vaccine quantities in real time to better monitor delivery chains in the community and improve supply. Monitoring the movement of vaccines at the national and district level is currently performed by the Nigerian immunization program. However, accurate monitoring at the local level requires alternative, more automated approaches to avoid human error. They will calibrate their Digimats to recognize the weight of specific vaccines, and identify 20 sites across three states, including storage warehouses and trucks, where they will be positioned to automatically transmit data over a period of six months. These data will be collected by mobile tablets and interfaced with the national vaccine delivery dashboard to provide real-time stock counts and resupply alerts.

Human-in-the-Loop Machine Learning and Improved Immunization Data

Benjamin FelsMacro-Eyes, Inc.Fall City, Washington, United States
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Benjamin Fels and Suvrit Sra of Macro-Eyes, Inc. in the U.S. will engage with frontline health workers in immunization centers and combine their knowledge with existing supply chain and immunization data using machine learning to better predict vaccine demand and thereby improve immunization coverage. Vaccine supply levels in Ethiopia are predicted using data that may be inaccurate or outdated. These low-confidence data could be enhanced with the unique insights of frontline health workers by using machine learning, which is a valuable statistical method for increasing the accuracy of predictions. They will test this at three health centers in Ethiopia by exploring approaches such as WhatsApp to engage health workers and collect relevant information on vaccine stocks and demand in the clinics. These data, along with available supply data, will be used to train so-called classifiers, or algorithms, that transform the input data into more accurate predictions of monthly vaccine use. They will test whether their method improves the accuracy of predictions compared to the original methods.

Using Data-Driven Algorithms to Detect False Data Entries

Mustafa NaseemUniversity of MichiganAnn Arbor, Michigan, United States
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Mustafa Naseem of the University of Michigan in the U.S. will apply machine-learning algorithms to identify potentially falsified digital vaccination records in Pakistan. Pakistan is one of only three remaining countries where polio is still endemic. Particularly rural healthcare facilities are struggling to provide enough vaccinations due to highly populous provinces and a lack of resources and staff, and there is a risk that records are falsified to save time or bias the results. They will first perform fieldwork to identify any putative recently falsified records by auditing 2,000 recorded vaccination events across 200 randomly-selected villages. These data will be used to generate an algorithm by using features such as record patterns that can then detect if a data-point is likely to be true or false. They will test their approach by auditing another 1,000 vaccination events that the algorithm predicted were falsified compared to 1,000 randomly selected vaccinations.

Aerial Plant Disease Surveillance by Spectral Signatures

Pierluigi BonelloOhio State UniversityColumbus, Ohio, United States
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Pierluigi Bonello of Ohio State University in the U.S. will develop a surveillance system for crops using unmanned aerial vehicles (drones) to position sensors to help diagnose plant diseases in low-income countries. Plant diseases are usually identified first by the farmers or human scouts and then confirmed by laboratory testing. This process is inefficient and requires resources often unavailable in low-income countries, calling for alternative approaches. It is known that when a plant becomes infected, it produces specific chemicals. In addition, functional chemical groups in biological samples are known to vibrate in predictable ways after absorbing light. They will test whether this information can be exploited for the rapid and widespread detection of two plant diseases, rice blast and maize dwarf mosaic, by vibrational spectroscopy that could be positioned inside crop canopies by drones. Rice and maize grown in greenhouses and fields in the U.S. will be infected, and they will develop statistical methods to evaluate whether handheld spectrometers can distinguish between infected and uninfected plants. This technology could ultimately allow crop managers to control the spread of a disease even before plants show visual symptoms.

PLANT-DX: Field-Based Multiplexed Crop Pathogen Surveillance

Julius LucksNorthwestern UniversityEvanston, Illinois, United States
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Julius Lucks of Northwestern University in the U.S. will develop a low-cost diagnostic test that can detect multiple plant pathogens with a simple visual output for farmers in low-income countries to better monitor their crops. Current diagnostic field tests can only detect one disease and are generally difficult to use and costly. The alternative is laboratory testing, which is often unavailable in low-resource settings. Taking a different approach, they will develop a sensitive, multiplexed test that only requires basic sample preparation, such as mixing and using body heat, and can detect multiple pathogens using biosensors. The results will be visually presented using color changes that can be recorded by cell-phone cameras for analysis and reporting to aid global plant pathogen surveillance efforts. They will develop the methods and tools to detect three model plant pathogens and field test their diagnostic system in the U.S., Uganda, and Kenya.

