Awards

Anandkumar Naorem of the ICAR-Central Arid Zone Research Institute, Jodhpur in India will perform polyhouse farming experiments in the Indian state of Rajasthan to identify soil conditions that reduce emission of the greenhouse gas nitrous oxide. Polyhouses are greenhouse-style but enclosed in polyethylene rather than glass. They will grow tomato plants as a vegetable test crop, adjusting soil properties by varying factors including the type of mulch, irrigation frequency, the type of nitrogen compound added, and whether biochar is added. They will assess soil health through analysis of its physical, chemical, and biological properties, focusing on how they relate to nitrous oxide emission. The results will guide improvements in polyhouse farming particularly relevant as a sustainable agricultural strategy for arid regions.

Sujatha Sunil of the International Center of Genetic Engineering and Biotechnology in India will determine the temperature preference of Indian Aedes aegypti mosquitoes to build a mathematical model that predicts their prevalence across the country as well as hotspots for the arboviral diseases they transmit. To understand temperature preference, they will study laboratory-adapted Aedes aegypti, assessing their physiology and development in the laboratory across the mosquito life-cycle at a range of relevant temperatures. They will also sample mosquitoes across sites in Delhi, recording their physical and physiological features and their carriage of arboviruses, together with weather data from nearby weather stations and arboviral disease incidence data from nearby hospitals. The laboratory and field data will be integrated to build predictive models to identify areas in India most at risk of arboviral epidemics.

Sean Stowell of Brigham and Women's Hospital in the U.S. will analyze the human antibody repertoires targeting microbes in the female genital track (FGT) to guide the design and use of live biotherapeutic products for bacterial vaginosis. They will use their microarray platform, consisting of an array of antigens from FGT microbes, to analyze genital tract samples from a cohort of women in an HIV drug clinical study in South Africa. They will define the association between FGT antibody levels and specificity with FGT microbial colonization and inflammation. They will also perform experiments to explore potential mechanisms for antibody-mediated microbial attachment and colonization, focusing on antibody interactions with FGT mucin proteins. Together, the results will set the stage for using the microarray platform to identify patient-specific variables as biomarkers to predict the success of live biotherapeutic products.

Saliou Fall of the Institut Senegalais de Recherches Agricoles in Senegal will develop techniques to estimate biological nitrogen fixation (BNF) by legume crops to guide their use as alternatives to nitrogen fertilizers for more sustainable agriculture. They will assess BNF by estimating three underlying components. Crop biomass and the proportion that is nitrogen will be estimated by AI-based models, and the nitrogen fraction that comes from BNF will be estimated by measuring the levels of a stable isotope of nitrogen in the soil and in the plants. As test crops for data to train the AI models, they will grow groundnut and cowpea as staple legumes, with an adjacent non-nitrogen-fixing crop, and crotalaria as a cover crop. They will acquire images of the crops from drones or mobile phone applications, and perform laboratory analyses, including measuring biomass, analysis by near-infrared spectroscopy and wet chemistry, and measuring the natural isotope of nitrogen.

Daniel Kwaro of CREATES in Kenya will develop an early warning system for malaria outbreaks, floods, and heatwaves in Siaya County in Kenya, co-designing it with the local community. They will incorporate health and demographic surveillance system data, including a specific focus on maternal health indicators and birth outcomes, as well as data from automated weather stations, wearable devices, and mosquito traps. Through secondary data analyses, they will assess the probability and consequences of climate-related hazards, including identifying vulnerable communities, high-risk geographical areas, and occurrence patterns of climate-sensitive diseases. They will actively involve Siaya County residents, healthcare providers, and relevant local authorities in co-designing the early warning system paired with multiple mechanisms for communication to ensure the system is accessible and effective in responding to local needs.

Smit Gade of the Good Business Lab Foundation in India will perform a study in India to better understand the constraints for working mothers in accessing employer-provided childcare and the effects of increasing uptake of this childcare on working mothers and their children. They will perform a randomized controlled trial, recruiting sewing machine operators at a garment factory and unemployed women that will be offered job interviews at the factory. The factory offers free on-site childcare, but uptake is low. The trial arms will test the effect of subsidizing the cost of traveling with children to work, of providing information on the quality of the free creches at the factory, or of both combined. They will determine if the study treatments increase working mothers' uptake of childcare services and encourage unemployed women to interview for work. Trial outcome measures will include assessment of women's quality of life and of their children's welfare.

Avishek Banik of Presidency University in India will identify a bacterial consortium that can protect tea crops from Fusarium fungal pathogens. The global rise in temperature threatens tea crops in part through increased humidity that favors proliferation of disease-causing Fusarium. To develop a biocontrol strategy for these pathogens, they will isolate Fusarium species from tea plants in tea plantations in the Dooars region of West Bengal as well as bacteria growing on and in the plants. They will use these isolates to characterize the fungal disease process in high-humidity growth conditions in the laboratory and to screen for bacteria that can inhibit it. They will characterize the mechanism of inhibition, including analysis of plant gene regulation, to guide development of an antifungal bacterial product.

Anurag Agrawal of Ashoka University in India will develop an LLM-based platform to support medical decision making by home healthcare workers in India who are meeting the growing demand for home-based palliative care. The platform will use an existing proprietary LLM to extract and summarize relevant clinical information, connecting it with an existing open-source AI chatbot to generate advice in a conversational format for healthcare workers. They will test the platform using a dataset they will build of palliative care scenarios, focused initially on care for lung diseases, and they will compare outputs from several different open-source LLMs to guide the platform's final configuration. Expert clinicians will evaluate the clinical advice generated by the platform for its factual accuracy and relevance to the Indian sociocultural context.

Shraddha Jaybhave of DruFarm Technology Private Limited in India will test the DairyGuard wearable device for real-time monitoring of dairy cow health by small-scale farmers. They will test the system in dairy farms in the Indian states of Maharashtra and Gujarat. They will collect and analyze test data on cows, including identifying patterns in movement, feeding, rumination (cud chewing), and body temperature. They will validate the accuracy, reliability, and usefulness of the data and the associated alerts for farmers by comparing the monitoring system results to traditional livestock management methods and veterinary assessment. They will evaluate the impact of the monitoring system on participating farmers' productivity and income and identify opportunities to broaden its uptake and integration with existing agricultural extension services.

Aline Rocha of Fiocruz in Brazil will link datasets through the Center for Data Integration and Knowledge in Health (CIDACS) to measure the impact of extreme climate events on maternal and infant nutritional outcomes across diverse ecological settings and population groups in Brazil. They will integrate longitudinal data from two datasets, the 100 Million Brazilian Cohort and the Climate and Health Data Platform, connecting them through the municipality where mothers reside. The cohort database links data from social protection programs to administrative and health databases to assess the social determinants of health. The data platform extracts and links climate and environmental data from the year 2000 onwards from existing open-source databases. The integration of these two datasets will guide evidence-based programs to enhance the resilience of health services and mitigate the effects of climate change on maternal and child health, particularly for those most vulnerable.

This grant is funded by Grand Challenges Brazil.