Awards

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.

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.

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.

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.

Andréia Santo of the Associação Redes de Desenvolvimento da Maré in Brazil will collect temperature, humidity, and air quality data together with associated health data for residents in the Maré favelas in Rio de Janeiro to better understand the causes of respiratory diseases and reduce their burden. They will also train high school girls as citizen scientists to work alongside health professionals in collecting and analyzing data and developing practical technologies to mitigate the health effects of heat and poor air quality. This participatory science approach will serve as a sustainable mechanism to understand the impacts of climate change on the health of particularly vulnerable communities in Brazil and to guide the development of innovative solutions. In selected residences in Maré, they will pilot an intervention consisting of a bio-concrete wall coating to reduce indoor relative humidity as a cause of heat stress for occupants.

This grant is funded by Grand Challenges Brazil.

Cari van Schalkwyk of Stellenbosch University in South Africa will expand and support the African community of polio and measles disease modelers. The work will be done through the South African Centre for Epidemiological Modelling and Analysis (SACEMA), which is hosted at Stellenbosch University. It will build on an ongoing fellowship program for health policy modeling by recruiting and supporting two new cohorts. Modelers will use available data to develop, validate, and package modeling methods for polio and measles that help African decision-makers assess the risk of outbreaks and the impact of vaccination programs. Additional work will target research goals that include developing enhanced methods to estimate population immunity to polio, comparing existing methods to determine how consistent they are, and extending ongoing modeling work evaluating wastewater-based surveillance of polio and measles as an early-warning signal for outbreaks and to monitor outbreak dynamics.

Sheetal Silal of the University of Cape Town in South Africa will establish a research consortium to analyze how climate change affects the transmission and control of mosquito-borne diseases, focusing on how to optimize interventions for malaria, chikungunya and dengue in Southern Africa. The consortium will integrate research projects led by local data scientists working closely with local decision-makers. Through mathematical and statistical modeling together with climate science, these projects will determine climate scenarios across time scales relevant for management of mosquito-borne diseases. These time scales will encompass short-term windows (6-12 months) as well as longer windows (5-10 years) relevant for policy planning and that incorporate the predicted impact and costs of new interventions. The consortium will also explore even longer windows (over 30 years) to provide predictions useful to initiate policy discussions and bring attention to the long-term implications of climate change on disease control strategies.

This grant is funded by The Wellcome Trust.