Smart Armyworm Surveillance (SAS)

James BellRothamsted ResearchHertfordshire, United Kingdom
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

James Bell of Rothamsted Research in the United Kingdom will test an integrated surveillance system for the real-time detection of ground and upper atmospheric levels of the fall armyworm, which is a moth that devastates maize crops. Maize is a vital food source in Kenya but is currently largely imported and has become too expensive for most households. They propose to help local farmers grow maize by developing an early warning system for the African moth pests. Their system will integrate an entomological radar to detect moths flying up to 1,200 metres overhead, with twenty ground traps covering 7,000 km2 that transmit data to a central institute, and a smart-phone application for workers and growers that automatically detects the caterpillars and moths. They will optimize the equipment and software to detect the specific moth species and test it in a region of Western Kenya over one year. Their system will also reveal details of seasonal moth migrations, ground spread, and crop growth to help develop effective pest management strategies.

Low-Cost Paper Sensor for Surveillance of Cereal Crops

Jun KameokaTexas A&M UniversityCollege Station, Texas, United States
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Jun Kameoka of Texas A&M University in the U.S. will develop multiplex, battery-less and wireless durable paper sensors for positioning under the soil in crop fields to detect the early signs of pests and diseases, and communicate the data to overhead drones via radio frequency to improve pest management. The sensor will be designed to monitor physical, biological and chemical soil conditions that are altered by plant diseases. They will test its performance in commercial garden soil with maize and sorghum plants in a vinyl house.

Biomimetic In-Field, IoT, "Sentinel" Fungal & Viral Sensor

Bruce GrieveUniversity of ManchesterManchester, United Kingdom
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Bruce Grieve of Manchester University in the United Kingdom will develop a low-cost, stereo-printed sensor that mimics plant leaves and stems and can detect and signal the presence of live pathogens as an early warning system to help protect crops in low-resource settings. They will demonstrate proof-of-concept of their approach in the laboratory by designing three dimensional sensors with specific patterns of cells and chemically-doped polymers to identify an ideal surface on which pathogenic fungal spores can grow and differentiate. Incorporated sensor cells will be designed to detect the live pathogens and produce a detectable response, such as a visible density change, and results can be stored locally or transmitted wirelessly. They will test different sensor designs for the detection of rust pathogens in wheat. Their approach can be adapted to detect multiple pathogens simultaneously, including viruses, as well as for human and livestock pathogens, and when deployed in the field can ultimately be linked to national surveillance systems.

Accurate Phone-Based Plant Disease Diagnostics

Jan KreuzeInternational Potato CenterLima, Peru
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Jan Kreuze of the International Potato Center in Peru will develop a low-cost, mobile phone-based diagnostic test for African farmers that uses artificial intelligence to quickly and accurately detect plant diseases such as cassava brown streak and banana bunchy top, which devastate crops and are threatening to spread. Accurately diagnosing plant diseases is difficult because visual symptoms can be highly variable. Artificial intelligence (AI) has shown promise for analyzing images of plants taken by mobile phone to detect diseases in low-resource settings, but it is not accurate enough. Alternatively, chemical-based diagnostic tests that detect the underlying viruses are far more accurate but difficult to use without training and require costly equipment. They will enhance the accuracy of AI for diagnosing a range of plant diseases by mobile phone by training it with validated diagnostic test results from their microfluidic amplification and detection device used by researchers and inspection agents. Their approach has the potential to recognize hard-to-detect symptoms in plants that may even be missed by crop specialists.

