Awards

Ani Varghese of ZeroEarth Private Limited in India will pilot test a climate-smart dairy farming platform supporting rural women farmers in the Indian state of Tamil Nadu. Through partnerships with financial institutions, they will set up mechanisms facilitating farmers' access to credit to sustainably increase their farming income. They will launch a pilot business center, which will provide training in entrepreneurship and climate-smart farming practices; centralized access to veterinary services; and coordination between dairy, calf-rearing, and fodder farmers. Farming practices supported by the center will include those to improve the health of soil for growing fodder; to optimize feed to minimize greenhouse gas emissions and enhance milk quality; and to efficiently manage manure, with the launch of a biogas plant to generate electricity.

Satadal Saha of the Foundation for Innovations in Health in India will develop an AI-based platform to support public health interventions for women living in the Sundarban Biosphere Reserve, focusing on anemia, urogenital tract infections, and anxiety and depression. The Reserve is a river delta region highly susceptible to climate change-driven severe weather. The project will build on the team's existing digital platform for health data that supports community health workers deliver primary care to island communities. They will collect environmental data, including data for weather and air and water quality, and expand the platform with software enabling regular monitoring and integrated analysis of health and environmental data. This includes incorporating an AI-based predictive model to guide the proactive design and implementation of public health interventions for vulnerable women in this region.

Raghuram Dharmaraju of the I-Hub for Robotics and Autonomous Systems Innovation Foundation in India will improve heatwave forecasting using AI approaches and develop an early warning system for the Indian state of Karnataka to enhance preparedness for heat-induced health risks. The improvements in forecasting will encompass increases in accuracy, lead time, and spatial resolution. The early warning system will use web-based dashboards, mobile apps, and social media platforms to communicate heatwave alerts in local languages. It will include messages tailored to particularly vulnerable groups as well as alerts to healthcare providers to actively monitor these groups. It will also send notifications to relevant government agencies about the potential severity of health impacts. This system will guide public health interventions while helping establish data collection mechanisms for ongoing improvement of the system.

Tavpritesh Sethi of Indraprastha Institute of Information Technology Delhi in India will develop an AI-based platform to support responses to vector-borne diseases in the face of climate change in the Indian state of Uttar Pradesh. They will establish a comprehensive database that integrates climate data with data from existing programs for the control of vector-borne diseases (malaria, dengue, chikungunya, Zika, and Japanese encephalitis). Data will be at the block level of local government in Uttar Pradesh and will include real-time data. For analysis, they will develop an AI-based platform, named Sanketak, that includes modules to capture data, provide automated alerts, visualize changes in disease incidence, and identify early warning signs that predict disease hotspots. They will pilot test the platform, evaluating its potential to preempt, detect, and manage vector-borne disease outbreaks in a timely and effective manner.

Tavpritesh Sethi of Indraprastha Institute of Information Technology Delhi in India will develop an AI-based platform for AMR surveillance and management across a broad network of public and private hospitals in India. The platform will extract weekly data on AMR from the All India Institute of Medical Sciences, New Delhi (AIIMS Delhi) hospital and the Max Healthcare hospital network, including patterns of antibiotic prescriptions across the network. It will use a federated data analysis approach (joint analysis without sharing the data itself), and they will develop and integrate AI-based models to identify and predict trends in AMR. They will also create applications driven by these models to widely and effectively communicate the analyses to healthcare professionals. This will support antibiotic stewardship and data-driven AMR management at both the local and regional levels.

Sai Raj Reddy of Daia Tech Private Limited in India will develop a program to increase access to health education and related resources for adolescent girls in rural areas of the Indian state of Karnataka. The program will be developed in partnership with the Karnataka Health Promotion Trust, building on their ongoing work with local schools, healthcare providers, community leaders, and government agencies. After engaging community members to understand the local context, they will develop resources for adolescent girls including life skills courses and health education workshops and pilot test the program in selected villages. They will integrate AI tools across the program to broaden participation and to broaden the range of health outcomes improved for adolescent girls.

Chiranjay Mukhopadhyay of the Manipal Institute of Virology in India will perform a two-year longitudinal study in the Western Ghats region of India, focusing on sentinel surveillance of tick-borne pathogens and their transmission dynamics. This mountain range region is known for its high biological diversity, and they will sample across 12 sites representing diverse ecological habitats where people and wild and domestic animals interact most frequently. They will collect host-seeking ixodid ticks, screen them for eight tick-borne pathogen groups, and perform whole-genome sequencing for the pathogens identified. Corresponding weather data will be collected from the Indian Meteorological Department. They will combine this longitudinal data to develop statistical models that predict the spatial and temporal transmission of tick-borne pathogens and the corresponding disease risk, which will guide public health interventions.

