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Envisioning the future of public health through open data science
In 2013, the Bill & Melinda Gates Foundation created the Healthy Birth, Growth, and Development program (HBGD) to ensure that all children can regain control of their futures, maximize their potential, and have the opportunity to lead a healthy and productive life.
Within HBGD, the knowledge integration initiative (HBGDki) aims to answer the key questions by analyzing the large body of data that already exists. We have organized a team of researchers, data scientists, visualization experts, and policy makers from around the world for this work.
Steve Kern, PhDDeputy Director, Quantitative SciencesBill & Melinda Gates Foundation
Thea Norman, PhDSenior Program Officers of Quantitative Sciences (Co-lead of Knowledge Integration)Bill & Melinda Gates Foundation
Ben Pierson, MBASenior Program Officers of Quantitative Sciences (Co-lead of Knowledge Integration)Bill & Melinda Gates Foundation
HBGDki Surge Teams
Global Health Analytics Platform
The HBGDki Global Health Analytics Platform, or GHAP, is a cloud-based computing platform that enables users to contribute, curate, and analyze data securely. Data Contributors upload data sets to GHAP, and analysts launch virtual computing environments to access diverse applications and tools to perform modeling and analyses with authorized data sets.
Quantitative Physiologic Modeling
The HBGDki Quantitative Physiologic Modeling – or qPM – surge team is developing an integrative framework to quantitatively characterize the relations between physiological mechanisms of growth and clinically observable growth endpoints. Team experts in physiology, nutrition, and quantitative modeling review published mechanistic physiology studies to establish meaningful and relevant model components and estimate the strength of interactions between covariates.
Policy, Delivery, & Implementation
The HBGDki Policy, Delivery, & Implementation surge team– renamed Population & Surveillance Data Integration team – is analyzing the effects of multilevel factors on poor growth outcomes. The team is developing models and tools to quantitatively characterize heterogeneity and interactions between factors in populations that suffer from growth faltering and impaired neurocognitive development.
Lifecycle, Auxology, and Neurocognitive Development
The HBGDki Lifecycle, Auxology, and Neurocognitive Development surge team strives to better understand the variability in sensitivity, intensity, and duration of growth faltering caused by insults, and to optimize how targeted interventions may promote recovery during critical growth and development periods across the life cycle. The team members are modeling growth trajectories to enable better predictions about outcomes of growth and neurocognitive development.
The HBGDki Neurocognitive Development Team aims to quantify relations and drivers of variability in neurocognitive growth and development in children. The team also seeks to characterize the neurocognitive effects of different environmental exposures and socioeconomic conditions, and to identify clear, data-driven, actionable targets to lower risk factors for delayed neurocognitive development.
Data Management & Visualization—Visualization
The success of HBGDki in finding solutions to growth faltering and impaired neurocognitive development depends on our best possible understanding of the data. Solutions are discovered faster when data analysis and modeling are tightly coupled with visualization in the iterative research process.
Fetal Growth, Pregnancy, & Newborn Outcomes
The HBGDki Fetal Growth, Pregnancy, & Newborn Outcomes surge team includes experts in applied statistics and mathematics, biostatistics, and clinical research. They are leveraging with the HBGDki knowledge base to quantitatively characterize the interactions between maternal and fetal factors that drive fetal development, pregnancy and newborn outcomes, and postnatal growth and development.
HBGDki Knowledge Management Platform (kikm)
The HBGDki Knowledge Management platform – or kikm – uses modern graph and knowledge-enhanced search capabilities to maximize communication and accelerate learning between the HBGDki data curators, data analysts, model developers, statisticians, and leadership. As new information and insights are generated, the kikm graph matures and enables detailed deep-dive into problems and solutions addressed by HBGDki to improve maternal and child health globally.
Data Management & Visualization—Curation
The Data Management & Visualization surge team reduces the time to early insights by curating analysis data sets with state-of-the-art common data specification, security, and quality standards. The Data team serves as the critical link for all HBGDki teams by making the data available with proper format and documentation to support all deep data analyses and modeling.
Data Contributors & Partners
The HBGDki knowledge base and science work wouldn’t be possible without our partners who contribute their study data and talents. List complete as of Feb. 14, 2018.
Abbas Ourmazd, PhDUniversity of Wisconsin Milwaukee
Abdullah H. Baqui, MBBS, MPH, DrPHProfessor, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University
Abed Mutemi, MSc, StatisticsFinancial Services for the Poor
Akshay RaviSenior Associate at Global Health Strategies
Alan Hubbard, PhDDivision of Epidemiology and Biostatistics, University of California, Berkeley
Albert Park, PhDHong Kong University of Science and Technology
Alex Groisman, PhDDepartment of Physics, UCSD
Alex Ng, MBChBBill & Melinda Gates Foundation
Alexey Radul, PhDMassachusetts Institute of Technology
Alexis Medina, MARural Education Action Program (REAP), Stanford University
Ali Arjomand, PhDPropel Innovation Consulting
Ali Dashti, PhDUniversity of Wisconsin Milwaukee
Alison Jones, MA, International StudiesBill & Melinda Gates Foundation
Aluisio J. D. Barros, PhDFederal University of Pelotas, Pelotas, Brazil
Amee Manges, PhDUniversity of British Columbia, School of Population and Public Health
Amrit Singh, MPPMAlvarez and Marsal
Amy Racine-Poon, PhD, StatisticsNovartis Pharma
Andrada Ivanescu, PhDMontclair State University
Andrew J. Prendergast, DPhilQueen Mary University of London, UK
Andrew Mertens, MSUniversity of California, Berkeley
Andrew Prentice, PhDMRC Unit The Gambia
Andrew Tatem, PhDWorldPop/Flowminder, University of Southampton
Anita Zaidi, SMBill & Melinda Gates Foundation
Anna Bershteyn, PhDInstitute for Disease Modeling
Anna Dyson, M.ArchYale University
Anna Noel-Storr, MScOxford University
Anne CC Lee, MD, MPHBrigham and Women's Hospital, Harvard Medical School
Anoushka Millear, BAInstitute for Health Metrics and Evaluation
Anthony K. Ngugi, PhDAga Khan University
Archana Bhattacharya, MBA, Project ManagementSociety of Clinical Data Management
Arnab MaityAssociate Professor, Department of Statistics, North Carolina State University
Aryeh D. Stein, PhDEmory University
Asad Ali, MDAga Khan University, Pakistan
Atul Butte, MD, PhDUniversity of California, San Francisco
Avlant Nilsson, MSChalmers University of Technology
Bai Yu, PhDShaanxi Normal University
Bakary SonkoMRC Unit The Gambia & MRC International Nutrition Group, London School of Hygiene & Tropical Medicine