Integrated Platform for Effective Surveillance

Christopher GilliganUniversity of CambridgeCambridge, United Kingdom
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Christopher Gilligan of the University of Cambridge in the United Kingdom will develop a data collection and analysis platform for crop diseases that uses Bayesian modelling frameworks to better integrate data from diverse sources and identifies cost-effective pest and disease control solutions for small-holder farmers. Current crop disease surveillance programs generally collect data from limited sources and lack the capacity to use the data to advise farmers how to manage any disease outbreaks. By integrating a wider variety of data, including meteorological data, and grower and market behaviour such as household nutrition, their approach can predict much broader consequences of crop diseases on individual households and thereby provide more valuable solutions. They will focus on pests and diseases of maize, wheat, and cassava in East Africa and pilot test their SMS and smart phone platform by holding training workshops for participants, testing data analytics and validating the results.

Pest and Disease Surveillance via High-Resolution Satellites

David HughesPennsylvania State UniversityUniversity Park, Pennsylvania, United States
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

David Hughes, and Nita Bharti of Penn State University in the U.S. together with James Legg at the International Institute of Tropical Agriculture in Tanzania and the Charity, Self Help Africa, will leverage daily, high-resolution satellite imagery of farms in Kenya to monitor crop pests and diseases. Publicly funded satellites have the capacity to measure crop health, soil moisture, and water availability across wide areas. However, they are unable to accurately diagnose crop diseases particularly in smallholder farms because of the presence of many different types of often unhealthy-looking vegetation caused by lack of water or nutrients rather than plant diseases. They will use ground data on crop diseases and pests being collected as part of a five-year EU-funded project at 1,400 farms in seven counties growing a variety of crops. They will also collect maps of the farms using drones flying at different heights and see how well any pests and diseases can be detected using the daily satellite data. They will validate their approach for detecting pests and diseases on an additional 1,400 farms.

A Crowd-Sourcing Approach to Large-Scale Monitoring of Pests by Smallholder Farmers

Menale KassieInternational Centre of Insect Physiology and EcologyNairobi, Kenya
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Menale Kassie of the International Centre of Insect Physiology and Ecology in Kenya along with Ram Fishman and Opher Mendelsohn from Tel Aviv University in Israel will take a community-based crowdsourcing approach to crop protection of smallholder farms in low-resource settings by developing a simple software platform for basic feature phones to monitor pest incidence. Human-based monitoring of crops is the most accurate way to identify pests, but there are too few public monitoring agents in low-resource settings, leaving the majority of farms unprotected. Engaging the smallholder farmers to monitor their own crops is a promising solution, but most of them lack sophisticated equipment like smart phones and have low technical knowledge, so simpler solutions are needed. Therefore, they will adapt commercially-available software that collates and analyzes pest incidence data for basic feature phones and, together with smallholder farmers, design simple interfaces for SMS communication. They will test their approach by performing a pilot study to monitor wheat and maize, covering one to two counties in Kenya, and teach smallholder farmers and government agents how to use the monitoring system and compare the data with that collected by expert field agents.

Zero-Power Chemical Sensors for Pests and Disease Monitoring

Matteo RinaldiNortheastern UniversityBoston, Massachusetts, United States
Grand Challenges Explorations
Crop Disease Surveillance
1 Nov 2018

Matteo Rinaldi of Northeastern University in the U.S. will develop a miniaturized, maintenance-free chemical sensor that can detect specific volatile organic chemical vapors released from diseased crops as an effective surveillance system suitable for low-resource settings. Manual surveillance is time-consuming and requires prior knowledge of disease symptoms. Automated, sensor-based crop surveillance is far more effective, but relatively expensive, and the sensors constantly consume power, making them unsuitable for low-resource settings. They will develop a low-energy sensor-based monitoring system by exploiting a recently developed technology that comprises a micromechanical switch made of two cantilever beams. One of the beams will be coated with a polymer sensitive to the plant-based chemical and exposed to the environment. In the presence of that chemical, the beam undergoes a change in mechanical stress, causing it to bend and make contact with the second beam to trigger the switch. They will develop the microswitch-based chemical sensors, integrate them with a low-power long-range wireless module to signal pest detection, and test the performance of prototypes in the laboratory.