Bruno Mmbando of Kampala International University in Tanzania will model the combined impact of malaria chemoprevention strategies and vaccines on the burden of childhood malaria in Africa. A modeling focus will be on determining the level of vaccine uptake at which chemoprevention strategies cease to be cost-effective in settings with moderate to high malaria transmission. Data modeling will include the short- and long-term effects of parasite antimalarial drug resistance on the combined impact of chemoprevention and vaccines. The multidisciplinary team will include data modelers, health economists, clinical trialists, and epidemiologists. They will work closely with malaria decision-making organizations, leading to tools and processes that better support the use of malaria data modeling to inform public health interventions.

This grant is funded by The Wellcome Trust.

Karthik Sasihithlu of the Indian Institute of Technology Bombay in India will map urban heat islands across India and test radiative cooling paint on building rooftops to reduce temperatures, heat-related illnesses, and energy consumption for cooling. Urban centers in India face extreme summer temperatures, worsened by the heat island effect in developed areas relative to rural areas and by heatwaves increasing in frequency because of climate change. Radiant cooling paint, because it does not require structurally modifying buildings, could be an affordable and sustainable intervention to reduce the negative health and economic impacts of heat. Heat islands will be mapped using satellite imagery, and radiative cooling paint will be tested in the severe heat islands identified.

Arup Ghosh of CSIR-Central Salt and Marine Chemicals Research Institute in India will design a feed additive for Indian cattle that combines algae and bacteria to reduce enteric methane emission, improve livestock health, and enhance agricultural productivity. From Indian sources, they will select seaweed, marine microalgae, and bacteria, screening them for their ability to inhibit methanogenesis in vitro and in the rumen of cattle. They will also assess their effect on the rumen microbiota and on cattle physiology and productivity. Candidate products made from these additives will be evaluated for their economic viability, including their potential for large-scale cost-effective production, storage, and distribution, as well as for their benefits to farmers relative to existing solutions.

Belehalli Pavan of Strideaide Private Limited in India will develop an AI-based platform to increase timely access to diagnosis and treatment for diabetic foot ailments. Early detection of peripheral neuropathy, peripheral arterial disease, and diabetic foot ulcers would enable interventions that reduce the need for limb amputation. The platform will build on their existing network of podiatry clinics located in a variety of public spaces. These clinics are staffed with a paramedic providing treatment guided by diagnostic tools including a foot mat with a plantar pressure sensor to help predict and assess foot-bottom ulceration. Existing and new digital data from these clinics will be used to build a diabetic foot registry, to improve automated assessment through AI-based analysis, and to train an LLM with a chatbot interface for clinical decision support across the podiatry clinics.

Amrita Mahale of ARMMAN in India will incorporate an LLM-based chatbot into the Kilkari mobile health service to answer questions about pregnancy and infant care. Kilkari currently provides weekly pre-recorded messages on preventive care, and it is implemented in partnership with India's Ministry of Health and Family Welfare. They will assess different available LLMs and train the best candidate with the Kilkari database of vetted content. They will pilot test the model with Kilkari users through WhatsApp, engaging users in Delhi and in the state of Jharkhand to encompass diverse participants spanning urban, rural, and tribal populations. The test will include regular surveys to measure the service's accuracy, relevance, and usability.

Mohanasankar Sivaprakasam of the Healthcare Technology Innovation Centre at the Indian Institute of Technology Madras in India will develop an AI-based platform to support diagnosis and report generation for endoscopic gastrointestinal exams. They will use curated datasets of annotated endoscopic images to develop an AI-based model for diagnosing gastrointestinal abnormalities, such as polyps and ulcers. The data will also be used to train a Large Language Model (LLM) to generate diagnostic reports of endoscopic exams including representative images and text descriptions. This will improve report quality and consistency for better diagnosis and more accurate, detailed patient records, with the report automation reducing the time and personnel required. Together, these platform components will improve patient care in gastroenterology, including more efficient care across more patients.