Milk Exosomes and RNA for Optimal Growth and Immune Function

Janos ZempleniUniversity of Nebraska-LincolnLincoln, Nebraska, United States
Grand Challenges Explorations
Next Generation Nutrition
1 Nov 2018

Janos Zempleni of the University of Nebraska-Lincoln in the U.S. will test whether supplementing milk formula with exosomes from milk could have the potential to improve the growth of babies aged between 6 and 12 months and help protect them from infections. Exosomes are membrane-bound vesicles naturally present in all bodily fluids and are thought to transfer small molecules such as RNAs between different cells to regulate various cell functions. However, during the production of milk formula for babies, the exosomes are destroyed. They have preliminary data demonstrating that RNAs and exosomes in milk enhance growth and the immune response in mouse pups. They will expand these studies to confirm their results in mice, with a view to progressing to clinical trials to test the value of exosome-fortified milk formula in humans.

Uganda Vacc+: User-Centered Data Collection and Use

Monica NolanMU-JHU Care LimitedKampala, Uganda
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Monica Nolan of MU-JHU Care Limited in Uganda will adapt the existing open source Smart Register Platform, which digitally stores health records, for the real-time collection and transfer of immunization data, to improve vaccine coverage and other healthcare services for women and children in Uganda. In many low- to middle-income countries, records of childhood vaccinations are usually written by hand and can be poor quality. Digital records are of better quality and value, as they also enable the integration of different types of healthcare services, such as HIV services and vaccinations, to improve overall health. They will adapt existing technology and infrastructure, including the Smart Register Platform, which is already integrated into several national health systems and can produce automated SMS reminders of appointments. They will also design methods informed by mothers with young families, health workers and managers, to optimize data use and delivery of health services. They will use surveys and analyze health data to evaluate their approach for improving vaccine timeliness and coverage at selected clinics.

Optical Scanning of the Mother and Child Protection Card

Aaditeshwar SethOnionDev Technologies Pvt. Ltd.Gurgaon, Haryana, India
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Aaditeshwar Seth of OnionDev Technologies Pvt. Ltd. in India in collaboration with the University of Montreal Hospital Research Centre (CRCHUM) via the Tika Vaani project, will develop a smartphone application and digital processing techniques to digitize childhood immunization data from photographs of vaccination cards taken by health workers during clinic visits and store the data in a cloud to monitor adherence and send reminders to families. They will perform an 18-month pilot project to develop the application and optimize data collection and analyses, use by health workers, and performance of the messaging service for encouraging families to get their children properly vaccinated. The application will be designed around field conditions to account for low internet connectivity and the capabilities of health workers in India and will be linked with other digital health platforms to improve the overall quality of healthcare.

Crowd-Sourcing Vital Records to Improve Subnational Data

Chinedu ChugboAvigo Health L.L.C.Washington, District of Columbia, United States
Grand Challenges Explorations
Immunization Delivery
1 Nov 2018

Chinedu Chugbo of Avigo Health L.L.C. in the U.S. will develop an approach to crowdsource reports of infant births and deaths from community members by health workers to better monitor vaccine coverage in low- to middle-income countries. In Nigeria, only 30% of births are registered, making it difficult to estimate numbers of vaccine-eligible children and ensure every child is properly vaccinated. Current methods for estimating population sizes include household surveys, which are costly, or records from health clinics, which suffer from limited coverage. Crowdsourcing is a proven method for efficient data collection, although data quality may be variable. They will develop electronic data-collection and storage tools and pilot test their crowdsourcing approach in a selected region in Nigeria. Health workers will be trained to administer brief interviews to community members visiting clinics and during outreach programs to document local births and deaths. They will evaluate the performance of their approach and particularly data accuracy by comparing it with data collected by household surveys in the same region.

Tracking MRSA Evolution to Discover Important Biomarkers to Quickly Characterize Unique MRSA Clones in Hospital Bloodstream Infections

Agnes FigueiredoUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project will use molecular approaches, including genomics and phylogenomics, to find biomarkers that could indicate the location in the genetic code driving bacterial adaptation. In addition, these biomarkers could be used as a rapid method for screening predominant and high-virulency MRSA clones in hospitals, and thus quickly provide infection control committees with key data on MRSA spread and its antimicrobial resistance profile.

An Artificial Intelligence System to Strengthen Antimicrobial Prescription in a Children's Hospital: SMART-EP

Marcelo PillonettoPontifícia Universidade Católica do ParanáCuritiba, Paraná, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The idea is to develop an artificial intelligence model capable of simultaneously analyzing data from the Laboratory Information System and from the Hospital Information System. This technology aims to enable the delivery to hospital physicians of a ranked list of antimicrobials that are more suitable to treat infection by multi-resistant microorganism with a focus on newborn and young children.

Applying the Metagenomic Approach for the Detection of EsβL- and Carbapenemase-Producing Enteric Pathogens Recovered from Different Hosts

Ana GalesUniversidade Federal de São PauloSão Paulo, São Paulo, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project will study the genetic material from environmental samples from humans (healthy and ill), cattle and their meat to estimate the proportion of E. coli and K. pneumoniae in the microbiome. The main objective is to better understand the distribution of bacteria and its resistance genes, Escherichia coli and Klebsiella pneumoniae bacteria and extended spectrum beta-lactamase (EsβL) and carbapenemases encoding genes in distinct ecological sources.

OneBR: Integrated Genomic Database for Surveillance, Diagnosis, Management and Treatment of Antimicrobial Resistance in the Human-Animal-Environment Interface

Nilton LincopanUniversidade de São PauloSão Paulo, São Paulo, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

This project proposes the development of the One Health Brazilian Resistance (OneBR), a curated and integrated genomic database. OneBR will use algorithms based on artificial intelligence to conduct surveillance, diagnosis, management and treatment of antimicrobial resistance (AMR) in the human-animal-environment interface. The goal is for this platform to be used by Brazilian health professionals in diverse settings, particularly within the Unified Healthcare System (SUS).

Data Science on Drug-Resistant Tuberculosis in Brazil

Rejane PinheiroUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The researcher will use machine learning techniques and a linked database to analyze mortality from drug-resistant tuberculosis. The goal is to better understand how the flow of patients through the health services network have influenced, or not, the occurrence of resistance.

The Dynamics of Antibiotic-Resistant Microorganism Flow Between Animal Farming and Medical Hospital Assistance

Thaís SinceroUniversidade Federal de Santa CatarinaFlorianópolis, Santa Catarina, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project proposes to characterize the resistant determinants of microbial communities from key sources in hospitals, environment and farms to model the dynamics of the flow of antibiotic resistant microorganisms. The goal is to understand how the hospital environment and animal farming affect the ecology of antibiotic resistance movement. The project will rely on a methodology that allows the analysis of genes related to antibiotic resistance in a complex microbial community derived from specific samples instead of culture based methods for AMR identification.

Plasmid Curing by an Ethiopian Barley: A Natural Food Approach to Reduce Plasmid Mediated Antibiotic Resistance

Bruno PennaUniversidade Federal FluminenseRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

Bacterial plasmids are genetic elements that can carry genes for antibiotic resistance from one bacteria to another acting as "messengers". Plasmid transfers contribute to the appearance of multidrug resistant bacteria. This project aims to use a "kill the messenger, not the bacteria" approach to tackle the problem of increasing antibiotic resistance. The goal is to test the elimination of plasmids carrying genes for antimicrobial resistance.

Application of Low-Cost and Sustainable Solar Oxidation Treatment to Prevent Microbial Resistance in Effluents in Brazil

Camila AmaralUniversidade Federal de Minas GeraisBelo Horizonte, Minas Gerais, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

This project will test a sustainable solar oxidation system as a way to remove antibiotic resistant bacteria from wastewater. The hypothesis is that this technology can enable the inactivation of antibiotic resistant bacteria and the elimination of antibiotic resistant genes from effluents in Brazil.