Ntombifikile Mtshali of Shout-It-Now with Elona Toska of the University of Cape Town, both in South Africa, will pilot test use of ChatGPT to provide information on sexual and reproductive health that helps young women and adolescent girls in South Africa make informed decisions and effectively access health services. They will test integration of the chatbot into Shout-It-Now's existing platforms: a tablet-based platform in mobile clinics staffed by young women and a mobile phone app. They will train ChatGPT to provide information on sensitive topics, including gender-based violence, HIV infection risk, and pregnancy, using existing materials and guided by a workshop with mobile clinic staff. Users' perception of the chatbot and the chatbot's effectiveness in increasing the use of health services will be assessed using on-line questionnaires and phone surveys across five demographically different districts.

Vijay Sai Trap of OnionDev Technologies Pvt. Ltd. in India will develop an AI-based platform to provide accurate and private automated answers to questions on sexual health and mental well-being for youth and women in rural India. They will generate a dataset of community-generated questions on these topics during a mental health awareness campaign in the Indian states of Uttar Pradesh, Madhya Pradesh, and Tamil Nadu. With the support of subject matter experts, they will add answers to these questions from the relevant literature. They will then create a master dataset of questions and answers, including translations using an existing LLM trained on local Indian languages. This dataset will be used to compare different AI-based models to identify the one best able to effectively answer questions on these sensitive topics.

Himanshu Sinha of the Indian Institute of Technology Madras in India will develop an LLM-based chatbot to provide personalized reliable guidance on antenatal care in multiple Indian languages, particularly for mothers without regular access to health care. The chatbot will use an open-source LLM and will be incorporated into a mobile phone application. The project will begin by surveying pregnant women seeking care in a variety of health care settings and across all three trimesters, asking them what features they would want in a pregnancy app. The LLM will be trained with information from textbooks, clinical manuals, government health resources, and guidelines from professional organizations. Initially the chatbot will function in Hindi and Tamil, with additional Indian languages to follow. The app will track pregnancy milestones and deliver relevant evidence-based advice.

Ananda Kumar Mishra of Cowbit Technologies Pvt Ltd in India will pilot test the Cowbit, a wearable device for real-time monitoring of dairy cow health. They will test the device across farms in different states in India, along with a mobile app in local languages for user-friendly readout of the data. The device's sensors will measure elements of cow health particularly relevant for guiding farm management. This includes measurements such as udder temperature for early diagnosis of mastitis and prompt veterinary treatment. It also includes behavioral measurements to identify cows without typical signs of estrus (silent heat) who are ready for insemination to maximize breeding efficiency. They will collaborate with farmers and other stakeholders to ensure the device is relevant for increasing farm productivity and has potential for broad uptake.

Kavitha Sairam of FIB-SOL Life Technologies Private Limited in India will develop mulch sheets that are biodegradable and can be tilled into the soil or composted. Mulch sheets can improve crop yields while reducing the need for irrigation and addition of agricultural chemicals. Traditional polyethylene mulch sheets, however, need to be removed each crop cycle, which is labor intensive, and they are a source of plastic pollution. To develop a biodegradable mulch product, they will explore various materials and fabrication technologies. They will characterize the physical and chemical properties of the candidate product and pilot test its performance and rate of degradation in the field with two different crops as compared to a commercial polyethylene sheet.

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.

Livia Casseb of Evandro Chagas Institute in Brazil will develop models to understand and predict the impact of climate change on the Aedes mosquito-transmitted arboviral diseases dengue, chikungunya, and Zika in Brazil. The models will integrate a variety of existing data for the different geographic regions of Brazil, including historical data on climate, landscape characteristics, population density, mosquito distribution, and public health. They will also incorporate structured and unstructured data from community networks, teaching and research institutions, and state government entities. The models will reveal interdependent relationships and interactions, including spatial correlations between the arboviral diseases over time. They will develop distinct models for individual geographic regions to serve as early warning systems for arboviral disease outbreaks and to guide local interventions.

This grant is funded by Grand Challenges Brazil.

Hernan Argibay of Fiocruz in Brazil will support a participatory research approach for communities in urban slums in Salvador, Brazil to develop and monitor the impact of interventions to reduce the risk of vector-borne and zoonotic diseases. Guided by local needs, new community-led projects will focus on environmentally transmitted diseases (e.g., leptospirosis and enteric infections) and vector-borne diseases (e.g., leishmaniasis, rickettsiosis, and those caused by the arboviruses dengue, chikungunya, and Zika), all of whom could increase in incidence due to climate change. Intervention projects will include environmental clean-up to reduce disease transmission by mosquitos and rats, planting to improve drainage and provide additional food sources, and using an app to map potential risk factors and guide new projects. They will measure intervention impact, including community-led pathogen surveillance using vector traps, water sampling, and metagenomic sequencing.

This grant is funded by Grand Challenges Brazil.