Monitor AMR in Community Uropathogens and Correlate Them with the Determinants of Resistance in Animal Enterobacteria Isolates

Eliana Carolina VesperoUniversidade Estadual de LondrinaLondrina, Paraná, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project aims to monitor AMR in microorganisms of the urinary tract and correlate it with the genetic determinants of resistance in animal enterobacteria. The study results will be disseminated in order to inform potential changes to guidelines regarding selection of the appropriate antimicrobials first-line treatment for urinary tract infections (UTI).

Engineers, Pharmacists and Chemists Collaborating on the Development of an Aerobic Granular Sludge (AGS) to Remove Antibiotics from Hospital Wastewater

Leonardo MouraUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project proposes to use an aerobic granular sludge (AGS) - a technology based on microbial community - to remove antibiotics and antimicrobial resistant genes from hospital wastewater. AGS is one of the latest innovations and it has not yet been applied for the treatment of hospital wastewater.

The Use of Low-Cost Immobilized DNA Aptamers on a Cellulose Filter to Remove Antibiotic Residues from Effluents

Tiago MendesUniversidade Federal de ViçosaViçosa, Minas Gerais, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project will develop a cellulose filter containing immobilized DNA aptamers, molecules that bind to a specific target molecule, that act as specific and high affinity probes for the uptake and retention of antibiotic molecules present in effluents. Nowadays, the removal of antibiotic residues from effluents is mainly based on chemical processes and physical methods that require expensive technologies and costly maintenance. The success of this project will represent a wastewater treatment option that is low-cost and environment-friendly.

New Gestational Weight Gain Recommendations for the Brazilian Unified Health System (SUS)

Gilberto KacUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

Aims to validate the International Fetal and Newborn Growth Consortium for the 21st century (Intergrowth-21st) standards for gestational weight gain (GWG) and create new recommendations of GWG based on those standards for first trimester normal and overweight women to be used in the Brazilian Unified Health System (SUS). GWG recommendations currently used in SUS have not been properly tested or validated, thus the project might improve prenatal nutritional care and reduce post gestational weight retention.

Potential Pregnancy Days Lost (PPDL): An Innovative Gestational Age Measure to Assess Maternal and Child Health Interventions and Outcomes

Carmen DinizUniversidade de São PauloSão Paulo, São Paulo, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

The main goal of the project is to develop and explore an innovative measure of gestational age - "potential pregnancy days lost" (PPDL) - to produce evidence of its association with maternal and child health, morbidity and mortality in the short, medium and long term. The indicator also aims to convince women and policy makers about the need to promote less interventions and "harm-free care" during pregnancy.

Early Childhood Development Friendly Index: Assessing the Enabling Environment for Nurturing Care in Brazilian Municipalities

Muriel GubertUniversidade de BrasíliaBrasília, Distrito Federal, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

The study aims to develop an Early Childhood Development friendly index (ECD-FI) based on a core set of evidence-based nurturing care indicators to assess the factors contributing to enabling environments and promote ECD at the municipal level by monitoring and identifying opportunities to scale up ECD programs. The index will be created through machine learning and will run analytical models considering demographic information and risk factors at the municipal level. This disaggregated data is not available in Brazil.

How and When: Disentangling Cash and Care Effects of Conditional Cash Transfers on Birth Outcomes

Cecilia MachadoFundação Getúlio VargasRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

Seeks to understand the impacts of the Bolsa Família conditional cash transfer on birth outcomes (e.g., birth weight, gestational weeks, etc). The proposed design will disentangle the measured effects into two components: one that is associated to the cash transfer; and another related to prenatal care assistance. Moreover, this strategy will allow the researchers to determine the window of opportunity where CCT interventions exhibit highest impacts on birth outcomes, recognizing heterogeneous impacts according to how early in the pregnancy the CCT intervention starts.

Decision-Making Support Platform Based on Visual Analytics and Machine Learning to Subsidize Public Politics Focused on Gestational Health

Tiago CarvalhoInstituto Federal de São PauloCampinas, São Paulo, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

The project will develop a platform to provide services for decision-making support for neonatal death preventive actions by using data from CIDACS cohort. The platform will offer three services: cohort data visualization for decision-making support by comparative human visual analysis, prediction of risk of neonatal death based on machine learning models, and simulator of public policies impact influencing on the risk of neonatal death.

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